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Hob performance degradation assessment method based on cyclic statistical energy

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Abstract

During the gear hobbing machine process, the hob performance degradation assessment is significant for optimizing the tool changing frequency and improving machining efficiency. It is challenging to recognize hob wear state through vibration analysis and signal processing. Especially in the condition of intense vibration and noise interference, extracting signal features that reflect the wear state is challenging work. This paper proposes a feature extraction method called Cyclic Statistical Energy (CSE) to obtain the hob wear characteristics by tracking the sensitive frequency band. For the method, the vibration signal model of hob spindle is established first based on the vibration-generation mechanism of the machining process. Then, an index E is proposed to track the wear resonance frequency band of the vibration signal. Furthermore, the cyclic statistical order is analyzed and discussed. The hob performance degradation assessment can be realized by analyzing the energy index E with time variation. The experimental setup has been designed, and the two tests have been conducted in the production line: (1) impact hammer test and (2) hob whole life cutting test. The impact hammer test is set to obtain the modal parameters of the hob. Based on this, the whole life cutting test is designed and realized by which the vibration data of whole life with different wear states can be acquired. The proposed method CSE is successfully applied into online industry experiments test. The results show that the proposed method can give a more accurate performance degradation assessment curve for tool condition monitoring compared with traditional methods such as Wavelet Packet Decomposition (WPD).

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Acknowledgements

This research is supported by the National Key R&D Program of China (Grant No. 2019YFB1703700), ten thousand people plan project of Zhejiang Province, and the “Qizhen Program” of Zhejiang University.

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Authors and Affiliations

  1. State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou, Zhejiang, China

    Feiyun Cong, Jiani Wu, Li Chen & Feng Lin

  2. Zhejiang Shuanghuan Driveline Co., Ltd, Hangzhou, Zhejiang, China

    Faxiang Xie

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  1. Feiyun Cong
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Contributions

Feiyun Cong: conceptualization, supervision, writing—review and editing

Jiani Wu: writing and visualization

Li Chen: methodology, writing, data collection and analysis

Feng Lin: investigation and data curation

Faxiang Xie: resources and data curation

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Correspondence to Feiyun Cong.

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Cong, F., Wu, J., Chen, L. et al. Hob performance degradation assessment method based on cyclic statistical energy. Int J Adv Manuf Technol 125, 2103–2120 (2023). https://doi.org/10.1007/s00170-022-10635-z

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