Design And Implementation Of Bearing Health Status Evaluation System Based On Data Fusion Technology

In the case of equipment monitoring and fault diagnosis technology becoming more mature and bring a lot of value,the health status of equipment has been more people’s attention.At the same time,multi-sensor fusion technology has been more important than single sensor monitoring and has become a research hotspot with the development of sensor technology.Therefore,in this context,we establish the design and implementation of equipment health status evaluation system based on the decision-making data fusion technology through the research on the relevant technology.As the bearing is the core of mechanical equipment,the proposed views and research results on the mechanical and electrical health management level,etc.have a good theoretical significance and practical value.The main contents and methods of this paper are as follows:(1)Illustrates all the technical theories and research status involved in the evaluation of bearing health status.Including equipment monitoring and fault diagnosis technology,multi-sensor data fusion technology,equipment health status evaluation technology.On the basis of fault diagnosis technology,data fusion technology is regarded as the core technology in the evaluation of bearing health status,which embodies the objective and scientific nature of equipment health status evaluation.(2)The paper studies and establishes the selection and calculation of the evaluation index of bearing equipment health status.Considering the sensitivity and stability of the mechanical equipment to the evaluation index,the paper combinations of the statistical feature extraction and the feature extraction of the empirical mode decomposition algorithm.Through the SVM classifier,the evaluation index is selected to judge the health status of the rolling bearing,and the fusion precision is improved for the subsequent data fusion technology.(3)The core algorithm of D-S evidence fusion for multi-sensor data fusion is established,and the problem of conflict of evidence is solved by the algorithm.The BPA output of posterior probability of SVM algorithm solves the problem of basic probability distribution.The validity,accuracy and advantages of the algorithm are verified by simulation data.(4)The paper constructs the model of equipment health status evaluation based on multi-sensor data fusion technology,and the validity of the algorithm is verified by rolling bearing simulation data.The experimental data show that the model can effectively identify the health status of rolling equipment,which has high recognition accuracy,strong stability,and broad applicability...