An Intelligent Sensing Algorithm for Early Warning of Equipment Failure in Hydropower Stations

In view of the problem that hydropower station equipment is prone to multiple faults during operation, and to detect SF6 gas leakage faults, this paper proposes a gas detection method based on differential photoacoustic spectroscopy. First, differential absorption photoacoustic spectroscopy technology is used to detect flowing SF6 gas. The system includes a detection module, acquisition module, sampling module, amplification module, control module, and calculation module. Nitrogen is used as power to control the six-way valve for information exchange. SF6 gas is quantitatively injected, samples are transmitted, and the photoacoustic signal is amplified and analyzed. Then, the equipment state space model is constructed, and the particle filter algorithm is applied for state variable estimation. The process is divided into state prediction, update, and resampling. Finally, the residual value is obtained by comparing the real-time measured value and the estimated value, and an adaptive threshold method is added to detect equipment faults and avoid false alarms. The experimental results show that the system in this paper detects a vibration signal of 0.89[Formula: see text]V when the current is 1000[Formula: see text]A, and has a good early warning effect on contact system faults and point faults.