Journal ArticleDOI
A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection
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TLDR
A novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2017-07-01. It has received 192 citations till now.read more
Citations
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Journal ArticleDOI
Applications of machine learning to machine fault diagnosis: A review and roadmap
TL;DR: A review and roadmap to systematically cover the development of IFD following the progress of machine learning theories and offer a future perspective is presented.
Journal ArticleDOI
Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
TL;DR: By analyzing the kernels of the convolutional layers of DNCNN via NAM algorithm, it is found that these kernels act as filters and they become complex when the layers go deeper, which may help to understand what DNCNN has learned in intelligent fault diagnosis of machinery.
Journal ArticleDOI
Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review
TL;DR: A systemic and pertinent state-of-art review on WT planetary gearbox condition monitoring techniques on the topics of fundamental analysis, signal processing, feature extraction, and fault detection is provided.
Journal ArticleDOI
An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition
Zirui Wang,Jun Wang,Youren Wang +2 more
TL;DR: The experimental results show that the developed SDAE-GAN method for planetary gearbox has good anti-noise ability and achieve better fault diagnosis performance in the case of small samples.
Journal ArticleDOI
The Entropy Algorithm and Its Variants in the Fault Diagnosis of Rotating Machinery: A Review
TL;DR: This paper aims to investigate the applications of entropy for the fault characteristics extraction of rotating machines and reviews the applications using the original entropy method and the improved entropy methods, respectively.
References
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Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
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The Mathematical Theory of Communication
TL;DR: The Mathematical Theory of Communication (MTOC) as discussed by the authors was originally published as a paper on communication theory more than fifty years ago and has since gone through four hardcover and sixteen paperback printings.
Journal ArticleDOI
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Feature selection based on mutual information: criteria ofmax-dependency, max-relevance, and min-redundancy
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
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