Research on Fault Diagnosis Method Based on RSAPSO-DBN
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-26354-6_29
Reference22 articles.
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3. Zhang, L.-P., et al.: Fault diagnosis technology of rolling bearing based on LMD and BP neural network. In: Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, pp. 1327–1331 (2016)
4. Gangsar, P., Tiwari, R.: Comparative investigation of vibration and current monitoring for prediction of mechanical and electrical faults in induction motor based on multiclass-support vector machine algorithms. Mech. Syst. Signal Process. 94, 464–481 (2017)
5. Yang, J.J., et al.: Improved fault Petri nets of unmanned seafloor drilling based on traces transition. J. Coast. Res. 83, 479–485 (2018)
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