首页 » 文章 » 文章详细信息
Shock and Vibration Volume 2019 ,2019-07-24
Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation
Research Article
Xing Zhang 1 , 2 Wei Li 1 , 2 Zhencai Zhu 1 , 2 Shanguo Yang 1 , 2 Fan Jiang 1 , 2
Show affiliations
DOI:10.1155/2019/6986240
Received 2019-04-14, accepted for publication 2019-06-13, Published 2019-06-13
PDF
摘要

A scraper conveyor is a key component of large-scale mechanized coal mining equipment, and its failure patterns are mainly caused by chain jam and chain fracture. Due to the difficulties with direct measurement for multiple performance parameters of the scraper chain, this paper deals with a novel strategy for fault detection of the scraper chain based on vibration analysis of the chute. First, a chute vibration model (CVM) is applied for modal analysis, and the hammer impact test (HIT) is conducted to validate the accuracy of the CVM; second, the measuring points for vibration analysis of the chute are determined based on the modal assurance criterion (MAC); and third, to simulate the actual vibration properties of the chute, a dynamic transmission system model (DTSM) is constructed based on finite element modeling. The fixed-point experimental testing (FPET) is then conducted to indicate the correctness of simulation results. Subsequently, the DTSM-based vibration responses of the chute under different operating conditions are obtained. In this paper, the proposed strategy is employed to determine the occurrence of chain faults by amplitude comparisons, while failure patterns are distinguished by the adaptive optimal kernel time-frequency representation (AOKR).

授权许可

Copyright © 2019 Xing Zhang et al. 2019
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

通讯作者

Wei Li.School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, China, cumt.edu.cn;Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment, China University of Mining and Technology, Xuzhou 221116, China, cumtb.edu.cn.liwei_cmee@163.com

推荐引用方式

Xing Zhang,Wei Li,Zhencai Zhu,Shanguo Yang,Fan Jiang. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration ,Vol.2019(2019)

您觉得这篇文章对您有帮助吗?
分享和收藏
0

是否收藏?

参考文献
[1] Y. Zhang, X. Ma, Y. Jianxiang. Fuzzy neural network fault diagnosis and online vibration monitoring system for the coal scraper conveyor based on rough set theory. :6134-6138. DOI: 10.1515/amsc-2015-0002.
[2] S. B. Jiang, X. Zhang, K. D. Gao, J. Gao. et al.(2017). Multi-body dynamics and vibration analysis of chain assembly in armoured face conveyor. International Journal of Simulation Modelling.16(3):458-470. DOI: 10.1515/amsc-2015-0002.
[3] B. Zhang, A. C. C. Tan, J.-h. Lin. (2016). Gearbox fault diagnosis of high-speed railway train. Engineering Failure Analysis.66:407-420. DOI: 10.1515/amsc-2015-0002.
[4] R. Nie, B. He, P. Yuan, L. Zhang. et al.(2015). Novel approach to and implementation of design and analysis of armored face conveyor power train. Science China Technological Sciences.58(12):2153-2168. DOI: 10.1515/amsc-2015-0002.
[5] S.-s. Xue, X.-c. Li, X.-y. Xu. Fault tree and Bayesian network based scraper conveyer fault diagnosis. :783-795. DOI: 10.1515/amsc-2015-0002.
[6] M. Pastor, M. Binda, T. Harčarik. (2012). Modal assurance criterion. Procedia Engineering.48:543-548. DOI: 10.1515/amsc-2015-0002.
[7] E. Parloo, P. Verboven, P. Guillaume, M. Van Overmeire. et al.(2002). Autonomous structural health monitoring-part ii: vibration-based in-operation damage assessment. Mechanical Systems and Signal Processing.16(4):659-675. DOI: 10.1515/amsc-2015-0002.
[8] M. Dolipski, P. Cheluszka, E. Remiorz, P. Sobota. et al.(2015). Follow-up chain tension in an armoured face conveyor/nadążne napinanie lańcucha zgrzebłowego W przenośniku scianowym. Archives of Mining Sciences.60(1):25-38. DOI: 10.1515/amsc-2015-0002.
[9] B. He, G. Li, H. Shi. Dynamic behaviour modelling and simulation of the chain transmission system for an armoured face conveyor. :1000-1004. DOI: 10.1515/amsc-2015-0002.
[10] C. D. Brown. (2002). Design, build and test of a longwall armoured face conveyor. Longwall Mining. DOI: 10.1515/amsc-2015-0002.
[11] R. Nie, B. He, L. Zhang, G. Li. et al.(2014). Modelling of the transmission system in conveying equipment based on Euler method with application. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics.228(3):294-306. DOI: 10.1515/amsc-2015-0002.
[12] L. A. Morley, J. L. Kohler, H. M. Smolnikar. (1988). A model for predicting motor load for an armored face-conveyor drive. IEEE Transactions on Industry Applications.24(4):649-659. DOI: 10.1515/amsc-2015-0002.
[13] M. Myszkowski, D. Loehning. (2001). Chain force measurements on armoured face conveyors and coal plows in heavy-duty longwalls. CIM Bulletin.94(1054):72-75. DOI: 10.1515/amsc-2015-0002.
[14] H. Wang, Q. Zhang, F. Xie. (2017). Dynamic tension test and intelligent coordinated control system of a heavy scraper conveyor. IET Science, Measurement and Technology.11(7):871-877. DOI: 10.1515/amsc-2015-0002.
[15] X. Gong, X. Ma, Y. Zhang. Application of fuzzy neural network in fault diagnosis for scraper conveyor vibration. :1135-1140. DOI: 10.1515/amsc-2015-0002.
[16] W. J. Staszewski, K. Worden, G. R. Tomlinson. (1997). Time-frequency analysis in gearbox fault detection using the Wigner-ville distribution and pattern recognition. Mechanical Systems and Signal Processing.11(5):673-692. DOI: 10.1515/amsc-2015-0002.
[17] C. S. Sakaris, J. S. Sakellariou, S. D. Fassois. (2017). Random-vibration-based damage detection and precise localization on a lab-scale aircraft stabilizer structure via the Generalized Functional Model Based Method. Structural Health Monitoring: An International Journal.16(5):594-610. DOI: 10.1515/amsc-2015-0002.
[18] A. A. Ordin, A. A. Metel’kov. (2015). Analysis of longwall face output in screw-type cutter-loader-and-scraper conveyor system in underground mining of flat-lying coal beds. Journal of Mining Science.51(6):1173-1179. DOI: 10.1515/amsc-2015-0002.
[19] J.-D. Wu, P.-H. Chiang. (2009). Application of Wigner-Ville distribution and probability neural network for scooter engine fault diagnosis. Expert Systems with Applications.36(2):2187-2199. DOI: 10.1515/amsc-2015-0002.
[20] Z. Feng, M. Liang. (2014). Fault diagnosis of wind turbine planetary gearbox under nonstationary conditions via adaptive optimal kernel time-frequency analysis. Renewable Energy.66:468-477. DOI: 10.1515/amsc-2015-0002.
[21] S. Sen, M. X. Min, Y. Z. She. Diagnosis of coal scraper conveyor based on Fuzzy Fault tree. :392-395. DOI: 10.1515/amsc-2015-0002.
[22] Y. Zhang, W. Song, M. Karimi, C.-H. Chi. et al.(2018). Fractional autoregressive integrated moving average and finite-element modal: the forecast of tire vibration trend. IEEE Access.6:40137-40142. DOI: 10.1515/amsc-2015-0002.
文献评价指标
浏览 9次
下载全文 0次
评分次数 0次
用户评分 0.0分
分享 0次