Current-Based Gear Fault Detection for Locomotive Gearboxes

Zhang, Zhang; Yang, Jiangtian

doi:10.1109/phm-chongqing.2018.00211

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…In fact, a local fault in the gear causes torque oscillations that modulate the frequency component of the stator current signal and generate sidebands in the power spectrum of the stator current. Hence, Zhang et al [66] proposed a fault diagnosis method based on wavelet energy entropy and dual-tree complex wavelet transform. The wavelet energy entropy can be used for a preliminary diagnosis of the signal, while the dual-tree complex wavelet transform can provide further insight into the fault type.…”

Section: Signal Processing Algorithmsmentioning

confidence: 99%

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

Zhao,

Chen

2024

JDMD

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The railway vehicle gearbox is an important part of the railway vehicle traction transmission system which ensures the smooth running of railway vehicles. However, as the running speed of railway vehicles continues to increase, the railway vehicle gearbox is exposed to a more demanding operating environment. Under both internal and external excitations, the gearbox is prone to faults such as fatigue cracks, broken teeth, etc. It is crucial to detect these faults before they result in severe failures and accidents. Therefore, understanding the dynamics and fault diagnosis of railway vehicle gearbox is needed. At present, there is a lack of systematic review of railway vehicle gearbox dynamics and fault diagnosis. So, this paper systematically summarizes the research progress on railway vehicle gearbox dynamics and fault diagnosis. To this end, this paper first summarizes the latest research progress on the dynamics of railway vehicle gearboxes. The dynamics and vibration characteristics of the gearbox are summarized under internal and external excitations, as well as faulty conditions. Then, the state-of-the-art signal processing and artificial intelligence methods for fault diagnosis of railway vehicle gearboxes are reviewed. In the end, future research prospects are given. Conflict of Interest Statement The authors declare no conflicts of interest.

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Section: Signal Processing Algorithmsmentioning

confidence: 99%

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

Zhao,

Chen

2024

JDMD

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“…e continual monitoring without extra sensors and hardware makes this method especially suitable for vehicle applications [17,18]. e tooth localized faults of gears produce mechanical impacts, causing additional mechanical torque fluctuations [19]. e motor will produce an additional torque fluctuation to balance.…”

Section: Introductionmentioning

confidence: 99%

Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current

Zhang

Yang

Zhang

2021

Shock and Vibration

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The motor current signature analysis (MCSA) provides a nondestructive method for gear fault detection. The motor current in the faulty gear system not only involves the frequency information related to the fault but also the electric supply frequency and gear meshing-related frequency, which not only contaminates the fault characteristics but also increases the difficulty of fault extraction. To extract the fault characteristic frequency effectively, an innovative method based on the wavelet bispectrum (WB) is proposed. Bispectrum is an effective tool for identifying the fault-related quadratic phase coupling (QPC). However, it requires a large amount of data averaging, which is not suitable for short data analysis. In this paper, the wavelet bispectrum is introduced to motor current analysis and the problem of QPC extraction under variable speed conditions is preliminarily solved. Furthermore, a fault diagnostic approach for locomotive gears using the wavelet bispectrum and wavelet bispectral entropy is suggested. The presented method was effectively applied to the locomotive online running operations, and faults of the drive gear were successfully diagnosed.

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Current-Based Gear Fault Detection for Locomotive Gearboxes

Cited by 2 publications

References 15 publications

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current

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