Gearbox fault detection by Haar wavelet and envelope spectrum analysis of motor current

Squirrel Cage Induction Motors (SCIMs) are major workhorse of Indian Railways. Continuous online condition monitoring of the SCIMs like Traction Motor (TM) are essential to prevent unnecessary stoppage time in case of a complete failure. Before a complete failure, the TMs generally develop incipient or weak faults. Weak faults have minute influence on the motor performance but eventually leads to complete failure of the motor. If these weak faults are identified at the earliest then, a scheduled maintenance can be planned which will prevent any unplanned stoppage. The signals used for SCIM fault detection are motor current, voltage, vibration, temperature, voltage induced in search coil, etc. The most popular fault detection technology is based on Motor Current Signature Analysis (MCSA). MCSA based online and onboard TM condition monitoring system can be very useful for Indian railways to reduce the cost of operation and unplanned delay by shifting from unnecessary scheduled maintenance to condition-based maintenance of TM and other auxiliary SCIMs.

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Using Motor Current Analysis for Broken Rotor Bar Fault Detection in Rotary Machines

2018 3rd International Conference on Communication and Electronics Systems (ICCES) ◽

10.1109/cesys.2018.8724071 ◽

2018 ◽

Author(s):

Amandeep Sharma ◽

Pankaj Verma ◽

Lini Mathew ◽

Shantanu Chatterji

Keyword(s):

Fault Detection ◽

Current Analysis ◽

Broken Rotor Bar ◽

Motor Current ◽

Rotary Machines

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Bearings Fault Detection and Diagnosis Using Envelope Spectrum of Laplace Wavelet Transform

2009 2nd International Congress on Image and Signal Processing ◽

10.1109/cisp.2009.5303485 ◽

2009 ◽

Author(s):

Hui Li ◽

Lihui Fu ◽

Haiqi Zheng

Keyword(s):

Wavelet Transform ◽

Fault Detection ◽

Fault Detection And Diagnosis ◽

Detection And Diagnosis ◽

Envelope Spectrum

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Special Issue on Intelligence Techniques in Computer Games and Simulations

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2008.p0105 ◽

2008 ◽

Vol 12 (2) ◽

pp. 105-105

Author(s):

Ruck Thawonmas ◽

Keyword(s):

Fault Detection ◽

Computer Games ◽

Force Feedback ◽

Traffic Simulation ◽

Haar Wavelet ◽

Online Game ◽

Special Issue ◽

Ant Colony Optimization Algorithm ◽

Microscopic Traffic Simulation ◽

Games And Simulations

This issue presents eight research papers focusing on different aspects of intelligence techniques and their applications in computer games and simulations. They are extended papers from those accepted and presented at the International Symposium on Intelligence Techniques in Computer Games and Simulations that was held in Shiga, Japan on March 1-2, 2007. The issue starts with a paper entitled gUsing Automatic Calibration with Microscopic Traffic Simulation,h which focuses on the use of a genetic algorithm for searching parameter spaces of a microscopic traffic simulation. The second paper, gOn-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques,h presents the use of modelling information for the fault detection of hydraulic driven machines as well as for the compensation of incipient faults. The third paper, gGeneration of Character Motion by Using Reactive Motion Capture System with Force Feedback,h focuses on animation making with reactive motion data generated from the interaction with force feedback and the virtual environment. The fourth paper, gModeling of Wood Aging Caused by Biological Deterioration,h looks into an application of an ant colony optimization algorithm to generation of wood aging patterns caused by biological deterioration. The next three papers are related to network games. The fifth paper, gIntelligent Synchronization for Mirrored Game Servers: A Real Case Study,h examines the effectiveness of an intelligent optimistic synchronization scheme for mirrored game server architectures in real multiplayer-online-game environment. The sixth paper, gI3P: A Protocol for Increasing Reliability and Responsiveness in Massively Multiplayer Games,h presents a peer-to-peer (P2P) approach for minimizing the server bottleneck in online gaming and for increasing response and reliability. The seventh paper, gHaar Wavelets for Online-Game Player Classification with Dynamic Time Warping,h presents an application of Haar wavelet for reduction of online game players' action sequences used in player classification. Finally, the eighth paper, gDeveloping Natural Language Enabled Games in SCXML,h looks into the potential of SCXML for the game design and implementation. As the guest editor of this special issue, I would like to express my sincere gratitude to the authors in this issue for their hard job. Special thanks go to the anonymous referees for their assistance in the review process. Finally, I wish to thank JACIII staffs for their helps in coordinating the publication of the issue.

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Gear Fault Diagnosis Based on Time Synchronous Average and Envelope Analysis

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.303-306.502 ◽

2013 ◽

Vol 303-306 ◽

pp. 502-505 ◽

Cited By ~ 1

Author(s):

Yun Li ◽

Yan Gao ◽

Jun Guo ◽

Xian Jun Yu ◽

Yan Xue Liu

Keyword(s):

Fault Diagnosis ◽

Simulation Study ◽

Spectrum Analysis ◽

Rotation Frequency ◽

High Accuracy ◽

Envelope Analysis ◽

Gear Mesh ◽

Gear Fault ◽

Gear Fault Diagnosis ◽

Envelope Spectrum

This paper proposed a new method of gear fault diagnosis in gearbox. Mainly it stresses on the combination of time synchronous average (TSA) and envelope analysis, using TSA technique to eliminate the random noises in the gearbox. Then, the clear rotation frequency, gear mesh frequency and their harmonics can be obtained through the envelope spectrum analysis. Simulation study indicates that this method can effectively detect the gear faults with a high accuracy.

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EMD and Envelope Spectrum Based Bearing Fault Detection

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.459.233 ◽

2012 ◽

Vol 459 ◽

pp. 233-237 ◽

Cited By ~ 1

Author(s):

Zhen Tao Li ◽

Hui Li

Keyword(s):

Fault Detection ◽

Empirical Mode Decomposition ◽

Vibration Signal ◽

Fault Detection And Diagnosis ◽

Mode Decomposition ◽

Analysis Technique ◽

Oscillation Modes ◽

Intrinsic Oscillation ◽

Detection And Diagnosis ◽

Envelope Spectrum

A novel method to fault diagnosis of bearing based on empirical mode decomposition (EMD) and envelope spectrum is presented. EMD method is self-adaptive to non-stationary and non-linear signal. The methodology developed in this paper decomposes the original vibration signal in intrinsic oscillation modes, using the empirical mode decomposition. Then the envelope spectrum is applied to the selected intrinsic mode function that stands for the bearing faults. The basic principle is firstly introduced in detail. Then the EMD is applied in the research of the fault detection and diagnosis of the bearing. The experimental results show that the proposed method based on EMD and envelope spectrum analysis technique can effectively diagnose the faults of bearing.

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