The Identification and Assessment of Rail Corrugation Based on Computer Vision

The identification and assessment of rail corrugation are two of the essential tasks of daily railway inspection to guarantee the safety of train operation and promote the development of an efficient maintenance strategy. In view of the requirements for automatic identification and smart decision-ma...

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Bibliographic Details
Published in:Applied sciences 2019-09, Vol.9 (18), p.3913
Main Authors: Wei, Dehua, Wei, Xiukun, Liu, Yuxin, Jia, Limin, Zhang, Wenqiang
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Classification
Computer vision
Corrugation
Decision making
Frequency analysis
Frequency domain analysis
Identification
Identification methods
Inspection
Maintenance costs
Methods
Model matching
Morphology
Noise
period estimation
rail corrugation identification
severity assessment
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Summary:The identification and assessment of rail corrugation are two of the essential tasks of daily railway inspection to guarantee the safety of train operation and promote the development of an efficient maintenance strategy. In view of the requirements for automatic identification and smart decision-making, computer vision-based rail corrugation identification and assessment methods are presented in this paper. Firstly, an improved Spatial Pyramid Matching (SPM) model, integrating multi-features and locality-constrained linear coding (IMFLLC), is proposed for rail corrugation identification. After that, an innovative period estimation method for rail corrugation is proposed based on the frequency domain analysis of each column in the corrugation region. Finally, the severity of the rail corrugation is assessed with the help of the wear saliency calculation and fuzzy theory. The experiment results demonstrate that the proposed corrugation identification method achieves a higher precision rate and recall rate than those of traditional methods, reaching 99.67% and 98.34%, respectively. Besides, the validity and feasibility of the proposed methods for the rail corrugation period estimation and severity assessment are also investigated.
ISSN:2076-3417
2076-3417
DOI:10.3390/app9183913