Research on Fault Diagnosis of Control System Based on Multi-sensor Data Fusion Algorithm

With the progress of science and technology nowadays and the enhancements in control system optimization field, system fault diagnosis has become a hot topic in the industry, and many models of fault diagnosis using various artificial intelligence algorithms have emerged. However, with the increasing complexity of fault, the accuracy of fault diagnosis from a single data source gradually declines. Based on this, this paper proposal an intelligent diagnosis model innovationally basing on multi-sensor intelligent fusion algorithm, which uses BP neural network, a typical artificial intelligence algorithm, to generate evidence from multi-sensor data, on this basis, D-S evidence theory is used for data fusion to improve the accuracy of fault diagnosis and the performance of fault diagnosis algorithm in multi-type control systems.