Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment
المؤلفون المشاركون
Hua, Liang
Zhang, Xinsong
Qiang, Yujian
Gu, Juping
Chen, Ling
Zhu, Hairong
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-09-16
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Automatic extraction of time-frequency spectral image of mechanical faults can be achieved and faults can be identified consequently when rotating machinery spectral image processing technology is applied to fault diagnosis, which is an advantage.
Acquired mechanical vibration signals can be converted into color time-frequency spectrum images by the processing of pseudo Wigner-Ville distribution.
Then a feature extraction method based on quaternion invariant moment was proposed, combining image processing technology and multiweight neural network technology.
The paper adopted quaternion invariant moment feature extraction method and gray level-gradient cooccurrence matrix feature extraction method and combined them with geometric learning algorithm and probabilistic neural network algorithm, respectively, and compared the recognition rates of rolling bearing faults.
The experimental results show that the recognition rates of quaternion invariant moment are higher than gray level-gradient cooccurrence matrix in the same recognition method.
The recognition rates of geometric learning algorithm are higher than probabilistic neural network algorithm in the same feature extraction method.
So the method based on quaternion invariant moment geometric learning and multiweight neural network is superior.
What is more, this algorithm has preferable generalization performance under the condition of fewer samples, and it has practical value and acceptation on the field of fault diagnosis for rotating machinery as well.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hua, Liang& Qiang, Yujian& Gu, Juping& Chen, Ling& Zhang, Xinsong& Zhu, Hairong. 2015. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hua, Liang…[et al.]. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hua, Liang& Qiang, Yujian& Gu, Juping& Chen, Ling& Zhang, Xinsong& Zhu, Hairong. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1074514
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