Applicable to train visual positioning and defect detection method and device
A visual positioning and defect detection technology, which is applied in computer equipment and storage media, and in the field of visual positioning and defect detection of trains, can solve the problems of difficult template selection and high missed detection rate, reduce the loss of human resources, improve speed and accuracy The effect of reducing the probability of missed detection or false detection
Active Publication Date: 2021-12-07
江苏中车数字科技有限公司
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Problems solved by technology
However, this type of detection is based on traditional methods, and the missed detection rate is high, and due to the influence of the lighting environment, it is difficult to select a template when matching
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[0053] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0054] The visual positioning and defect detection method suitable for trains provided by this application can be applied to such as figure 1 shown in the application environment. Wherein, the terminal 102 communicates with the server 104 through the network. Wherein, the terminal 102 can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices, and the server 104 can be realized by an independent server or a server cluster composed of multiple servers.
[0055] In one embodiment, such as figur...
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The application relates to a visual positioning and defect detection method, system, computer equipment and storage medium suitable for trains. The method includes: acquiring two-dimensional image information and three-dimensional point cloud information of the area to be measured, and preprocessing the two-dimensional image information; inputting the preprocessed two-dimensional image information into the first visual positioning network model , to determine the first target information in the two-dimensional image information; input the first target information into the first defect network model to determine whether the first target information has obvious defects; according to the first target information Calibrating the 3D point cloud information to determine second target information in the 3D point cloud information; extracting depth features of the second target information to determine whether there is a depth defect in the second target information. This method can meet the needs of the detection of key parts at the bottom of the train, and integrate traditional image processing methods and deep learning to achieve efficient and accurate visual detection.
Description
technical field [0001] The present application relates to the technical field of train detection, in particular to a visual positioning and defect detection method, device, computer equipment and storage medium suitable for trains. Background technique [0002] With the rapid progress of my country's economic flow and trade, rail transit, as an important mode of modern transportation, has also been greatly developed and improved. As of 2020, a total of 44 cities across the country have opened and operated 233 urban rail transit lines, and the operating mileage 7545.5 kilometers, and the operating speed can reach up to 160km / h. Compared with cars and other modes of transportation, due to the high-speed characteristics of rail transit, any small faults and hidden dangers may cause extremely serious consequences if they cannot be detected in time. [0003] At present, most of the daily inspections of rail transit trains in our country are limited to manual completion. However, ...
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IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06T7/0002G06N3/08G06T2207/10004G06T2207/10028G06T2207/20081G06T2207/20084G06T2207/30248G06N3/045
Inventor 李峰景宁杨泽迎洪晓杰张玉刘达张壮王攀
Owner 江苏中车数字科技有限公司