Fault detection for wireless networked systems with compressed measurements

In this paper, the fault detection problem is investigated for a class of wireless networked systems with compressed measurements. A new compressed fault detection framework is proposed. The measurement data is compressed with a compressed sensing technique before being transferred to the fault detection node via wireless communication channel. Besides, the influence of compressed measurements on fault detectability is analyzed and a new fault detection method is provided based on the integration of model-based and statistical methods. The residual generator is designed by the available compressed measurements and priori knowledge about the system, and the statistic testing method is developed to determine whether there is a fault. Maintaining the acceptable fault detection performance, the compressed fault detection framework can greatly reduce the cost of data acquisition, transmission and storage. As the compressed data is utilized directly in the fault detection process, our method can also reduce computational requirements and enhance the efficiency of the whole fault detection system. Finally, a simulation study is carried out to demonstrate the effectiveness and applicability of the proposed method.