Event Triggered Analog Data Acquisition Using the Exponential Moving Average

The Defence Science and Technology Organisation has developed a number of sensor interfaces and an associated versatile, low-power networked sensor design, and protocol for structural monitoring of naval vessels. A consideration for many data acquisition system such as these is the large data sets that are easily gathered. This requires large hard discs to store the data and also can strain the resources required to analyze the data. In many instances much of the data may be collected during periods of inactivity and are of no interest. This can be avoided if data logging is triggered on the detection of significant events and thus only occurs when there are data of interest. This paper considers the implementation of event triggered data acquisition based on event windows centered on an exponential moving average (EMA) formed from the incoming signal. The frequency dependence of the EMA complicates the understanding of event triggering and is thoroughly examined. Noise can result in false triggering of data logging and considerations on how to avoid this are also discussed. It is concluded that the EMA is a valuable technique that can be easily implemented within the limited computational resources of microcontrollers and is thus suitable for smart sensor interfaces.