A detection method for the loosening of wire-connected bolts
Through the method of fusion of two-dimensional image and point cloud data, neural network and linear detection technology are used to solve the problem of preload detection of wire-connected bolts, efficient and accurate intelligent detection is achieved, and the level of automated patrol is improved.
CN114494126BActive Publication Date: 2025-07-04CRRC HANGZHOU DIGITAL TECH CO LTD
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Patent Information
- Application Number
- CN202111585572.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-12-23
- Publication Date
- 2025-07-04
- Estimated Expiration
- 2041-12-23
AI Technical Summary
Technical Problem
The existing detection methods cannot accurately detect the disappearance of preloading force of wire series bolts, resulting in a low recognition rate of wire series bolts during intelligent inspections.
Method used
Using a fusion method based on two-dimensional image and point cloud data, image data is obtained through a 3D color camera, target detection is performed using neural networks, and linear detection and point cloud data dimensionality reduction are used to calculate the wire depth curvature to judge the relaxation state.
Benefits of technology
It improves the accuracy of wire-connected bolt detection, realizes contactless and efficient intelligent detection, saves labor costs, and improves the level of automation of detection.
✦ Generated by Eureka AI based on patent content.
Abstract
The present invention discloses a detection method for the looseness of wire-connected bolts, belonging to the technical field of machine vision detection. Two-dimensional color data and three-dimensional point cloud data of the wire-connected bolt group to be detected are obtained through a 3D camera, and a neural network is used to perform target detection on the wire-connected bolt group; the position of the wire to be detected is obtained by performing line detection on the detection area, and the point cloud data of the corresponding area is extracted; the dimensionality reduction in the depth direction is performed on the point cloud data; the shape of the wire in the depth direction is obtained, and the curvature of the depth change of the wire is calculated to realize the detection of the connection state of the wire. The present invention locates the position of the wire through a two-dimensional image, judges its fracture or missing failure form, and further combines the three-dimensional point cloud data to judge the curvature of the depth change of the wire for looseness detection, which can effectively improve the detection accuracy and assist in intelligent daily maintenance operations.
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