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thanks + how to detect a persistent signal anomaly

(i'm posting here because i could adopt both an hardware or software solution (having a fixed point dsp available); _if you think i'm off-topic_ and that the solution lies on the software side, i can re-post the question on comp.dsp, virtually "closing" the thread here...)

hello

i would like to thank you for the answers to this thread

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which have been *extremely* useful and effective both in understanding my problem better and as a solution; after some exploration we chose a specific gaussian filter which - for the kind of application i'm working on - behaves "spectacularly well" ;-)

now to _my current problem_ (i'm looking for *any generic hint about the subject*, then i will google about what you suggest):

i would like to recognize an incoming persistent anomaly of the signal (for example "sudden offset increase": what should be "zero" suddenly becomes +2 because of sudden voltage skew and stays like that for a reasonably long amount of time (not a "spike"), or sudden "white noise" because a wire gets loose, or....)

i would like to do that "as fast as possible" (where "fast" means "with the shortest latency/delay possible with respect to the appearance of the anomaly on the signal")

does exist a standard way of dealing with anomalies? a "toolset of procedures" i can study to understand what i can do?

since i think that the kind of problems i can face could be related to the sensor technologies: i'm using cheap micromachined capacitive accelerometers. the system can tolerate the specific sensor noise but i don't know how they can _malfunction_.

thank you again, guys! gst

Reply to
gst
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What's your signal? Google "maximal likelyhood detection". You need to model your signal, perhaps using more than one sensor, and model.

Now, generate a signal with differences between your model (where 'difference' is dependant on your measuring) and your signal.

For example, with a diesel engine, if your input is a vibration sensor next to the crankshaft, and an additional sensor is a voltage divisor on an injector, with a crank position sensor as a third, you might have four seperate models running. One which uses all three sensors, and one each with a sensor missing. You flag an error on significant divergance.

Reply to
Ian Stirling

right now i'm googling for MLE/MLD thanks

the signal:

- i have the 1 accelerometer for each axis (thus no redundancy right now, but i could ask for more...)

- basically i have to quickly detect a mechanical shock, and distinguish it from an anomaly.

- the shock detection must be very very quick, thus i think i cannot see enough signal to find peculiar frequencies if they exist (and being the shock a sort of "prolonged impulse" i don't think they are there, i cannot spot them using fft analysis or "eyeball detection" ;-) ). right now i distinguish it from normal behaviour using only time/amplitude information.

- the shock is itself something very different from the usual/statistical behaviour of the system (where everything is usually "quiet")

- i think this could be a problem to distinguish it from a quick voltage increase caused by an hardware problem.....

Reply to
gst

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