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A vibration segmentation approach for the multi-action system of numerical control turret

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Abstract

Numerical control (NC) turret constitutes a key component for NC lathe. Due to its strategic role in the successful machining, it is important to monitor the NC turret conditions to recognize the need for maintenance, thereby avoiding unplanned downtime. Signal segmentation is a very basic work in such a multi-action system condition monitoring. This paper borrows the idea of speech segmentation and proposes a simple vibration segmentation approach to obtain action-known segments. In this approach, we formulate a segment optimization problem by a new fitness function, and present a three-layer genetic algorithm to decouple the problem. The advantage of the approach is the little requirement of expert knowledge, which is friendly to users. The case study of NC turret from the experiment bench uses fourfold cross-validation to indicate that the approach has a good performance on segment production, action recognition, and the two combination. The ablation tests demonstrate the contribution of the component of the approach.

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Acknowledgements

This work was supported by National Natural Science Foundation of China [Grant Number 51975249]; Key Research and Development Plan of Jilin Province [Grant Number 20190302017GX]; and China Scholarship Council [Grant Number 202006170069].

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Authors and Affiliations

  1. Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun, 130025, China

    Wei Hu, Zhaojun Yang, Chuanhai Chen & Bo Sun

  2. Technical Development Department Welding Process Section, Faw Jiefang Automotive Co., Ltd, Changchun, 130025, China

    Qunya Xie

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  1. Wei Hu
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  2. Zhaojun Yang
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  3. Chuanhai Chen
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  4. Bo Sun
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Correspondence to Chuanhai Chen.

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Hu, W., Yang, Z., Chen, C. et al. A vibration segmentation approach for the multi-action system of numerical control turret. SIViP 16, 489–496 (2022). https://doi.org/10.1007/s11760-021-01990-7

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  • DOI: https://doi.org/10.1007/s11760-021-01990-7

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