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A Computationally Efficient and Adaptive Approach for Online Embedded Machinery Diagnosis in Harsh Environments
المؤلفون المشاركون
المصدر
Advances in Mechanical Engineering
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-08-29
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Condition-based monitoring (CBM) has advanced to the stage where industry is now demanding machinery that possesses self-diagnosis ability.
This need has spurred the CBM research to be applicable in more expanded areas over the past decades.
There are two critical issues in implementing CBM in harsh environments using embedded systems: computational efficiency and adaptability.
In this paper, a computationally efficient and adaptive approach including simple principal component analysis (SPCA) for feature dimensionality reduction and K-means clustering for classification is proposed for online embedded machinery diagnosis.
Compared with the standard principal component analysis (PCA) and kernel principal component analysis (KPCA), SPCA is adaptive in nature and has lower algorithm complexity when dealing with a large amount of data.
The effectiveness of the proposed approach is firstly validated using a standard rolling element bearing test dataset on a personal computer.
It is then deployed on an embedded real-time controller and used to monitor a rotating shaft.
It was found that the proposed approach scaled well, whereas the standard PCA-based approach broke down when data quantity increased to a certain level.
Furthermore, the proposed approach achieved 90% accuracy when diagnosing an induced fault compared to 59% accuracy obtained using the standard PCA-based approach.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, Chuan& Huang, Samuel H.. 2013. A Computationally Efficient and Adaptive Approach for Online Embedded Machinery Diagnosis in Harsh Environments. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-502981
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, Chuan& Huang, Samuel H.. A Computationally Efficient and Adaptive Approach for Online Embedded Machinery Diagnosis in Harsh Environments. Advances in Mechanical Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-502981
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, Chuan& Huang, Samuel H.. A Computationally Efficient and Adaptive Approach for Online Embedded Machinery Diagnosis in Harsh Environments. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-502981
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-502981
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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