Research on mixed-fault diagnosis of mine-used belt conveyor gearbox
| Autor: | YANG Yun, XIONG Jijun, SONG Yaobin, MA Liyun, WANG Xiangling |
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| Jazyk: | čínština |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Gong-kuang zidonghua, Vol 45, Iss 5, Pp 51-55 (2019) |
| Druh dokumentu: | article |
| ISSN: | 1671-251X 1671-251x |
| DOI: | 10.13272/j.issn.1671-251x.2018110004 |
| Popis: | In view of problem that fault diagnosis methods of mine-used belt conveyor gearbox based on vibration signal analysis are not easy to process mixed-fault signals, a new mixed-fault diagnosis method of mine-used belt conveyor gearbox based on self-organizing map network was proposed. The standard multi-fault samples of mine-used belt conveyor gearbox are pre-processed by wavelet threshold denoising method incorporating Shannon entropy，Gaussian mixture distribution model is established for the standard multi-fault samples after pre-treatment, and the expectation-maximization algorithm is used to estimate the parameters of the model to obtain corresponding feature vectors which are input into the self-organizing map network. At last, the fault signals of different fault types are clustered and identified by self-organizing map network to determine the fault category. The test results show that the method can effectively diagnose the fault type of mine-used belt conveyor gearbox, and the overall accuracy of the diagnostic method is 88%, and the accuracy under six conditions is 100%. It provides a new method for gearbox fault diagnosis of mine electromechanical equipment. |
| Databáze: | Directory of Open Access Journals |
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