Circuit breaker contact system fault assessment method based on multi-task deep learning
A technology of fault assessment and contact system, applied in the direction of neural learning methods, information technology support systems, instruments, etc., can solve problems such as operators' distribution network security threats, circuit breaker property losses, etc., and achieve average accuracy and improve Accuracy, effect of reducing model parameters
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[0053] The fault evaluation method of the circuit breaker contact system based on multi-task deep learning of the present embodiment, the specific steps are as follows:
[0054] The first step is to build a fault test platform with DW15-1600 universal circuit breaker as the test product, and use the LC0159 acceleration sensor to measure the vibration signal, the acceleration sensor is powered by the LC0201 signal conditioner, and the vibration signal is sampled by the USB-7648A data acquisition card, the sampling frequency is 20kHz, and the single vibration sampling time is 250ms;
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