Processing of sensor data

I am working on a system with laser trip detectors(if something breaks the laser path I get a one on the output of the laser receiver).

I have many of these trip detectors and I want to detect if one is malfunctio开发者_如何学运维ning, but I do not know how to go about doing this. The lasers should not trip all that often..maybe a few times a day.

A typical case would be that the laser gets tripped for a .5-2 seconds, or brief intermittent tripping for a short time period, and possibly again after that(within 2-10 seconds)...

Are there any good ways to check the sensor is malfunctioning using a good statistical methodology?

You could just create a "profile" which includes the avg/mean/min/max of how often each sensor is tripped/how long it is tripped/how long is the time between a trip and the next trip etc. for example by using the data of some period of time like the last week/month or similar...

THEN you can compare the current state of a sensor to its profile... when the deviation is "big enough" you can assume an exceptional situation/perhaps a malfunction... the hardest part is to adjust the threshold for the deviation from the profile which in turn if hit triggers for example "malfunction handling"...