Based on the success of the stroboscope software, I rewrote the dimmer software for my desk lamp (see LED lamp projects for more about the lamps).  The new software provides smoother control of the light levels (having 256 levels plus off, rather than 63 levels plus off) and now has a 256:1 brightness range rather than the approximately 256:6 range of the previous code.

I removed a lot of the general-purpose crap that was inherited from core13 (which was in turn stripped down from the Arduino core software).  I did not get rid of all of core13, so I could probably take out another 50–100 bytes, but the code is down to 222 bytes (and the ATtiny13A has 1kB of flash, so I’m way below the limit).

The actual brightness range of the new dimmer is a bit more than 256:1, because on the shortest pulse the FET doesn’t turn all the way on.  The pulse duration from the ATtiny13A is approximately 3.4µs times the brightness level (9.6MHz clock divided down by 4 and by 8), but I had deliberately slowed the FET transitions by adding a series resistor to the gate, so that nFET doesn’t finish turning on for 5.2µs (as judged by the end of the Miller plateau on the gate).  So at the lowest brightness level, the nFET does not turn all the way on and the voltage on the drain only gets down to 3.5V, which leaves 5.5V across the LED board—enough to turn on the LED, but with only about 10mA, not 118mA. At this low level, the LEDs sometimes flicker, perhaps as a result of some thermal feedback effects. The all flicker together, so the effect is probably in the dimmer’s nFET, not on the LED boards.

ATtiny output (green) and gate voltage (yellow) at 2V/division and 2µs/division for the shortest pulse length. The gate voltage has not quite reached the end of the Miller plateau before being discharged again.

ATtiny output (green) and drain voltage (yellow) at 2V/division and 2µs/division for the shortest pulse length. The BitScope BS-10 oscilloscope clips the voltage to 5.5V—it actually goes to 9V.

At the next brightness level, the drain voltage does drop to 0V for at least 2.4µs and stays low enough for the LED board to be at maximum current (below 2.5V) for at least 5.5µs.  There is an enormous difference in brightness between length 2 and length 1 pulses (more like 1:20 than 1:2), because of the low current for pulse length 1, but for length 2 and longer the steps in brightness are pretty much as one would expect from the pulse lengths.

ATtiny output (green) and gate voltage (yellow) at 2V/division and 2µs/division for the shortest pulse length. The gate voltage has gone past the end of the Miller plateau and started charging past that point. The Miller plateau is also visible on the discharge as the nFET turns off.

ATtiny output (green) and drain voltage (yellow) at 2V/division and 2µs/division for the second shortest pulse length. The BitScope BS-10 oscilloscope clips the voltage to 5.5V—it actually goes to 9V.
The longer pulses allow the nFET to turn on fully.

The conversion from the linear 10-bit analog-to-digital reading (0–1023) to pulse lengths is done by the following method:

expon = ADC>>7
frac = 0x80 + (ADC & 0x7f)
pulse_len = ADC < 0x20? 0:  ADC < 0x40? 1: 1+ (frac>> (7-expon))

The stepwise nature of the brightness at low levels is apparent in a plot of the conversion function:

The steps in brightness are quite visible at the low end, but after the first 10 steps, the differences are small enough not to be easily noticed.

Overall, I’m pleased with the rework of the dimmer code. I’ll probably have to solder up another of the dimmer boards this summer, since I’ll want one for the light fixture that I haven’t started building yet and one for the Halloween stroboscope.

The log amplifier that I’ve spent the last several days understanding (posts a, b, c) is not the only non-linear circuit needed for a loudness detector.  We also need to convert the audio input signal into a slowly changing amplitude signal that we can take the logarithm of.  As I discussed in the first post on log amps, I had rejected true-RMS converter chips as too expensive for the application (though the original application has gone away), and decided to try a rectifier and low-pass filter.

[Incidentally, my son is now looking at a different processor chip, the KL25 from Freescale (an ARM Cortex chip), which has a 16-bit ADC that is much faster than the ATMega's, so the entire loudness-detector could be done in software, except for a one-op-amp preamplifier.  With a  16-bit ADC, we can get almost 90dB of range without needing a log amplifier. We're planning to order a development board that is compatible with Arduino shields (but has lots more I/O pins available) and that has an accelerometer on the board.  Amazingly, the development board is only $13, about half the price of an Arduino.]

A single diode does not work for our rectifier needs in the loudness circuit, because diodes don’t turn on until the voltage across them is at least a “diode drop” (about 0.7v for silicon diodes and 0.45v for Schottky diodes).  However, the simple circuit for the log amplifier is also the circuit for a precision rectifier:

This circuit is both a log amplifier and a precision rectifier. If Vb is set to a constant voltage, then Vout1 varies as log(Vb–Va). Vout2 is max(Va,Vb). 
The diode can be connected in the opposite direction, to get Vout2=min(Va,Vb) and Vout1 varying with log(Va–Vb).

The log-amplifier circuit I used in the previous posts had a transistor in place of the diode, so that the crucial voltage that was being exponentiated was referenced to the bias voltage, rather than the input. We also needed a compensation capacitor in parallel with the transistor to prevent oscillation in the negative feedback loop.

For the precision rectifier, we swap the inputs, so that Va is the signal input and Vb is a constant threshold voltage for the rectifier. We do not need (or want) the compensation capacitor, as that would cause the circuit to act as a unity gain amplifier at high frequency, rather than as a rectifier.

Because I did not happen to have any diodes, but had plenty of transistors, I experimented with the rectifier circuit using diode-connected bipolar transistors (collector and base connected together). Because the output of the rectifier is not directly driven by an op amp, I used unity-gain buffers to isolate the test circuitry (Arduino analog inputs or BitScope oscilloscope) from the amplifier:

Test circuit for low-speed testing of precision rectifier circuit. Here the NPN transistor is used as a diode, in the opposite direction as in the first schematic, so Vout should be min(Vin, Vbias)

My initial test setup did not have the unity-gain buffer for Vin, but I found that one of my Arduino analog input pins was quite low impedance and was discharging my capacitor. Switching to a different pin helped, but I eventually decided to avoid that kluge and use a unity-gain buffer instead.

I tried several different values for R₂. The most predictable effect of changing the value is a change in the range over which the rectifier operates. Clipping occurs because the output of the op amp is limited to be between the rails of the power supply. The feedback transistor is conducting when the rectifier is following the input, so the op amp output has to be substantially lower than Vout.  The function implemented is max(Vclip, min(Va,Vbias)).  Vclip should go down as R₂ is increased (at about 60mV for each factor of 10 in resistance—the same shift as in the log amplifier).

Here are a couple of plots of Vout vs. Vin for the S9018 transistor:

(click to embiggen) With a 1kΩ resistor, the clipping voltage is fairly high, and we have a somewhat limited range for the rectifier.  The offset voltage for the rectifier between the output and the input is much less than the resolution of the Arduino ADC (about 5mV).

(click to embiggen) With a 10kΩ resistor, the clipping voltage is lower, giving us more range for the rectifier.

Using a PNP transistor instead of an NPN has the effect of reversing the diode and producing Vout=min(Vclip, max(Vin, Vbias)):

(click to embiggen) With an S9012 PNP transistor and a 1kΩ resistor, we get clipping at the high end.

(click to embiggen) With a 10kΩ resistor we get a larger range.

So why not go for a very large resistor and maximize the range? From a DC perspective this looks like a win (though it is hard to see in the limit how Vbias would affect the result if the resistance went to infinity).  Of course, the problem is with high-frequency response.  Consider the difference between the S9018 NPN transistor with a 1kΩ resistor and a 330kΩ resistor:

(click to embiggen) With an S9018 NPN transistor and a 330kΩ resistor at 1kHz. Note the overshoot when the rectifier shuts off.

(click to embiggen) Fairly clean signal with a S9018 NPN transistor and a 10kΩ resistor at 1kHz.

(click to embiggen) With a 1kΩ resistor, there is very little overshoot as the rectifier turns off, but we can see a bit of a problem when the rectifier turns back on.

There is a problem with the rectifier turning on slowly, because Vout has to move all the way from the top rail down to the bias voltage, and the op amp has a slew-rate limitation. This phenomenon can be seen more clearly at a higher frequency:

(click to embiggen) The S9018 NPN transistor with a 10kΩ resistor and a 15kHz input signal. The overshoot as the rectifier turns off is about 50mV, and the turn-on delay is about 8µsec. The turn-on delay does not vary much with the input resistance, unlike the turn-off overshoot.

I believe that the overshoot as the rectifier turns off is due to capacitance, as adding a small feedback capacitor in parallel with the diode increases the overshoot substantially:

(click to embiggen) With a 33pF capacitor in parallel with the diode (an S9018 NPN transistor), a 10kΩ resistor, and a 15kHz input, the overshoot goes up to about 290mV from 50mV without the capacitor. The turn-on delay is masked somewhat by the high-frequency feedback.

Note: the S9018 has the best high-frequency response (if you consider 15kHZ high frequency) of any of the transistors I looked, probably because it has the lowest capacitance. For example, with a 10kΩ resistor the S9013 NPN has 120mV of overshoot at 15kHz, instead of only 50mV, and the S9012 PNP has -180mV. With a 1kΩ resistor, I can’t measure the overshoot on any of these three transistors. So the limited range with a 1kΩ resistor is compensated for by the much cleaner turn-off behavior.  I should be able to get better range by using a fast-response Schottky diode instead of diode-connected transistor.

Of course, the turn-on behavior is a bigger problem and one that can’t be fixed by playing with the resistor or the diode, because the problem is with the large voltage swing needed from the op amp in order to turn on. There are standard solutions that limit the voltage swing, but I think I’ll leave that for a later blog post.

The log amplifier that I’ve spent the last several days understanding (posts a, b, c) is not the only non-linear circuit needed for a loudness detector.  We also need to convert the audio input signal into a slowly changing amplitude signal that we can take the logarithm of.  As I discussed in the first post on log amps, I had rejected true-RMS converter chips as too expensive for the application (though the original application has gone away), and decided to try a rectifier and low-pass filter.

[Incidentally, my son is now looking at a different processor chip, the KL25 from Freescale (an ARM Cortex chip), which has a 16-bit ADC that is much faster than the ATMega’s, so the entire loudness-detector could be done in software, except for a one-op-amp preamplifier.  With a  16-bit ADC, we can get almost 90dB of range without needing a log amplifier. We’re planning to order a development board that is compatible with Arduino shields (but has lots more I/O pins available) and that has an accelerometer on the board.  Amazingly, the development board is only $13, about half the price of an Arduino.]

A single diode does not work for our rectifier needs in the loudness circuit, because diodes don’t turn on until the voltage across them is at least a “diode drop” (about 0.7v for silicon diodes and 0.45v for Schottky diodes).  However, the simple circuit for the log amplifier is also the circuit for a precision rectifier:

This circuit is both a log amplifier and a precision rectifier. If Vb is set to a constant voltage, then Vout1 varies as log(Vb–Va). Vout2 is max(Va,Vb). 
The diode can be connected in the opposite direction, to get Vout2=min(Va,Vb) and Vout1 varying with log(Va–Vb).

The log-amplifier circuit I used in the previous posts had a transistor in place of the diode, so that the crucial voltage that was being exponentiated was referenced to the bias voltage, rather than the input. We also needed a compensation capacitor in parallel with the transistor to prevent oscillation in the negative feedback loop.

For the precision rectifier, we swap the inputs, so that Va is the signal input and Vb is a constant threshold voltage for the rectifier. We do not need (or want) the compensation capacitor, as that would cause the circuit to act as a unity gain amplifier at high frequency, rather than as a rectifier.

Because I did not happen to have any diodes, but had plenty of transistors, I experimented with the rectifier circuit using diode-connected bipolar transistors (collector and base connected together). Because the output of the rectifier is not directly driven by an op amp, I used unity-gain buffers to isolate the test circuitry (Arduino analog inputs or BitScope oscilloscope) from the amplifier:

Test circuit for low-speed testing of precision rectifier circuit. Here the NPN transistor is used as a diode, in the opposite direction as in the first schematic, so Vout should be min(Vin, Vbias)

My initial test setup did not have the unity-gain buffer for Vin, but I found that one of my Arduino analog input pins was quite low impedance and was discharging my capacitor. Switching to a different pin helped, but I eventually decided to avoid that kluge and use a unity-gain buffer instead.

I tried several different values for R₂. The most predictable effect of changing the value is a change in the range over which the rectifier operates. Clipping occurs because the output of the op amp is limited to be between the rails of the power supply. The feedback transistor is conducting when the rectifier is following the input, so the op amp output has to be substantially lower than Vout.  The function implemented is max(Vclip, min(Va,Vbias)).  Vclip should go down as R₂ is increased (at about 60mV for each factor of 10 in resistance—the same shift as in the log amplifier).

Here are a couple of plots of Vout vs. Vin for the S9018 transistor:

(click to embiggen) With a 1kΩ resistor, the clipping voltage is fairly high, and we have a somewhat limited range for the rectifier.  The offset voltage for the rectifier between the output and the input is much less than the resolution of the Arduino ADC (about 5mV).

(click to embiggen) With a 10kΩ resistor, the clipping voltage is lower, giving us more range for the rectifier.

Using a PNP transistor instead of an NPN has the effect of reversing the diode and producing Vout=min(Vclip, max(Vin, Vbias)):

(click to embiggen) With an S9012 PNP transistor and a 1kΩ resistor, we get clipping at the high end.

(click to embiggen) With a 10kΩ resistor we get a larger range.

So why not go for a very large resistor and maximize the range? From a DC perspective this looks like a win (though it is hard to see in the limit how Vbias would affect the result if the resistance went to infinity).  Of course, the problem is with high-frequency response.  Consider the difference between the S9018 NPN transistor with a 1kΩ resistor and a 330kΩ resistor:

(click to embiggen) With an S9018 NPN transistor and a 330kΩ resistor at 1kHz. Note the overshoot when the rectifier shuts off.

(click to embiggen) Fairly clean signal with a S9018 NPN transistor and a 10kΩ resistor at 1kHz.

(click to embiggen) With a 1kΩ resistor, there is very little overshoot as the rectifier turns off, but we can see a bit of a problem when the rectifier turns back on.

There is a problem with the rectifier turning on slowly, because Vout has to move all the way from the top rail down to the bias voltage, and the op amp has a slew-rate limitation. This phenomenon can be seen more clearly at a higher frequency:

(click to embiggen) The S9018 NPN transistor with a 10kΩ resistor and a 15kHz input signal. The overshoot as the rectifier turns off is about 50mV, and the turn-on delay is about 8µsec. The turn-on delay does not vary much with the input resistance, unlike the turn-off overshoot.

I believe that the overshoot as the rectifier turns off is due to capacitance, as adding a small feedback capacitor in parallel with the diode increases the overshoot substantially:

(click to embiggen) With a 33pF capacitor in parallel with the diode (an S9018 NPN transistor), a 10kΩ resistor, and a 15kHz input, the overshoot goes up to about 290mV from 50mV without the capacitor. The turn-on delay is masked somewhat by the high-frequency feedback.

Note: the S9018 has the best high-frequency response (if you consider 15kHZ high frequency) of any of the transistors I looked, probably because it has the lowest capacitance. For example, with a 10kΩ resistor the S9013 NPN has 120mV of overshoot at 15kHz, instead of only 50mV, and the S9012 PNP has -180mV. With a 1kΩ resistor, I can’t measure the overshoot on any of these three transistors. So the limited range with a 1kΩ resistor is compensated for by the much cleaner turn-off behavior.  I should be able to get better range by using a fast-response Schottky diode instead of diode-connected transistor.

Of course, the turn-on behavior is a bigger problem and one that can’t be fixed by playing with the resistor or the diode, because the problem is with the large voltage swing needed from the op amp in order to turn on. There are standard solutions that limit the voltage swing, but I think I’ll leave that for a later blog post.

Yesterday, in Logarithmic amplifier, I ended with the following plot:

(click plot to see larger version) The cloud of points is broad enough to be consistent with slightly different parameter values.

I was bothered by the broad cloud of points, and wanted to come up with a better test circuit—one that would give me more confidence in the parameters.  It was also quite difficult to get close to Vbias—the closest this could measure was one least-significant-bit of the DAC away (about 5mV).  A factor of 512 from the largest to the smallest signal is 54dB, but only about the upper 40dB of that was good enough data for fitting (and very little time was spent at near the Vbias value).

I think that part of the problem with the cloud was that the input signal was changing fairly quickly, and the Arduino serializes its ADC, so that the input and output are measured about 120µsec apart.  I decided to use a very simple slow-changing signal: a capacitor charging toward Vbias through a large resistor.  My first attempt used a 1MΩ resistor and a 10µF capacitor, for a 10-second time constant:

Output voltage from log amplifier (with 3x gain in second stage) as capacitor charges. (click picture for larger version) One fit uses the Arduino-measured Vin and Vbias voltages, the other attempts to model the RC charging as well. What are the weird glitches?

The capacitor charging should be a smooth curve exponential decay to Vbias, so the log amplifier output should be a straight line with time. There were two obvious problems with this first data—the output was not a straight line and there were weird glitches about every 15–20 seconds.

The non-straight curve comes from the capacitor not charging to Vbias. Even when the capacitor was given lots of time to charge, it remained stubbornly below the desired voltage. In think that the problem is leakage current: resistance in parallel with the capacitor. The voltage was about 1% lower than expected, which would be equivalent to having a 100MΩ resistor in parallel with the capacitor.  I can well believe that I have sneak paths with that sort of resistance on the breadboard as well as in the capacitor.

According to Cornell Dublier, a capacitor manufacturer, a typical parallel resistance for a 10µF aluminum electrolytic capacitor would be about 10MΩ [http://www.cde.com/catalogs/AEappGUIDE.pdf‎]:

Typical values are on the order of 100/C MΩ with C in μF, e.g. a 100 μF capacitor would have an Rp of about 1 MΩ.

So I may be lucky that I got as close to Vbias as I did.

The glitches had a different explanation: they were not glitches in the log amplifier circuit, but in the 5V power supply being used as a reference for the ADC on the Arduino board—I had forgotten how bad the USB power is coming out of my laptop, though I had certainly observed the 5V supply dropping for a second about every 20 seconds on previous projects.  The drop in the reference for the ADC results in a bogus increase in the measured voltages.  That problem was easy to fix: I plugged in the power supply for the Arduino rather than running off the USB power, so I had a very steady voltage source using the Arduino’s on-board regulator.

(click picture for larger version) With a proper power supply, I get a clean charge and the output is initially a straight line, but I’m still not getting close to Vbias. Again the blue fit uses the measured Vin and Vbias voltages, while the green curve tries to fit an RC decay model. Note the digitization noise on the measured inputs towards the end of the charging time.

To solve the problem of the leakage currents, I tried going to a larger capacitor and smaller resistor to get a similar RC time constant. At that point I had not found and read the Cornell Dublier application note, though I suspected that the parallel resistance might scale inversely with the capacitor size, in which case I would be facing the same problem no matter how I chose the R-vs-C tradeoff. Only reducing the RC time constant would work for getting me closer to Vbias.

Using a 47kΩ resistor and a 470µF capacitor worked a bit better, but the time constant was so long that I got impatient:

(click image for larger version) The blue fit is again using the measured Vin and Vbias, and has a pretty good fit. The green fit using an RC charge model does not seem quite as good a fit.

The calibration of 9.7mV/dB seems pretty good, so the 409mV range of the recording corresponds to a 42dB range. The line is straighter, but I’m still not getting as close to Vbias as I’d like.

I then tried a smaller RC time constant (hoping that the larger current with the same capacitor would result in getting closer to Vbias, and so testing a larger dynamic range on the log amplifier). I tried 16kΩ with the 470µF capacitor:

(click image to embiggen) I’m now getting a clear signal from the log amplifier even after the input voltage has gotten less than one least-significant-bit away from Vbias (the blue fit). I found it difficult to fit parameters for modeling the RC charge (the green fit).

The two models I fit to the data give me somewhat different mV/dB scales, though both fit the data fairly well. The blue curve fits better up to about 65 seconds, then has quantization problems. Using that estimate of 9.8mV/dB and the 560mV range of the output, we have a dynamic range here of 57dB. There is still some flattening of the curve—we aren’t quite getting to the Vbias value, but it is pretty straight for the first 50 seconds.

Note: the parallel resistance of the capacitors would not explain the not-quite-exponential behavior we saw in the RC time constant lab, since those measurements were discharging the capacitor to zero. A parallel resistance would just change the time constant, not the final voltage.

I was using the Duemilanove board for the log-amplifier tests. I retried with the Uno board, to see if differences in the ADC linearity make a difference in the fit:

(click to embiggen) Using the Uno Arduino board I still had trouble with the fit, and the Uno ADC seems to be noisier than the Duemilanove ADC. The missing parts of the blue curve are where the Uno board read the input as having passed Vbias.

The 625 mV range over 250 seconds corresponds to about 69dB, assuming that the 9.1 mV/dB calibration is reasonably accurate (and 64dB if the earlier 9.8mV/dB calibration is better).
My measurements of the log amplifier do not seem to yield a very consistent mV/dB parameter, with values from 9.1mV/dB to 9.8mV/dB using just the Arduino measurements (and even less consistency when a model of RC charging is used).  I’m not sure how I can do more consistent measurements with the equipment I have.  Anyone have any ideas?
Incidentally, my son has decided not to include a microphone in his project.  The silicon MEMS mic was small enough, but the op amp chip for the analog processing was too big for the small board area he had left in his layout, and he decided that the loudness detector was not valuable enough for the board area and parts cost. I believe that his available board area shrunk a little today, because he discovered that the keep-away check had not been turned on in the Eagle design-rule checker.  Turning it on indicated that he had packed the capacitors too close in places, and he had to spread them out. (At least, I think that’s what he told me—I’ve not been following his PC board layout very closely.)
I’m still interested in learning about log amplifiers and precision rectifiers, so I’m still going to breadboard the components of the design and test them out.  I’m not sure when I’ll ever use the knowledge, since the Applied Circuits course does not cover the nonlinear behavior of pn junctions nor the forward-voltage drop of diodes (we don’t use diodes in the course).

Yesterday, in Logarithmic amplifier, I ended with the following plot:

(click plot to see larger version) The cloud of points is broad enough to be consistent with slightly different parameter values.

I was bothered by the broad cloud of points, and wanted to come up with a better test circuit—one that would give me more confidence in the parameters.  It was also quite difficult to get close to Vbias—the closest this could measure was one least-significant-bit of the DAC away (about 5mV).  A factor of 512 from the largest to the smallest signal is 54dB, but only about the upper 40dB of that was good enough data for fitting (and very little time was spent at near the Vbias value).

I think that part of the problem with the cloud was that the input signal was changing fairly quickly, and the Arduino serializes its ADC, so that the input and output are measured about 120µsec apart.  I decided to use a very simple slow-changing signal: a capacitor charging toward Vbias through a large resistor.  My first attempt used a 1MΩ resistor and a 10µF capacitor, for a 10-second time constant:

Output voltage from log amplifier (with 3x gain in second stage) as capacitor charges. (click picture for larger version) One fit uses the Arduino-measured Vin and Vbias voltages, the other attempts to model the RC charging as well. What are the weird glitches?

The capacitor charging should be a smooth curve exponential decay to Vbias, so the log amplifier output should be a straight line with time. There were two obvious problems with this first data—the output was not a straight line and there were weird glitches about every 15–20 seconds.

The non-straight curve comes from the capacitor not charging to Vbias. Even when the capacitor was given lots of time to charge, it remained stubbornly below the desired voltage. In think that the problem is leakage current: resistance in parallel with the capacitor. The voltage was about 1% lower than expected, which would be equivalent to having a 100MΩ resistor in parallel with the capacitor.  I can well believe that I have sneak paths with that sort of resistance on the breadboard as well as in the capacitor.

According to Cornell Dublier, a capacitor manufacturer, a typical parallel resistance for a 10µF aluminum electrolytic capacitor would be about 10MΩ [http://www.cde.com/catalogs/AEappGUIDE.pdf‎]:

Typical values are on the order of 100/C MΩ with C in μF, e.g. a 100 μF capacitor would have an Rp of about 1 MΩ.

So I may be lucky that I got as close to Vbias as I did.

The glitches had a different explanation: they were not glitches in the log amplifier circuit, but in the 5V power supply being used as a reference for the ADC on the Arduino board—I had forgotten how bad the USB power is coming out of my laptop, though I had certainly observed the 5V supply dropping for a second about every 20 seconds on previous projects.  The drop in the reference for the ADC results in a bogus increase in the measured voltages.  That problem was easy to fix: I plugged in the power supply for the Arduino rather than running off the USB power, so I had a very steady voltage source using the Arduino’s on-board regulator.

(click picture for larger version) With a proper power supply, I get a clean charge and the output is initially a straight line, but I’m still not getting close to Vbias. Again the blue fit uses the measured Vin and Vbias voltages, while the green curve tries to fit an RC decay model. Note the digitization noise on the measured inputs towards the end of the charging time.

To solve the problem of the leakage currents, I tried going to a larger capacitor and smaller resistor to get a similar RC time constant. At that point I had not found and read the Cornell Dublier application note, though I suspected that the parallel resistance might scale inversely with the capacitor size, in which case I would be facing the same problem no matter how I chose the R-vs-C tradeoff. Only reducing the RC time constant would work for getting me closer to Vbias.

Using a 47kΩ resistor and a 470µF capacitor worked a bit better, but the time constant was so long that I got impatient:

(click image for larger version) The blue fit is again using the measured Vin and Vbias, and has a pretty good fit. The green fit using an RC charge model does not seem quite as good a fit.

The calibration of 9.7mV/dB seems pretty good, so the 409mV range of the recording corresponds to a 42dB range. The line is straighter, but I’m still not getting as close to Vbias as I’d like.

I then tried a smaller RC time constant (hoping that the larger current with the same capacitor would result in getting closer to Vbias, and so testing a larger dynamic range on the log amplifier). I tried 16kΩ with the 470µF capacitor:

(click image to embiggen) I’m now getting a clear signal from the log amplifier even after the input voltage has gotten less than one least-significant-bit away from Vbias (the blue fit). I found it difficult to fit parameters for modeling the RC charge (the green fit).

The two models I fit to the data give me somewhat different mV/dB scales, though both fit the data fairly well. The blue curve fits better up to about 65 seconds, then has quantization problems. Using that estimate of 9.8mV/dB and the 560mV range of the output, we have a dynamic range here of 57dB. There is still some flattening of the curve—we aren’t quite getting to the Vbias value, but it is pretty straight for the first 50 seconds.

Note: the parallel resistance of the capacitors would not explain the not-quite-exponential behavior we saw in the RC time constant lab, since those measurements were discharging the capacitor to zero. A parallel resistance would just change the time constant, not the final voltage.

I was using the Duemilanove board for the log-amplifier tests. I retried with the Uno board, to see if differences in the ADC linearity make a difference in the fit:

(click to embiggen) Using the Uno Arduino board I still had trouble with the fit, and the Uno ADC seems to be noisier than the Duemilanove ADC. The missing parts of the blue curve are where the Uno board read the input as having passed Vbias.

The 625 mV range over 250 seconds corresponds to about 69dB, assuming that the 9.1 mV/dB calibration is reasonably accurate (and 64dB if the earlier 9.8mV/dB calibration is better).
My measurements of the log amplifier do not seem to yield a very consistent mV/dB parameter, with values from 9.1mV/dB to 9.8mV/dB using just the Arduino measurements (and even less consistency when a model of RC charging is used).  I’m not sure how I can do more consistent measurements with the equipment I have.  Anyone have any ideas?
Incidentally, my son has decided not to include a microphone in his project.  The silicon MEMS mic was small enough, but the op amp chip for the analog processing was too big for the small board area he had left in his layout, and he decided that the loudness detector was not valuable enough for the board area and parts cost. I believe that his available board area shrunk a little today, because he discovered that the keep-away check had not been turned on in the Eagle design-rule checker.  Turning it on indicated that he had packed the capacitors too close in places, and he had to spread them out. (At least, I think that’s what he told me—I’ve not been following his PC board layout very closely.)
I’m still interested in learning about log amplifiers and precision rectifiers, so I’m still going to breadboard the components of the design and test them out.  I’m not sure when I’ll ever use the knowledge, since the Applied Circuits course does not cover the nonlinear behavior of pn junctions nor the forward-voltage drop of diodes (we don’t use diodes in the course).

My son wanted to design a circuit to convert microphone inputs to loudness measurements usable by an Arduino (or other ATMega processor).  We discussed the idea together, coming up with a few different ideas.

The simplest approach would be to amplify the microphone then do everything digitally on the Arduino. There are several features of this approach:

• The analog circuit is about as simple as we can get: a DC-blocking capacitor and an amplifier.  This would only need one op amp, one capacitor, and 2 resistors (plus something to generate a bias voltage—perhaps another op amp, perhaps a low-drop-out regulator).
• Using digital processing, he can do true RMS voltage computation, and whatever low-pass filtering to smooth the result that he wants.
• He can’t sample very fast on the ATMega processor, so high frequencies would not be handled properly.  He might be able to sample at 9kHz (about as fast as the ADC operates), but that limits him to 4.5kHz. For his application, that might be good enough, so this doesn’t kill the idea.
• He’d like to have a 60dB dynamic range (say from 50dB to 110dB) or more, but the ADC in the ATMega is only a 10-bit converter, so a 60dB range would require the smallest signal to be ±½LSB, which is at the level of the quantization noise.  With careful setting of the gain for the microphone preamp, one might be able to get 55dB dynamic range, but that is pushing it a bit.  The resolution would be very good at maximum amplitude, but very poor for quiet inputs.

Although the mostly digital solution has not been completely ruled out, he wanted to know what was possible with analog circuits.  We looked at two main choices:

• True-RMS converter chips (intended for multimeters).  These do all the analog magic to convert an AC signal to a DC signal with the same RMS voltage.  Unfortunately, they are expensive (over $5 in 100s) and need at least a 5v power supply (he is planning to use all 3.3v devices in his design).  Also true RMS is a bit of overkill for his design, as log(amplitude) would be good enough.
• Using op amps and discrete components to make an amplifier whose output is the logarithm of the amplitude of the input.  Together we came up with the following block diagram:

Block diagram of the loudness circuit. (drawn with SchemeIt).

We then spent some time reading on the web how to make good rectifier circuits and logarithmic amplifiers. I’ll do a post later about the rectifier circuits, since there are many variants, but I was most interested in the logarithmic amplifier circuits, which rely on the exponential relationship between current and voltage on a pn junction—often the emitter-base junction of a bipolar transistor.

My son wanted to know what the output range of the log amplifier would be and whether he would need another stage of amplification after the log amplifier. Unfortunately, the theory of the log amplifier uses the Shockley ideal diode equation, which needs the saturation current of the pn junction—not something that is reported for transistors.  There is also a “non-ideality” parameter, that can only be set empirically.  So we couldn’t compute what the output range would be for a log amplifier.

Today I decided to build a log amplifier and see if I could measure the output.  I also wanted to figure out what sort of dynamic range he could get from a log amp. Here is the circuit I ended up with, after some tweaking of parameters:

The top circuit is just a bias voltage generator to create a reference voltage from a single supply. I’m working off of 5v USB power, so I set the reference to 2.5v. He might want to use a 1.65v reference, if he is using 3.3v power.
The bottom circuit is the log amplifier itself.

I chose a PNP transistor so that Vout would be more positive as the input current got further from Vbias.  I have 6 different PNP transistors from the Iteadstudio assortment of 11 different transistors, and I chose the A1015 rather arbitrarily, because it had the lowest current gain. I should probably try each of the other PNP transistors in this circuit, to see how sensitive the circuit is to the transistor characteristics.  I suspect it is very sensitive to them.

The circuit only works if the collector-base junction is reverse-biased (the usual case for bipolar transistors), so that the collector current is determined by the base current. The emitter-base junction may be either forward or reverse biased.  Note that if Vin is larger than Vbias, the collector-base junction becomes forward-biased, the negative input of the op amp is slightly above Vbias, and the op amp output hits the bottom rail.

As long as Vin stays below Vbias, the current through R2 should be , and the output voltage should be for some constants A and B that depend on the transistor. Note that changing R2 just changes the offset of the output, not the scaling, so the range of the output is not adjustable without a subsequent amplifier.

The 1000pF capacitor across the transistor was not part of the designs I saw on the web, but I needed to add it to suppress high-frequency (around 3MHz) oscillations that occurred. The oscillations were strongest when the current through R2 was large, and the log output high.  I first tried adding a base-emitter capacitor, which eliminated the oscillations, but I still has some lower-frequency oscillations when the transistor was shutting off (very low currents).  Moving the capacitor to be across the whole transistor as shown in the schematic cleaned up both problems.

I put ramp and sine wave inputs into the log amplifier.  The waveforms were generated with the Bitscope function generator, which does not allow setting the offset very precisely—there is only an 8-bit DAC generating the waveform.  Here is a sample waveform:

Click picture for larger image. The green trace is the input, the yellow trace is the output. The horizontal axis in the middle is at 2.5V for the input (so the input is always below 2.5V) and at 3V for the output. The scale is 1V/division for the input and 50mV/division for the output.  [And all those values should be visible in the saved snapshot, but they aren't.]

Using the cursors on the BitScope, I was able to measure the output voltages for input voltages of Vbias-0.5V, Vbias-1V, and Vbias-2.5V.  From these, I concluded that the scaling factor for the output was about 3.1–3.2 mv/dB.  The output was 3±0.07V, so the dynamic range is 140mV/(3.2 mv/dB), or about 44dB.  We can see the logarithmic response in an X-Y plot of the output vs the input:

(Click for larger image) Output vs. input of the log amplifier. Note that the output is the log of Vbias-Vin, so the log curve looks backwards here.  It’s a shame that BitScope throws away the grid on XY plots, as the axes are still meaningful.

I also tried using an external oscillator, so that I could get better control of the offset voltage, and thus (perhaps) a better view of the dynamic range. I could fairly reliably get an output range of about 200mV, without the hysteresis that occurs when the collector-base junction gets forward biased. That would be over 60dB of dynamic range, which should be fine.

I should be able to adjust the voltage offset of the amplifier by changing R2. Increasing R2 reduces the current, which should lower the voltage. I tried several different values for R2 and measured the maximum output voltage, using the same input throughout:

The 60dB difference in current produces a 170mV difference in output, for 2.83 mV/dB.

Oops, those weren’t quite all the same, as the load from the resistor changes the input. Adding a unity-gain buffer driving the inputs and adjusting the input so that the output of the unity gain buffer has a slight flat spot at 0V gives me a new table:

which is consistent with 3mV/dB. I was not able to extend this to lower resistances, as I started seeing limitations on the output current of the op amp. But it is clear that the amplifier can handle a 75dB range of current, with pretty good log response.

An Arduino input is about 5mV/count, so the resolution feeding the output of the log amplifier directly into the Arduino would be about 1.7dB/count. We could use a gain of 4 without saturating an op amp (assuming that we use 2.5V as the center voltage still), for about a 0.4 dB resolution. More reasonably, we could use a gain of 3 to get a resolution of about 0.54dB/count.

I tried that, getting the following table:

This table is consistent with 9.1 mv/dB, for a resolution of about 0.54 dB/step on the Arduino.

I tried using the Arduino to collect the same data and fit with gnuplot:

(click plot to see larger version) The gnuplot fit agrees fairly well with the measurements made with the BitScope for 5 resistor values. The resolution of the Arduino DAC limits the ability to measure the dynamic range, and the cloud of points is broad enough to be consistent with slightly different parameter values.

The next thing for me to do on the log amp is probably to try different PNP transistors, to see how that changes the characteristics. My son will probably want to use a surface-mount transistor, so we’ll have to find one that is also available as a through-hole part, so that we can check the log amplifier calibration.

My son wanted to design a circuit to convert microphone inputs to loudness measurements usable by an Arduino (or other ATMega processor).  We discussed the idea together, coming up with a few different ideas.

The simplest approach would be to amplify the microphone then do everything digitally on the Arduino. There are several features of this approach:

• The analog circuit is about as simple as we can get: a DC-blocking capacitor and an amplifier.  This would only need one op amp, one capacitor, and 2 resistors (plus something to generate a bias voltage—perhaps another op amp, perhaps a low-drop-out regulator).
• Using digital processing, he can do true RMS voltage computation, and whatever low-pass filtering to smooth the result that he wants.
• He can’t sample very fast on the ATMega processor, so high frequencies would not be handled properly.  He might be able to sample at 9kHz (about as fast as the ADC operates), but that limits him to 4.5kHz. For his application, that might be good enough, so this doesn’t kill the idea.
• He’d like to have a 60dB dynamic range (say from 50dB to 110dB) or more, but the ADC in the ATMega is only a 10-bit converter, so a 60dB range would require the smallest signal to be ±½LSB, which is at the level of the quantization noise.  With careful setting of the gain for the microphone preamp, one might be able to get 55dB dynamic range, but that is pushing it a bit.  The resolution would be very good at maximum amplitude, but very poor for quiet inputs.

Although the mostly digital solution has not been completely ruled out, he wanted to know what was possible with analog circuits.  We looked at two main choices:

• True-RMS converter chips (intended for multimeters).  These do all the analog magic to convert an AC signal to a DC signal with the same RMS voltage.  Unfortunately, they are expensive (over $5 in 100s) and need at least a 5v power supply (he is planning to use all 3.3v devices in his design).  Also true RMS is a bit of overkill for his design, as log(amplitude) would be good enough.
• Using op amps and discrete components to make an amplifier whose output is the logarithm of the amplitude of the input.  Together we came up with the following block diagram:

Block diagram of the loudness circuit. (drawn with SchemeIt).

We then spent some time reading on the web how to make good rectifier circuits and logarithmic amplifiers. I’ll do a post later about the rectifier circuits, since there are many variants, but I was most interested in the logarithmic amplifier circuits, which rely on the exponential relationship between current and voltage on a pn junction—often the emitter-base junction of a bipolar transistor.

My son wanted to know what the output range of the log amplifier would be and whether he would need another stage of amplification after the log amplifier. Unfortunately, the theory of the log amplifier uses the Shockley ideal diode equation, which needs the saturation current of the pn junction—not something that is reported for transistors.  There is also a “non-ideality” parameter, that can only be set empirically.  So we couldn’t compute what the output range would be for a log amplifier.

Today I decided to build a log amplifier and see if I could measure the output.  I also wanted to figure out what sort of dynamic range he could get from a log amp. Here is the circuit I ended up with, after some tweaking of parameters:

The top circuit is just a bias voltage generator to create a reference voltage from a single supply. I’m working off of 5v USB power, so I set the reference to 2.5v. He might want to use a 1.65v reference, if he is using 3.3v power.
The bottom circuit is the log amplifier itself.

I chose a PNP transistor so that Vout would be more positive as the input current got further from Vbias.  I have 6 different PNP transistors from the Iteadstudio assortment of 11 different transistors, and I chose the A1015 rather arbitrarily, because it had the lowest current gain. I should probably try each of the other PNP transistors in this circuit, to see how sensitive the circuit is to the transistor characteristics.  I suspect it is very sensitive to them.

The circuit only works if the collector-base junction is reverse-biased (the usual case for bipolar transistors), so that the collector current is determined by the base current. The emitter-base junction may be either forward or reverse biased.  Note that if Vin is larger than Vbias, the collector-base junction becomes forward-biased, the negative input of the op amp is slightly above Vbias, and the op amp output hits the bottom rail.

As long as Vin stays below Vbias, the current through R2 should be , and the output voltage should be for some constants A and B that depend on the transistor. Note that changing R2 just changes the offset of the output, not the scaling, so the range of the output is not adjustable without a subsequent amplifier.

The 1000pF capacitor across the transistor was not part of the designs I saw on the web, but I needed to add it to suppress high-frequency (around 3MHz) oscillations that occurred. The oscillations were strongest when the current through R2 was large, and the log output high.  I first tried adding a base-emitter capacitor, which eliminated the oscillations, but I still has some lower-frequency oscillations when the transistor was shutting off (very low currents).  Moving the capacitor to be across the whole transistor as shown in the schematic cleaned up both problems.

I put ramp and sine wave inputs into the log amplifier.  The waveforms were generated with the Bitscope function generator, which does not allow setting the offset very precisely—there is only an 8-bit DAC generating the waveform.  Here is a sample waveform:

Click picture for larger image. The green trace is the input, the yellow trace is the output. The horizontal axis in the middle is at 2.5V for the input (so the input is always below 2.5V) and at 3V for the output. The scale is 1V/division for the input and 50mV/division for the output.  [And all those values should be visible in the saved snapshot, but they aren't.]

Using the cursors on the BitScope, I was able to measure the output voltages for input voltages of Vbias-0.5V, Vbias-1V, and Vbias-2.5V.  From these, I concluded that the scaling factor for the output was about 3.1–3.2 mv/dB.  The output was 3±0.07V, so the dynamic range is 140mV/(3.2 mv/dB), or about 44dB.  We can see the logarithmic response in an X-Y plot of the output vs the input:

(Click for larger image) Output vs. input of the log amplifier. Note that the output is the log of Vbias-Vin, so the log curve looks backwards here.  It’s a shame that BitScope throws away the grid on XY plots, as the axes are still meaningful.

I also tried using an external oscillator, so that I could get better control of the offset voltage, and thus (perhaps) a better view of the dynamic range. I could fairly reliably get an output range of about 200mV, without the hysteresis that occurs when the collector-base junction gets forward biased. That would be over 60dB of dynamic range, which should be fine.

I should be able to adjust the voltage offset of the amplifier by changing R2. Increasing R2 reduces the current, which should lower the voltage. I tried several different values for R2 and measured the maximum output voltage, using the same input throughout:

The 60dB difference in current produces a 170mV difference in output, for 2.83 mV/dB.

Oops, those weren’t quite all the same, as the load from the resistor changes the input. Adding a unity-gain buffer driving the inputs and adjusting the input so that the output of the unity gain buffer has a slight flat spot at 0V gives me a new table:

which is consistent with 3mV/dB. I was not able to extend this to lower resistances, as I started seeing limitations on the output current of the op amp. But it is clear that the amplifier can handle a 75dB range of current, with pretty good log response.

An Arduino input is about 5mV/count, so the resolution feeding the output of the log amplifier directly into the Arduino would be about 1.7dB/count. We could use a gain of 4 without saturating an op amp (assuming that we use 2.5V as the center voltage still), for about a 0.4 dB resolution. More reasonably, we could use a gain of 3 to get a resolution of about 0.54dB/count.

I tried that, getting the following table:

This table is consistent with 9.1 mv/dB, for a resolution of about 0.54 dB/step on the Arduino.

I tried using the Arduino to collect the same data and fit with gnuplot:

(click plot to see larger version) The gnuplot fit agrees fairly well with the measurements made with the BitScope for 5 resistor values. The resolution of the Arduino DAC limits the ability to measure the dynamic range, and the cloud of points is broad enough to be consistent with slightly different parameter values.

The next thing for me to do on the log amp is probably to try different PNP transistors, to see how that changes the characteristics. My son will probably want to use a surface-mount transistor, so we’ll have to find one that is also available as a through-hole part, so that we can check the log amplifier calibration.

Yesterday, my son was thinking of adding a microphone to the design he is working on, and was considering adding a fast Fourier transform (FFT) to detect pitch.

He spent a few hours after his 10 a.m.–5 p.m. theater class reading about the FFT algorithm. He found an implementation of the FFT for an Arduino, which he tried reading along with the FFT explanations he found on the web.  I’m actually surprised the the Arduino was capable of doing an FFT, given the slowness of the processor.  It is true that the example code only does a 64-sample FFT with a sampling rate of 1kHz, using 8-bit samples and 16-bit integer arithmetic, but it is reported to do it at better than 10 FFTs per second.

I also pointed him to the Discrete Cosine Transform (DCT), which has somewhat smaller boundary artifacts, and can be computed about twice as fast, but he hasn’t had time to read that yet.  Somewhat surprisingly the DCT article in Wikipedia much better written than the general one on Fourier Transforms, which uses awkward notation and a rather dry, formal factoid dump.

I wanted to show him that FFT did not make pitch extraction trivial (at least not in real musical contexts), so I wired up a microphone and amplifier to my BitScope Pocket Analyzer and we turned on some Internet radio (our local public radio station, KUSP).  The complex mass of rapidly shifting peaks in the FFT made it clear that tracking a pitch would not be easy.  (I think that there are some useful pitch-extraction algorithms that are based on FFT, but they are not trivial.) I think I convinced him that he is better off trying to extract loudness than pitch, if he wants a useful control parameter for his device.

Incidentally, he spent some time yesterday looking for cheap electret microphones. There are quite a few on the market, but many of them say “hand solder only” on the datasheets—even some of the ones with just solder pads! There are mics that can be reflow soldered, but finding prices for them in the 100s is difficult—they mostly seem to be quotes from the manufacturers only. One promising one is the SiSonic SPQ2410HR5H-PD, which is only  3.76mm by 2.24mm and uses a ball grid array (it costs 92¢ in 100s, substantially more than 57¢ for the cheapest through-hole mic (though that needs to be hand soldered). CORRECTION 2013 July 10—that’s a MEMS silicon mic, not an electret.

We looked at digital mics that do the A-to-D conversion already, but the only one with a useful output format was the ADMP441, which costs $4.52 in 100s (way too expensive). The cheaper (down to about $1.02) digital mics all use PDM (pulse-density modulation), but to get that into a usable form inside the ATMega, he’d have to low-pass filter it and pass it through the A/D converter. Still, that may not be any more expensive than an analog mic, DC-blocking high-pass filter, and amplifier, though using a separate amplifier would let him design for the proper microphone sensitivity.  He’s going to have to figure out whether the board area and parts cost are worth the extra functionality of the microphone.  If the board area is not a problem, he could design the mic in, but then have the devices only partially populated to save parts costs, if necessary.

We also noticed that we could tell the bandwidth of the radio station we were listening to, because there was a very clear drop in the spectrum at 10kHz.  I tried capturing that this afternoon, but the station we listened to had a talk program rather than a music program, and I never captured a moment when they were using the full bandwidth.  I tried a different Internet music source, and got the following plot, which seemed to indicate a 12kHz bandwidth, but that may have been limited by the music recording they were playing, rather than the codec used for transmission over the internet.

Snapshot of FFT showing a bandwidth of about 12kHz. The grid for the spectrum is 10dB per division vertically and 6kHz per division horizontally.

Before we’d played with sound input, we’d looked at sine waves generated by the BitScope, by connecting a wire from the GEN output to the CHA input. I don’t think I was able to explain to him why the windowing function used for removing boundary artifacts in the FFT results in spreading the single-frequency spikes into wider peaks. It was too late at night to go into the theory of transforms and how multiplication in the time domain turns into convolution in the frequency domain, and vice versa. For that matter, he hasn’t even had convolution yet, so some of the fundamentals needed for the explanation were missing.

At one point I thought that the FFT on the Bitscope was a crude rectangular window, but I was informed by the Bitscope people that they use a Kaiser window. I should have been able to tell that they were doing some sort of windowing by seeing the spread of the spikes for sine waves, but I wouldn’t have been able to guess which window. (It may be buried in the documentation somewhere.) Actually, now that I look at the spikes, they seem too wide for a Kaiser window, unless they set the α parameter much too large.  They only need the sidelobes to be about 60dB down, which should be a much narrower main lobe—not the 18-bin width I think I’m seeing. Perhaps there is something else spreading the peaks, not just the Kaiser window.

Sine wave and FFT analysis of it (Click on image for larger, clearer picture). Note the harmonic distortion (2nd, 3rd, and 4th harmonic at about –40dB, –45dB, and —53dB).
Good luck figuring out the settings of the Bitscope from the information they show on the display!  TB is the time per division on the x-axis of the plot, while BW=120kHz is the full width of the spectrum (so 12kHz per division), and the sine wave is at about 3kHz.

It is interesting to look a a sine wave that is an exact submultiple of the sampling frequency:

Here is a 2975Hz sine wave, where each period should be 8 samples long. Note the appearance of side bands to either side of the main peak. These artifacts are much smaller if we move to a frequency that does not fit so neatly into the FFT buffer.
Note that the time base is different for this screenshot (20ms/division).

We also looked at the spectra of triangle waves and square waves (since the BitScope waveform generator can do those also). Playing with the duty cycle was fun also. I had not been aware that a duty cycle of 1/n on a square wave or triangle wave suppressed the nth, 2nth, 3nth, … harmonics. I had known that a 50% duty cycle square wave or triangle wave suppressed the even harmonics, but I had never thought about other duty cycles.

Triangle wave with 25% duty cycle, showing suppression of the 4th, 8th, 12th, and 16th harmonics.

Yesterday, my son was thinking of adding a microphone to the design he is working on, and was considering adding a fast Fourier transform (FFT) to detect pitch.

He spent a few hours after his 10 a.m.–5 p.m. theater class reading about the FFT algorithm. He found an implementation of the FFT for an Arduino, which he tried reading along with the FFT explanations he found on the web.  I’m actually surprised the the Arduino was capable of doing an FFT, given the slowness of the processor.  It is true that the example code only does a 64-sample FFT with a sampling rate of 1kHz, using 8-bit samples and 16-bit integer arithmetic, but it is reported to do it at better than 10 FFTs per second.

I also pointed him to the Discrete Cosine Transform (DCT), which has somewhat smaller boundary artifacts, and can be computed about twice as fast, but he hasn’t had time to read that yet.  Somewhat surprisingly the DCT article in Wikipedia much better written than the general one on Fourier Transforms, which uses awkward notation and a rather dry, formal factoid dump.

I wanted to show him that FFT did not make pitch extraction trivial (at least not in real musical contexts), so I wired up a microphone and amplifier to my BitScope Pocket Analyzer and we turned on some Internet radio (our local public radio station, KUSP).  The complex mass of rapidly shifting peaks in the FFT made it clear that tracking a pitch would not be easy.  (I think that there are some useful pitch-extraction algorithms that are based on FFT, but they are not trivial.) I think I convinced him that he is better off trying to extract loudness than pitch, if he wants a useful control parameter for his device.

Incidentally, he spent some time yesterday looking for cheap electret microphones. There are quite a few on the market, but many of them say “hand solder only” on the datasheets—even some of the ones with just solder pads! There are mics that can be reflow soldered, but finding prices for them in the 100s is difficult—they mostly seem to be quotes from the manufacturers only. One promising one is the SiSonic SPQ2410HR5H-PD, which is only  3.76mm by 2.24mm and uses a ball grid array (it costs 92¢ in 100s, substantially more than 57¢ for the cheapest through-hole mic (though that needs to be hand soldered). CORRECTION 2013 July 10—that’s a MEMS silicon mic, not an electret.

We looked at digital mics that do the A-to-D conversion already, but the only one with a useful output format was the ADMP441, which costs $4.52 in 100s (way too expensive). The cheaper (down to about $1.02) digital mics all use PDM (pulse-density modulation), but to get that into a usable form inside the ATMega, he’d have to low-pass filter it and pass it through the A/D converter. Still, that may not be any more expensive than an analog mic, DC-blocking high-pass filter, and amplifier, though using a separate amplifier would let him design for the proper microphone sensitivity.  He’s going to have to figure out whether the board area and parts cost are worth the extra functionality of the microphone.  If the board area is not a problem, he could design the mic in, but then have the devices only partially populated to save parts costs, if necessary.

We also noticed that we could tell the bandwidth of the radio station we were listening to, because there was a very clear drop in the spectrum at 10kHz.  I tried capturing that this afternoon, but the station we listened to had a talk program rather than a music program, and I never captured a moment when they were using the full bandwidth.  I tried a different Internet music source, and got the following plot, which seemed to indicate a 12kHz bandwidth, but that may have been limited by the music recording they were playing, rather than the codec used for transmission over the internet.

Snapshot of FFT showing a bandwidth of about 12kHz. The grid for the spectrum is 10dB per division vertically and 6kHz per division horizontally.

Before we’d played with sound input, we’d looked at sine waves generated by the BitScope, by connecting a wire from the GEN output to the CHA input. I don’t think I was able to explain to him why the windowing function used for removing boundary artifacts in the FFT results in spreading the single-frequency spikes into wider peaks. It was too late at night to go into the theory of transforms and how multiplication in the time domain turns into convolution in the frequency domain, and vice versa. For that matter, he hasn’t even had convolution yet, so some of the fundamentals needed for the explanation were missing.

At one point I thought that the FFT on the Bitscope was a crude rectangular window, but I was informed by the Bitscope people that they use a Kaiser window. I should have been able to tell that they were doing some sort of windowing by seeing the spread of the spikes for sine waves, but I wouldn’t have been able to guess which window. (It may be buried in the documentation somewhere.) Actually, now that I look at the spikes, they seem too wide for a Kaiser window, unless they set the α parameter much too large.  They only need the sidelobes to be about 60dB down, which should be a much narrower main lobe—not the 18-bin width I think I’m seeing. Perhaps there is something else spreading the peaks, not just the Kaiser window.

Sine wave and FFT analysis of it (Click on image for larger, clearer picture). Note the harmonic distortion (2nd, 3rd, and 4th harmonic at about –40dB, –45dB, and —53dB).
Good luck figuring out the settings of the Bitscope from the information they show on the display!  TB is the time per division on the x-axis of the plot, while BW=120kHz is the full width of the spectrum (so 12kHz per division), and the sine wave is at about 3kHz.

It is interesting to look a a sine wave that is an exact submultiple of the sampling frequency:

Here is a 2975Hz sine wave, where each period should be 8 samples long. Note the appearance of side bands to either side of the main peak. These artifacts are much smaller if we move to a frequency that does not fit so neatly into the FFT buffer.
Note that the time base is different for this screenshot (20ms/division).

We also looked at the spectra of triangle waves and square waves (since the BitScope waveform generator can do those also). Playing with the duty cycle was fun also. I had not been aware that a duty cycle of 1/n on a square wave or triangle wave suppressed the nth, 2nth, 3nth, … harmonics. I had known that a 50% duty cycle square wave or triangle wave suppressed the even harmonics, but I had never thought about other duty cycles.

Triangle wave with 25% duty cycle, showing suppression of the 4th, 8th, 12th, and 16th harmonics.

I’ve been thinking of expanding the pressure sensor lab for the Applied Circuits Course to do something more than just measure breath pressure.  Perhaps something that conveys another physics or engineering concept.

One thing I thought of doing was measuring the back pressure and air flow on an aquarium air pump bubbling air into an aquarium. Looking at the tradeoff of flow-rate and back pressure would be a good characterization of an air pump (something I wish was clearly shown in advertisements for aquarium air pumps and air stones).  Measuring flow rate is a bit of a pain—about the best I could think of was to bubble air into an inverted soda bottle (or other known volume) and time it.

This would be a good physics experiment and might even make a decent middle-school product-science science fair project (using a cheap mechanical low-pressure gauge, rather than an electronic pressure sensor), but setting up tanks of water in an electronics lab is a logistic nightmare, and I don’t think I want to go there.

I can generate back pressure with just a simple clamp on the hose, though, and without a flow rate measurement we could do everything completely dry.

Setup for measuring the back pressure for an aquarium air pump (needs USB connection for data logger and power).

Using the Arduino data loggger my son wrote, I recorded the air pressure while adjusting the clamp (to get the y-axis scale correct, I had to use the estimated gain of the amplifier based on resistor sizes used in the amplifier).

The peak pressure, with the clamp sealing the hose shut, seems to be about 14.5 kPa (2.1psi).

I was interested in the fluctuation in the pressure, so I set the clamp to get about half the maximum back pressure, then recorded with the Arduino data logger set to its highest sampling frequency (1ms/sample).

The fluctuation in back pressure seems to have both a 60Hz and a 420Hz component with back pressure at about half maximum.

Because the Arduino data logger has trouble dealing with audio frequency signals, I decided to take another look at the signals using the Bitscope pocket analyzer.

The waveform for the pressure fluctuations from the AQT3001 air pump, with the back pressure about 7.5kPa (half the maximum).

One advantage of using the Bitscope is that it has FFT analysis:

Spectrum for the back pressure fluctuation. One can see many of the multiples of 60Hz, with the particularly strong peak at 420Hz.

I was also interested in testing a Whisper40 air pump (a more powerful, but quieter, pump). When I clamped the hose shut for that air pump, the hi-gain output of the amplifier for the pressure sensor saturated, so I had to use the low gain output to determine the maximum pressure (24.8kPA, or about 3.6psi). The cheap Grafco clamp that I used is a bit hard to get complete shutoff with (I needed to adjust the position of the tubing and use pliers to turn the knob).  It is easy to get complete shutoff if the tube is folded over, but then modulation of less than complete shutoff is difficult.

The fluctuation in pressure shows a different waveform from the AQT3001:

The Whisper40 air pump, with the clamp set to get a bit less than half the maximum back pressure, produces a 60Hz sawtooth pressure waveform, without the strong 420Hz component seen from the AQT3001. The peak-to-peak fluctuation in pressure seems to be largest around this back pressure. The 3kPa fluctuation is larger than for the AQT3001, but the pump seems quieter.

The main noise from the pump is not from the fluctuation in the pressure in the air hose, but radiation from the case of the pump. That noise seems to be least when the back pressure is about 1.1kPa (not at zero, surprisingly). The fluctuation is then all positive pressure, ranging from 0 to 2.2kPa and is nearly sinusoidal, with some 2nd and 3rd harmonic.

As the back pressure increases for the Whisper40, the 2nd, 3rd, and 4th harmonics get larger, but the 60Hz fundamental gets smaller. The 4th harmonic is maximized (with the 1st through 4th harmonics almost equal) at about 22.8kPa, above which all harmonics get smaller, until the air hose is completely pinched off and there is no pressure variation.

When driving the large airstone in our aquarium, the Whisper40 has a back pressure of about 7.50kPa (1.1psi) with a peak-to-peak fluctuation of about 2.6kPa.

I’m not sure whether this air-pump back-pressure experiment is worth adding to the pressure sensor lab.  If I decide to do it, we would need to get a dozen cheap air pumps.  The Tetra 77853 Whisper 40 air pump is $11.83 each from Amazon, but the smaller one for 10-gallon aquariums is only $6.88.  With 12 Ts and 12 clamps, this would cost about $108, which is not a significant cost for the lab.