基于光纤传感的轴承异常状态识别研究

Research on Bearing Abnormal State Identification Based on Optic Fiber Sensing

为了解决当前轴承异常状态识别过程中存在的难题,提高轴承异常状态识别效果,提出了一种基于光纤传感的轴承异常状态识别方法。首先采用光纤传感技术获得轴承异常状态信号,并对轴承异常状态信号进行预处理,消除轴承异常状态信号中一些无用信息,然后将处理后的轴承异常状态信号输入到隐马尔科夫模型进行学习和训练,建立轴承异常状态识别的分类器,并对分类器参数进行优化,接着根据分类器进行轴承异常状态的识别,最后采用具体的实例进行了轴承异常状态识别的仿真测试。测试结果表明,这种方法的轴承异常状态识别正确率高,减少了轴承异常状态的漏识率和误识率,同时轴承异常状态识别时间短,加快了轴承异常状态识别速度,获得了理想的轴承异常状态识别结果。

In order to solve the problems existing in the process of bearing abnormal state recognition,and improve the effect of bearing abnormal state recognition,a bearing abnormal state recognition method based on optical fiber sensing is proposed in this paper.Firstly,the optical fiber sensing technology is used to obtain the bearing abnormal state signal,and the bearing abnormal state signal is preprocessed to eliminate some useless information of the bearing abnormal state signal.Then,the processed bearing abnormal state signal is input to the hidden semi Markovian model for learning and training,and the classifier of bearing abnormal state recognition is established,and the classifier parameters are optimized.Finally,the algorithm is used to identify the bearing abnormal state.According to the classifier,the abnormal state of the bearing is identified.Finally,the simulation test of the abnormal state of the bearing is carried out with a specific example.The test results show that the proposed method has high recognition accuracy of bearing abnormal state,reduces the missing recognition rate and error recognition rate of bearing abnormal state,shortens the recognition time of bearing abnormal state,speeds up the recognition speed of bearing abnormal state,and obtains ideal recognition results of bearing abnormal state.