Choosing Proper Filters for High-Speed Accelerometer Impact Sensing

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SUMMARY

The discussion focuses on selecting appropriate filters for high-speed accelerometer impact sensing using the ADXL375 or ADXL1001 accelerometers. The goal is to sample at a minimum of 10,000 S/s for accurate measurement of peak accelerations during crash tests. The consensus is to implement an anti-aliasing low-pass filter with a cutoff frequency of 5 kHz to ensure proper signal reconstruction while adhering to the Nyquist theorem. The conversation highlights the importance of understanding the relationship between sampling rates, filter choices, and the specific measurement goals in crash testing scenarios.

PREREQUISITES
  • Understanding of Nyquist sampling theory
  • Familiarity with low-pass and high-pass filter design
  • Knowledge of accelerometer specifications, particularly the ADXL375 and ADXL1001
  • Basic electronics principles, including ADC bit depth considerations
NEXT STEPS
  • Research anti-aliasing filter design techniques
  • Learn about the specifications and applications of the ADXL375 and ADXL1001 accelerometers
  • Study the implications of sampling rates on data accuracy and signal integrity
  • Explore advanced filtering methods, such as Chebyshev filters, for specific applications
USEFUL FOR

Engineers and researchers involved in crash testing, particularly those focusing on high-speed impact measurements and data analysis from accelerometers.

ConnorM
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I’m planning on using the ADXL375 (200g/3200Hz Bandwidth) or ADXL1001 (100g/11,000Hz Bandwidth) to measure the peak accelerations in a crash test dummy’s head during a bicycle/car crash. My goal is to sample at atleast 10,000 S/s using either a Teensy 3.6 or a Rasp Pi3.

The dummy will be mounted on the bike and launched at 20km/hr, then it will be struck by a car from the rear and from the side driving at 30km/hr.

My question is about filter choice after the analog accelerometer that I choose. Should a low or high pass filter be chosen, and where should the corners be?
I would just like some guidance and I’d like to learn how I can go about choosing proper filters for sensors. I have taken a course on electronics that briefly covered Chebychev and other popular filters.
 
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What filter you choose depends on what you are trying to resolve. You would certainly want some kind of anti-aliasing low-pass filter, but whether you wanted your cutoff to be lower than Nyquist or a high-pass of any kind depends on your measurement goals, really.
 
So for my situation,

- I am looking to measure the acceleration of a crash test dummy’s head during a very brief impact (15milliseconds).

- I want to be able to measure the accelerometer at 10 kSamples/s

- The current accelerometer that I am looking at measures +/-150 g’s with a bandwidth of 2 Hz —> 20 kHz (https://www.digikey.com/product-detail/en/te-connectivity-measurement-specialties/1-1001220-0/MSP1001-ND/279641)

What from these should I be using to determine my filter? I obviously want to be able to look at my acceleration data after and be able to analyze the head acceleration with as little noise from other sources as possible.
 
Is there any reason you want 10 kS/s? That's extremely overkill for your chosen sensor.
 
10 kS/s is the specified minimum sample rate that sensors in crash test dummy’s should be sampled at. This is a design project through my school and we are trying to get as close to this sample rate as possible.

Also, 10 kS/s will give us some assurance that the peak acceleration was captured.
 
Actually I misread your last post. Still, look up sampling theory and the Nyquist rate. In order to resolve the full 20 kHz of your sensor you would need to sample at 40 kHz. Since you are so far limited to 10 kHz, it means any content above 5 kHz in your signal will be lost. It also means you should use an anti-aliasing filter with a 5 kHz cutoff. You can look up anti-aliasing to check that out.
 
Oh thank you I have been reading about Nyquist Theory and you finally clued me into where the filtering aspect comes into play. This sensor can output 20 kHz but I can cut this to 5 kHz via a LPF, so I can sample at 10 kS/s for a full reconstruction of the analog wave.

So this would this ensure a smoother digital output? Are there any considerations I should make that would give me the clearest possible digital reconstruction?
 
You might also consider the bit depth of your ADC.
 
Do you have an idea of how much deflection you expect the accelerometer to experience on impact?
 
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  • #10
It's always good to do a sanity check before you start building so that you know that it's going to work. So let's throw a few numbers around and see what happens.

In the first example with the bike going 20 km/hr, the car 30 km/hr and approaching from behind, the difference in speed is 10 km/hr. You are expecting the impact to ocurr in less than 15 ms with a peak acceleration of less than 150 G's. Converting everything to meters and seconds we get v = 2.78 m/s. Since I can only calculate average acceleration instead of peak, I'm going to use 75 G's instead of 150. v = a*t so t = 0.00378 s or 3.78 ms. (I multiplied 75 G's by 9.8 to get acceleration in m/s^2 of 735.) Using these numbers the bicyclist's head would move 735*0.00378^2/2 or 0.525 cm during impact? Does that seem reasonable?

Using the side collision at 30 km/hr the numbers we get are t = 11.3 ms, a = 75 G's and the distance the head moves during impact is 4.72 cm. Is this what you're expecting?
 
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