Journal ArticleDOI
Bearing fault diagnosis of a permanent magnet synchronous motor via a fast and online order analysis method in an embedded system
Siliang Lu,Qingbo He,Jiwen Zhao +2 more
TLDR
In this article, a fast and online OA (FOOA) method is proposed to realize variable-speed PMSM bearing fault diagnosis in an embedded system for online fault diagnosis, which consists of two algorithms: rotating phase information is extracted from the sinusoidal current of the PMSM, and a series of equal phase sampling pulses are generated.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2017-03-17. It has received 64 citations till now. The article focuses on the topics: Bearing (mechanical) & Fault (power engineering).read more
Citations
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Journal ArticleDOI
An adaptive deep transfer learning method for bearing fault diagnosis
TL;DR: An adaptive deep transfer learning method for bearing fault diagnosis is proposed, a long-short term memory recurrent neural network model based on instance-transfer learning is constructed, and grey wolf optimization algorithm is introduced to adaptively learn key parameters of joint distribution adaptation.
Journal ArticleDOI
Fault Diagnosis Method Based on Principal Component Analysis and Broad Learning System
TL;DR: Experimental results show that the PCA method can effectively eliminate the feature correlation and realize the dimension reduction of the feature matrix, the BLS can take on better adaptability, faster computation speed, and higher classification accuracy, and the PABSFD method can efficiently and accurately obtain the fault diagnosis results.
Journal ArticleDOI
An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems
TL;DR: This work presents a novel diagnosis framework that combines the spatiotemporal pattern network (STPN) approach with convolutional neural networks (CNN) to build a hybrid ST-CNN scheme, and it is verified that the spatial features can elevate the diagnosis accuracy.
Journal ArticleDOI
A novel bearing intelligent fault diagnosis framework under time-varying working conditions using recurrent neural network.
TL;DR: A new intelligent fault diagnosis framework inspired by the infinitesimal method is proposed that has higher accuracy with simpler structure, and is superior to the traditional method in bearing fault diagnosis.
Journal ArticleDOI
Tacholess Speed Estimation in Order Tracking: A Review With Application to Rotating Machine Fault Diagnosis
TL;DR: Recent advances in the development of tacholess speed estimation methods for OT with its applications to fault diagnosis are summarized and the shortcuts of these methods are discussed in detail.
References
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Journal ArticleDOI
Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review
TL;DR: A review paper describing different types of faults and the signatures they generate and their diagnostics' schemes will not be entirely out of place to avoid repetition of past work and gives a bird's eye view to a new researcher in this area.
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A review on empirical mode decomposition in fault diagnosis of rotating machinery
TL;DR: This paper attempts to survey and summarize the recent research and development of EMD in fault diagnosis of rotating machinery, providing comprehensive references for researchers concerning with this topic and helping them identify further research topics.
Journal ArticleDOI
Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
TL;DR: A comprehensive review of the PHM field is provided, followed by an introduction of a systematic PHM design methodology, 5S methodology, for converting data to prognostics information, to enable rapid customization and integration of PHM systems for diverse applications.
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Wavelets for fault diagnosis of rotary machines: A review with applications
TL;DR: Current applications of wavelets in rotary machine fault diagnosis are summarized and some new research trends, including wavelet finite element method, dual-tree complex wavelet transform, wavelet function selection, newWavelet function design, and multi-wavelets that advance the development of wavelet-based fault diagnosed are discussed.
Journal ArticleDOI
Cyclostationarity by examples
TL;DR: In this paper, a tutorial on cyclostationarity oriented towards mechanical applications is presented, with 20 examples devoted to illustrating key concepts on actual mechanical signals and demonstrating how cyclostatarity can be taken advantage of in machine diagnostics, identification of mechanical systems and separation of mechanical sources.