Online Change Detection Algorithm Based on the Continuous Wavelet Transform, the CUSUM Algorithm and an Autoregressive Model

Abstract

In this article, we present a change point detection algorithm based on the continuous wavelet transform, the CUSUM algorithm and an autoregressive model. At the beginning of the article, we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that, we show how the CUSUM algorithm works on our testing signals. Then we describe the structure of AR models which can be used to improve change detection abilities of the CUSUM algorithm. Finally, we present the results of our proposed approach. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.