Dust collector localization in trouble of moving freight car detection system

Zhou, Fuqiang; Zou, Rong; He, Gaohong

doi:10.1631/jzus.c1200223

Cited by 12 publications

(5 citation statements)

References 24 publications

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“…For 5000 live BSK images in each place, our system had correct inspection rates above 99.2%, confirming the system's very high inspection reliability. Usually, visual inspection systems have an accuracy of 85%-95% (Marino et al, 2007;Yella et al, 2009;Zhou et al, 2013). Under conditions of variable illumination, our system can achieve an accuracy rate of 99.2%, which is fully able to meet actual requirements.…”

Section: Detection Resultsmentioning

confidence: 88%

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Real-time monitoring of brake shoe keys in freight cars

Zou

et al. 2015

Frontiers Inf Technol Electronic Eng

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Condition monitoring ensures the safety of freight railroad operations. With the development of machine vision technology, visual inspection has become a principal means of condition monitoring. The brake shoe key (BSK) is an important component in the brake system, and its absence will lead to serious accidents. This paper presents a novel method for automated visual inspection of the BSK condition in freight cars. BSK images are first acquired by hardware devices. The subsequent inspection process is divided into three stages: first, the region-of-interest (ROI) is segmented from the source image by an improved spatial pyramid matching scheme based on multi-scale census transform (MSCT). To localize the BSK in the ROI, census transform (CT) on gradient images is developed in the second stage. Then gradient encoding histogram (GEH) features and linear support vector machines (SVMs) are used to generate a BSK localization classifier. In the last stage, a condition classifier is trained by SVM, but the features are extracted from gray images. Finally, the ROI, BSK localization, and condition classifiers are cascaded to realize a completely automated inspection system. Experimental results show that the system achieves a correct inspection rate of 99.2% and a speed of 5 frames/s, which represents a good real-time performance and high recognition accuracy.

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Section: Detection Resultsmentioning

confidence: 88%

“…Railway condition inspection routines are conducted periodically to ensure a proper condition of the structure or material (Márquez et al, 2010;Oukhellou et al, 2010;Zhou et al, 2013;2014). The traditional condition inspection process is performed by trained personnel who frequently searches for visual anomalies.…”

Section: Introductionmentioning

confidence: 99%

Real-time monitoring of brake shoe keys in freight cars

Zou

et al. 2015

Frontiers Inf Technol Electronic Eng

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“…In order to improve the detection efficiency, it is necessary to do the following improvements. 1) Use the region of interest to reduce invalid accumulation The use of prior knowledge to reduce the detection area can reduce the amount of image data and improve the detection efficiency [13]. The axle and the side frame of the original image from the edge of each of the 16 contained in the region, the region is S.…”

Section: Feature Extraction Of Axlementioning

confidence: 99%

“…Therefore, the ministry of railways is vigorously to promote a safety inspection system──Trouble of moving freight car detection system (TFDS) [1,2]. TFDS uses equipment to shoot fast-moving freight train, image acquisition, and then the use of computer image recognition, thus picking fault [3,4].…”

Section: Introductionmentioning

confidence: 99%

An Automatic Method for Detecting Side Frame Key Using Histogram of Oriented Gradient and Local Binary Pattern

Zhang¹,

Wang²,

Feng³

et al. 2017

IJCA

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“…Sobol sensitivity analysis method [5][6] is a global sensitivity analysis method based on variance, it breaks the function   f X into the sum of 2 n increasing terms, by calculating the total variance of the model response, the contribution of a single input to the output variance and the contribution of multiple input to the output variance (sensitivity index), so as to evaluate the sensitivity of a single input and multiple input interaction effect. Sobol method requires that the input parameters follow uniform distribution U [0,1], but it is difficult to meet the requirements in practical application; if the input parameters do not follow uniform distribution U [0,1],using the Sobol sensitivity analysis model, the illogical analysis results will appear.For   1 2…”

Section: Introductionmentioning

confidence: 99%

An Improved Sobol Sensitivity Analysis Method

Chen,

Xu,

Huang

et al. 2024

J. Phys.: Conf. Ser.

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The Sobol method is a variance-based global sensitivity analysis method that evaluates single-input and multiple-input interaction effects by calculating the contribution of a single input to the output variance and the contribution of multiple inputs to the output variance. The Sobol method requires each input to obey a uniform distribution of U [0,1], but it is difficult to meet the requirements in practice. Taking the sum function as an example, this paper analyzes the inapplicability of the existing Sobol method when the input does not obey the uniform distribution U [0,1]. To solve the inapplicability of the Sobol method and broaden the application scope, an improved Sobol sensitivity analysis method is proposed. First, the effect of the joint probability density function not 1 on sensitivity calculation is studied; second, the input parameters are changed to uniform distribution U [0,1] through variable substitution; finally, a complete algorithm model is presented and logical sensitivity analysis results are obtained. Application verification shows that the improved Sobol method is more scientific, applicable and practical.

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Dust collector localization in trouble of moving freight car detection system

Cited by 12 publications

References 24 publications

Real-time monitoring of brake shoe keys in freight cars

Real-time monitoring of brake shoe keys in freight cars

An Automatic Method for Detecting Side Frame Key Using Histogram of Oriented Gradient and Local Binary Pattern

An Improved Sobol Sensitivity Analysis Method

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