A time domain approach to diagnose gearbox fault based on measured vibration signals

Hong, Liu; Dhupia, Jaspreet Singh

doi:10.1016/j.jsv.2013.11.033

Cited by 134 publications

(59 citation statements)

References 29 publications

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“…In [152], a statistical method for the detection of sensor abrupt faults in aircraft control systems was presented, where the covariance of the sensing signals was used for feature extraction. Recently, a time-domain signal-based diagnostic algorithm was developed in [153] for monitoring of gear faults, by combining fast dynamic time warping (Fast DTW) as well as correlated kurtosis (CK) techniques. The fast DTW algorithm was employed to extract the periodic impulse excitations caused from the faulty gear tooth, and the extracted signal was then resampled for subsequent diagnostic analysis using the CK technique.…”

Section: A Time-domain Signal Based Methodsmentioning

confidence: 99%

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

Gao

Cecati

Ding

2015

IEEE Trans. Ind. Electron.

2,297

937

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Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS Abstract-With the ever increase of complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease and safety hazards, which greatly stimulates to detect and identify any kinds of potential abnormalities and faults as early as possible, and implement realtime fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results were reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review for real-time fault diagnosis and fault tolerant control with particular attention on the results reported in the last decade. In the first-part review, fault diagnosis approaches and their applications are reviewed comprehensively from model-based and signal-based perspectives, respectively.

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Section: A Time-domain Signal Based Methodsmentioning

confidence: 99%

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

Gao

Cecati

Ding

2015

IEEE Trans. Ind. Electron.

2,297

937

View full text Add to dashboard Cite

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“…3 for wear in multistage planetary gearboxes. Hong et al [72] described a timedomain approach to diagnose planetary gearbox faults using fast dynamic time warping (DTW) and correlated kurtosis (CK) techniques. They claim to characterize the local gear fault, and identify the corresponding faulty gear and its position.…”

Section: Time-series Methodsmentioning

confidence: 99%

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Kandukuri

Klausen

Karimi

et al. 2016

Renewable and Sustainable Energy Reviews

165

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“…More and more methods allow not only for a detection of a fact of deterioration of the technical condition of the transmission, but also the precise determination of location, type and size of the damage. For example in [29], the time-domain fault detection method was presented based on the fast dynamic time warping and correlated kurtosis techniques for this purpose. This method was able to extract periodic impulse excitations caused from the faulty gear tooth using an estimated reference signal that has the same frequency as the nominal gear mesh harmonic and is built using vibration characteristics of the gearbox operated under presumed healthy conditions.…”

Section: Introductionmentioning

confidence: 99%

Model-based detection of local defects in gears

Mączak¹,

Jasiński²

2017

Arch Appl Mech

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The paper is presenting a methodology for developing model-based method of gear fault diagnostics. First the simulation model of the helical gearbox is discussed allowing analysis of the phenomena taking place during teeth mating in the presence of manufacturing and assembly errors. It includes observation of influence of errors on the generated signals. The model was initially used to analyze the teeth contact in the presence of pitch errors and later to verify the sensitiveness of proposed diagnostic methods and their availability to detect the fatigue damages of teeth. The common feature of discussed approach is the direct use of time signal processing algorithms, and in contrary to the methods based on spectral analysis it allows precise localization of gear defects like pitting and tooth fracture associating them to the particular pinion or gear teeth. Their advantage is the simplicity and speed of action that is of great significance for the implementation in the autonomous transmission diagnostic systems and diagnostic systems working online. Presented methods of signal processing were first tested on a simulation model of the gear assembly and later verified during the experiments on a back-to-back test stand.

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A time domain approach to diagnose gearbox fault based on measured vibration signals

Cited by 134 publications

References 29 publications

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Model-based detection of local defects in gears

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