传感器数据处理
我正在开发一个带有激光跳闸探测器的系统（如果有东西破坏了激光路径，我会在激光接收器的输出上得到一个）。
我有很多这样的行程检测器，我想检测其中一个是否出现故障，但我不知道如何去做。激光器不应该经常跳闸……也许一天几次。
典型的情况是激光器跳闸 0.5-2 秒，或者短时间短暂间歇跳闸，并且可能在此之后再次跳闸（在 2-10 秒内）...
是否有任何好的方法来检查使用良好的统计方法时传感器出现故障？
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 malfunctioning, 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?
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您可以创建一个“配置文件”，其中包括每个传感器跳闸频率的平均/平均值/最小/最大/跳闸多长时间/一次行程与下一次行程之间的时间等，例如通过使用某个时间段的数据，例如上周/上个月或类似的数据...
然后您可以将传感器的当前状态与其配置文件进行比较...当偏差“足够大”时，您可以假设一种特殊情况/也许故障...最难的部分是调整阈值与配置文件的偏差，如果命中则触发例如“故障处理”......
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"...