基于云模型的多信道电机故障信号择优选取

Optimized selection of multichannel fault signals of motor based on cloud model

在当前电机故障诊断领域已实现多传感器多信道故障信号采集的背景下,针对如何有效处理高维电机故障数据以达到快速、准确诊断的难题,提出云隶属度新模型与多信道信号择优选取方法.该方法首先将属性相似算法与逆向云发生器相结合求取传感器位置权重与隶属基准值,进而引入正云发生器,得到各个信道信号的数字特征,最后根据云运算原理求取各个信号的云隶属度,以实现择优选取部分信道信号,达到减小多信道信号的冗余性的效果.通过实例仿真分析验证该方法的可行性.

Against the background that acquisition of multichannel-multitransducer fault signals in current field of motor fault diagnosis has already realized and aimed at the challenge of how to effectively deal with the problem of high-dimensional data of motor fault to achieve rapid and accurate diagnosis,a new model of cloud membership and optimized selection method of multichannel signal is proposed.In this method,the weights of sensor positions and standard value of membership is found first by combining the attribute similarity algorithm and backward cloud generator,then the digital feature of each channel signal is obtained by introducing forward cloud generator,and finally,according to the principle of cloud operation the cloud membership degree of each signal is found to realize optimized selection of partial channel signals and achieve the result of reduction of the redundancy of the multichannel signal.It is verified by actual simulation analysis that this method will be feasible.