CN103542819A - Detection and quality judgment method for strip steel weld surface appearance - Google Patents
Detection and quality judgment method for strip steel weld surface appearance Download PDFInfo
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Abstract
Description
技术领域 technical field
本发明涉及带钢表面检测技术,特别涉及一种带钢焊缝表面形貌的检测和质量判定方法。The invention relates to a strip steel surface detection technology, in particular to a detection and quality judgment method for the surface appearance of a strip steel weld seam.
背景技术 Background technique
目前带钢焊缝的质量通常由现场的操作工肉眼判断,这一判别方法明显存在操作人员的经验和判别标准上的缺陷,存在效率低和判别不准的问题。At present, the quality of strip welds is usually judged by on-site operators with naked eyes. This method of discrimination obviously has defects in the experience of operators and judgment standards, and there are problems of low efficiency and inaccurate judgment.
Miebach公司推出的QCDS系统可实现焊缝形貌的自动检测,该系统采用在线的CCD视频观测带钢表面的焊缝形貌,可及时给出焊缝表面的形貌图,并给出焊缝凹陷和错边的曲线供操作人员判断焊缝的质量,实现焊缝表面形貌的实时在线检测,但该系统无法判断严重影响焊缝抗断裂能力的咬边缺陷,判别标准上也存在不足。The QCDS system launched by Miebach can realize the automatic detection of the weld seam appearance. The system uses online CCD video to observe the weld seam appearance on the surface of the strip steel, and can provide the topography map of the weld seam surface in time, and the weld seam The concave and misaligned curves allow the operator to judge the quality of the weld and realize the real-time online detection of the surface morphology of the weld. However, the system cannot judge the undercut defect that seriously affects the fracture resistance of the weld, and there are also deficiencies in the judgment standard.
中国专利申请号200810229989公开了“一种基于线结构光的焊缝表面质量视觉传感器”,利用该传感器可得到焊缝表面的形貌,但该专利并未提及线型激光器的具体参数,特别是扫描的频率,并且该专利提及的技术并不具备对测试结果的分析功能。Chinese patent application number 200810229989 discloses "a visual sensor for weld surface quality based on line structured light", which can be used to obtain the topography of the weld surface, but the patent does not mention the specific parameters of the line laser, especially is the scanning frequency, and the technology mentioned in this patent does not have the function of analyzing the test results.
发明内容 Contents of the invention
本发明的目的在于提供一种带钢焊缝表面形貌的检测和质量判定方法,快速检测到焊缝表面的形貌,并进行快速的评价,确保酸洗和冷轧过程的连续和快速运行,防止带钢断带事故的发生。The object of the present invention is to provide a method for detecting and quality judging the surface appearance of the welded seam of strip steel, which can quickly detect the appearance of the welded seam surface, and perform rapid evaluation to ensure the continuous and rapid operation of the pickling and cold rolling process , to prevent the occurrence of strip broken belt accidents.
为达到上述目的,本发明的技术方案是:For achieving the above object, technical scheme of the present invention is:
本发明采用线型激光器对焊缝表面的进行扫描,根据扫描所得到的数据绘制出焊缝的表面形貌图,同时根据所得到的扫描数据,通过计算得到焊缝堆高、凹陷、咬边、错边等数值,根据该数值对焊缝的表面形貌质量进行判别,从而实现对焊缝表面形貌质量的连续评判。The invention uses a linear laser to scan the surface of the weld seam, draws the surface topography map of the weld seam according to the data obtained by scanning, and at the same time obtains the height, depression, and undercut of the weld seam through calculation according to the obtained scanning data. , misalignment and other values, according to which the surface topography quality of the weld is judged, so as to realize the continuous evaluation of the surface topography quality of the weld.
在酸轧机组中,为保证轧机的连续运行,前行带钢和后行带钢需要采用焊接的方法将其连接在一起,焊缝的焊接质量是确保焊缝能够顺利通过轧机的先决条件,焊接中的焊接缺陷将直接导致焊缝在拉矫和轧机中断裂,形成断带事故。带钢焊缝在进入到轧机前将承受多次的反复弯曲,在反复弯曲的过程中,焊缝中的应力集中部位会产生疲劳裂纹,这些裂纹的产生将直接降低焊缝的强度,影响焊缝表面应力集中严重程度的焊缝形貌缺陷有:焊缝堆高、焊缝凹陷、焊缝咬边和焊缝错边。In the pickling mill, in order to ensure the continuous operation of the rolling mill, the forward strip and the rear strip need to be connected together by welding. The welding quality of the weld is a prerequisite to ensure that the weld can pass through the rolling mill smoothly. Welding defects in welding will directly lead to the fracture of the weld seam in the tension leveling and rolling mill, resulting in a broken belt accident. The welded seam of the strip steel will be subjected to repeated bending for many times before entering the rolling mill. During the repeated bending process, fatigue cracks will be generated in the stress concentration part of the welded seam. The generation of these cracks will directly reduce the strength of the welded seam and affect the welding seam. The defects of weld seam morphology according to the severity of stress concentration on the seam surface include: weld pile height, weld depression, weld undercut and weld misalignment.
具体地,本发明的一种带钢焊缝表面形貌的检测和质量判定方法,采用线型激光器扫描实时检测焊缝表面的形貌数据,包括焊缝堆高、凹陷、咬边、搭接,计算上述焊缝特征值、统计特征值最大部位和截面特征,建立焊缝形貌评价标准,再实时检测焊缝表面的形貌,得到焊缝表面形貌的特征值,与焊缝形貌评价标准比对,从而实现焊缝表面质量的判定;其中:Specifically, a method for detecting and quality judging the surface topography of a strip steel weld according to the present invention uses a line laser to scan and detect the topography data of the weld surface in real time, including weld pile height, depression, undercut, lap joint, etc. , calculate the above-mentioned weld seam eigenvalue, statistical eigenvalue maximum position and cross-section characteristics, establish the weld seam appearance evaluation standard, and then detect the weld seam surface appearance in real time, obtain the weld seam surface appearance eigenvalue, and weld seam appearance Comparison of evaluation standards, so as to realize the judgment of weld surface quality; among them:
a)堆高a) Stack height
焊缝堆高表示焊缝高于母材的数值,堆高当量面积的计算公式为:The weld heap height indicates the value that the weld is higher than the base metal, and the calculation formula for the equivalent area of the heap is:
式中:h1(i)是第i次扫描所得数据的堆高值,mm;H为激光器扫描扫描的频率,Hz,u为焊接速度,mm/s,TT为整条焊缝的扫描次数;In the formula: h 1 (i) is the pile height value of the i-th scan data, mm; H is the scanning frequency of the laser, Hz, u is the welding speed, mm/s, TT is the number of scans of the entire weld ;
焊缝的堆高会使焊缝处产生应力集中,堆高对焊缝强度的影响用堆高系数表示,堆高系数的计算公式为:The pile height of the weld will cause stress concentration at the weld, and the influence of the pile height on the strength of the weld is expressed by the pile height coefficient. The calculation formula of the pile height coefficient is:
式中:h1(i)是第i次扫描所得数据的堆高值,t为带钢的厚度,mm;In the formula: h 1 (i) is the stack height value of the i-th scan data, t is the strip thickness, mm;
b)搭接b) Overlap
搭接是指焊缝二边带钢的错边量,搭接当量面积的计算公式为:Lap joint refers to the amount of misalignment of the strip steel on both sides of the weld, and the calculation formula for the equivalent area of the lap joint is:
式中:h2(i)是焊缝的第i次扫描所得数据的搭接值,mm;H为扫描的频率,Hz;u为焊接速度,mm/s;In the formula: h 2 (i) is the overlap value of the data obtained from the i-th scan of the weld, mm; H is the scanning frequency, Hz; u is the welding speed, mm/s;
焊缝的搭接会使焊缝处产生应力集中,搭接对焊缝强度的影响用搭接系数表示,搭接系数的计算公式为:The overlap of the weld will cause stress concentration at the weld, and the influence of the overlap on the strength of the weld is expressed by the overlap coefficient. The calculation formula of the overlap coefficient is:
式中:h2(i)是第i根焊缝截面线中心线处的搭接值,mm;t为带钢的厚度,mm;In the formula: h 2 (i) is the overlap value at the center line of the section line of the i-th weld, mm; t is the thickness of the strip steel, mm;
c)凹陷c) sunken
焊缝凹陷是指焊缝区域的高度低于带钢母材的高度值,考虑到焊缝的搭接将加深凹陷部位的应力集中严重程度,因此在计算凹陷当量面积时将搭接系数考虑在内,凹陷面积的计算公式为:Weld sag means that the height of the weld area is lower than the height of the strip base metal. Considering that the overlap of the weld will deepen the stress concentration of the sag, the overlap coefficient is taken into account when calculating the equivalent area of the sag. Inside, the formula for calculating the area of the depression is:
h3(i)是第i次扫描所得数据的凹陷值,mm;H为扫描的频率,Hz;u为焊接速度,mm/s;h 3 (i) is the sag value of the i-th scanning data, mm; H is the scanning frequency, Hz; u is the welding speed, mm/s;
d)咬边d) undercut
咬边是指焊缝熔合线左右1mm范围内的最低点作为咬边值,同时考虑到焊缝咬边位置的焊缝堆高和搭接将加重咬边部位应力集中的严重程度,因此在计算咬边面积时将堆高和搭接系数考虑在内,总咬边量的当量面积计算公式为:The undercut refers to the lowest point within 1mm of the weld fusion line as the undercut value. At the same time, considering the weld pile height and overlap at the undercut position of the weld will aggravate the severity of the stress concentration at the undercut position, so in the calculation When considering the undercut area, the pile height and the lap coefficient are taken into consideration, and the formula for calculating the equivalent area of the total undercut is:
焊缝形貌评价标准:Weld appearance evaluation criteria:
进一步,线型激光器对焊缝形貌的扫描,扫描宽度范围在3~10mm,高度检测范围在50~150mm,检测精度在0.001~0.005mm,检测到的数据实时发送到上位工控机中,扫描频率不低于30Hz。Further, the linear laser scans the weld seam appearance, the scanning width ranges from 3 to 10 mm, the height detection range is 50 to 150 mm, and the detection accuracy is 0.001 to 0.005 mm. The detected data is sent to the upper industrial computer in real time, and the scanning The frequency is not lower than 30Hz.
又,本发明采用包括线型激光器、触发开关、上位工控机,下位PC机,线型激光器、触发开关、上位工控机固定在焊机上,在检测过程中随焊机移动;上位工控机负责信号的采集和处理,将线型激光器所采集到的数据进行过滤,收集焊缝及焊缝二边3mm范围内的数据,将该数据通过以太网发送到下位PC机,由下位PC机对焊缝检测数据进行分析;触发开关用于控制线型激光器的启动和停止,当触发开关检测到带钢的边缘时,线型激光器开始工作并向上位工控机连续发送检测数据,焊机结束后,触发开关检测到焊机离开带钢后,触发开关通知上位工控机关闭线型激光器,激光器停止工作,触发开关所发出的信号为脉冲信号。Again, the present invention adopts and comprises linear laser device, trigger switch, upper position industrial computer, lower position PC, line type laser, trigger switch, upper position industrial computer are fixed on the welding machine, moves with welding machine during detection process; Upper position industrial control computer is responsible for Signal collection and processing, filtering the data collected by the linear laser, collecting the data within 3mm of the weld and the two sides of the weld, and sending the data to the lower PC through Ethernet, and the lower PC is welded The seam detection data is analyzed; the trigger switch is used to control the start and stop of the linear laser. When the trigger switch detects the edge of the strip, the linear laser starts to work and continuously sends detection data to the upper industrial computer. After the welding machine is finished, After the trigger switch detects that the welding machine leaves the strip, the trigger switch notifies the upper industrial computer to turn off the linear laser, the laser stops working, and the signal sent by the trigger switch is a pulse signal.
下位PC机承担对焊缝检测数据的分析处理工作。The lower PC is responsible for the analysis and processing of the weld detection data.
本发明的有益效果Beneficial effects of the present invention
本发明方法可有效检测出焊缝表面形貌缺陷,评价系统中强大的分析功能可根据检测结果及时评价焊缝的质量,对于存在超标缺陷的焊缝给出实时的提示,该系统对防止带钢焊缝的断带具有重要的作用。The method of the present invention can effectively detect the defects of the surface appearance of the weld, and the powerful analysis function in the evaluation system can evaluate the quality of the weld in time according to the detection results, and give real-time prompts for the welds with excessive defects, and the system can prevent belt defects Broken bands of steel welds play an important role.
附图说明 Description of drawings
图1为本发明焊缝形貌缺陷-堆高的示意图。Fig. 1 is a schematic diagram of weld seam morphology defect-pile height in the present invention.
图2为本发明焊缝形貌缺陷-凹陷的示意图。Fig. 2 is a schematic diagram of the weld seam morphology defect-depression according to the present invention.
图3为本发明焊缝形貌缺陷-咬边的示意图。Fig. 3 is a schematic diagram of the weld seam morphology defect-undercut according to the present invention.
图4为本发明焊缝形貌缺陷-搭接的示意图。Fig. 4 is a schematic diagram of the weld seam morphology defect-overlap in the present invention.
图5为本发明系统实施例的示意图。Fig. 5 is a schematic diagram of an embodiment of the system of the present invention.
具体实施方式 Detailed ways
下面结合实施例对本发明做进一步说明。The present invention will be further described below in conjunction with embodiment.
参见图1~图5,本发明采用线型激光器对焊缝表面的进行扫描,根据扫描焊缝的表面形貌所得到的数据,通过计算得到焊缝堆高、凹陷、咬边、错边等数值,根据该数值对焊缝的表面形貌质量进行判别,从而实现对焊缝表面形貌质量的连续评判。Referring to Figures 1 to 5, the present invention uses a linear laser to scan the surface of the weld seam, and calculates the weld pile height, depression, undercut, misalignment, etc. according to the data obtained by scanning the surface topography of the weld seam. According to the numerical value, the quality of the surface topography of the weld is judged, so as to realize the continuous evaluation of the quality of the surface topography of the weld.
参见图5,本发明带钢焊缝表面形貌的检测和质量判定方法,采用包括线型激光器1、触发开关2、上位工控机3,下位PC机4,线型激光器、触发开关、工控机固定在焊机上,在检测过程中随焊机移动;上位工控机负责信号的采集和处理,将线型激光器所采集到的数据进行过滤,收集焊缝及焊缝二边3mm范围内的数据,将该数据通过以太网发送到下位PC机,由下位PC机对焊缝检测数据进行分析;触发开关用于控制线型激光器的启动和停止,当触发开关检测到带钢5的边缘时,线型激光器开始工作并向上位工控机连续发送检测数据,焊机结束后,触发开关检测到焊机离开带钢后,触发开关通知上位工控机关闭线型激光器,激光器停止工作,触发开关所发出的信号为脉冲信号。Referring to Fig. 5, the detection and quality judgment method of the strip weld surface topography of the present invention, adopt and comprise
实施例1Example 1
冷轧作业线汽车板的轧制过程。Rolling process of automotive sheet in cold rolling line.
1)该焊缝检测系统由激光器、触发开关、上位工控机和下位PC机组成,激光器、触发开关、上位工控机固定在焊机上,在检测过程中随焊机移动,下位PC机则放置在操作室,下位机中安装有焊缝评估系统。1) The weld detection system consists of a laser, a trigger switch, an upper industrial computer and a lower PC. The laser, trigger switch, and upper industrial computer are fixed on the welding machine and move with the welding machine during the detection process. The lower PC is placed In the operating room, a weld evaluation system is installed in the lower computer.
2)线型激光器采用美国Bytewise公司的CC3000-30完成对焊缝形貌的扫描,扫描宽度范围10mm,高度检测范围在30mm,检测精度在0.015mm,检测到的数据实时发送到上位工控机中,检测频率为30HZ。上位工控机负责信号的采集和处理,将激光器所采集到的数据进行过滤,采集焊缝及焊缝两边3mm(共10mm)范围内的数据,将该数据通过以太网发送到下位PC,有下位PC对焊缝检测数据进行分析。2) The linear laser adopts CC3000-30 from American Bytewise Company to complete the scanning of the weld seam shape. The scanning width range is 10mm, the height detection range is 30mm, and the detection accuracy is 0.015mm. The detected data are sent to the upper industrial computer in real time , The detection frequency is 30HZ. The upper industrial computer is responsible for the collection and processing of signals, filters the data collected by the laser, collects the data within the range of 3mm (10mm in total) on both sides of the weld and the weld, and sends the data to the lower PC through Ethernet. The PC analyzes the weld inspection data.
3)触发开关采用NPN常关型号,型号ES12-D15C1,当触发开关检测到带钢的边缘时,激光器开始工作并向上位工控机连续发送检测数据,焊机结束后,触发开关检测到焊机离开带钢后,触发开关通知上位工控机关闭激光器,激光器停止工作。3) The trigger switch adopts NPN normally closed model, model ES12-D15C1. When the trigger switch detects the edge of the strip steel, the laser starts to work and continuously sends detection data to the upper industrial computer. After the welding machine is finished, the trigger switch detects the welding machine After leaving the strip, the trigger switch notifies the upper industrial computer to turn off the laser, and the laser stops working.
4)下位PC机接收到检测装置发送的数据后,可显示焊缝形貌显示、计算焊缝特征值(堆高、凹陷、咬边、搭接)的计算、统计特征值最大部位和截面特征、给出焊缝质量评价结果功能,所有检测到的数据保持在系统中。4) After the lower PC receives the data sent by the detection device, it can display the appearance of the weld seam, calculate the calculation of the characteristic value of the weld seam (pile height, depression, undercut, lap joint), and count the largest part of the characteristic value and the cross-sectional characteristics , Provide the function of weld quality evaluation results, and all detected data are kept in the system.
5)下位PC机检测到焊缝信号后,计算焊缝的特征值,总体评判标准见表1。5) After the lower PC detects the weld signal, it calculates the characteristic value of the weld, and the overall evaluation criteria are shown in Table 1.
表1用于汽车板的评价指标Table 1 Evaluation indicators for automotive panels
6)采用表1的控制指标,对汽车板焊缝进行检测和评价,对于焊缝质量较好的焊缝,判断结果合格”。对于焊缝表面存在严重质量问题的焊缝检测判断结果不合格;从检测结果看,该焊缝在中部板形不良,边部存在有明显的凹陷,判断结果为不合格,但该评价结果未引起焊工的重视,放行后在轧机的第2机架发生断带,断带正好发生在存在明显凹陷的边部。6) Use the control indicators in Table 1 to test and evaluate the welds of automobile plates. For welds with good weld quality, the judgment results are qualified. For welds with serious quality problems on the surface of the welds, the inspection and judgment results are unqualified ; From the test results, the weld was in poor shape in the middle, and there were obvious depressions in the edge, and the judgment result was unqualified, but the evaluation result did not attract the attention of the welders. band, and the broken band occurs exactly at the edge where there is an obvious depression.
实施例2Example 2
系统的组成和实施例1相同,对于低牌号硅钢,由于材料的脆性很大,需要对评价指标进行调整,调整后的指标见表2。采用该指标进行低牌号硅钢焊缝的评价,可将断带率控制在1‰以下。The composition of the system is the same as that of Example 1. For low-grade silicon steel, due to the high brittleness of the material, the evaluation index needs to be adjusted. The adjusted index is shown in Table 2. Using this index to evaluate low-grade silicon steel welds can control the broken belt rate below 1‰.
表2用于低牌号硅钢的评价指标Table 2 Evaluation indicators for low-grade silicon steel
实施例3Example 3
系统的组成和实施例1相同,对于中牌号硅钢,由于材料中的硅含量较高高,材料的脆性较大,需要严格限定缺陷门槛值,调整后的指标见表3。采用该指标进行中牌号硅钢焊缝的评价,可将断带率控制在1‰以下。The composition of the system is the same as that of Example 1. For medium-grade silicon steel, due to the high silicon content in the material and the high brittleness of the material, it is necessary to strictly limit the defect threshold. The adjusted indicators are shown in Table 3. Using this index to evaluate the weld seam of medium-grade silicon steel can control the broken belt rate below 1‰.
表3用于低牌号硅钢的评价指标Table 3 Evaluation indicators for low-grade silicon steel
实施例4Example 4
系统的组成和实施例1相同,对于高牌号硅钢,由于材料中的硅含量高,材料的脆性很大,需要严格限定缺陷门槛值,调整后的指标见表4。采用该指标进行高牌号硅钢焊缝的评价,可将断带率控制在1‰以下。The composition of the system is the same as that of Example 1. For high-grade silicon steel, due to the high silicon content in the material, the material is very brittle, and the defect threshold needs to be strictly limited. The adjusted indicators are shown in Table 4. Using this index to evaluate high-grade silicon steel welds can control the broken belt rate below 1‰.
表4用于低牌号硅钢的评价指标Table 4 Evaluation indicators for low-grade silicon steel
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS59112209A (en) * | 1982-12-20 | 1984-06-28 | Nippon Steel Corp | Measuring method of shape of steel tube weld zone |
JPH04329345A (en) * | 1991-04-30 | 1992-11-18 | Nippon Steel Corp | Steel plate surface defect inspection equipment |
JPH0890066A (en) * | 1994-09-21 | 1996-04-09 | Nippon Steel Corp | UO steel pipe weld surface flaw inspection method |
CN1034834C (en) * | 1992-02-18 | 1997-05-07 | 英国钢铁公司 | Improvements in and relating to shape determination |
CN101416044A (en) * | 2005-12-23 | 2009-04-22 | Posco公司 | Apparatus and method for on-line detecting welding part of strip |
CN101750416A (en) * | 2008-12-19 | 2010-06-23 | 中国科学院沈阳自动化研究所 | Visual welding seam surface quality detection sensor based on line structure light |
-
2012
- 2012-07-17 CN CN201210246506.1A patent/CN103542819A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS59112209A (en) * | 1982-12-20 | 1984-06-28 | Nippon Steel Corp | Measuring method of shape of steel tube weld zone |
JPH04329345A (en) * | 1991-04-30 | 1992-11-18 | Nippon Steel Corp | Steel plate surface defect inspection equipment |
CN1034834C (en) * | 1992-02-18 | 1997-05-07 | 英国钢铁公司 | Improvements in and relating to shape determination |
JPH0890066A (en) * | 1994-09-21 | 1996-04-09 | Nippon Steel Corp | UO steel pipe weld surface flaw inspection method |
CN101416044A (en) * | 2005-12-23 | 2009-04-22 | Posco公司 | Apparatus and method for on-line detecting welding part of strip |
CN101750416A (en) * | 2008-12-19 | 2010-06-23 | 中国科学院沈阳自动化研究所 | Visual welding seam surface quality detection sensor based on line structure light |
Non-Patent Citations (1)
Title |
---|
颜家元等: "涡流检测在带钢焊缝质量评价中的应用", 《机械工程与自动化》 * |
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