research-article

Vibration Based Fault Diagnosis of Automobile Gearbox Using Soft Computing Techniques

Authors:

T Praveen Kumar,

Anurag Jasti,

M Saimurugan,

K. I. RamachandranAuthors Info & Claims

ICONIAAC '14: Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing

Article No.: 13, Pages 1 - 7

https://doi.org/10.1145/2660859.2660918

Published: 10 October 2014 Publication History

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Abstract

Gearbox is the core component in any automotive/industrial application and it consists of gears and gear trains to vary the speed and torque of the machine. In order to reduce the machine breakdown cost and to increase the service life it is vital to know its operating conditions frequently to find the point of defect. The vibration signals are used to extract statistical features for 3 different classes namely Gearbox with Good gear, Gear Tooth breakage and Gear Face wear. The features were collected according to the experimental conditions with 3 fault classes, 3 speeds and 1 load condition with total of 9 testing conditions. The prominent statistical features were selected using decision tree algorithm. The set of IF-Then rule was generated and coded in LabVIEW for automated machine fault diagnosis.

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Cited By

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Verasis Kour Parveen Kumar Lehana (2024)GMM Based Fault Signature Estimation of Electromechanical Machines for Small and Medium-Sized Enterprises in IoT EnvironmentAutomatic Control and Computer Sciences10.3103/S014641162470113X58:6(663-678)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.3103/S014641162470113X
Balaji PSugumaran V(2023)Comparative study of machine learning and deep learning techniques for fault diagnosis in suspension systemJournal of the Brazilian Society of Mechanical Sciences and Engineering10.1007/s40430-023-04145-645:4Online publication date: 23-Mar-2023
https://doi.org/10.1007/s40430-023-04145-6
Milo MPetrone GCasaburo ADe Rosa SBrancati RRocca E(2022)Condition Monitoring of a Gear Box by Acoustic Camera and Machine Learning TechniquesEuropean Workshop on Structural Health Monitoring10.1007/978-3-031-07322-9_74(739-748)Online publication date: 22-Jun-2022
https://doi.org/10.1007/978-3-031-07322-9_74
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Index Terms

Vibration Based Fault Diagnosis of Automobile Gearbox Using Soft Computing Techniques
1. Applied computing
  1. Physical sciences and engineering
    1. Engineering
2. Computing methodologies
  1. Modeling and simulation

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Published In

ICONIAAC '14: Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing

October 2014

374 pages

ISBN:9781450329088

DOI:10.1145/2660859

General Chair:
P. Venkat Rangan,
Program Chair:
Bharat Jayaraman

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Amrita: Amrita Vishwa Vidyapeetham

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Association for Computing Machinery

New York, NY, United States

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Published: 10 October 2014

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ICONIAAC '14

ICONIAAC '14: International Conference on Interdisciplinary Advances in Applied Computing

October 10 - 11, 2014

Amritapuri, India

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ICONIAAC '14 Paper Acceptance Rate 69 of 176 submissions, 39%;

Overall Acceptance Rate 69 of 176 submissions, 39%

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Verasis Kour Parveen Kumar Lehana (2024)GMM Based Fault Signature Estimation of Electromechanical Machines for Small and Medium-Sized Enterprises in IoT EnvironmentAutomatic Control and Computer Sciences10.3103/S014641162470113X58:6(663-678)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.3103/S014641162470113X
Balaji PSugumaran V(2023)Comparative study of machine learning and deep learning techniques for fault diagnosis in suspension systemJournal of the Brazilian Society of Mechanical Sciences and Engineering10.1007/s40430-023-04145-645:4Online publication date: 23-Mar-2023
https://doi.org/10.1007/s40430-023-04145-6
Milo MPetrone GCasaburo ADe Rosa SBrancati RRocca E(2022)Condition Monitoring of a Gear Box by Acoustic Camera and Machine Learning TechniquesEuropean Workshop on Structural Health Monitoring10.1007/978-3-031-07322-9_74(739-748)Online publication date: 22-Jun-2022
https://doi.org/10.1007/978-3-031-07322-9_74
Das SSaha ASujith Kumar C(2020)Calibrated non‐contact vibrational harmonics measurement based on self‐vibration compensated 2D‐PSD with MEMS accelerometer using FFT analysisIET Science, Measurement & Technology10.1049/iet-smt.2019.022914:8(877-882)Online publication date: 28-Sep-2020
https://doi.org/10.1049/iet-smt.2019.0229
Kokane PBagavathi Sivakumar P(2018)Online Model for Suspension Faults Diagnostics Using IoT and AnalyticsInternational Conference on Advanced Computing Networking and Informatics10.1007/978-981-13-2673-8_17(145-154)Online publication date: 28-Nov-2018
https://doi.org/10.1007/978-981-13-2673-8_17
Sumesh AThekkuden DNair BRameshkumar KMohandas K(2015)Acoustic Signature Based Weld Quality Monitoring for SMAW Process Using Data Mining AlgorithmsApplied Mechanics and Materials10.4028/www.scientific.net/AMM.813-814.1104813-814(1104-1113)Online publication date: Nov-2015
https://doi.org/10.4028/www.scientific.net/AMM.813-814.1104

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Recommendations

Monitor and Fault Diagnosis of Vibration Abnormal State of Gearbox for Shape Rolling Mill

Application of Wavelet Neural Networks on Vibration Fault Diagnosis for Wind Turbine Gearbox

Research on Feature Level Fusion Data Association Method for the Gearbox Fault Diagnosis

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