Prediction of pick wear degradation based on Wiener process

Qiang Zhang; Jiayao Zhang

doi:10.1117/12.2625253

12 December 2021 Prediction of pick wear degradation based on Wiener process

Qiang Zhang, Jiayao Zhang

Proceedings Volume 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021); 121272P (2021) https://doi.org/10.1117/12.2625253
Event: International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 2021, Qingdao, China

Abstract

Aiming at the wear state problem of heading machine, a wear state prediction model based on Wiener process was established. The vibration and acoustic emission data samples were extracted by setting up a test system, and WPD was applied to denoise the data. Six kinds of pick wear degree states were defined, and 50 groups of data samples were taken from each state to verify the accuracy of the model, which all met the accuracy requirements. Then, the model was used for data prediction research, and the experimental data were compared. The results show that the prediction accuracy of vibration signal acceleration energy and lower Wiener process is 99.01%, and that of acoustic emission signal acceleration energy and lower wiener process is 99.13%.The prediction error is small and the prediction accuracy is high, which provides a new method for the prediction of heading machine pick wear degradation state.

Citation Download Citation

Qiang Zhang and Jiayao Zhang "Prediction of pick wear degradation based on Wiener process", Proc. SPIE 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 121272P (12 December 2021); https://doi.org/10.1117/12.2625253

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