Abstract
Nowadays, most of the fault diagnosis methods are based on the collected data, which can not realize the timely prediction of fault diagnosis, and the measurement information based on a single sensor cannot fully and accurately reflect the working status of lift, thus causing the uncertainty and inaccuracy of fault diagnosis. An lift fault diagnosis algorithm based on DS data fusion is proposed. Multi-sensor fusion is used to initialize the initial reliability distribution of the sensor according to the membership degree of each diagnostic category. The data collected by each sensor is taken as evidence body. The final diagnosis results are obtained by data fusion method. Experiments on lift fault diagnosis show that the proposed method can correctly and timely predict the fault, overcome the uncertainty and inaccuracy of single sensor fault diagnosis, and improve the accuracy of lift fault diagnosis and prediction.
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Acknowledgements
The work is supported by Natural Science Research Major Project of higher education institution of Jiangsu Province (grant no. 17KJA460001).
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Jiang, X., Namokel, M., Hu, C., Tian, R. (2020). Research on Lift Fault Prediction and Diagnosis Based on Multi-sensor Information Fusion. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation IX. IWAMA 2019. Lecture Notes in Electrical Engineering, vol 634. Springer, Singapore. https://doi.org/10.1007/978-981-15-2341-0_20
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DOI: https://doi.org/10.1007/978-981-15-2341-0_20
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