Noise subtraction and marginal enhanced square envelope spectrum (MESES) for the identification of bearing defects in centrifugal and axial pump

Kumar, Anil; Tang, Hesheng; Vashishtha, Govind; Xiang, Jiawei

doi:10.1016/j.ymssp.2021.108366

Cited by 67 publications

(23 citation statements)

References 32 publications

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“…Step 6: Fuzzy function m(Dist t co m REB ij , O, r) is utilized to calculate the degree of similarity Sim t co m REB ij with the help of Equation (27).…”

Section: Continuous Monitoring Of Reb Health By Wsefementioning

confidence: 99%

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Continuous monitoring of rolling element bearing health by nonlinear weighted squared envelope-based fuzzy entropy

Noman

Wen

et al. 2023

Structural Health Monitoring

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Fuzzy entropy (FE) can be regarded as an effective measure for nonlinear characterization of rolling element bearing (REB) health condition by quantifying the complexity of vibration signals. However, during continuous monitoring operation under heavy noise, transient impulses corresponding to a REB fault get submerged under unnecessary random noise components. As a consequence, FE algorithm not only fails to detect a REB fault at the earliest point of inception but also performs poorly in monitoring the development of the incepted fault in an efficient manner. Aiming at solving the aforementioned limitations of FE in continuous monitoring of REB health, background noise associated with collected vibration signals is eliminated by weighting the corresponding square envelope signal. Due to the utilization of weighted squared envelope signal, the proposed measure is termed as weighted square envelope-based FE (WSEFE). One simulated case and two different run-to-failure experimental cases are used for validation. The comparison results demonstrate that the proposed WSEFE not only overcomes the limitations of original FE but also performs better than conventional permutation entropy and advanced FE-based measure multiscale FE (MFE) in continuous monitoring of REB health.

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“…Step 6: Fuzzy function m(Dist t co m REB ij , O, r) is utilized to calculate the degree of similarity Sim t co m REB ij with the help of Equation (27).…”

Section: Continuous Monitoring Of Reb Health By Wsefementioning

confidence: 99%

“…24,25 Different from aforementioned signal preprocessing techniques, lately square envelope (SE) analysis has been proven effective for extracting the REB fault features. 26,27 Being a function of the original signal, a SE signal is suitable for continuous monitoring of REB health.…”

Section: Introductionmentioning

confidence: 99%

Continuous monitoring of rolling element bearing health by nonlinear weighted squared envelope-based fuzzy entropy

Noman

Wen

et al. 2023

Structural Health Monitoring

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“…Combined with the historical data, Schmidt et al [117] proposed an abnormal envelope spectrum, which can automatically detect gearbox faults through smoothing. Kumar et al [118] proposed a new marginal band selection criterion to calculate the marginal enhancement envelope, so as to extract features.…”

Section: Improvement and Developmentmentioning

confidence: 99%

Review of spectrum analysis in fault diagnosis for mechanical equipment

Wang,

Sun

2023

Eng. Res. Express

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Various mechanical equipment play a crucial role, and their health or status may affect efficiency and safety seriously. Spectrum analysis of the corresponding signal has been widely used to diagnose the fault in the past decades. The diagnosis method based on spectrum analysis technology covers almost all aspects of mechanical fault diagnosis. However, there is a lack of review of diagnostic methods of spectrum analysis technologies in the field of mechanical equipment fault diagnosis. In order to fill this gap, this paper reviews the spectrum analysis technology in mechanical equipment diagnosis in detail. First of all, in order to let the researchers who are in contact with spectrum analysis technology for the first time quickly understand this field, the principles of spectrum are systematically sorted out, including spectrum, cepstrum, energy spectrum, power spectrum, higher-order spectrum, Hilbert spectrum, marginal spectrum, envelope spectrum, singular spectrum and so on. Furthermore, the characteristics of corresponding spectrum analysis technologies are summarized, and their advantages and disadvantages are analyzed and compared. High-quality references in recent ten years are cited for illustration to enhance persuasiveness. Finally, the prospect of spectrum analysis technology is summarized, and the future development trend of spectrum analysis technology is pointed out. It is believed that the joint diagnosis of fault severity, variable speed fault diagnosis, combined with deep learning and multiple spectrum analysis technologies should be given more attention in the future. This paper is expected to provide a comprehensive overview of mechanical fault diagnosis based on spectrum analysis theory, and help to develop corresponding spectrum analysis technologies in practical engineering.

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“…A Hilbert transform approach is used for extracting the current signal envelope [34,35]. Hilbert transform is a time-domain convolution and mathematically can be expressed as…”

Section: Health Indicator For Tool Wear Progression Monitoringmentioning

confidence: 99%

A novel current sensor indicator enabled WAFTR model for tool wear prediction under variable operating conditions

Kundu

Luo

Qin

et al. 2022

Journal of Manufacturing Processes

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Noise subtraction and marginal enhanced square envelope spectrum (MESES) for the identification of bearing defects in centrifugal and axial pump

Cited by 67 publications

References 32 publications

Continuous monitoring of rolling element bearing health by nonlinear weighted squared envelope-based fuzzy entropy

Continuous monitoring of rolling element bearing health by nonlinear weighted squared envelope-based fuzzy entropy

Review of spectrum analysis in fault diagnosis for mechanical equipment

A novel current sensor indicator enabled WAFTR model for tool wear prediction under variable operating conditions

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