Abstract
Aiming at the problem of large amount of data and low utilization rate in complex industrial systems and processes, an association analysis method of process variables and faults is proposed. Because of the characteristic that large number of process variables and large data volume consist in complex industrial system, a subspace clustering based quantitative association rule mining method is proposed to the association analysis between multiple process-variables and faults. The validity and efficiency of the method is verified by using the fault datasets of TE process.
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Zhong, Y., Zhang, K., Chai, Y. (2019). Subspace Clustering Based Association Analysis Between Multiple Process-Variable-Parameters and Faults. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2018 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 528. Springer, Singapore. https://doi.org/10.1007/978-981-13-2288-4_42
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DOI: https://doi.org/10.1007/978-981-13-2288-4_42
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