Hi Anderson!

If you're looking for away to do this inside the PLC a good way is to use a floating average:

2,3 + 4,5 + 6,7 + ....... +3,3 (n)
n
Then you adjust the value of elements in the numerator to make a smooth value.

Regards Mårten

Have look at this:

FILTERED_SIGNAL:= K*FILTERED_SIGNAL + (1-K)*ACTUAL_ANALOG_SIGNAL
K - should be in range from 0 to 1, close to 0 weak filter, close to 1 strong filter

As K can be changed during runtime, you can tune this filter without changing program.

I agree that "smoothing", as far as it isan established expression is the best way to accomplish a filtered signal.

consider implementing the floating average functionality that I suggested in my first post,

n = nbr of input values
AI = signal that should be filtered
F_OUT = filtered signal

then F_OUT := (AI+(n-1)*F_OUT)/n substitute n = 1/K and use some algebra...

=> F_OUT := AI*K+(1-K)*F_OUT) which is the same as what jacek d suggested but the other way around.

If n i.e. nbr of elements in the numerator is equal to 1 => K=1 and F_OUT = AI.

So I guess I join in that "smoothing" is the best way to implement this.

Late I don't have the Simatic Manager here but I will have a look at your code later.

Regards Mårten

I know, that it is a polemic theme, but I want do some considerations:

If you use a filter of the type: out = last out + k * in, you have a new calculated value in each program cycle. However, a past value has a “weight” for a long time. So, it reacts quickly but has also inertia.

If you use a mean (average) formulation, statisticly, you can clear any random noise. However you need some samplings, i.e. your filtered value is always “old”. So it is applicable if you can sample your signal quickly as you need.

Better as mean is a regression analysis to a f(y)= a * t +b, so, you can obtain a more precise value at the last sample moment.

Dear Pegaia,
guy is asking how to smooth input signal - possibly in a PLC (what you could suspect from the name of this conference). And your answer is to use a linear reggresion. Don't you think that's a little bit overkill ?

BTW, I like this: "So, it reacts quickly but has also inertia." - so it's fast and slow at same time. Neat.