Trackside acoustic detection of axle-box bearing fault based on cyclic beamforming

Hu, Dingyu; Zhang, Yanzhe; Chen, Hangyu; Shi, Wei; Liao, Aihua

doi:10.1016/j.apacoust.2024.110065

Applied Acoustics

2024

DOI: 10.1016/j.apacoust.2024.110065

|View full text |Cite

Trackside acoustic detection of axle-box bearing fault based on cyclic beamforming

Dingyu Hu,

Yanzhe Zhang,

Hangyu Chen

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A two-step bearing fault diagnosis strategy under variable speed based on symplectic geometry modal decomposition and practical fault feature extraction framework

Huang,

Li,

Wang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

Strong noise interference can lead to failure of bearing fault diagnosis techniques. This paper proposes a two-step fault diagnosis strategy to address the challenge of weak fault feature extraction in bearing fault diagnosis using acoustic or vibration data at varying speed. Firstly, the paper introduces a short-time symplectic modal decomposition (stSGMD) method that utilizes fractional Fourier transform. This method involves signal processing with short-time windowing to extract fault-sensitive components. The window is then expanded to obtain the complete component through fractional Fourier narrow-band filtering based on energy concentration in the fractional Fourier domain. A novel entropy index, standard deviation discrete entropy, is introduced to quantify the intensity of fault shocks in non-stationary signal and is used to select components in the stSGMD. Subsequently, a fault feature extraction framework called global objective deconvolution (GOD) is presented for extracting instantaneous fault features at varying speed. This method establishes a global objective matrix for the extraction process. The GOD is utilized to deconvolute the complete fault-sensitive component, followed by envelope order analysis for demodulating the fault feature order. Numerical simulations and experimental studies on acoustics and vibration are performed. The results demonstrate that stSGMD improves the demodulation capability of SGMD, while GOD effectively extracts fault features. It is expected that the presented method will be effectively utilized for fault feature extractions in bearings operating under linear variable speed conditions.

show abstract

A two-step bearing fault diagnosis strategy under variable speed based on symplectic geometry modal decomposition and practical fault feature extraction framework

Huang,

Li,

Wang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Trackside acoustic detection of axle-box bearing fault based on cyclic beamforming

Cited by 1 publication

References 31 publications

A two-step bearing fault diagnosis strategy under variable speed based on symplectic geometry modal decomposition and practical fault feature extraction framework

A two-step bearing fault diagnosis strategy under variable speed based on symplectic geometry modal decomposition and practical fault feature extraction framework

Contact Info

Product

Resources

About