Operating Reliability Assessment Of Rotating Machinery Based On Information Processing And Cosine Similarity

With the social demand,the function of mechanical equipment has higher requirements,and its structure is more complex.The average reliability based on a large number of data and mathematical statistics is difficult to meet the needs of equipment operation reliability assessment,so the operation reliability assessment based on equipment status information has been paid more and more attention.By establishing the relationship between the operating state information and the reliability of the equipment,the operating state of the equipment can be evaluated.Based on signal processing,this paper studies feature extraction and operation reliability evaluation,and proposes a operation reliability evaluation method based on information processing and cosine similarity,which is applied to rotating machinery.Firstly,in order to obtain the valid data in the running state of the device,a state feature extraction method based on fast variational modal decomposition,fuzzy approximate entropy and principal component analysis is proposed.The method uses fast variational mode decomposition and fuzzy approximate entropy to process the signals generated during the operation of the equipment,and then using principal component analysis to perform feature extraction,It can reduce the redundant data generated in the signal processing process,and the proposed method is applied to the measured signals of bearings to verify its effectiveness.Secondly,through the analysis of the performance degradation law of mechanical equipment,and aiming at the problem that the evaluation result of the operation reliability described by the support vector data is inconsistent with the actual performance degradation law of the equipment,cosine similarity is introduced on the basis of information processing in this paper,a cosine similarity evaluation model based on state information is proposed.And the proposed evaluation model is applied to the measured signals of rolling bearings to verify its effectiveness.Finally,the collected experimental data under different operating states of gears are analyzed by using the operation reliability assessment method based on informationprocessing and cosine similarity proposed in this paper.The experimental results show that the method proposed in this paper is not only effective in distinguishing the running states of gears,but also close to the performance degradation law of gears.