Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions

Vibration signal analysis is an important technique for bearing fault diagnosis. For bearings operating under constant rotational speed, faults can be diagnosed in the frequency domain since each type of fault has a specific Fault Characteristic Frequency (FCF), which is proportional to the shaft ro...

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Main Authors: Huan Huang, Natalie Baddour, Ming Liang
Format: Article
Language:English
Published: Elsevier 2019-01-01
Series:MethodsX
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016119301402
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spelling doaj-fe3692b0ff334da091093b1fd9f104c12020-11-25T01:15:24ZengElsevierMethodsX2215-01612019-01-01614151432Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditionsHuan Huang0Natalie Baddour1Ming Liang2Corresponding author.; Department of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, CanadaDepartment of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, CanadaDepartment of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, CanadaVibration signal analysis is an important technique for bearing fault diagnosis. For bearings operating under constant rotational speed, faults can be diagnosed in the frequency domain since each type of fault has a specific Fault Characteristic Frequency (FCF), which is proportional to the shaft rotational speed. However, bearings often operate under time-varying speed conditions. Additionally, the measurement of the time-varying rotational speed requires instruments, such as tachometers, which leads to extra cost and installation. With the development of time-frequency analysis, the time-varying FCFs manifest as curves in the Time-Frequency Representation (TFR). It has been shown that extracting multiple time-frequency curves from the TFR and then identifying the Instantaneous Fault Characteristic Frequency (IFCF) and Instantaneous Shaft Rotational Frequency (ISRF), bearing faults can be automatically diagnosed under time-varying speed conditions without using tachometers. However, the existing method used to identify the IFCF and the ISRF may lead to inaccurate results. In this study, the complete MATLAB© codes and a more reliable approach to use Multiple Time-Frequency Curve Extraction (MTFCE) for automatic bearing fault diagnosis under time-varying speed conditions are presented. • A Multiple time-frequency curve extraction (MTFCE) Matlab code is presented to extract multiple curves from the TFR. • Custom Matlab code for automatic bearing fault diagnosis under time-varying speed conditions without using tachometer data via the MTFCE is given and explained. • A new parameter, the allowable variance of the curve-to-curve ratio, is proposed to identify the IFCF and ISRF more reliably. Method name: Automatic bearing fault diagnosis under time-varying speed conditions via multiple time-frequency curve extraction, Keywords: Multiple time-frequency curve extraction, Time-frequency representations, Instantaneous frequency, Bearing fault diagnosis, Time-varying speedhttp://www.sciencedirect.com/science/article/pii/S2215016119301402
collection DOAJ
language English
format Article
sources DOAJ
author Huan Huang
Natalie Baddour
Ming Liang
spellingShingle Huan Huang
Natalie Baddour
Ming Liang
Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
MethodsX
author_facet Huan Huang
Natalie Baddour
Ming Liang
author_sort Huan Huang
title Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
title_short Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
title_full Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
title_fullStr Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
title_full_unstemmed Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
title_sort multiple time-frequency curve extraction matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
publisher Elsevier
series MethodsX
issn 2215-0161
publishDate 2019-01-01
description Vibration signal analysis is an important technique for bearing fault diagnosis. For bearings operating under constant rotational speed, faults can be diagnosed in the frequency domain since each type of fault has a specific Fault Characteristic Frequency (FCF), which is proportional to the shaft rotational speed. However, bearings often operate under time-varying speed conditions. Additionally, the measurement of the time-varying rotational speed requires instruments, such as tachometers, which leads to extra cost and installation. With the development of time-frequency analysis, the time-varying FCFs manifest as curves in the Time-Frequency Representation (TFR). It has been shown that extracting multiple time-frequency curves from the TFR and then identifying the Instantaneous Fault Characteristic Frequency (IFCF) and Instantaneous Shaft Rotational Frequency (ISRF), bearing faults can be automatically diagnosed under time-varying speed conditions without using tachometers. However, the existing method used to identify the IFCF and the ISRF may lead to inaccurate results. In this study, the complete MATLAB© codes and a more reliable approach to use Multiple Time-Frequency Curve Extraction (MTFCE) for automatic bearing fault diagnosis under time-varying speed conditions are presented. • A Multiple time-frequency curve extraction (MTFCE) Matlab code is presented to extract multiple curves from the TFR. • Custom Matlab code for automatic bearing fault diagnosis under time-varying speed conditions without using tachometer data via the MTFCE is given and explained. • A new parameter, the allowable variance of the curve-to-curve ratio, is proposed to identify the IFCF and ISRF more reliably. Method name: Automatic bearing fault diagnosis under time-varying speed conditions via multiple time-frequency curve extraction, Keywords: Multiple time-frequency curve extraction, Time-frequency representations, Instantaneous frequency, Bearing fault diagnosis, Time-varying speed
url http://www.sciencedirect.com/science/article/pii/S2215016119301402
work_keys_str_mv AT huanhuang multipletimefrequencycurveextractionmatlabcodeanditsapplicationtoautomaticbearingfaultdiagnosisundertimevaryingspeedconditions
AT nataliebaddour multipletimefrequencycurveextractionmatlabcodeanditsapplicationtoautomaticbearingfaultdiagnosisundertimevaryingspeedconditions
AT mingliang multipletimefrequencycurveextractionmatlabcodeanditsapplicationtoautomaticbearingfaultdiagnosisundertimevaryingspeedconditions
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