Fault Detection for Enclosed Board with Autocorrelation Analysis

The board of control system is a key for accuracy of data acquisition. It is a challenge to judge the status of with tunnels of board because the board is always working on an enclosed way in order to safety and reliability which leads to their inner states be unmeasurable directly. In this paper a novel approach is proposed to detect the status of board by only using external time series information. The data series are analyzed by autocorrelation theory and the shape comparison is employed to the target sequence. Then the fault of the enclosed board channel is diagnosed according to the data autocorrelation characteristics. The simulation shows the proposed approach is effective.