193.174.19.232Abstract: J. Li, Q. Wang, Y. Zhang (2021)

Jisuanji Jicheng Zhizao Xitong/ Computer Integrated Manufacturing Systems, CIMS, 27(5), 1341–1350p. (2021) DOI:10.13196/j.cims.2021.05.010

Energy efficiency analysis and state monitoring of machining processes in mixed flow production mode based on recurrence analysis

J. Li, Q. Wang, Y. Zhang

Aiming at the energy efficiency research problem of machining process under the mixed-flow production mode, a method of energy efficiency analysis and state monitoring based on recurrence analysis and image processing technology was proposed. The machining power data of different workpieces was collected through off-line experiments. Then the time-domain characteristics of each workpiece's power under different states were computed and the clustering centers were found by clustering analysis on the power samples. After that, the reference power database of the workpieces was established based on the clustering centers. In mixed-flow production mode, the similarity between the real-time input power and the reference power of all kinds of workpiece was evaluated by recurrence analysis and image matching algorithm, and then the type and state of the processed workpiece were identified. Based on the result of workpiece state recognition, the energy efficiency for processing the workpiece was calculated. Based on the cross recurrence plot of the real-time machining power and its corresponding reference power of each machining process, the process state was monitored according to the recurrence quantification analysis. The effectiveness of the method was verified with a case study. It proved that the proposed method could be applied to analyze the energy efficiency of workpiece and identify the anomaly during the machining process in the mixed-flow production mode, and the identification accuracy was about 98.33%.

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