CN107764205B - Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning - Google Patents

Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning Download PDF

Info

Publication number
CN107764205B
CN107764205B CN201711079863.2A CN201711079863A CN107764205B CN 107764205 B CN107764205 B CN 107764205B CN 201711079863 A CN201711079863 A CN 201711079863A CN 107764205 B CN107764205 B CN 107764205B
Authority
CN
China
Prior art keywords
welded
laser
weld
center
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201711079863.2A
Other languages
Chinese (zh)
Other versions
CN107764205A (en
Inventor
王会峰
姚乃夫
王晓蒙
艾雪雯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xi'an Zhongce Control Technology Co ltd
Original Assignee
Changan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Changan University filed Critical Changan University
Priority to CN201711079863.2A priority Critical patent/CN107764205B/en
Publication of CN107764205A publication Critical patent/CN107764205A/en
Application granted granted Critical
Publication of CN107764205B publication Critical patent/CN107764205B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/24Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/25Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
    • G01B11/2518Projection by scanning of the object
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/02Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/022Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness by means of tv-camera scanning
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/02Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/06Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
    • G01B11/0608Height gauges

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

本发明提供一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置及检测方法,所述装置包括线结构光传感器、线位移传送系统及计算机。其中线结构光传感器包括激光器、工业相机及固定面板;线位移传送系统包括底座、步进电机及步进电机控制器。将被焊物件放置在传送系统的底座上,采用线结构光扫描,工业相机拍摄得到焊缝激光光条图像,通过软件系统处理得到焊缝三维点云数据,分析得到焊缝宽度、高度等形貌特征,从而可以对焊缝质量进行判断。本发明具有精度高、安全可靠、实时检测等优点,提高了焊缝质量检测的效率,可以实现焊缝质量的自动检测。

Figure 201711079863

The invention provides a three-dimensional detection device and a detection method for the profile of a high-frequency resistance welding seam based on linear structured light scanning. The device comprises a linear structured light sensor, a linear displacement transmission system and a computer. The linear structured light sensor includes a laser, an industrial camera and a fixed panel; the linear displacement transmission system includes a base, a stepping motor and a stepping motor controller. Place the object to be welded on the base of the conveying system, use line structured light scanning, industrial camera to capture the laser light bar image of the weld, and process the three-dimensional point cloud data of the weld through the software system, and analyze the width, height and other shapes of the weld. appearance characteristics, so that the quality of the weld can be judged. The invention has the advantages of high precision, safety and reliability, real-time detection, etc., improves the efficiency of welding seam quality inspection, and can realize automatic inspection of welding seam quality.

Figure 201711079863

Description

Three-dimensional detection device and detection method for high-frequency resistance welding seam appearance based on line structure light scanning
Technical Field
The invention relates to three-dimensional detection, in particular to three-dimensional detection of high-frequency resistance welding seam appearance based on line structure light scanning.
Background
At present, a welding inspection ruler is mainly adopted to detect the welding seam of the steel bar. The welding inspection ruler is a measuring instrument for inspecting the width, height, welding gap, groove angle, undercut depth and the like of a welding part by using the principles of line and vernier measurement and the like. The inspection ruler is influenced by various factors in the using process, different errors can exist in the detected result, manual detection is time-consuming and labor-consuming, efficiency is not high, and three-dimensional shape information of the surface of the welding seam cannot be acquired in real time for quality detection.
The structured light method is one of machine vision measurement methods, and comprises a point structured light method, a line structured light method and a surface structured light method, and the topography measurement of the surface of an object can be completed by using the structured light method. However, no report of measuring the shape of the weld joint by using a structured light method is seen at present, and the main problem is how to quickly and accurately acquire point cloud data about the shape of the weld joint, and one of the reasons for the problem is that the laser light strip image is affected by reflected light, and the central position of the laser line on the weld joint cannot be accurately determined.
Disclosure of Invention
The invention aims to overcome the defects and provides a three-dimensional detection device and a detection method for the appearance of a high-frequency resistance welding seam based on line structure light scanning; the method is simple to operate, high in detection efficiency and reliable in detection quality.
In order to achieve the purpose, the invention adopts the following technical scheme:
a three-dimensional detection device for high-frequency resistance welding seam appearance based on line structure light scanning comprises a line structure light sensor and a computer; the line structure light sensor comprises a laser for scanning a welded object and an industrial camera for collecting laser light strip images of the welded object, wherein a line structure light plane of the laser is intersected with a welding seam (when laser is projected onto the welding seam) on the surface of the welded object; the industrial camera is connected with the computer; the computer comprises a software system, wherein the software system comprises a video data acquisition module, a point cloud data processing module, an I/O and control module and a system calibration module;
the system calibration module is used for calibrating internal parameters and external parameters of the industrial camera; the external parameters are the pose relation between the light plane of the linear structure and the industrial camera;
the video data acquisition module is used for transmitting the laser light strip images of the welded object acquired by the industrial camera to the point cloud data processing module; the laser light strip image of the welded object is a laser line image which is projected on the surface of the welded object and is distorted and collected by an industrial camera;
the point cloud data processing module is used for acquiring three-dimensional point cloud data of a welding seam according to laser light bar images of welded objects and the relation between pixel coordinates of the light bar images obtained through calibration and actual world coordinates, and measuring the width and height of the welding seam;
the I/O and control module is used for monitoring the input of the industrial camera, informing the video data acquisition module to start or stop acquiring the video image, outputting a signal according to the point cloud data acquired by the point cloud data processing module and the welding seam measurement result and displaying the signal by a computer.
Preferably, the point cloud data processing module comprises a sub-module A, a sub-module B, a sub-module C and a sub-module D; the sub-module A is a light strip center sub-pixel coordinate extraction module and is used for performing sub-pixel precision extraction on the laser light strip center coordinate; the sub-module B is a welding line and object segmentation module and is used for segmenting the center of the laser light bar according to the welded object and the welding line and reserving the center coordinate of the laser light bar at the welding line; the sub-module C is an image coordinate and world coordinate mapping module and is used for converting the divided laser light bar central coordinates at the welding seam into world coordinates to obtain welding seam surface point cloud data; and the sub-module D is a parameter acquisition and display module and is used for calculating the width and height information of the welding seam and generating a welding seam three-dimensional model in real time according to the point cloud data on the surface of the welding seam.
Preferably, in the line-structured light sensor, the laser is selected from a red laser with a wavelength range of 630nm to 660nm, and the red laser has low divergence, good collimation and high transmittance, so that a red laser with a wavelength of about 650nm is selected; the included angle range between the industrial camera and the vertical direction is 31-43 degrees, so that the image collected by the industrial camera contains laser light bars, wherein 37 degrees is selected, the light bars can be positioned in the center of the image, and the information of the complete light bar image can be conveniently extracted.
Preferably, the three-dimensional detection device further comprises a linear displacement transmission system and a fixed panel positioned above the linear displacement transmission system, and the laser and the industrial camera are arranged on the fixed panel; the linear displacement transmission system comprises a stepping motor, a stepping motor controller, a linear movement mechanical device driven by the stepping motor and a base for bearing the welded object; the base is fixed on the mechanical device; the stepping motor is connected with a stepping motor controller, and the stepping motor controller is connected with the computer.
Preferably, the I/O and control module stops the linear displacement transmission system from driving the base to perform the linear movement while notifying the video data acquisition module to stop acquiring the video image.
A three-dimensional detection method for the appearance of a high-frequency resistance welding seam based on line structure light scanning comprises the following steps:
1) scanning the welded object by adopting line structured light generated by a laser, and acquiring a laser light strip image of the welded object by an industrial camera; the line-structured light plane of the laser is intersected with a welding seam (when the laser is projected on the welding seam) on the surface of the welded object;
2) and processing the laser light stripe image of the welded object to obtain welding seam three-dimensional point cloud data and welding seam width and height morphology characteristics.
Preferably, the step 2) specifically comprises the following steps: inputting the laser light strip image of the welded object collected in real time into a computer, and converting the central coordinate of the laser light strip on the surface of the welding seam into a world coordinate by the computer according to the laser light strip image of the welded object and the relation between the pixel coordinate of the light strip image and the actual world coordinate to obtain the three-dimensional coordinate value of each point on the laser light strip on the surface of the welding seam; the width (horizontal distance between two ends of the cross section of the welding seam) and the height (vertical distance between the current highest point of the welding seam and the highest point of the surface of the welded object) of the welding seam are measured by the coordinate values.
Preferably, the method for extracting the central coordinates of the laser light bar on the surface of the weld seam comprises the following steps: firstly, performing dynamic threshold segmentation on a laser light bar image of a welded object to obtain an image region of interest; applying a gray threshold gravity center method to the region of interest to obtain the initial center of the structured light stripes; after obtaining the initial center of the structured light stripe, a Sobel operator is used for obtaining a gradient vector of a stripe pixel point, then a neighborhood (the number of vertical pixels of a direction block is 5-11 and is determined by the width of the light stripe, the number of horizontal pixels is 2-5 and is determined by the horizontal resolution of a light stripe image, such as 7 multiplied by 2) of each pixel point is selected as the direction speed of the point, the horizontal gradient and the vertical gradient of the direction block are obtained, the direction angle of the direction block, namely the direction field of the direction block, is obtained through calculation of the horizontal gradient and the vertical gradient, and the sub-pixel precision center of the laser light stripe is obtained along the direction field direction; and finally, removing the center point of the sub-pixel projected on the surface of the welded object on the laser light strip image of the welded object, and reserving the center point of the sub-pixel projected on the surface of the welding seam.
Preferably, the relationship between the coordinates of the pixels of the image of the light bars and the coordinates of the real world is obtained by calibrating a line-structured light sensor consisting of a laser and an industrial camera.
Preferably, the step 1) specifically comprises the following steps: and placing the welded object on a base of the linear displacement transmission system, continuously acquiring laser light strip images of the welded object by using an industrial camera along with the movement of the welded object, and sequentially inputting the laser light strip images into a computer for processing until the laser finishes scanning the welding seam on the whole welded object.
The invention has the beneficial effects that:
the invention can adopt a non-contact measurement mode to obtain the shape characteristics of the width, the height and the like of the welding line, can be used for judging the quality of the welding line and realizing the automatic detection of the quality of the welding line, has the advantages of high precision, safety, reliability, real-time detection and the like, and improves the efficiency of the detection of the quality of the welding line.
Furthermore, the method solves the problem of influence of light reflection of the welded object on the identification of the laser light bar image by extracting the sub-pixel coordinates in the center of the light bar, and improves the measurement precision.
Drawings
FIG. 1 is a schematic structural diagram of a three-dimensional detection device for the appearance of a high-frequency resistance welding seam;
in fig. 1: 1. laser 2, industrial camera 3, welded object 4, step motor controller 5, computer 6, base 7, mechanical device.
FIG. 2 is a flow chart of laser light bar sub-pixel center extraction.
Detailed Description
The invention is further illustrated by the following figures and examples. The examples are given solely for the purpose of illustration and are not intended to be limiting.
Examples
Referring to fig. 1, the three-dimensional detection device for the weld morphology of the high-frequency resistance welding based on line structure light scanning comprises a 650mm red light laser, an industrial camera with the model of WAT-902H2, a stepping motor controller, a computer and a base, wherein the red light laser 1 and the industrial camera 2 are fixed in the same panel to form a line structure light sensor, the industrial camera 2 inclines downwards and forms an included angle of 37 degrees with the vertical direction, the base 6 is fixed on a mechanical device 7 with a stepping motor (with the model of ASM66AC), the mechanical device 7 can enable the base 6 to move linearly under the driving of the stepping motor, an object to be welded 3 is fixed on the base 6, the industrial camera 2 and the stepping motor controller 4 are respectively connected with the computer 5, and the stepping motor is connected with the stepping motor controller 4.
The device is a non-contact scanning device and is used for acquiring three-dimensional information of the welding seam. An oil-gas pipeline with a welding line is placed on a base 6, a panel of a stepping motor controller comprises a power switch, a forward indicator light and a backward indicator light, the power switch of the stepping motor controller is turned on, a red laser is connected with a power supply of a red laser, the red laser is projected downwards to an object 3 to be welded in a mode of being perpendicular to the welding line (the line structure light plane of the laser is perpendicularly intersected with the welding line on the object to be welded), an instruction is sent out through a computer, the stepping motor controller 4 receives user instruction control, reads a signal and sends the signal to a stepping motor to enable the stepping motor to act, the base 6 is driven to linearly move (if the forward instruction is sent, the stepping motor controller receives the instruction, the forward indicator light starts to flash, the stepping motor is controlled to rotate clockwise, the base 6 is driven to linearly move on a mechanical device, and if the backward instruction is sent, the, the back indicator light begins to flash, the stepping motor is controlled to rotate in the anticlockwise direction, the base 6 is driven to perform reverse linear displacement action on the mechanical device), and the industrial camera 2 is informed to begin to collect videos. The device comprises an automatic termination function, wherein an image of a current welded object is shot by an industrial camera, the image of the welded object is processed by a computer, if a laser light bar in the current image is not projected on the surface of a welding seam any more, the scanning is judged to be finished, a stop instruction is sent by the computer to stop a stepping motor, and the shooting of the industrial camera is stopped. In addition, the device also comprises a manual termination function, when the automatic termination function is invalid, the system can be manually terminated, the motor stops operating, and the industrial camera stops shooting.
The industrial camera 2 shoots a laser line image which is projected on the surface of the welded object and generates distortion, namely a laser light strip image of the welded object, the image is transmitted to the computer 5 through a data line, the computer 5 processes the collected light strip image, three-dimensional coordinate values of a welding seam are obtained, a three-dimensional model of the welding seam is reconstructed, and the three-dimensional coordinate values are displayed through a computer display, and the method specifically comprises the following steps:
(1) light bar center sub-pixel coordinate extraction
As shown in fig. 2, firstly, performing dynamic threshold segmentation on a light stripe image to obtain an image region of interest (ROI), preliminarily calculating the center of the stripe by using a gray threshold gravity center method, obtaining the preliminary center of the structured light stripe, then obtaining gradient vectors of stripe pixel points by using Sobel operators, then selecting a 7 × 2 neighborhood of each pixel point as the direction speed of the point, calculating the horizontal gradient and the vertical gradient of a direction block, calculating the direction angle of the direction block, namely the direction field of the direction block, and calculating the sub-pixel precision center of the laser stripe along the direction of the direction field.
(2) Separation of welded seam and welded article
Because the welded object is an oil-gas pipeline, the cross section of the oil-gas pipeline is circular, the cross section of the oil-gas pipeline projected by laser is arc-shaped, 200 pixel points (depending on the size of the welded object) at the left end and the right end (namely outward along the width direction of a welding seam) of the sub-pixel precision center of the laser stripe extracted in the step (1) are selected for curve fitting (fitting of different orders can be selected according to the cross section shape of the welded object), and a curve equation of the cross section shape of the oil-gas pipeline is obtained. Removing the pixel points (namely the sub-pixel central points projected on the surface of the welded object) belonging to the 3 x 3 neighborhood of each pixel point on the curve equation from the light strip image of the welded object, and reserving the pixel points which are not in the neighborhood, wherein the reserved points are the sub-pixel central points projected on the surface of the welding line, thereby realizing the segmentation of the welding line and the welded object in the image.
(3) Calibration of line structured light sensor
The calibration of the line structured light sensor comprises the calibration of internal parameters and external parameters, the internal parameters of the industrial camera are calibrated by a checkerboard and Zhang Zhengyou calibration method, the external parameters are the position and posture relation of a structured light plane and the industrial camera, and the external parameters are calibrated by a sawtooth target method. And finally, the calibration result is the relationship between the pixel coordinate in the light bar image and the actual world coordinate.
(4) Image coordinate to world coordinate mapping
The industrial camera continuously shoots the laser light strip image of the welded object after the action along with the continuous action of the stepping motor, the laser can complete the scanning of the whole welding seam, the coordinates of the central point of the laser light strip projected on the welding seam at each moment are obtained, and all the coordinates of the central point can be converted into the coordinates of the actual world through the calibration result, namely the relationship between the pixel coordinates in the light strip image and the coordinates of the actual world, so that the point cloud data of the welding seam is obtained; and then establishing a world coordinate system through opengl, drawing the point cloud data into a three-dimensional model, and displaying the three-dimensional model on a display.
According to the three-dimensional coordinate data of the welding seam, the computer can obtain the characteristic information of the welding seam, such as real-time width, height and the like, the width and height numerical values are visually displayed on the display, and the welding quality of the welding seam is judged by comparing the characteristic information with the existing standard.
The invention has the following advantages:
1. and non-contact optical three-dimensional scanning is adopted, so that the reliability of the system is improved.
2. Compared with the manual detection technology, the detection efficiency is improved.
3. The measurement precision is high and can reach 0.1 mm.
4. The continuous scanning of the surface of the welding seam can be realized.
5. The weld joint image can be shot in real time by the industrial camera for processing, and real-time detection is facilitated.

Claims (10)

1.一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置,其特征在于:该三维检测装置包括线结构光传感器和计算机(5);所述线结构光传感器包括用于扫描被焊物件(3)的激光器(1)以及用于采集被焊物件激光光条图像的工业相机(2),工业相机(2)与竖直方向夹角范围为31°~43°,激光器(1)的线结构光平面与被焊物件(3)上的焊缝相交;工业相机(2)与计算机(5)相连;计算机(5)包括软件系统,该软件系统包括视频数据采集模块、点云数据处理模块、I/O与控制模块及系统标定模块;1. A three-dimensional detection device based on line structured light scanning high-frequency resistance welding seam morphology, is characterized in that: this three-dimensional detection device comprises a line structured light sensor and a computer (5); The laser (1) of the object to be welded (3) and the industrial camera (2) for collecting the image of the laser light bar of the object to be welded, the included angle between the industrial camera (2) and the vertical direction ranges from 31° to 43°, and the laser ( The linear structured light plane of 1) intersects with the welding seam on the object to be welded (3); the industrial camera (2) is connected with the computer (5); the computer (5) includes a software system, and the software system includes a video data acquisition module, a point Cloud data processing module, I/O and control module and system calibration module; 所述系统标定模块用于标定工业相机(2)内部参数以及外部参数;所述外部参数是指线结构光平面与工业相机(2)之间的位姿关系;The system calibration module is used to calibrate the internal parameters and external parameters of the industrial camera (2); the external parameters refer to the pose relationship between the linear structured light plane and the industrial camera (2); 所述视频数据采集模块用于将工业相机(2)采集的被焊物件激光光条图像传输至点云数据处理模块;所述被焊物件激光光条图像是指通过工业相机(2)采集的投射在被焊物件(3)表面、与被焊物件(3)上的焊缝相交并发生畸变的激光线图像;The video data acquisition module is used to transmit the laser light bar image of the object to be welded collected by the industrial camera (2) to the point cloud data processing module; the laser light bar image of the welded object refers to the image of the laser light bar of the welded object collected by the industrial camera (2). A laser line image projected on the surface of the object to be welded (3), intersecting with the weld on the object to be welded (3) and distorted; 所述点云数据处理模块用于根据被焊物件激光光条图像提取激光光条中心坐标,并将激光光条中心按照被焊物件与焊缝进行分割,以及通过标定得到的光条图像像素坐标与实际世界坐标之间的关系获取焊缝三维点云数据,并测量焊缝的宽度和高度;The point cloud data processing module is used to extract the center coordinates of the laser light bar according to the laser light bar image of the object to be welded, and divide the center of the laser light bar according to the object to be welded and the weld, and obtain the pixel coordinates of the light bar image through calibration. The relationship with the actual world coordinates to obtain the 3D point cloud data of the weld, and measure the width and height of the weld; 所述激光光条中心坐标的提取方法包括以下步骤:首先对被焊物件激光光条图像进行动态阈值分割,获取图像感兴趣区域;在感兴趣区域应用灰度阈值重心法求取结构光条纹初步中心;获得结构光条纹初步中心后,应用Sobel算子获取条纹像素点的梯度向量,接着选取每个像素点的5~11×2~5邻域作为该点的方向块并通过方向块的水平梯度和垂直梯度计算得到方向场,沿方向场方向求取激光光条亚像素精度中心;The method for extracting the center coordinates of the laser light stripe includes the following steps: firstly, performing dynamic threshold segmentation on the laser light stripe image of the object to be welded to obtain a region of interest in the image; applying the grayscale threshold centroid method in the region of interest to obtain a preliminary structure of the light stripe center; after obtaining the preliminary center of the structured light stripe, apply the Sobel operator to obtain the gradient vector of the stripe pixel point, and then select the 5-11×2-5 neighborhood of each pixel point as the direction block of the point and pass the level of the direction block. Gradient and vertical gradient are calculated to obtain the direction field, and the sub-pixel accuracy center of the laser light bar is obtained along the direction of the direction field; 由于被焊物件截面为圆形,被激光投射的截面部分为弧形,选取提取出的激光光条亚像素精度中心沿焊缝宽度方向向外的像素点进行曲线拟合,得到截面形状的曲线方程,在被焊物件光条图像中去除属于该曲线方程上的投射在被焊物件表面的亚像素中心点,保留的点即为投射在焊缝表面的亚像素中心点,因此实现图像中焊缝与被焊物件的分割;Since the cross-section of the object to be welded is circular and the cross-section projected by the laser is arc-shaped, select the pixel points from the sub-pixel precision center of the extracted laser stripe along the width direction of the weld to perform curve fitting to obtain the curve of the cross-sectional shape. Equation, in the light bar image of the object to be welded, the sub-pixel center point projected on the surface of the object to be welded belonging to the curve equation is removed, and the remaining point is the sub-pixel center point projected on the surface of the weld, thus realizing welding in the image. The separation of seam and welded object; 所述I/O与控制模块用于监控工业相机(2)的输入并通知视频数据采集模块开始或停止采集视频图像,以及用于根据点云数据处理模块获取的点云数据和焊缝测量结果输出信号并显示。The I/O and control module is used for monitoring the input of the industrial camera (2) and notifying the video data acquisition module to start or stop the acquisition of video images, and is used for point cloud data and weld measurement results obtained by the point cloud data processing module Output signal and display. 2.根据权利要求1所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置,其特征在于:所述点云数据处理模块包括子模块A、子模块B、子模块C及子模块D;子模块A为光条中心亚像素坐标提取模块,用于根据被焊物件激光光条图像对激光光条中心坐标进行亚像素精度提取;子模块B为焊缝与物体分割模块,用于将激光光条中心按照被焊物件与焊缝进行分割,保留位于焊缝处的激光光条中心坐标;子模块C为图像坐标与世界坐标映射模块,用于将分割出的位于焊缝处的激光光条中心坐标转换为世界坐标,得到焊缝表面点云数据;子模块D为参数获取与显示模块,用于根据焊缝表面点云数据实时生成焊缝三维模型并计算焊缝的宽度和高度信息。2. A three-dimensional detection device based on line structured light scanning high-frequency resistance welding seam morphology according to claim 1, characterized in that: the point cloud data processing module comprises a sub-module A, a sub-module B, and a sub-module C and sub-module D; sub-module A is a sub-pixel coordinate extraction module for the center of the light bar, which is used to extract the center coordinates of the laser light bar with sub-pixel accuracy according to the laser light bar image of the object to be welded; sub-module B is a welding seam and object segmentation module , which is used to divide the center of the laser light bar according to the object to be welded and the welding seam, and retain the coordinates of the center of the laser light bar at the welding seam; sub-module C is the image coordinate and world coordinate mapping module, which is used to divide the divided parts located in the welding seam. The center coordinates of the laser light bar at the seam are converted into world coordinates to obtain the point cloud data of the weld surface; sub-module D is a parameter acquisition and display module, which is used to generate the 3D model of the weld seam in real time and calculate the weld seam according to the point cloud data of the weld seam surface. width and height information. 3.根据权利要求1所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置,其特征在于:所述线结构光传感器中,激光器(1)选自波长范围为630nm~660nm的红光激光器。3. A three-dimensional detection device based on line structured light scanning high frequency resistance welding seam morphology according to claim 1, characterized in that: in the line structured light sensor, the laser (1) is selected from a wavelength range of 630nm~ 660nm red laser. 4.根据权利要求1所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置,其特征在于:所述三维检测装置还包括线位移传送系统以及位于该线位移传送系统上方的固定面板,激光器(1)以及工业相机(2)设置在固定面板上;线位移传送系统包括步进电机、步进电机控制器(4)及由步进电机驱动的用于承载被焊物件(3)的底座(6);步进电机与步进电机控制器(4)相连,步进电机控制器(4)与所述计算机(5)相连。4. A three-dimensional detection device based on line structured light scanning high-frequency resistance welding seam morphology according to claim 1, characterized in that: the three-dimensional detection device further comprises a linear displacement transmission system and is located above the linear displacement transmission system. The fixed panel, the laser (1) and the industrial camera (2) are arranged on the fixed panel; the linear displacement transmission system includes a stepping motor, a stepping motor controller (4) and a stepping motor driven by the stepping motor for carrying the object to be welded (3) the base (6); the stepper motor is connected with the stepper motor controller (4), and the stepper motor controller (4) is connected with the computer (5). 5.根据权利要求4所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测装置,其特征在于:所述I/O与控制模块在通知视频数据采集模块停止采集视频图像的同时,使线位移传送系统停止驱动底座(6)进行线性移动的动作。5. A three-dimensional detection device based on line structured light scanning high-frequency resistance welding seam morphology according to claim 4, characterized in that: the I/O and the control module are notifying the video data acquisition module to stop collecting video images. At the same time, the linear displacement transmission system is stopped to drive the base (6) to move linearly. 6.一种基于线结构光扫描高频电阻焊焊缝形貌三维检测方法,其特征在于:包括以下步骤:6. A three-dimensional detection method based on line structured light scanning high frequency resistance welding seam morphology, characterized in that: comprising the following steps: 1)采用激光器(1)产生的线结构光扫描被焊物件(3),同时由与竖直方向夹角范围为31°~43°的工业相机(2)采集得到被焊物件激光光条图像;激光器(1)的线结构光平面与被焊物件(3)上的焊缝相交;1) The object to be welded (3) is scanned by the line structured light generated by the laser (1), and the laser light bar image of the object to be welded is collected by an industrial camera (2) with an angle ranging from 31° to 43° with the vertical direction at the same time ; the line structured light plane of the laser (1) intersects the weld on the object to be welded (3); 2)通过对被焊物件激光光条图像进行处理,提取激光光条中心坐标,将激光光条中心按照被焊物件与焊缝进行分割,并通过标定得到的光条图像像素坐标与实际世界坐标之间的关系,得到焊缝三维点云数据,以及焊缝宽度及高度形貌特征;所述被焊物件激光光条图像是指通过工业相机(2)采集的投射在被焊物件(3)表面、与被焊物件(3)上的焊缝相交并发生畸变的激光线图像;2) By processing the laser light bar image of the object to be welded, the center coordinates of the laser light bar are extracted, the center of the laser light bar is divided according to the object to be welded and the seam, and the pixel coordinates of the light bar image obtained by calibration are the actual world coordinates. The relationship between the three-dimensional point cloud data of the weld and the topographic features of the width and height of the weld are obtained; the laser light bar image of the object to be welded refers to the image of the object to be welded and projected on the object to be welded (3) collected by the industrial camera (2). The surface, intersecting and distorted image of the laser line on the weld on the object to be welded (3); 所述激光光条中心坐标的提取方法包括以下步骤:首先对被焊物件激光光条图像进行动态阈值分割,获取图像感兴趣区域;在感兴趣区域应用灰度阈值重心法求取结构光条纹初步中心;获得结构光条纹初步中心后,应用Sobel算子获取条纹像素点的梯度向量,接着选取每个像素点的5~11×2~5邻域作为该点的方向快并通过方向块的水平梯度和垂直梯度计算得到方向场,沿方向场方向求取激光光条亚像素中心;The method for extracting the center coordinates of the laser light stripe includes the following steps: firstly, performing dynamic threshold segmentation on the laser light stripe image of the object to be welded to obtain a region of interest in the image; applying the grayscale threshold centroid method in the region of interest to obtain a preliminary structure of the light stripe center; after obtaining the preliminary center of the structured light stripe, apply the Sobel operator to obtain the gradient vector of the stripe pixel point, and then select the 5-11×2-5 neighborhood of each pixel point as the direction of the point and pass the level of the direction block. Gradient and vertical gradient are calculated to obtain the direction field, and the sub-pixel center of the laser light bar is obtained along the direction of the direction field; 由于被焊物件截面为圆形,被激光投射的截面部分为弧形,选取提取出的激光光条亚像素精度中心沿焊缝宽度方向向外的像素点进行曲线拟合,得到截面形状的曲线方程,在被焊物件光条图像中去除属于该曲线方程上的投射在被焊物件表面的亚像素中心点,保留的点即为投射在焊缝表面的亚像素中心点,因此实现图像中焊缝与被焊物件的分割。Since the cross-section of the object to be welded is circular and the cross-section projected by the laser is arc-shaped, select the pixel points from the sub-pixel precision center of the extracted laser stripe along the width direction of the weld to perform curve fitting to obtain the curve of the cross-sectional shape. Equation, in the light bar image of the object to be welded, the sub-pixel center point projected on the surface of the object to be welded belonging to the curve equation is removed, and the remaining point is the sub-pixel center point projected on the surface of the weld, thus realizing welding in the image. The division of seam and welded object. 7.根据权利要求6所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测方法,其特征在于:所述步骤2)具体包括以下步骤:将实时采集的被焊物件激光光条图像输入计算机(5),由计算机(5)根据该被焊物件激光光条图像以及光条图像像素坐标与实际世界坐标之间的关系,将位于焊缝表面的激光光条中心坐标转换为世界坐标,得到焊缝表面点云数据,将焊缝表面点云数据绘制成三维模型,根据焊缝表面激光光条上各中心点的三维坐标值测量出焊缝宽度以及高度。7. A kind of three-dimensional detection method based on line structured light scanning high-frequency resistance welding seam morphology according to claim 6, characterized in that: the step 2) specifically comprises the following steps: The bar image is input to the computer (5), and the computer (5) converts the laser bar center coordinates on the surface of the weld into The world coordinates are obtained, the point cloud data of the weld surface is obtained, the point cloud data of the weld surface is drawn into a three-dimensional model, and the width and height of the weld are measured according to the three-dimensional coordinates of each center point on the laser light bar on the weld surface. 8.根据权利要求7所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测方法,其特征在于:所述焊缝表面的激光光条中心坐标的提取方法包括以下步骤:首先对被焊物件激光光条图像进行动态阈值分割,获取图像感兴趣区域;在感兴趣区域应用灰度阈值重心法求取结构光条纹初步中心;获得结构光条纹初步中心后,应用Sobel算子获取条纹像素点的梯度向量,接着选取每个像素点的5~11×2~5邻域作为该点的方向快,求取方向块的水平梯度和垂直梯度,通过水平梯度和垂直梯度计算得到方向块的方向角即该方向块的方向场,并沿方向场方向求取激光光条的亚像素精度中心;最后,在被焊物件激光光条图像上去除投射在被焊物件表面的亚像素中心点,保留投射在焊缝表面的亚像素中心点。8 . The three-dimensional detection method for high-frequency resistance welding seam morphology based on line structured light scanning according to claim 7 , wherein the method for extracting the center coordinates of the laser light bar on the surface of the weld comprises the following steps: firstly: 1. Perform dynamic threshold segmentation on the laser light stripe image of the welded object to obtain the region of interest in the image; apply the gray threshold centroid method to obtain the preliminary center of the structured light stripe in the region of interest; after obtaining the preliminary center of the structured light stripe, use the Sobel operator to obtain The gradient vector of the stripe pixel point, then select the 5~11×2~5 neighborhood of each pixel point as the direction of the point, obtain the horizontal gradient and vertical gradient of the direction block, and calculate the direction through the horizontal gradient and vertical gradient. The direction angle of the block is the direction field of the direction block, and the sub-pixel precision center of the laser light bar is obtained along the direction of the direction field; finally, the sub-pixel center projected on the surface of the welded object is removed from the laser light bar image of the welded object point, keeping the subpixel center point projected on the surface of the weld. 9.根据权利要求7所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测方法,其特征在于:所述光条图像像素坐标与实际世界坐标之间的关系是通过对由激光器(1)和工业相机(2)构成的线结构光传感器进行标定而得到。9. A three-dimensional detection method for high-frequency resistance welding seam morphology based on line structured light scanning according to claim 7, characterized in that: the relationship between the pixel coordinates of the light bar image and the actual world coordinates is determined by It is obtained by calibrating a line structured light sensor composed of a laser (1) and an industrial camera (2). 10.根据权利要求6所述一种基于线结构光扫描高频电阻焊焊缝形貌三维检测方法,其特征在于:所述步骤1)具体包括以下步骤:随着被焊物件(3)移动,利用工业相机(2)连续采集被焊物件激光光条图像,并依次输入计算机(5)进行处理,直至激光器(1)完成对整个被焊物件(3)上焊缝的扫描。10. A three-dimensional detection method for high frequency resistance welding seam morphology based on line structured light scanning according to claim 6, characterized in that: the step 1) specifically comprises the following steps: moving with the welded object (3) , using the industrial camera (2) to continuously capture the laser light bar image of the object to be welded, and sequentially input it to the computer (5) for processing, until the laser (1) completes the scanning of the welding seam on the entire object to be welded (3).
CN201711079863.2A 2017-11-06 2017-11-06 Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning Active CN107764205B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711079863.2A CN107764205B (en) 2017-11-06 2017-11-06 Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711079863.2A CN107764205B (en) 2017-11-06 2017-11-06 Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning

Publications (2)

Publication Number Publication Date
CN107764205A CN107764205A (en) 2018-03-06
CN107764205B true CN107764205B (en) 2020-05-12

Family

ID=61273862

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711079863.2A Active CN107764205B (en) 2017-11-06 2017-11-06 Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning

Country Status (1)

Country Link
CN (1) CN107764205B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
NL2025856B1 (en) * 2020-06-18 2022-02-17 Singa Ip B V Device and method for determining the three-dimensional geometry of an individual object

Families Citing this family (45)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109115128B (en) * 2018-10-29 2019-09-27 清华大学 A three-dimensional shape detection method of weld bead based on surface structured light
CN111156900B (en) * 2018-11-08 2021-07-13 中国科学院沈阳自动化研究所 A method for measuring the depth of the primer assembly of bullets with structured light
CN109443214B (en) * 2018-12-19 2021-03-16 广东工业大学 A calibration method and device for structured light three-dimensional vision, and a measuring method and device
CN109855574A (en) * 2019-02-01 2019-06-07 广东工业大学 A kind of weld seam side surface roughness detecting method, device, equipment and storage medium
CN110132975B (en) * 2019-03-28 2022-04-12 中核建中核燃料元件有限公司 Method and device for detecting surface of cladding of nuclear fuel rod
CN110149463A (en) * 2019-04-22 2019-08-20 上海大学 It is a kind of to carry the hand-held line-structured light camera for turning station measurement target
CN110702002B (en) * 2019-07-04 2020-12-11 天津大学 A method for multi-layer synchronous measurement of curved light-transmitting parts
CN110608684B (en) * 2019-08-12 2022-02-11 广东工业大学 A method and system for detecting the deposition effect of single-layer multi-pass welds
CN110455198B (en) * 2019-08-22 2020-12-25 吉林大学 Rectangular spline shaft key width and diameter measuring method based on line structure light vision
CN110977218A (en) * 2019-11-21 2020-04-10 上海船舶工艺研究所(中国船舶工业集团公司第十一研究所) 3D laser scanning equipment and automatic point cloud extraction and conversion method using same
CN111232347B (en) * 2019-11-25 2021-09-28 太原科技大学 Tube and bar bundling method based on binocular vision
CN111232346B (en) * 2019-11-25 2021-09-28 太原科技大学 Pipe and bar bundling system based on binocular vision
CN111174706A (en) * 2019-12-30 2020-05-19 广东博智林机器人有限公司 Floor installation detection method, electronic device and storage medium
RU2727049C1 (en) * 2020-01-10 2020-07-17 федеральное государственное бюджетное образовательное учреждение высшего образования "Алтайский государственный технический университет им. И.И. Ползунова" (АлтГТУ) Complex for measuring inspection of weld butt joints
CN111189393B (en) * 2020-01-21 2021-10-01 北京卫星制造厂有限公司 High-precision global vision measurement method for three-dimensional thin-wall structural weld joint
CN111408546B (en) * 2020-03-11 2022-09-16 武汉工程大学 An ore detection method and system based on laser scanning imaging
CN111489436A (en) * 2020-04-03 2020-08-04 北京博清科技有限公司 Three-dimensional reconstruction method, device and equipment for weld joint and storage medium
CN111462110B (en) * 2020-04-20 2021-04-13 广东利元亨智能装备股份有限公司 Weld quality inspection method, device, system and electronic equipment
CN111612848B (en) * 2020-04-30 2023-10-10 湖北煌朝智能自动化装备有限公司 Automatic generation method and system for arc welding track of robot
CN111855664B (en) * 2020-06-12 2023-04-07 山西省交通科技研发有限公司 Adjustable three-dimensional tunnel defect detection system
CN111551565A (en) * 2020-06-19 2020-08-18 湖南恒岳重钢钢结构工程有限公司 Wind power tower cylinder weld defect detection device and method based on machine vision
CN112129258B (en) * 2020-08-24 2022-07-26 中车唐山机车车辆有限公司 Scratch depth measuring method
CN112037189A (en) * 2020-08-27 2020-12-04 长安大学 Device and method for detecting geometric parameters of steel bar welding seam
CN112050753B (en) * 2020-09-10 2021-12-21 广东省特种设备检测研究院珠海检测院 Method and device for measuring edge angle of longitudinal weld of pressure vessel
CN112561854B (en) * 2020-11-11 2023-07-04 深圳大学 A Weld Seam Detection Method Based on Line Structured Light Point Cloud
CN112484664A (en) * 2020-11-26 2021-03-12 江苏国和智能科技有限公司 Defect identification device and method based on laser three-dimensional scanning
CN113313750A (en) * 2020-12-01 2021-08-27 中冶长天国际工程有限责任公司 System and method for detecting material layer thickness of sintering machine
CN112729151B (en) * 2020-12-04 2022-12-13 深圳大学 A 3D point cloud measurement method for welded seam structure
CN112781507A (en) * 2020-12-24 2021-05-11 山西大数据产业发展有限公司 Intelligent analysis system and method for laser thickness measurement of cold-rolled steel plate
CN113048882A (en) * 2021-03-09 2021-06-29 徐州徐工挖掘机械有限公司 Intelligent detection system for weld surface quality and implementation method
CN113028912B (en) * 2021-04-21 2022-09-20 湘潭大学 Bullet primer priming charge filling amount detection method based on 3D vision
CN113702384A (en) * 2021-07-19 2021-11-26 南京工程学院 Surface defect detection device, detection method and calibration method for rotary component
CN114252449B (en) * 2021-09-27 2023-10-24 上海电机学院 Aluminum alloy weld joint surface quality detection system and method based on line structured light
CN113989379B (en) * 2021-10-02 2022-06-24 南京理工大学 Hub welding seam three-dimensional characteristic measuring device and method based on linear laser rotation scanning
CN114061699B (en) * 2021-10-29 2022-07-12 中国科学院沈阳自动化研究所 Metal liquid level measurement system of continuous ingot casting line of non ferrous metal
CN114136219B (en) * 2021-11-18 2024-02-13 大连海事大学 A real-time detection device and method for the thickness of shotcrete of a tunnel wet spray vehicle based on line structured light
CN114877806B (en) * 2022-06-06 2024-06-25 泉州华中科技大学智能制造研究院 Dual-camera point cloud measurement method and device with color real-time mapping
CN114850741B (en) * 2022-06-10 2023-06-27 东南大学 Weld joint identification device and method suitable for flat butt weld joint
CN115236085A (en) * 2022-07-19 2022-10-25 中冶赛迪信息技术(重庆)有限公司 A Method for Identifying Surface Quality Using Projected Curves
CN115290524B (en) * 2022-08-03 2024-02-02 中南大学 A three-dimensional space particle concentration measurement device and method
CN115112049A (en) * 2022-08-31 2022-09-27 山东大学 A method, system and device for precise rotation measurement of three-dimensional topography by linear structured light
CN115574725B (en) * 2022-12-08 2023-04-25 江苏金恒信息科技股份有限公司 Steel plate size measurement method and system based on line structured light
CN117115140B (en) * 2023-09-25 2024-04-05 重庆大学溧阳智慧城市研究院 3D printing concrete column surface crack detection method based on point cloud segmentation registration
CN118190931A (en) * 2024-02-29 2024-06-14 中国机械总院集团哈尔滨焊接研究所有限公司 System, method and device for analyzing impact fracture of welded joint based on lattice laser scanning quantification
CN119268598B (en) * 2024-12-11 2025-03-21 宁波润华全芯微电子设备有限公司 A method and device for detecting wafer placement status in a wafer box

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004053427A (en) * 2002-07-22 2004-02-19 Shikoku Kakoki Co Ltd Quality evaluation method of welding bead and profile measuring method for it
CN105160641A (en) * 2015-08-04 2015-12-16 成都多贝科技有限责任公司 Image processing based X ray welding line zone extracting method

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101927395B (en) * 2010-07-26 2013-01-16 清华大学 Weld joint tracking detection equipment and method
CN104849284A (en) * 2015-06-03 2015-08-19 唐山英莱科技有限公司 Adjustable convergence light path tiny butt-joint weld-joint detection system with structured light
CN204730814U (en) * 2015-06-30 2015-10-28 长安大学 A kind of parts passer based on line laser three-dimensional measurement
CN105157603B (en) * 2015-07-29 2017-12-01 华南理工大学 A kind of line laser sensor
CN105571502B (en) * 2015-12-29 2019-08-09 上海交通大学 Measurement Method of Weld Gap in Friction Stir Welding
CN105716539B (en) * 2016-01-26 2017-11-07 大连理工大学 A kind of three-dimentioned shape measurement method of quick high accuracy
CN107131844A (en) * 2017-04-26 2017-09-05 西南交通大学 A kind of electric arc silk filling increasing material manufacturing surface quality automatic testing method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004053427A (en) * 2002-07-22 2004-02-19 Shikoku Kakoki Co Ltd Quality evaluation method of welding bead and profile measuring method for it
CN105160641A (en) * 2015-08-04 2015-12-16 成都多贝科技有限责任公司 Image processing based X ray welding line zone extracting method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
NL2025856B1 (en) * 2020-06-18 2022-02-17 Singa Ip B V Device and method for determining the three-dimensional geometry of an individual object

Also Published As

Publication number Publication date
CN107764205A (en) 2018-03-06

Similar Documents

Publication Publication Date Title
CN107764205B (en) Three-dimensional detection device and detection method of weld seam morphology of high-frequency resistance welding based on line structured light scanning
US9279662B2 (en) Laser scanner
JP7373037B2 (en) Graphic overlay for measuring feature dimensions using video inspection equipment
CN105571502B (en) Measurement Method of Weld Gap in Friction Stir Welding
CN103900494B (en) For the homologous points fast matching method of binocular vision 3 D measurement
US20160196643A1 (en) Method and device for measuring features on or near an object
US11170516B2 (en) Method and device for measuring features on or near an object
CN109146866B (en) Method and device for robot to process welding seam
CN108335286A (en) A kind of online appearance of weld visible detection method based on double structure light
WO2015065660A1 (en) Mapping damaged regions on objects
EP3353490B1 (en) Method and device for measuring features on or near an object
CN107560547B (en) Scanning system and scanning method
CN116878419B (en) Rail vehicle boundary detection method, system and electronic equipment based on three-dimensional point cloud data
CN102589516A (en) Dynamic distance measuring system based on binocular line scan cameras
CN109297412A (en) Image acquisition device for spline end face of spline shaft and spline detection method
KR101090082B1 (en) Stair Dimension Measurement System and Method Using Single Camera and Laser
CN107504917B (en) Three-dimensional size measuring method and device
TWI574003B (en) Weld bead three-dimensional image detecting device and detecting method thereof
CN111192246B (en) Automatic detection method for welding spots
EP4048979B1 (en) Method for inspection of a geometry
Wang et al. Detection of HF-ERW process by 3D bead shape measurement with line-structured laser vision
TWI742391B (en) Three-dimensional image surface defect detection system
CN104266594B (en) Thickness compensation method for block frozen shrimp net content detection based on different visual technologies
TWI457535B (en) Measurement method and device of irregular object size
CN105783782A (en) Surface curvature abrupt change optical contour measurement method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20210210

Address after: Room 11705, unit 1, building 2, Northwest Petroleum Pipeline community, 149 Weiyang Road, Xi'an Economic and Technological Development Zone, Shaanxi 710000

Patentee after: Xi'an Zhongce Control Technology Co.,Ltd.

Address before: 710064 No. 33, South Second Ring Road, Shaanxi, Xi'an

Patentee before: CHANG'AN University

TR01 Transfer of patent right