A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis
المؤلفون المشاركون
Zhang, Zhifen
Zhang, Qi
Tian, Tian
Wen, Guangrui
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-02
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
The application of the existing complex network in fault diagnosis is usually modelled based on the time domain, resulting in the loss of sign frequency-domain features, and the extracted topology features of network are too macroscopic and insensitive to local changes within the network.
This paper proposes a new method of local feature extraction based on frequency complex network (FCN) decomposition and builds a new complex network structure feature on this basis, namely, subnetwork average degree.
The variation law of signals in frequency domain is obtained with the aid of the structural features of complex network.
The local features that are sensitive to local changes of the network are applied to characterize the whole network, with flexible application and without limitation in mechanism.
The average degree of subnetwork could be regarded as feature parameters for rolling bearing fault diagnosis and degradation state recognition.
Analysis on the experimental data and bearing life cycle data shows that the method proposed in this paper is effective, revealing that the extracted features have effective separability and high accuracy in fault recognition and the degradation detection of the life cycle of rolling bearings combined with neural networks.
Moreover, the proposed method has reference value for the processing and recognition of other nonstationary signals.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Qi& Tian, Tian& Wen, Guangrui& Zhang, Zhifen. 2018. A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis. Shock and Vibration،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1215147
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Qi…[et al.]. A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis. Shock and Vibration No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1215147
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Qi& Tian, Tian& Wen, Guangrui& Zhang, Zhifen. A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1215147
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1215147
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