> You can get an excellent tool for characterizing
various filters from
> Nuhertz Technologies (www.nuhertz.com). I used their Filter Free
Ta, will have a look when time permits.
> One aspect of this filtering discussion that needs
mentioning is sample
> rate.
> You can have an excellent filter algorithm set up, and lose all
> benefits from it by sampling at the wrong rate.
The theory says to sample at least at twice the frequency of interest, I believe
in oversampling a tad, just in case.
One of the reasons lenghty algoritms can be counter productive, you can run out
of CPU cycles real quick even when dealing with things happening on a geological
time scale.
Cheers,
Theo
Reply by theobee00●March 8, 20042004-03-08
--- In , "Redd, Emmett R" <EmmettRedd@s...>
> > > Now stuff that into your excel
spreadsheet !!!
> >
> > Don't think excel has a clock.
>
> As a model, Excel works because each column (or row) can represent the
> calculation performed at each successive, uniformly spaced, time step.
>
In the context of the discussion clock meant, take ADC sample, put in cell, do
average, shift result to next group of cells etc.
For that you need a clock synchronised to the sample rate.
But hey, knowing M$ and their tendency to built in a few thousand extra features
a week, it probably is capable of that as well:-)
Cheers,
Theo
Reply by Darrell N.●March 8, 20042004-03-08
You could try this:
Average = 80%(OldSample) + 20%(NewSample). Store Average at
OldSample.
The percentages can be changed to whatever you want. This does
not require a big buffer or serious calculations. It does have
some disadvantages, however.
This gives rudimentary filtering, but you can sprinkle it around
in your code after calculations to make things smoother.
I also use a 16 value ring filter, where the new value is added
to a sum, and the oldest value is subtracted out. For 16 bit
values, this requires 32 bytes of buffer, a 2 byte sum, and a 2
byte pointer, as well as your original and filtered values.
This is a total of 40 bytes, which is a pretty good chunk of
RAM.
> I thought about doing it like this, but it would
need to have a
> large array to average the samples, and I can't afford the RAM
> space that would use.
>
> I'm sure there must be some clever way of doing this without
> using an array - just can't see it yet.
You can get an excellent tool for characterizing various filters from
Nuhertz Technologies (www.nuhertz.com). I used their Filter Free tool
years ago while researching digital filters for an embedded project. The
tool I used then (version 2.0) generated frequency response graphs,
electrical schematic equivalents, and transfer functions, which made code
generation much easier.
One aspect of this filtering discussion that needs mentioning is sample
rate. You can have an excellent filter algorithm set up, and lose all
benefits from it by sampling at the wrong rate. One product I worked on
was originally set up with an IIR filter tailored for 60Hz rejection, but
the software guy was executing it every 100 ms (10 Hz sample rate). Checks
with the Nuhertz tool showed that this resulted in 0 db filtering. By
using the same IIR filter, but sampling at an 11 Hz rate, 60Hz noise
rejection was better than -45 db. This improvement was confirmed in later
lab tests.
Karl
linktek
<linktek@shaw. To:
ca> cc:
Subject: Re: [68HC12] Re: Software Filtering of an ADC input
03/07/2004
01:58 PM
Please respond
to 68HC12
Hi,
You can always use IIR or a more computative FIR software filter with
taylored coefficients.
However, on the KISS solution. Lets say the problem is lack of data
memory. You would like a
adjustable software filter - field tunable. So how about a cascaded
running
average filter. In stead of one long array, you first average
the first 8 samples into a running average, and stuff the result of the
first average into a second array doing a running average of the results of
the first running average output in another 8 sample array and so on and so
on .... till you run out of memory. Its obvious to see that this is a
easely
tunable filter algorithm.
Now stuff that into your excel spreadsheet !!!
(deletia...)
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Reply by Redd, Emmett R●March 8, 20042004-03-08
See below.
Emmett Redd Ph.D. mailto:
Associate Professor (417)836-5221
Department of Physics, Astronomy, and Materials Science
Southwest Missouri State University Fax (417)836-6226
901 SOUTH NATIONAL Dept (417)836-5131
SPRINGFIELD, MO 65804 USA
> -----Original Message-----
> From: theobee00 [mailto:]
> Sent: Monday, March 08, 2004 1:10 AM
> To:
> Subject: [68HC12] Re: Software Filtering of an ADC input
>
> --- In , linktek <linktek@s...> wrote:
> > Now stuff that into your excel spreadsheet !!!
>
> Don't think excel has a clock.
As a model, Excel works because each column (or row) can represent the
calculation performed at each successive, uniformly spaced, time step.
>
>
> Cheers,
>
> Theo
Reply by Bruce McMillan●March 8, 20042004-03-08
Since you're working in assembler, here's some code that does
the
recursive smoothing described below...
--- In , "Robert Smith" <bobsmith5@e...> wrote: > Andrew --
>
> I have used the following method with good results on several projects:
>
> 1. Allocate an accumulator in RAM to hold the running average.
>
> 2. For every A/D sample update the accumulator as follows:
>
> Accum = (Prior Accum * 7/8) + 1/8 * New Sample.
>
> Working in assembler this is almost trival to implement. Use shifts and
> accumulates.
>
> Shift 'Prior Accum' left 3 to obtain 1/8 of 'Prior
Accum'
>
> Subtract 1/8 Prior Accum from 'Prior Accum' to obtain 7/8
'Prior Accum'
>
> Now compute 1/8 of 'New Sample' by shifting right 3 and add this
to '7/8
> Prior Accum' to
> obtain the Updated accumulator and smoothed value.
>
> The smoothing factor of 1/8 was arbitrairly chosen but is representative of > factors that have worked well in the past.
>
> You can adjust the "degree of filtering" by using different
smoothing
> factors such as 1/4 or 1/16.
> This only requires that you adjust the shift counts.
>
> Note: If you do this all in fixed point, you can expect to see binary
> truncation effects in the result. In effect the output will develop a dead > zone such that new samples very near the running
average will not affect the > filter output. The output will jump from one
smoothed value to another as > the new samples change by a few counts. This
creates a sort of dead zone > effect. This is an inevitble consequence of binary
truncation and will show > up in any filtering technique that you devise.
>
> It is much better to eliminate the noise at the source by careful attention > to hardware design and to use little or no
software filtering.
>
> Warning: Be very careful to consider the dynamic range of the intermediate > results of this calculation. Binary overfow at any
step of this process
> will produce absolute rubbish for output!!!
>
> You can examine the results of this filtering process by clever use of
> Excel.
>
> Good Luck, Bob Smith
>
>
Reply by theobee00●March 8, 20042004-03-08
--- In , linktek <linktek@s...> wrote:
> You can always use IIR or a more computative FIR
software filter with
> taylored coefficients.
Of course, the problem is the more 'interesting' the filter, the more
chance you have of introducing stability problems in control loops due to the
phase shifts.
It lets you specify the type of filter you want to use, corner frequencies,
poles etc, it shows you the graphs of freq, phase, impulse etc, and to top it
of, writes the C code for you with the parameters neatly filled in, piece of
cake.
> average filter. In stead of one long array, you
first average
> the first 8 samples into a running average, and stuff the result of the
> first average into a second array doing a running average of the results
of
> the first running average output in another 8 sample array and so on and
so
> on .... till you run out of memory. Its obvious to see that this is a
easely
> tunable filter algorithm.
If I read that right it's a simple to compute averaging filter over
8/64/128/etc samples, or did I miss something?
> Now stuff that into your excel spreadsheet !!!
Don't think excel has a clock.
Cheers,
Theo
Reply by Donald E Haselwood●March 7, 20042004-03-07
Andy,
From a frequency viewpoint, an average is a low-pass filter. For the
number of "taps" (values stored) it is not the sharpest filter. The
computation is simple, however, as shown in previous posts, and it has a
sharper cutoff than the simple RC digital filter.
The book, Digital Filters, R.W. Hamming, 1977, Prentice-Hall, has a section
on the frequency response of averages. The book (quite readable) is out of
print, but probably can be located through a university library system. In
case your interested, the passband equ:
H(w) = (w * sin(m+1/2) ) / ( (2*m+1)*sin(w/2) )
where w = freq (radians), m = number of taps
Here is a chapter of a (very readable) DSP book you can download (free)
that also talks about averages. He points out that the average is a filter
that responds the quickest to a step input, so for some situations it is
optimal. http://www.dspguide.com/ch15.htm
You mention "20%" for the filtering. That sounds like you are thinking
in
terms an IIR (infinite impluse response) filter, such as the simple digital
implementation of a RC filter, also in the previous posts. If you
implement that form for filter make sure the storage for the accumulated
value will accommodate the largest value. As that "%" gets smaller,
which
has the effect of making the cut-off freq lower, the accumulated value gets
very large (but, unlike the circular buffer/average filter, only one value
has to be stored, so it doesn't take a lot of memory).
The characteristics of the signal you are measuring determines the which
type of filter is best (assuming it fits in memory!). The IIR/RC type of
filter "remembers" a big glitch, or noise spike, "forever,"
i.e. a noise
spike takes a long time to "fade away," whereas the averaging
filtering
drops a big number after one cycle around the buffer.
Regards,
Donald E Haselwood
At 07:04 AM 3/7/04, you wrote: >I guess this is a bit of a general question, rather
than a specific
>HCS12 question, but I want to implement it on an HCS12.....
>
>I want to be able to 'filter' the value returned from an on-board
ADC.
>When I say 'filter' I think that perhaps 'average' would
be a better
>description.
>
>I want to be able to set an amount of filtering (say 20%) and none of
>the descriptions of digital filters I've found seem to allow this.
>They all seem to be designed to filter a specific frequency range that
>must be stated in the calculations used to design the filter.
>
>I thought about having a ring buffer to which you place the ADC
>results at a constant time interval, then summing the buffer, and
>dividing by the number of samples taken. But then how do you allow for
>the amount of filtering you want to apply ??
>
>I'm going round in circles with this !!
>
>Any thoughts or ideas would be very much appreciated.
>
>I also need the routine to be fairly quick and not take up too much
>RAM as I'm getting a bit short on it.
>
>Andy
>
>--------------------To learn more
>about Motorola Microcontrollers, please visit
><http://www.motorola.com/mcu" target="_blank" rel="nofollow">http://www.motorola.com/mcu>http://www.motorola.com/mcu
>o learn more about Motorola Microcontrollers, please visit
><http://www.motorola.com/mcu" target="_blank" rel="nofollow">http://www.motorola.com/mcu>http://www.motorola.com/mcu
>
>
>----------
>>Yahoo! Terms of Service.
Reply by Steve Russell●March 7, 20042004-03-07
Andy,
I can't resist summarizing what I understand from the previous
correspondence on this topic and Jack Crenshaw's columns in Embedded
Systems Programming. See this mailing list archive for a thread starting
on Jun 28, 2003 8:43 pm
with subject: OT: digital filtering.
Filter in hardware before sampling to reduce the noise in the digital
values due to high frequency noise in the input signal. The high frequency
noise WILL be there, so just do this, don't worry about it.
A simple RC filter will do if you have bandwidth to spare, which is likely.
The ideal is to have a "brick wall" filter that has zero attenuation
at
half the sampling frequency, and very large attenuation at the sampling
frequency and beyond.
A simple RC filter is fairly far from this ideal, but setting its cutoff
frequency as low as you can afford will help.
If the highest frequency of interest is well below a reasonable sampling
rate, then use some sort of digital low pass filter, such as averaging, is
needed.
The equivalent of an RC filer, which several have suggested, is the simple
filter which takes a fraction of the input and a fraction of the current
average and adds them.
I believe that the simplest statement of this in C is:
Avg +=( Avg - CurSample ) >> n.
Where Avg and CurSample are 16 bit fractions.
This takes a 16-bit subtract, a shift, and a 16-bit add. No array is
needed. There is a problem when n is 6 or greater because then you start
throwing away significant bits from CurSample. This can be gotten around
by clever code that makes Avg in effect a 24 or 32 bit fraction.
The corner frequency of this filter is set by n. You should choose it to
be above the highest frequency of interest, but probably not as much as 8
times has high.
The software filter is much cheaper that an analog filter for low
frequencies.
Hope this helps.
Steve Russell
Nohau Emulators
At 04:04 AM 3/7/2004, you wrote: >I guess this is a bit of a general question, rather
than a specific
>HCS12 question, but I want to implement it on an HCS12.....
>
>I want to be able to 'filter' the value returned from an on-board
ADC.
>When I say 'filter' I think that perhaps 'average' would
be a better
>description.
>
>I want to be able to set an amount of filtering (say 20%) and none of
>the descriptions of digital filters I've found seem to allow this.
>They all seem to be designed to filter a specific frequency range that
>must be stated in the calculations used to design the filter.
>
>I thought about having a ring buffer to which you place the ADC
>results at a constant time interval, then summing the buffer, and
>dividing by the number of samples taken. But then how do you allow for
>the amount of filtering you want to apply ??
>
>I'm going round in circles with this !!
>
>Any thoughts or ideas would be very much appreciated.
>
>I also need the routine to be fairly quick and not take up too much
>RAM as I'm getting a bit short on it.
>
>Andy
*************************************************************************
Steve Russell mailto:
Senior Software Design Engineer http://www.nohau.com
Nohau Corporation phone: (408)866-1820 ext. 1873
51 East Campbell Avenue fax: (408)378-7869
Campbell, CA 95008
*************************************************************************
Reply by linktek●March 7, 20042004-03-07
Hi,
You can always use IIR or a more computative FIR software filter with
taylored coefficients.
However, on the KISS solution. Lets say the problem is lack of data
memory. You would like a
adjustable software filter - field tunable. So how about a cascaded running
average filter. In stead of one long array, you first average
the first 8 samples into a running average, and stuff the result of the
first average into a second array doing a running average of the results of
the first running average output in another 8 sample array and so on and so
on .... till you run out of memory. Its obvious to see that this is a easely
tunable filter algorithm.
Now stuff that into your excel spreadsheet !!!
I adjustable software filter can take the for of I
----- Original Message -----
From: "theobee00" <>
To: <>
Sent: Sunday, March 07, 2004 12:48 PM
Subject: [68HC12] Re: Software Filtering of an ADC input
--- In , "Andrew Leech" <andrew_leech@y...> wrote:
> I want to be able to 'filter' the value
returned from an on-board ADC.
> When I say 'filter' I think that perhaps 'average'
would be a better
> description.
> I want to be able to set an amount of filtering
(say 20%) and none of
> the descriptions of digital filters I've found seem to allow this.
> They all seem to be designed to filter a specific frequency range that
> must be stated in the calculations used to design the filter.
Hi Andrew,
I am not sure if I read you right but it seems you are trying to compensate=
for some sort of noise in the incoming signal.
I have found it is best to consider analogue signals in their entirety, the=
bane of the computer programmers.
I.e. the origin of the signals is important because it determines the frequ=
ency range of interest.
Say a small motor with a varying load needs a faster response time then a w=
eigh-cell where accuracy is of more importance and the final measurement
may=
take a second or so.
So it is best to start a project with the input considerations first, lower=
the required frequency response as far as possible first of.
Say for the small motor it could mean a flywheel or other means of mass inc=
rease, for a weigher it could mean a dashpot.
The next step is to minimise the frequency response from amplifiers and oth=
er electronics to what the measurement requires, and of course to what the
c=
omputer can handle.
Since this is a relatively cheap step, don't spare the caps, it will
preven=
t all sorts of aliassing problems in your digital filters if the signal
vari=
ations (or mains noise) don't get that far or are minimised before they
get
=
to the converters.
I can't over stress that, you will find it takes an amazingly long time
and=
an even more amazing sample rate to get some form of accuracy in a signal
e=
mbedded in a sine-wave, to say nothing about reduced headroom in the signal
=
paths etc.
Keep it out of a device that has to work in a sample/hold fashion and only =
has a limited A/D accuracy as far as possible.
The last step is the one you are interested in, the measurement and/or cont=
rol loop in the computer.
You will find there are as many schemes as there are Engineers, but in the =
end they all try to do the same thing, provide a digital low pass filter in
=
some form or another, the cut of frequencies, poles etc determined by how
ke=
en the designer is and how fast the computer.
There are some rather involved tomes that will give you all the good stuff,=
but it is very rare to have to go that far, simple solutions usually
suffic=
e in most situations.
I.e. a few stages of RC low pass filtering limiting the signals presented t=
o the lowest frequency needed, followed by something similar in the
computer=
is usually enough to serve the purpose.
The trade of in computer filters is of course easily seen, the more involve=
d the filter, the slower your sample rate (or the faster the computer has
to=
be), often negating the gains by introducing aliassing problems.
I.e. sampling at a rate that coincides with some harmonic or other of the i=
ncoming signal will cause all sorts of grief.
If you have made sure to keep higher frequencies out of the signal path in =
the first place, a simple exponential scheme along the lines of adding the
n=
ew value to a multiple of the previous value and weighing it back usually
su=
ffices.
If you find you have to lower the cut of frequency beyond the time availabl=
e, re-evaluate the input filtering rather then trying to compensate in the
C=
PU with all sorts of interesting algorithms.