摘要
To overcome the problem that a single feature can not reflect the state of machinery in different stages,a method of vibration feature fusion based on self-organizing map(SOM) is presented.Minimum quantization error(MQE) is obtained unsupervised based on SOM network.And trend information of the MQE curve is extracted by the wavelet packet to enhance state differentiating.Experimental flat is designed for bearing accelerating fatigue.And experimental results show that the method of vibration feature fusion based on SOM can reflect the state of machinery in different stages effectively.
To overcome the problem that a single feature can not reflect the state of machinery in different stages,a method of vibration feature fusion based on self-organizing map（SOM） is presented.Minimum quantization error（MQE） is obtained unsupervised based on SOM network.And trend information of the MQE curve is extracted by the wavelet packet to enhance state differentiating.Experimental flat is designed for bearing accelerating fatigue.And experimental results show that the method of vibration feature fusion based on SOM can reflect the state of machinery in different stages effectively.
作者简介
Correspondence should bc addressed to LI Kang, E-mail： dalianshu @ gmail. com
