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Open AccessJournal ArticleDOI

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

TLDR
In this article, the authors present a comprehensive review of these qualitative approaches from both theoretical and practical aspects, and present some of the latest results of the qualitative fault diagnosis in high-speed trains.
Abstract
For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch. Therefore, this survey will present a comprehensive review of these qualitative approaches from both theoretical and practical aspects. The primary task of this paper is to review the current development of these qualitative IFD techniques and then to present some of the latest results. Another major focus of our research is to introduce the background of high-speed trains, like the composition of the core subsystems, system structure, etc., based on which it becomes convenient for researchers to extract the diagnostic knowledge of high-speed trains, where the purpose is to understand how to use these types of knowledge. By reasonable utilization of the knowledge, it is hopeful to address various challenges caused by the coupling among subsystems of high-speed trains. Furthermore, future research trends for qualitative IFD approaches are also presented.

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Citations
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Journal ArticleDOI

A Sound-Based Fault Diagnosis Method for Railway Point Machines Based on Two-Stage Feature Selection Strategy and Ensemble Classifier

TL;DR: In this paper , a sound-based diagnosis method for railway point machines (RPMs) is presented, where the sound signals are preprocessed using empirical mode decomposition (EMD) and the first 15 intrinsic mode functions (IMFs) are extracted.
Journal ArticleDOI

Synergy of anaerobic digestion and pyrolysis processes for sustainable waste management: A critical review and future perspectives

TL;DR: In this paper, the authors report on the importance of coupling anaerobic digestion and pyrolysis while providing evidence on the synergistic effects that may occur within such a combined waste bi-functional process.
Journal ArticleDOI

EntropyHub: An open-source toolkit for entropic time series analysis.

Matthew W. Flood, +1 more
- 04 Nov 2021 - 
TL;DR: EntropyHub as discussed by the authors is an open-source toolkit for performing entropic time series analysis in MATLAB, Python and Julia, which provides an extensive range of more than forty functions for estimating cross-, multi-scale, multiscale cross-, and bidimensional entropy, each including a number of keyword arguments that allow the user to specify multiple parameters in the entropy calculation.
Journal ArticleDOI

AI in drug development: a multidisciplinary perspective.

TL;DR: In this article, the authors present a mathematical vision of some of the key AI methods used in drug development closer to medicinal chemists and, on the other hand, brings the drug development process and the use of different models closer to mathematicians.
Journal ArticleDOI

Phase Loss Detection Using Current Signals: A Review

TL;DR: In this paper, the authors provide a classification of algorithms used for the detection of the loss of phase and explain the distinctive features of each group of methods, which are based on the analysis of the current signals.
References
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Journal ArticleDOI

WinBUGS – A Bayesian modelling framework: Concepts, structure, and extensibility

TL;DR: How and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design are discussed and how the framework may be extended.
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Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

Paul M. Frank
- 01 May 1990 - 
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
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Causal diagrams for empirical research

TL;DR: In this paper, a nonparametric framework for causal inference is proposed, in which diagrams are queried to determine if the assumptions available are sufficient for identifying causal effects from nonexperimental data.
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.
Journal ArticleDOI

A review of process fault detection and diagnosis Part II : Qualitative models and search strategies

TL;DR: This part of the paper reviews qualitative model representations and search strategies used in fault diagnostic systems and broadly classify them as topographic and symptomatic search techniques.
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