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Method for edge chipping monitoring based on vibration polar coordinate image feature analysis

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Abstract

Cutting-edge chipping is a randomly happened but critical tool failure, which could seriously affect machining quality without effective and timely treatment especially in the automated machining process. Accurate and timely monitoring chipping is the first key step for properly handling edge chipping issues, while there are still gaps between academic research and industrial application as chipping initiation and propagation are always stochastic especially for milling complex structural parts with mass of ever-changing cutting conditions. This paper proposes a chipping monitoring method for automated milling process based on cutting vibration polar coordinate image features and residual neural network (ResNet) model, which lies on the change of cutting vibration signals that reveal just after an event of edge chipping has occurred. With the creatively proposed polar coordinate transform method, cutting vibration signals are first preprocessed for real-time chipping detection. The preprocessed signals with easily distinguished shape features of polar coordinate images are then employed for developing a ResNet50-based classification model. And consequently, the cutting-edge chipping could be monitored in almost real time. Experimental validation for real-time chipping detection has been conducted with the proposed method. The accuracy of No. 5~8 experiments are 92%, 88%, 83% and 84%, respectively. More importantly, the method is suited for edge chipping monitoring for milling complex structural parts, where the effects of constantly changing cutting conditions have been eliminated.

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Funding

This work is supported by the National Natural Science Foundation of China (Grant No. 52090053, 52105432 and 52130506), the National Key R&D Program of China (Grant No. 2018YFA0702803), the Science and Technology Innovation Foundation of Dalian (Grant No. 2021RD08, Grant No. 2022JJ12GX027 and 2021JB12GX010).

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Authors and Affiliations

  1. State Key Laboratory of High-Performance Precision Manufacturing, Dalian University of Technology, Dalian, 116024, China

    Zhenxi Jiang, Fuji Wang & Rao Fu

  2. Chengdu Aircraft Industrial (Group) Co., Ltd, Chengdu, 610092, China

    Zhenxi Jiang, Wenping Mou, Shaowei Zhu & Zhiyong Yu

Authors
  1. Zhenxi Jiang
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  2. Fuji Wang
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  3. Wenping Mou
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  4. Shaowei Zhu
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  5. Rao Fu
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  6. Zhiyong Yu
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Correspondence to Rao Fu.

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Jiang, Z., Wang, F., Mou, W. et al. Method for edge chipping monitoring based on vibration polar coordinate image feature analysis. Int J Adv Manuf Technol 130, 5137–5146 (2024). https://doi.org/10.1007/s00170-024-12981-6

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  • DOI: https://doi.org/10.1007/s00170-024-12981-6

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