426 / 2017-04-27 17:08:02

Health status centered mechanical feature extraction for high voltage circuit breakers

health status,feature extraction,mechanical characteristics

Mechanical characteristics, including the displacement curves of the movable contacts and coil current waves are the most common routine monitoring objects of high voltage circuit breakers to evaluate the machine’s condition. Generally, a high-performance mechanical characteristic tester has the ability to offer dozens of parameters consisting of stroke, speed, magnitude of current and so on. Besides, lots of new features have been proposed for specific needs. So choosing useful features from all the features above becomes an inevitable problem. However, most of the features are extracted focusing on fault diagnosis and rare attention has been paid to the health condition evaluation. Here, a new health status centered mechanical feature extraction method is proposed. Firstly, a large-scale feature selection is carried out among 44 closing features and 50 opening features by monotonicity and consistency. Then the most sensitive ones are fed into a bottle-neck neural networks for supervised feature extraction by their remaining useful life. Real data collected from several high voltage circuit breakers of full life circle were used in the experimental studies, with the results showing the superiority of the extracted features.