Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation
المؤلفون المشاركون
Yang, Shanguo
Zhu, Zhencai
Wei, Li
Zhang, Xing
Jiang, Fan
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-07-24
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
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).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Xing& Wei, Li& Zhu, Zhencai& Yang, Shanguo& Jiang, Fan. 2019. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Xing…[et al.]. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Xing& Wei, Li& Zhu, Zhencai& Yang, Shanguo& Jiang, Fan. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1211466
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر