所属单位：自动化学院
发表刊物：Proc. - Progn. Syst. Health Manag. Conf., PHM-Paris
摘要：Planetary gearboxes are widely used in aerospace, marine and other important equipment for their unique advantages, and their health directly affects whether the equipment can work normally. The vibration signal generated when the fault occurs is extremely complicated, making it difficult to perform an effective diagnosis. In order to solve this problem, a planetary gearbox fault diagnosis method based on autocorrelation noise reduction combined with an improved convolutional neural network is proposed. The method firstly performs autocorrelation noise reduction on the fault signal. Secondly, the noise-reduced signal is used as the input of CNN for automatic feature extraction. The classifier is used to finally complete the intelligent diagnosis of the planetary gearbox. © 2019 IEEE.
是否译文：否
发表时间：2019-05-01
合写作者：Sun, Guodong,Sun, Canfei
通讯作者：王友仁
发表时间：2019-05-01