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Sensor Fault Detection for Superconducting Cable Monitoring System based on Swarm Optimization BP Neural Network

A reliable sensor network is essential for the superconducting cable monitoring system and designing an efficient sensor fault detection method is very important for the stable operation of the system. Aiming at the problem of sensor fault detection in superconducting cable monitoring system, a sensor fault detection method using particle swarm optimization BP neural network algorithm is presented. In the experiment, the real data collected in the cable monitoring system is used and the result show that the method has better performance compared with traditional BP neural network algorithms. A prototype software for model verification and application is established. It shows that the sensor fault detection system can detect a variety of sensor faults accurately and quickly.