I'm new at programming the Beaglebone Black and to Linux in general, so I'm trying to figure out what's happening when I'm setting up a SPI-connection. I'm running Linux beaglebone 3.8.13-bone47.
I have set up a SPI-connection, using a Device Tree Overlay, and I'm now running spidev_test.c to test the connection. For the application I'm making, I need a quite specific frequency. So when I run spidev_test and measure the frequency of the bits shiftet out, I don't get the expected frequency.
I'm sending a SPI-packet containing 0xAA, and in spidev_test I've modified the "spi_ioc_transfer.speed_hz" to 4000000 (4MHz). But I'm measuring a data transfer frequency of 2,98MHz. I'm seeing the same result with other speeds as well, deviations are usually around 25-33%.
How come the measured speed doesn't match the assigned speed?
How is the speed assigned in "speed_hz" defined?
How precise should I expect the frequency to be?
Thank you :)
Actually If you look closely on the DSO you can see that each clock cycles takes approx 312.5 ns , which makes the clock frequency to be 3.2Mhz,. May be the channel you're monitoring i
Then, the variation between the expected & actual speed,
In microncontrollers I've worked the all the peripherlas including the SPI derives ots clock from the Master clock which is supplied to the MCU(in your case MPU), the master frequency divided by some prescalar gives the frequency for periperal opearations, where as peripherals use this frequency and uses its prescalar for controlling the baud rate,
So in your case suppose if the master frequency is not proper this could lead to the behavior mentioned above.
So you have two options
1. Correct the MPU core frequency
2. Do a trial & error method to find the value which has to be given is spi test program to get the desired frequency
Related
My goal is to record audio using an electret microphone hooked into the analog pin of an esp8266 (12E) and then be able to play this audio on another device. My circuit is:
In order to check the output of the microphone I connected the circuit to the oscilloscope and got this:
In the "gif" above you can see the waves made by my voice when talking to microphone.
here is my code on esp8266:
void loop() {
sensorValue = analogRead(sensorPin);
Serial.print(sensorValue);
Serial.print(" ");
}
I would like to play the audio on the "Audacity" software in order to have an understanding of the result. Therefore, I copied the numbers from the serial monitor and paste it into the python code that maps the data to (-1,1) interval:
def mapPoint(value, currentMin, currentMax, targetMin, targetMax):
currentInterval = currentMax - currentMin
targetInterval = targetMax - targetMin
valueScaled = float(value - currentMin) / float(currentInterval)
return round(targetMin + (valueScaled * targetInterval),5)
class mapper():
def __init__(self,raws):
self.raws=raws.split(" ")
self.raws=[float(i) for i in self.raws]
def mapAll(self):
self.mappeds=[mapPoint(i,min(self.raws),max(self.raws),-1,1) for i in self.raws ]
self.strmappeds=str(self.mappeds).replace(",","").replace("]","").replace("[","")
return self.strmappeds
Which takes the string of numbers, map them on the target interval (-1 ,+1) and return a space (" ") separated string of data ready to import into Audacity software. (Tools>Sample Data Import and then select the text file including the data). The result of importing data from almost 5 seconds voice:
which is about half a second and when I play I hear unintelligible noise. I also tried lower frequencies but there was only noise there, too.
The suspected causes for the problem are:
1- Esp8266 has not the capability to read the analog pin fast enough to return meaningful data (which is probably not the case since it's clock speed is around 100MHz).
2- The way software is gathering the data and outputs it is not the most optimized way (In the loop, Serial.print, etc.)
3- The microphone circuit output is too noisy. (which might be, but as observed from the oscilloscope test, my voice has to make a difference in the output audio. Which was not audible from the audacity)
4- The way I mapped and prepared the data for the Audacity.
Is there something else I could try?
Are there similar projects out there? (which to my surprise I couldn't find anything which was done transparently!)
What can be the right way to do this? (since it can be a very useful and economic method for recording, transmitting and analyzing audio.)
There are many issues with your project:
You do not set a bias voltage on A0. The ADC can only measure voltages between Ground and VCC. When removing the microphone from the circuit, the voltage at A0 should be close to VCC/2. This is usually achieved by adding a voltage divider between VCC and GND made of 2 resistors, and connected directly to A0. Between the cap and A0.
Also, your circuit looks weird... Is the 47uF cap connected directly to the 3.3V ? If that's the case, you should connect it to pin 2 of the microphone instead. This would also indicate that right now your ADC is only recording noise (no bias voltage will do that).
You do not pace you input, meaning that you do not have a constant sampling rate. That is a very important issue. I suggest you set yourself a realistic target that is well within the limits of the ADC, and the limits of your serial port. The transfer rate in bytes/sec of a serial port is usually equal to baud-rate / 8. For 9600 bauds, that's only about 1200 bytes/sec, which means that once converted to text, you max transfer rate drops to about 400 samples per second. This issue needs to be addressed and the max calculated before you begin, as the max attainable overall sample rate is the maximum of the sample rate from the ADC and the transfer rate of the serial port.
The way to grab samples depends a lot on your needs and what you are trying to do with this project, your audio bandwidth, resolution and audio quality requirements for the application and the amount of work you can put into it. Reading from a loop as you are doing now may work with a fast enough serial port, but the quality will always be poor.
The way that is usually done is with a timer interrupt starting the ADC measurement and an ADC interrupt grabbing the result and storing it in a small FIFO, while the main loop transfers from this ADC fifo to the serial port, along the other tasks assigned to the chip. This cannot be done directly with the Arduino libraries, as you need to control the ADC directly to do that.
Here a short checklist of things to do:
Get the full ESP8266 datasheet from Expressif. Look up the actual specs of the ADC, mainly: the sample rates and resolutions available with your oscillator, and also its electrical constraints, at least its input voltage range and input impedance.
Once you know these numbers, set yourself some target, the math needed for successful project need input numbers. What is your application? Do you want to record audio or just detect a nondescript noise? What are the minimum requirements needed for things to work?
Look up in the Arduino documentartion how to set up a timer interrupt and an ADC interrupt.
Look up in the datasheet which registers you'll need to access to configure and run the ADC.
Fix the voltage bias issue on the ADC input. Nothing can work before that's done, and you do not want to destroy your processor.
Make sure the input AC voltage (the 'swing' voltage) is large enough to give you the results you want. It is not unusual to have to amplify a mic signal (with an opamp or a transistor), just for impedance matching.
Then you can start writing code.
This may sound awfully complex for such a small task, but that's what the average day of an embedded programmer looks like.
[EDIT] Your circuit would work a lot better if you simply replaced the 47uF DC blocking capacitor by a series resistor. Its value should be in the 2.2k to 7.6k range, to keep the circuit impedance within the 10k Ohms or so needed for the ADC. This would insure that the input voltage to A0 is within the operating limits of the ADC (GND-3.3V on the NodeMCU board, 0-1V with bare chip).
The signal may still be too weak for your application, though. What is the amplitude of the signal on your scope? How many bits of resolution does that range cover once converted by the ADC? Example, for a .1V peak to peak signal (SIG = 0.1), an ADC range of 0-3.3V (RNG = 3.3) and 10 bits of resolution (RES = 1024), you'll have
binary-range = RES * (SIG / RNG)
= 1024 * (0.1 / 3.3)
= 1024 * .03
= 31.03
A range of 31, which means around Log2(31) (~= 5) useful bits of resolution, is that enough for your application ?
As an aside note: The ADC will give you positive values, with a DC offset, You will probably need to filter the digital output with a DC blocking filter before playback. https://manual.audacityteam.org/man/dc_offset.html
There are several "hi-res" timestamping functions in ALSA:
snd_pcm_status_get_trigger_htstamp
snd_pcm_status_get_audio_htstamp
snd_pcm_status_get_driver_htstamp
snd_pcm_status_get_htstamp
I would like to understand what points in time the resulting functions represent.
My current understanding is that trigger_htstamp represents the time when stream was started/stopped/paused. snd_pcm_status_get_trigger_htstamp returns a constant value and when I add audio_htstamp to that value the result is very close to the current system time.
audio_htstamp seems to start from zero on my system and it is incremented by a value that is equal to the period size I use. Hence on my system it is a simple frame counter. If I understand ALSA correctly audio_htstamp can also work in different more accurate way depending on the system capabilities.
driver_htstamp I guess by the name is a timestamp generated by the audio driver.
Question 1: When is the timestamp driver_htstamp usually generated?
With htstamp I am really unsure where and when it is generated. I have a hunch that it may be related to DMA.
Question 2: Where is htstamp generated?
Question 3: When is htstamp generated?
Question 4: Is the assumption audio_htstamp < htstamp < driver_htstamp generally correct?
It seems like this with a little test program I wrote, but I want to verify my assumption.
I can not find this information in the ALSA documentation.
I just dug through the code for this stuff for my own purposes, so I figured I would share what I found.
The purpose of these timestamps is to allow you to determine subtle differences in the rate of different clocks; most importantly in this case the main system clock that Linux uses for general timekeeping compared with the different clock that determines the rate at which samples move in and out of the sound device. This can be very important for applications that need to keep audio from different hardware devices in sync, since the rates of different physical clocks are never exactly the same.
The technique used is sometimes called "cross-timestamping"; you capture timestamps from the clocks you want to compare as close to simultaneously as possible, and repeat this at regular intervals. There is usually some measurement error introduced, but some relatively simple filtering can get you a good characterization of the difference in the rate at which the clocks count.
The core PCM driver arranges to take a system clock timestamp as closely as possible to when an audio stream starts, and then it does a cross-timestamp between the system clock and audio clock (which can be measured in different ways) whenever it is asked to check the state of the hardware pointers for the DMA engine that moves samples around.
The default method of measuring the audio clock is via DMA hardware pointer comparsion. This isn't terribly precise, but over longer periods of time you can still get a good measure of the rate difference. At the start of snd_pcm_update_hw_ptr0, a system timestamp is captured; this will end up being htstamp. The DMA pointers are then checked, and if it's determined that they've moved since the last check, audio_htstamp is calculated based on the number of frames DMA has copied and the nominal frequency of the audio clock. Then, once all the DMA pointer update is done and right before snd_pcm_update_hw_ptr0 returns, another system timestamp is captured in driver_htstamp. This isn't meant to be used when you're using the DMA hw_ptr method of calculating the audio_htstamp though.
If you happen to have an audio device using the HDAudio driver, you can use an alternate and much more precise method of measuring the audio clock. It supplies an extra operation callback called get_time_info that is used instead of the default method of capturing the system and audio timestamps. It the HDAudio case, it takes a system timestamp for htstamp as close to possible to when it reads an interal counter driven by the same clock source as the audio clock; this forms the audio_htstamp. Afterwards, the same DMA hw_ptr bookkeeping is done, but the code that translates the pointer movement into time is skipped. The driver_htstamp is still taken right before the routine ends, though; this is "to let apps detect if the reference tstamp read by low-level hardware was provided with a delay" as the comment says in the code. This is because there's no guarantee that the get_time_info callback is going to take a new system timestamp; it may have previously recorded an audio timestamp along with a system timestamp as part of an interrupt handler. In this case, the timestamps you get might not match with the available frames and delay frames counts calculated by hw_ptr bookkeeping, but the driver_htstamp will let you know the closest system time to when those calculations were made.
In any case, the code is designed in both cases to capture htstamp and audio_htstamp as closely together as possible, and for htstamp - trigger_htstamp to represent the amount of system time that passed during the period measured by audio_htstamp of the audio clock. You mostly shouldn't need to use driver_htstamp, but I guess it might be used with the USB Audio driver, as I think it and HDAudio are the only ones that do anything special with these interfaces right now.
The documentation for this, although it doesn't contain all the details you might want to know, is part of the kernel documentation: http://lxr.free-electrons.com/source/Documentation/sound/alsa/timestamping.txt?v=4.9
I am beginning a project using GNUradio and an inexpensive SDR.
http://www.amazon.com/gp/product/B00SXZDUAQ?psc=1&redirect=true&ref_=oh_aui_search_detailpage
One portion of the project requires me to generate a reference audio tone and compare the phase of that tone to demodulated audio.
To simulate this portion of the system, I have generated a simple GNUradio flowchart:
I had some issues with the source and demodulated audio in that they would drift relative to each other. This occurred on the scope sync on the original flowgraph. To aid in troubleshooting I sent the demodulated audio out thru the soundcard’s second channel and monitored both audio streams in addition to the modulated RF on an external oscilloscope:
Initially all seems well but, the demodulated audio drifts in relation to the original source and RF:
My question is: am I doing something wrong in the flowgraph or am I expecting too much performance out of an inexpensive SDR?
Thanks in advance for any insights
You cannot expect to see zero phase drift in anything short of a fully digital simulation, or a fully analog circuit with exactly one oscillator, because no two (physical) oscillators have identical frequencies.
In your case, there are two relevant oscillators involved:
The sample clock in the RTL-SDR unit.
The sample clock in your sound card output.
Within an GNU Radio flowgraph, there is no time reference per se and everything depends on the sources and sinks which are connected to hardware.
The relevant source in your flowgraph is the RTL-SDR hardware; insofar as its oscillator is different from its nominal value (28.8 MHz, as it happens), everything it produces will be off-frequency in an absolute sense (both RF carrier frequencies and audio frequencies of demodulated output).
But you don't actually have an absolute frequency reference; you have the tone produced by your sound card. The sound card has its own oscillator, which determines the rate at which samples are converted to analog signals, and therefore the rate at which samples are consumed from the flowgraph.
Therefore, your reference signal will drift relative to your received and demodulated signal, at a rate determined by the difference in frequency error between the two oscillators.
Additionally, since your sound card will be accepting samples from the flowgraph at a slightly different real-time rate than the RTL-SDR is producing them, you will notice periodic glitches in the audio as the error accumulates and must be dealt with; they will start occurring either immediately (if the source is slower than the sink, requiring the sound card to play silence instead) or after a delay for buffers to hit their maximum size (if the source is faster than the sink, requiring the RTL-SDR to drop some samples).
I need to tune PI(D) gains in a system which has a quite large delay. It's a common temperature controller, but the temperature probe is far away from the heater. Some further info:
the response of the probe is delayed about 10 seconds from any change on the heater
the temperature is sampled # 1 Hz, with a resolution of 0.01 °C
the heater is controller in PWM with a period of 1 Hz, with a 10-bit PWM
the goal is to maintain the oscillation below ±0.05 °C
Currently I'm using the controller as PI. I can't avoid oscillations. The higher the gain, the smaller and faster the oscillations. Still too high (about ±0.15 °C).
Reducing the P and I gains leads to very long and deep oscillations.
I think this is due to the delay.
The settling time is not a problem, it may take all the time it needs.
I'm puzzling over how get the system to work. Let's think to use only I. When the probe reaches the target value and the I output starts to decrease, the temperature will rise for some other time. I cannot use the derivative term because the variations are too slow and the dError is very close to zero (if I set the dGain to a huge value there is too much noise).
Any idea?
Try P-only. How fast are the proportional-only oscillations? If you can't tune Kp small enough to get no oscillations, then your heater is overpowered for your system.
If the dead time of the of the system is on the order of 10s, the time constant (T_i) for the Integral term should be 3.3 times the dead time, using a Ziegler Nichols open-loop PI rule ( https://controls.engin.umich.edu/wiki/index.php/PIDTuningClassical#Ziegler-Nichols_Open-Loop_Tuning_Method_or_Process_Reaction_Method: ) , and then Integral term should be Ki = Kp/T_i. So with deadtime = 10s, then Ki should be Kp/33 or slower.
If you are getting integral-only oscillations, then the integral is winding up and down quicker than the process responds, and it should be even smaller.
Also -- think of the units of the different terms. It might not be the delay causing your problems so much as the resolution of the measurement and control systems. If you're driving a (for example) 100W heater with a 1/1024 resolution PWM, you've got 0.1W resolution per PWM count that you are trying to adjust based on 0.01C temperature differences. At less than Kp = 100 PWMcount/degree (or 10W/degree) you don't have enough resolution in the PWM to make changes in response to a 0.01C error. At a Kp=10PWM/C you might need a 0.10C change to result in an actual change in the PWM power. Can you use a higher resolution PWM?
Thinking of it the other way, if you want to operate a system over a range of 30C at 0.01C, I'd think you would want at least a 15bit PWM to have 10 times the resolution in the controlled system. With only 10 bits of PWM you only get about 1C of total range with control at 10x the resolution of the measurements.
Normally for large delays you have two options: Lower the gains of the system or, if you have a model of the plant you are controlling, use a Smith Predictior.
I would start by modelling your system (using open-loop steps in the input) to quantify the delay and the time constant of your plant, then check if the sampling of the temperature and the PWM rate are OK.
Notice that if your PWM frequency is too small in comparison to the plant dynamics, you will have sustained oscillations because of the slow PWM. You can check it using just an constant input to your PWM (with no controllers, open loop).
EDIT: Didn't see that the problem was already solved, but I'll leave this here for reference.
I am doing some performance profiling for part of my program. And I try to measure the execution with the following four methods. Interestingly they show different results and I don't fully understand their differences. My CPU is Intel(R) Core(TM) i7-4770. System is Ubuntu 14.04. Thanks in advance for any explanation.
Method 1:
Use the gettimeofday() function, result is in seconds
Method 2:
Use the rdtsc instruction similar to https://stackoverflow.com/a/14019158/3721062
Method 3 and 4 exploits Intel's Performance Counter Monitor (PCM) API
Method 3:
Use PCM's
uint64 getCycles(const CounterStateType & before, const CounterStateType &after)
Its description (I don't quite understand):
Computes the number core clock cycles when signal on a specific core is running (not halted)
Returns number of used cycles (halted cyles are not counted). The counter does not advance in the following conditions:
an ACPI C-state is other than C0 for normal operation
HLT
STPCLK+ pin is asserted
being throttled by TM1
during the frequency switching phase of a performance state transition
The performance counter for this event counts across performance state transitions using different core clock frequencies
Method 4:
Use PCM's
uint64 getInvariantTSC (const CounterStateType & before, const CounterStateType & after)
Its description:
Computes number of invariant time stamp counter ticks.
This counter counts irrespectively of C-, P- or T-states
Two samples runs generate result as follows:
(Method 1 is in seconds. Methods 2~4 are divided by a (same) number to show a per-item cost).
0.016489 0.533603 0.588103 4.15136
0.020374 0.659265 0.730308 5.15672
Some observations:
The ratio of Method 1 over Method 2 is very consistent, while the others are not. i.e., 0.016489/0.533603 = 0.020374/0.659265. Assuming gettimeofday() is sufficiently accurate, the rdtsc method exhibits the "invariant" property. (Yep I read from Internet that current generation of Intel CPU has this feature for rdtsc.)
Methods 3 reports higher than Method 2. I guess its somehow different from the TSC. But what is it?
Methods 4 is the most confusing one. It reports an order of magnitude larger number than Methods 2 and 3. Shouldn't it be also kind of cycle counts? Let alone it carries the "Invariant" name.
gettimeofday() is not designed for measuring time intervals. Don't use it for that purpose.
If you need wall time intervals, use the POSIX monotonic clock. If you need CPU time spent by a particular process or thread, use the POSIX process time or thread time clocks. See man clock_gettime.
PCM API is great for fine tuned performance measurement when you know exactly what you are doing. Which is generally obtaining a variety of separate memory, core, cache, low-power, ... performance figures. Don't start messing with it if you are not sure what exact services you need from it that you can't get from clock_gettime.