Re: method for digital filtering


teilersen wrote:

As for the non-uniform sampling. I don't get what that looks like. Your
not saying the sampling rate increases as a function of the load
applied? At any rate it may be a function of something so even though
your coordinate system may not be time you may have a uniform coordinate
system.

To be honest then I am not sure myself what it will look like. The sensor
measures two capacitors between each sample.
One will increase and the other will decrease, but it is the reciprocal
value of the capcitans which are linear with the force so I think it will
be some kind of a s-kurve.

Yes but what is the relationship of the sample spacing to real time and
what makes it non-uniform. Is it the weight of the object or the speed
of the belt? It isn't just randomly taking a sample every now and then
is it?



You have a sampling of the step response that should be good enough.
Getting the IR from that would just be a high pass filter that probably
adds nothing useful. But it might not be a bad idea to look at that.

Why do I get the IR If I high pass filter the signal?

In the digital domain finding the derivative or integral is functionally
just a high or low pass filter respectively. That's a bit simplified but
not much. The step response is the integral of the IR.


Jerry wrote that my "trapezoidal" signal will mostely contain low
frequncies.

Yes and one might guess that the low frequencies contain the information
you want. Finding the IR will involve removing the low frequencies
(removes DC completely) so I would guess it wouldn't be that helpful.


If I multiply that with my the IR in the frequency domain then

I suppose I get the frequency spectrum of the signal I measure.
I do not expext to get the IR back from a simple low pass filtering. I
would expect that I would have to try deconvolution which is hard because
I have zeroes in the frequency domain of the input (the "trapezoidal")

What you need to do is find something in there that correlates
accurately to the weight of the object. Maybe its the total energy over
a period of time or maybe its the magnitude of a certain frequency at
some point in the process. Once you know what your looking for you can
think about the design of a filter to achieve that.

Sounds like a good idea, but I am not sure how I should do that in
practice?

Well you need data for objects of known weight. If you find that certain
frequencies remain the same no matter what the object weighs then
filtering those frequencies out might be a logical first step. At that
point you would know what the filter you want to design is intended to
do.
My point

-jim

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