Damage Degree Detection of Cracks in a Locomotive Gear Transmission System

Liu, XinChang; Sun, Qi; Chen, Chunjun

doi:10.1155/2018/5761064

Cited by 5 publications

(4 citation statements)

References 28 publications

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“…The gear fault frequency primarily manifests in the gear meshing frequency band. Liu et al [39] obtained the vertical vibration acceleration of the locomotive body, bogie frame, wheelset, and motor under different degrees of tooth cracking using a dynamic locomotive model with gear transmission. The results indicate that when a tooth root crack occurs in the pinion of the gear transmission system, the vibration signal exhibits the pinion's rotational frequency and its harmonics.…”

Section: Gear Tooth Crackmentioning

confidence: 99%

“…As shown in Fig. 11, Liu et al [39] used the PCA and the Grey relational analysis methods to detect the degree of tooth root crack damage in the locomotive gear transmission system. Firstly, the multidimensional characteristic parameter matrix is established by calculating various indicators of vertical vibration of the vehicle body.…”

Section: Artificial Intelligence Algorithmsmentioning

confidence: 99%

“…11. Flow chart of detecting the degree of tooth root crack damage [39] When labeled data is not available, fault detection algorithms become more applicable.…”

Section: Identification Of Damage Degreementioning

confidence: 99%

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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: Gear Tooth Crackmentioning

confidence: 99%

Section: Artificial Intelligence Algorithmsmentioning

confidence: 99%

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Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

Zhao,

Chen

2024

JDMD

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“…Yang et al [43] established a local model of the gear system of high-speed trains and conducted in-depth research on the variation law of bifurcation behavior with rotational speed under wear faults. Liu et al [44] established a dynamic locomotive model with gear transmission and analyzed the dynamic response to assist the feature selection in fault detection. Chen et al [45] applied a 2D vehicle-track-coupled model to investigate the vibration feature evolution and proposed an angular synchronous average technique to suppress the noise caused by track irregularities.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Characteristics and Fault Mechanism of the Gear Tooth Spalling in Railway Vehicles under Traction Conditions

Lin

Chen

et al. 2023

Applied Sciences

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Gear tooth spalling is one of the inevitable fault modes in the long-term service of the traction transmission system of railway vehicles, which can worsen the dynamic load of the rotating mechanical system and reduce the operating quality. Therefore, it is necessary to study its fault mechanism to guide fault diagnosis scientifically. This paper established a planar railway vehicle model with a traction transmission system and an analytical time-varying meshing stiffness (TVMS) model of the spalling spur gear. Then, it analyzed the dynamic characteristics under traction conditions. The research found that the spalling length and depth affect the amplitude of the TVMS at the defect, while the width affects the range of the TVMS loss. The crest factor is the best evaluation indicator in ideal low-noise environments due to its sensitivity and linearity, but it is not good in strong-noise environments. Similarly, a time–frequency analysis tool cannot significantly detect the sideband characteristics that are excited by spalling. After high-pass filtering, the root mean square and variance exhibit excellent classification and vehicle speed independence in strong-noise environments. This research achievement can provide adequate theoretical support for feature selection and making strategies for fault diagnosis of railway vehicle gear systems.

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