2022
DOI: 10.1061/jtepbs.0000678
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Mud Pumping Defect Detection of High-Speed Rail Slab Track Based on Track Geometry Data

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Cited by 5 publications
(8 citation statements)
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References 26 publications
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“…The redundancy removal operation of the detection box is an important part of defect detection networks, which directly affects the training effectiveness. NMS filters the prediction boxes based on a fixed threshold, as shown in (1). Using threshold judgment, object detection boxes with high confidence are reserved, whereas false detection boxes with low confidence are suppressed.…”
Section: E Soft-nms Blockmentioning
confidence: 99%
See 1 more Smart Citation
“…The redundancy removal operation of the detection box is an important part of defect detection networks, which directly affects the training effectiveness. NMS filters the prediction boxes based on a fixed threshold, as shown in (1). Using threshold judgment, object detection boxes with high confidence are reserved, whereas false detection boxes with low confidence are suppressed.…”
Section: E Soft-nms Blockmentioning
confidence: 99%
“…In intelligent industrial manufacturing scenarios [1], [2], [3], the product surface is inevitably affected by factors such as the processing technology, environmental temperature and manual operation errors, which lead to porosity and scratches. Therefore, defect detection is an important step in evaluating the quality of industrial products [3].…”
Section: Introductionmentioning
confidence: 99%
“…As a means of transportation for high-speed rail operation, the quality of heavy rail is an significant condition to ensure the safe transportation of railroads. In addition to the more stringent material, processing technology, geometric size and physical and chemical properties, surface defects have become an significant technical indicator [1][2][3] . Take a rail beam factory's heavy rail defects manual inspection method as an example, the traditional 100m heavy rail inspection line has 3 teams, each team is responsible for one-third of the length of the inspection, each team of 4 people, respectively, to inspect each side of the heavy rail.…”
Section: Introductionmentioning
confidence: 99%
“…Li et al [37,38] proposed a data-driven method for infrastructure deformation identification based on the characteristics of track geometry data, as well as a spatio-temporal identification model for identifying high-speed railway infrastructure deformation by using four years of track geometry data. Li et al [39] analyzed the time and frequency characteristics of track geometry irregularity signals at the locations of mud pumps and used a multi-scale signal decomposition method to extract defect-sensitive features and then realize automatic detection of mud pumping problems. The nearly continuous and real-time track health monitoring of the entire rail networks could be possibly accomplished in a timely and cost-efficient manner by mounting robust sensors on in-service trains.…”
Section: Introductionmentioning
confidence: 99%