Journal ArticleDOI
Optimum multi-fault classification of gears with integration of evolutionary and SVM algorithms
D. J. Bordoloi,Rajiv Tiwari +1 more
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TLDR
The main focus of the paper is to examine the performance of the multiclass ability of SVM technique by optimizing its parameters using the grid-search method, the genetic algorithm (GA) and the artificial-bee-colony algorithm (ABCA).About:
This article is published in Mechanism and Machine Theory.The article was published on 2014-03-01. It has received 59 citations till now. The article focuses on the topics: Structured support vector machine & Ranking SVM.read more
Citations
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Journal ArticleDOI
Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals
Chuan Li,Chuan Li,René-Vinicio Sánchez,Grover Zurita,Mariela Cerrada,Diego Cabrera,Rafael E. Vásquez +6 more
TL;DR: In this article, the authors proposed a deep random forest fusion (DRFF) technique to improve fault diagnosis performance for gearboxes by using measurements of an acoustic emission (AE) sensor and an accelerometer that are used for monitoring the gearbox condition simultaneously.
Journal ArticleDOI
Support vector machines in engineering: an overview
TL;DR: The aim of this study is to review the current state of the SVM technique, and to show some of its latest successful results in real‐world problems present in different engineering fields.
Journal ArticleDOI
Compound gear-bearing fault feature extraction using statistical features based on time-frequency method
TL;DR: New compound fault features, extracted from continuous and discrete wavelet transform of vibration signal are proposed and fault classification accuracy of these features is found to be better than the conventional time and frequency domain parameters.
Journal ArticleDOI
A Review on Fault Detection and Process Diagnostics in Industrial Processes
TL;DR: Current research and developments of F DD approaches for process monitoring as well as a broad literature review of many useful FDD approaches are presented.
Journal ArticleDOI
A hybrid intelligent multi-fault detection method for rotating machinery based on RSGWPT, KPCA and Twin SVM.
TL;DR: Experimental results demonstrate that the proposed hybrid method is effective for multi-fault detection of rotating machinery and the TWSVM is also indicated that has better classification performance and faster convergence speed than the normal SVM.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Related Papers (5)
Support vector machine based optimization of multi-fault classification of gears with evolutionary algorithms from time–frequency vibration data
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