Unlock instant, AI-driven research and patent intelligence for your innovation.

A method for automatic detection of truck axlebox spring faults

An axle box spring and automatic detection technology, which is applied in the direction of measuring devices, optical testing defects/defects, image enhancement, etc., can solve the problems of low accuracy and stability, and cannot ensure the safety of trucks, so as to improve the universality of the system performance, improve detection efficiency and accuracy, and identify simple and efficient effects

Active Publication Date: 2021-03-30
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problem that the accuracy and stability of fault detection in the manual detection image mode of the existing truck axle box spring is not high, and the driving safety of the truck cannot be ensured.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method for automatic detection of truck axlebox spring faults
  • A method for automatic detection of truck axlebox spring faults
  • A method for automatic detection of truck axlebox spring faults

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0021] Specific implementation mode one: refer to figure 1 To illustrate this embodiment, this embodiment is an automatic detection method for truck axlebox spring faults, including:

[0022] Step 1. Build imaging equipment around the track. The imaging equipment has a certain elevation angle to the side of the vehicle body. After the truck passes through the imaging equipment, obtain the large image of the axle box spring (that is, the rough positioning image, according to the wheelbase information and combined with the axle box spring on the bogie. The prior knowledge of the middle position intercepts the image containing the axlebox spring but the range is larger than the axlebox spring), and the large image includes a height image and a grayscale image;

[0023] Step 2, correcting the height image in the large image of the axlebox spring;

[0024] Step 3. Obtain the sub-image of the overall height of the axlebox spring and the gray-scale sub-image respectively;

[0025] ...

specific Embodiment approach 2

[0027] Embodiment 2: This embodiment differs from Embodiment 1 in that in Step 1, an imaging device is built around the track, and after the truck passes through the device, a large image of the axlebox spring is obtained, and the large image of the axlebox spring includes a height image and grayscale images; the specific process is:

[0028] The imaging device includes a camera acquisition unit, a magnetic steel unit, a 3D image acquisition industrial computer unit, a control industrial computer unit and an image recognition unit, wherein the camera acquisition unit includes a camera and a compensation light module;

[0029] The camera acquisition unit shoots and collects the images of passing trucks, and the 3D image acquisition industrial computer unit stores the collected images; the magnetic steel unit transmits the signals of the near-end magnetic steel and the far-end magnetic steel to the control industrial computer unit, and the control industrial computer unit passes ...

specific Embodiment approach 3

[0032] Embodiment 3: This embodiment differs from Embodiment 1 or Embodiment 2 in that the step 2 corrects the height image in the large image of the axlebox spring; the specific process is:

[0033] The side image of the truck is taken by a camera with an elevation angle, so the depth information of the same plane in the initially obtained 3D image is not the same. For example, the 3D image of the bearing is not an ideal cylinder, but the depth information value of the part far from the ground Small, the depth information value of the part close to the ground is larger;

[0034] For objects on the same plane, the ideal depth information value should be the same, but initially in the depth image, it is different in different rows of images; there is a certain disturbance in the depth information, but generally the actual depth information is different from the initial depth information. The relationship between the difference value and the number of rows in the image is equiva...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

PropertyMeasurementUnit
greyscaleaaaaaaaaaa
Login to View More

Abstract

The invention relates to an automatic detection method for a truck axle box spring failure, which belongs to the technical field of truck operation. The invention aims to solve the problem that the fault detection accuracy and stability of the axle box spring of the truck are not high enough to ensure the driving safety of the truck by manual detection of images. The method of the present invention includes: building a 3D high-definition imaging device around the track, and obtaining a height image and a grayscale image after the truck passes through the device; using hardware wheelbase information combined with prior knowledge to perform rough positioning of the axle box spring components in the image; After height image correction, use the image processing method to identify the vehicle type of the axle box spring and then accurately locate the axle box spring; use advanced image processing algorithms and pattern recognition methods to analyze the fault of the axle box spring to determine whether it has sprung out or broken A fault occurs; upload an alarm to the faulty axle box spring component, and the staff will deal with it according to the identification result. The invention is used for fault detection of axle box springs of trucks.

Description

technical field [0001] The invention relates to an automatic detection method for a truck axle box spring failure. The utility model belongs to the technical field of truck operation. Background technique [0002] The truck axle box spring plays the role of cushioning and fixing, which is used to avoid the instability of the vehicle's snake movement within the operating speed range, ensure good guiding performance when the curve passes, reduce the wear and noise between the wheel rim and the rail, and ensure safe and secure operation. smooth. The breakage or escape of the axlebox spring will endanger the safety of the train. Therefore, the relevant departments of the railway attach great importance to the fault detection of the axlebox spring. In the fault detection of axlebox springs, fault detection is generally carried out by manually inspecting images. However, due to the fact that the inspectors are prone to fatigue and inattention during the work process, and may al...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/10G06T7/70G06T5/00G01N21/88
CPCG01N21/8851G01N2021/8854G01N2021/8887G06T5/006G06T7/0002G06T2207/10012G06T2207/20024G06T2207/20221G06T7/10G06T7/70
Inventor 刘丹丹
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com