دورية أكاديمية

Research on mixed-fault diagnosis of mine-used belt conveyor gearbox

التفاصيل البيبلوغرافية
العنوان: Research on mixed-fault diagnosis of mine-used belt conveyor gearbox
المؤلفون: YANG Yun, XIONG Jijun, SONG Yaobin, MA Liyun, WANG Xiangling
المصدر: Gong-kuang zidonghua, Vol 45, Iss 5, Pp 51-55 (2019)
بيانات النشر: Editorial Department of Industry and Mine Automation, 2019.
سنة النشر: 2019
المجموعة: LCC:Mining engineering. Metallurgy
مصطلحات موضوعية: mine-used belt conveyor, gearbox, vibration signal, mixed-fault diagnosis, expectation-maximization algorithm, self-organizing map network, gaussian mixture distribution model, som, Mining engineering. Metallurgy, TN1-997
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1671-251X
1671-251x
Relation: https://doaj.org/toc/1671-251X
DOI: 10.13272/j.issn.1671-251x.2018110004
URL الوصول: https://doaj.org/article/b01eb09d0b51446d895d87b5f7088ae3
رقم الأكسشن: edsdoj.b01eb09d0b51446d895d87b5f7088ae3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1671251X
1671251x
DOI:10.13272/j.issn.1671-251x.2018110004