Recognition of pick wear condition based on Grey-Markov chain model

• Autorzy: Zhang Qiang , Zhang Jiayao

Identyfikatory

DOI

10.15632/jtam-pl/161683

• Języki publikacji: EN

Abstrakty

EN

An attempt is made in this paper to solve the pick wear problem of mining machinery and propose a pick wear degradation model based on the Grey-Markov chain by using generated characteristics signals and certain pick wear parameters to enhance the prediction accuracy. The vibration and acoustic emission signals generated during the catting pick are extracted and analyzed. The energy and the value of the characteristic signal are obtained by wavelet analysis to construct a characteristic sample library of the signals. Two kinds of signals are applied to the model to analyze the error between the real and the predicted values. The model prediction results demonstrate a 1.43% error of the vibration signal, 1.64% error of the acoustic emission signal with 98% prediction accuracy, thus offers a new method for monitoring the pick wear of mining machinery.

Słowa kluczowe

EN

pick wear; vibration acceleration signal; acoustic emission signal; Grey-Markov method

• Wydawca: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
• Czasopismo: Journal of Theoretical and Applied Mechanics
• Rocznik: 2023
• Tom: Vol. 61 nr 2
• Strony: 289--303
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Zhang Qiang

• School of Mechanical Engineering, Liaoning Technical University, Liaoning, China
• School of Mechatronics, Shandong University of Science and Technology, Shandong, China

autor

Zhang Jiayao

• School of Mechanical Engineering, Liaoning Technical University, Liaoning, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).