Visual Fault Detection of Multiscale Key Components in Freight Trains

Zhang, Yang; Zhou, Yang; Pan, Huilin; Wu, Bo; Sun, Guodong

doi:10.1109/tii.2022.3224989

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…In the field of railway transportation, fault detection for key components in the braking system of freight trains is critical for ensuring railway transportation safety [1] since the abnormal state of these components can result in serious consequences. Therefore, it is very necessary to detect the abnormal state of these components of freight trains during transportation so as to deal with these anomalies in time to ensure the safety of freight trains [2].…”

Section: Introductionmentioning

confidence: 99%

Coarse-to-Fine Localization for Detecting Misalignment State of Angle Cocks

Lei,

Cao,

2023

Sensors

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The state of angle cocks determines the air connectivity of freight trains, and detecting their state is helpful to improve the safety of the running trains. Although the current research for fault detection of angle cocks has achieved high accuracy, it only focuses on the detection of the closed state and non-closed state and treats them as normal and abnormal states, respectively. Since the non-closed state includes the fully open state and the misalignment state, while the latter may lead to brake abnormally, it is very necessary to further detect the misalignment state from the non-closed state. In this paper, we propose a coarse-to-fine localization method to achieve this goal. Firstly, the localization result of an angle cock is obtained by using the YOLOv4 model. Following that, the SVM model combined with the HOG feature of the localization result of an angle cock is used to further obtain its handle localization result. After that, the HOG feature of the sub-image only containing the handle localization result continues to be used in the SVM model to detect whether the angle cock is in the non-closed state or not. When the angle cock is in the non-closed state, its handle curve is fitted by binarization and window search, and the tilt angle of the handle is calculated by the minimum bounding rectangle. Finally, the misalignment state is detected when the tilt angle of the handle is less than the threshold. The effectiveness and robustness of the proposed method are verified by extensive experiments, and the accuracy of misalignment state detection for angle cocks reaches 96.49%.

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Section: Introductionmentioning

confidence: 99%

Coarse-to-Fine Localization for Detecting Misalignment State of Angle Cocks

Lei,

Cao,

2023

Sensors

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“…The strategy encompasses an image generation technique based on deep learning, which allows for data augmentation of industrial objects with limited samples. Robust pose measurement of surface key points of the target object is achieved through an enhanced anchor-based object detection network [13]. By combining this with the EPnP pose estimation iterative algorithm [14], the robot becomes capable of measuring the 6DOF pose and grasping the target workpiece.…”

mentioning

confidence: 99%

Research on Robot Monocular Vision-Based 6DOF Object Positioning and Grasping Approach Combined With Image Generation Technology

Wan,

Chen,

Zhang

et al. 2023

IEEE Access

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In order to tackle the challenges related to poor positioning accuracy and high usage cost of 6DOF visual measurement systems in industrial settings, this paper presents a monocular vision-based robot vision guidance approach. The goal is to address the issues of expensive 6DOF pose measurement and limited measurement robustness when robots need to manipulate metal objects in industrial environments. The proposed approach enables precise and robust measurement of the 6DOF pose of the target workpiece. The approach integrates two main algorithms: a virtual reality-based image data enhancement algorithm and a 6DOF pose measurement algorithm that combines a multi-keypoint detection model and the Efficient Perspective-n-Points (EPnP) algorithm. The image data enhancement algorithm enhances the data of small-sample industrial objects using image enhancement techniques. This improves the robustness of the detection model by mitigating the challenges of high-cost image acquisition and long acquisition time associated with industrial objects. On the other hand, the 6DOF pose measurement algorithm performs the pose measurement of the target workpiece using a single image, enabling cost-effective 6DOF pose measurement by utilizing only a monocular camera. Experimental results demonstrate that the proposed method achieves measurement errors of 4.21% in the X direction, 2.94% in the Y direction, and 0.39% in the Z direction of the target workpiece. These results highlight the effectiveness of the proposed approach in achieving accurate and reliable pose measurement.

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Spatial-Wise Dynamic Distillation for MLP-Like Efficient Visual Fault Detection of Freight Trains

Zhang,

Pan,

et al. 2024

IEEE Trans. Ind. Electron.

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Visual Fault Detection of Multiscale Key Components in Freight Trains

Cited by 5 publications

References 44 publications

Coarse-to-Fine Localization for Detecting Misalignment State of Angle Cocks

Coarse-to-Fine Localization for Detecting Misalignment State of Angle Cocks

Research on Robot Monocular Vision-Based 6DOF Object Positioning and Grasping Approach Combined With Image Generation Technology

Spatial-Wise Dynamic Distillation for MLP-Like Efficient Visual Fault Detection of Freight Trains

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