A COMPARISON OF 3 TIME-DOMAIN ANOMALY DETECTION METHODS

Three anomaly detection methods based on a comparison of signal values with predictions from an autoregressive model are presented. These me thods are: the extremes method, the chi(2) method and the sequential p robability ratio test. The methods are used to detect a change of the standard deviation of the residual noise obtained from applying an aut oregressive model. They are fast and can be used in on-line applicatio ns. For each method some important anomaly detection parameters are de termined by calculation or simulation. These parameters are: the false alarm rate, the average time to alarm and - being of minor importance - the alarm failure rate. Each method is optimized with respect to th e average time to alarm for a given value of the false alarm rate. The methods are compared with each other, resulting in the sequential pro bability ratio test being clearly superior.