Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm

المؤلفون المشاركون

Wang, Xiao-hua
Zhou, Guang-xing
Miao, Zhong-hua
He, Chuang-xin

المصدر

Advances in Mechanical Engineering

العدد

المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2013-09-12

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

هندسة ميكانيكية

الملخص EN

An immune relevant vector machine (IRVM) based intelligent classification method is proposed by combining the random real-valued negative selection (RRNS) algorithm and the relevant vector machine (RVM) algorithm.

The method proposed is aimed to handle the training problem of missing or incomplete fault sampling data and is inspired by the “self/nonself” recognition principle in the artificial immune systems.

The detectors, generated by the RRNS, are treated as the “nonself” training samples and used to train the RVM model together with the “self” training samples.

After the training succeeds, the “nonself” detection model, which requires only the “self” training samples, is obtained for the fault detection and diagnosis.

It provides a general way solving the problems of this type and can be applied for both fault detection and fault diagnosis.

The standard Fisher's Iris flower dataset is used to experimentally testify the proposed method, and the results are compared with those from the support vector data description (SVDD) method.

Experimental results have shown the validity and practicability of the proposed method.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Miao, Zhong-hua& Zhou, Guang-xing& Wang, Xiao-hua& He, Chuang-xin. 2013. Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-480533

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Miao, Zhong-hua…[et al.]. Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm. Advances in Mechanical Engineering No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-480533

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Miao, Zhong-hua& Zhou, Guang-xing& Wang, Xiao-hua& He, Chuang-xin. Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-480533

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-480533