CN117760343B - Flatness inspection method for cleaning after welding - Google Patents
Flatness inspection method for cleaning after welding Download PDFInfo
- Publication number
- CN117760343B CN117760343B CN202311782095.2A CN202311782095A CN117760343B CN 117760343 B CN117760343 B CN 117760343B CN 202311782095 A CN202311782095 A CN 202311782095A CN 117760343 B CN117760343 B CN 117760343B
- Authority
- CN
- China
- Prior art keywords
- welding
- weld
- internal
- hydroelectric generator
- contour line
- 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
Links
- 238000003466 welding Methods 0.000 title claims abstract description 379
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000004140 cleaning Methods 0.000 title claims abstract description 8
- 238000007689 inspection Methods 0.000 title claims description 18
- 230000007547 defect Effects 0.000 claims abstract description 71
- 230000007847 structural defect Effects 0.000 claims abstract description 30
- 238000005516 engineering process Methods 0.000 claims abstract description 12
- 238000001514 detection method Methods 0.000 claims abstract description 10
- 238000011156 evaluation Methods 0.000 claims abstract description 9
- 238000005452 bending Methods 0.000 claims description 47
- 238000002844 melting Methods 0.000 claims description 19
- 230000008018 melting Effects 0.000 claims description 19
- 238000004458 analytical method Methods 0.000 claims description 16
- 230000004927 fusion Effects 0.000 claims description 14
- 239000002893 slag Substances 0.000 claims description 10
- 238000012544 monitoring process Methods 0.000 claims description 9
- 239000003086 colorant Substances 0.000 claims description 8
- 230000005856 abnormality Effects 0.000 claims description 7
- 238000012937 correction Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 4
- 238000010248 power generation Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000007667 floating Methods 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 abstract description 11
- 230000002265 prevention Effects 0.000 abstract description 3
- 230000000007 visual effect Effects 0.000 abstract description 3
- 230000002950 deficient Effects 0.000 description 3
- 239000000758 substrate Substances 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000000877 morphologic effect Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000005476 soldering Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 208000010392 Bone Fractures Diseases 0.000 description 1
- 206010017076 Fracture Diseases 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 239000011324 bead Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000012466 permeate Substances 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Landscapes
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention belongs to the field of post-welding flatness detection of hydroelectric generators, and particularly discloses a flatness detection method for post-welding cleaning, which comprises the following steps: by introducing a three-dimensional laser scanning technology to identify the internal structural images of all welding seams of the hydroelectric generator, visual display of welding defects is realized, tiny internal structural defects of the welding seams are more intuitively presented, and then potential problems possibly causing faults are timely found. The structural risk factors of the weld joint positions are evaluated by acquiring the vibration amplitude of the vibration motor of the hydroelectric generator under the rated power, so that the influence coefficient of each internal weld joint structural defect on the operation of the hydroelectric generator is analyzed, the fault risk of the weld joint in the operation process of the hydroelectric generator is effectively predicted, and the early warning and the possible fault prevention are facilitated. And by analyzing the flatness evaluation index corresponding to each defect type, the welding position of each defect of the hydroelectric generator is accurately positioned, so that an important basis can be provided for the establishment of a maintenance plan.
Description
Technical Field
The invention belongs to the field of post-welding flatness detection of hydroelectric generators, and relates to a flatness detection method for post-welding cleaning.
Background
As an important energy source device, the hydroelectric generator is welded in the manufacturing process, wherein the welding quality directly affects the performance and the safety of the hydroelectric generator. In order to improve the quality control level and the working efficiency of the hydroelectric generator and promote the progress and development of the manufacturing technology of the hydroelectric generator, a new mode suitable for the post-welding flatness inspection of the hydroelectric generator needs to be improved and innovated so as to solve the problems existing in the past.
The hydroelectric generator can not permeate from a water source, so that the water resource leakage and electric shock faults can be caused by the connection defect of the welding line in the operation process of the hydroelectric generator. However, the existing post-welding flatness inspection method is mainly focused on inspecting the appearance flatness of the surface of the welding point substrate, and cannot deeply evaluate quality defects such as air holes, cracks and the like in the welding joint, so that potential welding defects cannot be effectively found, and the inspection result is insufficient in comprehensiveness. Meanwhile, the welding point position of the hydroelectric generator is usually narrow or difficult to observe, so that the visibility of post-welding detection is limited, the detail and the internal structure of the welding line are difficult to sufficiently observe by a detector, and some minor defects can be ignored or misjudged.
In addition, the existing weld quality inspection result is often based on the condition that the hydroelectric generator is in a static mode, the condition that the hydroelectric generator is greatly vibrated and jolted in the running process is ignored, and if partial weld joints are insufficiently fused or fusion points are defective, the whole fracture risk of the weld joints in the running vibration process of the machine can be caused.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the above-mentioned background art, a flatness inspection method for cleaning after soldering is proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides a flatness inspection method for cleaning after welding, which comprises the following steps: b1, weld joint statistics of the hydroelectric generator: the hydroelectric generator is scanned by using three-dimensional laser scanning, the corresponding surface welding seams and the corresponding internal welding seams of the hydroelectric generator are identified, the numbers of the surface welding seams are marked as 1,2, … r … and a, and the numbers of the internal welding seams are marked as 1,2, … k … and c.
B2, detecting the flatness of the surface welding seam: and identifying each surface welding seam contour line, wherein each surface welding seam contour line comprises a left contour line and a right contour line, extracting the torsion degree of each surface welding seam contour line, and further analyzing the deformation degree χ r of each surface welding seam.
B3, detecting internal weld defects: and obtaining structural images of all the internal welding seams by using a flaw detection technology, further evaluating the welding roughness of all the internal welding seams, and analyzing the influence coefficient lambdak of structural defects of all the internal welding seams on the operation of the hydroelectric generator according to the structural images.
B4, detecting the flatness of the welding piece: and (3) acquiring the standard connection shape of the welding parts corresponding to the positions of the welding points of the hydroelectric generator, and identifying the welding color of the connection parts of the welding parts corresponding to the positions of the welding points, thereby evaluating the abnormal degree of the welding parts corresponding to the positions of the welding points.
B5, flatness analysis: and analyzing the post-welding flatness of the hydroelectric generator by combining the deformation degree of each surface welding seam, the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure anomaly degree of each welding point position, so as to judge the post-welding flatness grade of the hydroelectric generator, wherein the post-welding flatness grade comprises a high grade, a medium grade and a low grade.
B6, fixed-point early warning: and carrying out early warning display on the post-welding leveling grade of the hydroelectric generator, extracting flatness evaluation indexes corresponding to each defect type when the post-welding leveling grade is displayed as a low grade, further identifying each defect welding position of the hydroelectric generator, and carrying out early warning feedback on each defect welding position.
In a preferred embodiment, the analysis of the deformation of the weld joints of the respective surfaces is performed in the following manner: and (3) obtaining a standard contour line of the substrate corresponding to each surface welding seam position on the hydroelectric generator, comparing the standard contour line with the surface welding seam contour line at the corresponding position, identifying the gap area and the overflow area of each surface welding seam contour line, and summing to obtain the residual area S r Residue (C) of each surface welding seam contour line.
Obtaining the torsion degree gamma r of each surface welding seam contour line, and obtaining the torsion degree gamma r by a calculation formulaObtaining the deformation degree of each surface welding seam, wherein S 'and gamma' are respectively the residual area and the torsion degree of the surface welding seam contour line, and corresponding allowable values are set for the residual area and the torsion degree of the surface welding seam contour line, and the allowable values are respectively/areThe set residual area and the corresponding deformation degree influence duty ratio of the torsion degree are respectively set.
In a preferred embodiment, the specific method for acquiring the torsion degree of each surface weld contour line comprises the following steps: and arranging bending points on each surface welding seam contour line, wherein the bending points comprise left bending points and right bending points, connecting each surface welding seam contour line with each adjacent left bending point on the corresponding left side contour line to obtain each left connecting line segment of each surface welding seam contour line, and obtaining each right connecting line segment of each surface welding seam contour line in the same way, and further carrying out contour comparison on the left connecting line segments and the right connecting line segments of each surface welding seam contour line at the same bending point positions to obtain welding seam included angles theta ri of each surface welding seam contour line at the same bending point positions, wherein i represents the number of the bending point positions, and i=1, 2, … and v.
And comparing the left bending point and the right bending point on the same bending point positions on the surface welding seam contour lines to obtain the welding seam width D ri of the surface welding seam contour lines on the same bending point positions.
Calculating to obtain the torsion degree of each surface welding seam contour lineWherein θ' represents the set surface weld contour line corresponding to the reference weld angle, Δd represents the preset weld width error allowable value at two bending point positions, D r (i+1) represents the weld width of the (r) th surface weld contour line at the (i+1) th identical bending point position, v represents the number of bending point positions, and f 0 represents the set weld torsion corresponding deviation correction factor.
In a preferred embodiment, the method for evaluating the weld roughness of each internal weld bead comprises the following steps: uniformly distributing each monitoring point on each internal welding line, identifying the fusion depth of each internal welding line corresponding to each monitoring point from the structural image of each internal welding line, acquiring the position of each monitoring point in each internal welding line which is smaller than the set safe fusion depth, marking the position as the position of each internal welding line corresponding to each melting point, extracting the fusion area H kj of each internal welding line corresponding to each melting point position, wherein j represents the number of the melting point position, and j=1, 2, … and u.
And identifying whether bubbles exist at each melting point position in each internal welding line, and counting to obtain the bubble area S kj of each melting point position in each internal welding line.
Calculating the weld roughness of each internal weldWherein H' represents the set safe fusion depth, and S 0 represents the set bubble area reference value corresponding to the melting point position.
In a preferred embodiment, the analysis process for analyzing the influence coefficient of each internal weld structural defect on the operation of the hydroelectric generator is as follows: obtaining vibration amplitude F of a vibration motor of the hydroelectric generator under rated power generation, distance L k between the position of the vibration motor and the position of each internal weld joint, and evaluating importance specific gravity of each internal weld joint positionWherein F 'represents the corresponding reference vibration amplitude of the set vibration motor, L' represents the set reference distance between the position of the vibration motor and the position of the internal weld joint, and e is a natural constant.
Identifying whether each internal weld position is in the cable protection area, if a certain internal weld position is in the cable protection area, marking the structural risk factor of the internal weld position as tau 1, otherwise marking the structural risk factor as tau 2, and counting the structural risk factors tau k＝τ1 or tau 2 of each internal weld position.
Identifying whether cracks exist in each internal welding seam position, and when cracks exist in a certain internal welding seam position, acquiring the crack length of the internal welding seam position, and further analyzing the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generatorWherein L' k represents the crack length of the kth internal weld position, L 0 represents the set crack length contrast value, beta represents the set floating influence correction ratio corresponding to the internal weld structural defect, P1 represents that the internal weld position is in the cable protection area, and P2 represents that the internal weld position is not in the cable protection area.
In a preferred embodiment, the evaluation of the welding structure anomaly of each welding point position is performed as follows: extracting the connection shape of the welding parts corresponding to the positions of the welding points, and comparing the connection shape with the standard connection shape of the welding parts corresponding to the positions of the corresponding welding points of the hydroelectric generator to obtain the deviation area of the welding parts corresponding to the positions of the welding pointsM denotes the weld position number, m=1, 2, …, l.
And extracting standard welding colors of the welding positions from the web data end, and comparing the standard welding colors with the welding colors of the connecting parts of the welding parts corresponding to the welding positions to obtain the color anomaly epsilon m of each welding position.
Analyzing abnormality degree of welding piece corresponding to each welding point positionWhere S' represents a set weld deviation area contrast value, ε 0 represents a set color reference anomaly, and Δεrepresents a color anomaly corresponding to a set deviation tolerance.
In a preferred embodiment, the analysis of post-weld flatness of the hydro-electric generator corresponds to an analysis formula ofIn/>The flatness balance factors corresponding to the deformation degree of the surface welding seam, the influence coefficient of the internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure abnormality of the welding point position are respectively obtained.
And comparing the post-welding flatness of the hydroelectric generator with a preset post-welding flatness range corresponding to each post-welding flatness grade, and identifying the post-welding flatness grade of the hydroelectric generator.
In a preferred embodiment, the defect types include a surface weld defect type, an interior weld defect type, a welding defect type.
In a preferred embodiment, the identifying the correspondence of each defective welding position of the hydroelectric generator comprises: and identifying an image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line through an image identification technology, and counting to obtain each welding slag position to be cleaned in the hydroelectric generator when foreign matters exist in a certain position in the image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line, wherein welding slag exists between the left side contour line and the right side contour line corresponding to each surface welding seam contour line, and further the positions of the surface welding seam contour lines are marked as welding slag positions to be cleaned.
And comparing the deformation degree of each surface welding seam with a preset deformation degree threshold value, screening out the positions of each surface welding seam with the deformation degree exceeding the preset deformation degree threshold value, marking the positions as the positions to be processed of the surface forms of each welding seam, and summarizing and de-duplicating the positions to be cleaned of each welding slag and the positions to be processed of the surface forms of each welding seam in the hydroelectric generator to obtain the early warning positions of the defect types of the surface welding seam.
Comparing the running influence coefficient of each internal weld joint structural defect on the hydroelectric generator with a preset running influence coefficient threshold value of the hydroelectric generator, screening out the position of each internal weld joint structural defect, of which the running influence coefficient exceeds the preset running influence coefficient threshold value of the hydroelectric generator, marking the position as each early warning position of the internal weld joint defect type, and obtaining each early warning position of the welding defect type in the same way.
And counting all early warning positions of the surface weld defect type, all early warning positions of the internal weld defect type and all early warning positions of the welding defect type, namely all defect welding positions of the hydroelectric generator.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the invention, the three-dimensional laser scanning technology is introduced to identify the internal structure image of each welding seam of the hydroelectric generator, so that the data analysis is carried out on the internal structure image, the visual display of welding defects is realized, the problem of the internal structure of the welding seam is more intuitively presented, and the judgment and decision of operators are facilitated. Meanwhile, high-precision data can be obtained, and tiny internal structural defects of the welding line can be captured, so that potential problems possibly causing faults or accidents can be found early, and corresponding repair measures can be taken.
(2) According to the invention, the structural risk factors of the welding seam positions are evaluated by acquiring the vibration amplitude of the vibration motor of the hydroelectric generator under the rated power, so that the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generator is analyzed, the fault risk of the welding seam in the operation process of the hydroelectric generator is effectively predicted, the early warning and the prevention of possible faults are facilitated, and the analysis result can be used as the basis for decision makers to carry out risk management and maintenance planning, so that the safe operation of the hydroelectric generator is more effectively ensured.
(3) According to the invention, the welding positions of the defects of the hydroelectric generator can be accurately positioned by analyzing the flatness evaluation indexes corresponding to the defect types, an important basis can be provided for the establishment of a maintenance plan, and the maintenance priority positions can be determined by analyzing the distribution conditions of different defect positions, so that the maintenance work is more efficient and effective, and unnecessary maintenance cost and time waste are avoided. Meanwhile, an inspector can intensively inspect the welding defect position, so that the condition of missing inspection or misjudgment is avoided, and the accuracy and reliability of the detection result are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram showing the steps of the method of the present invention.
FIG. 2 is a schematic view of the contour of a surface weld according to the present invention.
FIG. 3 is a schematic illustration of the internal weld defect condition of the present invention.
Reference numerals: 1. left side contour line corresponding to the surface weld contour line, 2 right side contour line corresponding to the surface weld contour line, 3, inner weld, 4, crack of inner weld position.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a flatness inspection method for cleaning after soldering, which includes: b1, weld joint statistics of the hydroelectric generator: the hydroelectric generator is scanned by using three-dimensional laser scanning, the corresponding surface welding seams and the corresponding internal welding seams of the hydroelectric generator are identified, the numbers of the surface welding seams are marked as 1,2, … r … and a, and the numbers of the internal welding seams are marked as 1,2, … k … and c.
Specifically, the surface weld seam is specifically a connecting gap of a hydroelectric generator housing base material, and the internal weld seam is specifically a compact weld seam between internal structures of the hydroelectric generator.
B2, detecting the flatness of the surface welding seam: and identifying each surface welding seam contour line, wherein each surface welding seam contour line comprises a left contour line and a right contour line, extracting the torsion degree of each surface welding seam contour line, and further analyzing the deformation degree χ r of each surface welding seam.
In a specific embodiment of the invention, the corresponding analysis mode for analyzing the deformation degree of each surface weld joint is as follows: and (3) acquiring a standard contour line of the substrate corresponding to each surface welding seam position on the hydroelectric generator from the web data end, comparing the standard contour line with the surface welding seam contour line at the corresponding position, identifying the gap area and the overflow area of each surface welding seam contour line, and summing to obtain the residual area S r Residue (C) of each surface welding seam contour line.
The notch area refers to the area of a certain position on the surface welding seam contour line, which is lower than the corresponding position on the standard contour line of the base material, and the overflow area refers to the area of a certain position on the surface welding seam contour line, which is higher than the corresponding position on the standard contour line of the base material.
Obtaining the torsion degree gamma r of each surface welding seam contour line, and obtaining the torsion degree gamma r by a calculation formulaObtaining the deformation degree of each surface welding seam, wherein S 'and gamma' are respectively the residual area and the torsion degree of the surface welding seam contour line, and corresponding allowable values are set for the residual area and the torsion degree of the surface welding seam contour line, and the allowable values are respectively/areThe set residual area and the corresponding deformation degree influence duty ratio of the torsion degree are respectively set.
Referring to fig. 2, in another embodiment of the present invention, the specific method for obtaining the torsion degree of each surface weld contour line is as follows: and arranging bending points on each surface welding seam contour line, wherein the bending points comprise left bending points and right bending points, connecting each surface welding seam contour line with each adjacent left bending point on the corresponding left side contour line to obtain each left connecting line segment of each surface welding seam contour line, and obtaining each right connecting line segment of each surface welding seam contour line in the same way, and further carrying out contour comparison on the left connecting line segments and the right connecting line segments of each surface welding seam contour line at the same bending point positions to obtain welding seam included angles theta ri of each surface welding seam contour line at the same bending point positions, wherein i represents the number of the bending point positions, and i=1, 2, … and v.
And comparing the left bending point and the right bending point on the same bending point positions on the surface welding seam contour lines to obtain the welding seam width D ri of the surface welding seam contour lines on the same bending point positions.
Calculating to obtain the torsion degree of each surface welding seam contour lineWherein θ' represents the set surface weld contour line corresponding to the reference weld angle, Δd represents the preset weld width error allowable value at two bending point positions, D r (i+1) represents the weld width of the (r) th surface weld contour line at the (i+1) th identical bending point position, v represents the number of bending point positions, and f 0 represents the set weld torsion corresponding deviation correction factor.
B3, detecting internal weld defects: and obtaining structural images of all the internal welding seams by using a flaw detection technology, further evaluating the welding roughness of all the internal welding seams, and analyzing the influence coefficient lambada k of structural defects of all the internal welding seams on the operation of the hydroelectric generator according to the structural images.
Referring to fig. 3, in an embodiment of the present invention, the method for evaluating the weld roughness of each internal weld is as follows: uniformly distributing each monitoring point on each internal welding line, identifying the fusion depth of each internal welding line corresponding to each monitoring point from the structural image of each internal welding line, acquiring the position of each monitoring point in each internal welding line which is smaller than the set safe fusion depth, marking the position as the position of each internal welding line corresponding to each melting point, extracting the fusion area H kj of each internal welding line corresponding to each melting point position, wherein j represents the number of the melting point position, and j=1, 2, … and u. The fusion depth of the internal weld is the thickness of the weld joint.
And acquiring a weld cross-section image containing weld internal structure flaw information from a Web data end, wherein the flaw information comprises bubble flaw positions and crack flaw positions, extracting morphological characteristics corresponding to the flaw information based on an edge detection method, wherein the morphological characteristics comprise flaw sizes, shapes, boundary curves, texture information and the like, identifying whether bubbles exist at each melting point position in corresponding internal weld from the structural image of each internal weld through an image processing technology, and counting to obtain bubble areas S kj at each melting point position in each internal weld.
Calculating the weld roughness of each internal weldWherein H' represents the set safe fusion depth, and S 0 represents the set bubble area reference value corresponding to the melting point position.
In another embodiment of the present invention, the analysis process for analyzing the influence coefficient of each internal weld structural defect on the operation of the hydroelectric generator is as follows: obtaining vibration amplitude F of a vibration motor of the hydroelectric generator under rated power generation, distance L k between the position of the vibration motor and the position of each internal weld joint, and evaluating importance specific gravity of each internal weld joint positionWherein F 'represents the corresponding reference vibration amplitude of the set vibration motor, L' represents the set reference distance between the position of the vibration motor and the position of the internal weld joint, and e is a natural constant.
The vibration amplitude of the vibration motor of the hydroelectric generator under rated power generation, and the distance between the position of the vibration motor and the position of each internal welding seam are all preset standard structural design parameters of the hydroelectric generator.
Extracting a cable protection area of the hydroelectric generator from preset standard structural design parameters, comparing each internal welding seam position with the cable protection area of the hydroelectric generator, identifying whether each internal welding seam position is in the cable protection area, if so, marking the structural risk factor of each internal welding seam position as tau 1, otherwise, marking the structural risk factor as tau 2, and counting the structural risk factors tau k＝τ1 or tau 2 of each internal welding seam position.
Identifying whether cracks exist in each internal welding seam position, and when cracks exist in a certain internal welding seam position, acquiring the crack length of the internal welding seam position, and further analyzing the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generatorWherein L' k represents the crack length of the kth internal weld position, L 0 represents the set crack length contrast value, beta represents the set floating influence correction ratio corresponding to the internal weld structural defect, P1 represents that the internal weld position is in the cable protection area, and P2 represents that the internal weld position is not in the cable protection area.
The corresponding identification mode of the crack length of the inner weld joint position is the same as that of the bubble area of the melting point position.
According to the invention, the structural risk factors of the welding seam positions are evaluated by acquiring the vibration amplitude of the vibration motor of the hydroelectric generator under the rated power, so that the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generator is analyzed, the fault risk of the welding seam in the operation process of the hydroelectric generator is effectively predicted, the early warning and the prevention of possible faults are facilitated, and the analysis result can be used as the basis for decision makers to carry out risk management and maintenance planning, so that the safe operation of the hydroelectric generator is more effectively ensured.
B4, detecting the flatness of the welding piece: and acquiring the standard connection shape of the welding parts corresponding to the positions of the welding points of the hydroelectric generator from the web data end, and identifying the welding color of the connection parts of the welding parts corresponding to the positions of the welding points by using an image identification technology, thereby evaluating the abnormal degree of the welding parts corresponding to the positions of the welding points.
In a specific embodiment of the present invention, the process of evaluating the welding structure anomaly at each welding point position is as follows: extracting the connection shape of the welding parts corresponding to the positions of the welding points, and comparing the connection shape with the standard connection shape of the welding parts corresponding to the positions of the corresponding welding points of the hydroelectric generator to obtain the deviation area of the welding parts corresponding to the positions of the welding pointsM denotes the weld position number, m=1, 2, …, l.
And extracting standard welding colors of the welding positions from the web data end, and comparing the standard welding colors with the welding colors of the connecting parts of the welding parts corresponding to the welding positions to obtain the color anomaly epsilon m of each welding position.
Analyzing abnormality degree of welding piece corresponding to each welding point positionWhere S' represents a set weld deviation area contrast value, ε 0 represents a set color reference anomaly, and Δεrepresents a color anomaly corresponding to a set deviation tolerance.
The deviating area and the color anomaly of the welding point position corresponding to the welding piece are one of important indexes for evaluating the anomaly of the welding piece. The welding point position deviation area refers to the deviation degree between the welding point and the welding piece position, and if the welding point position deviation area exceeds a specified range, the welding abnormality exists in the welding point position of the welding piece. Under normal conditions, the colors around the welding points should be uniform and consistent, and no obvious color difference exists, however, when the temperature control is poor or the welding is insufficient in the welding process, the color of the welding area may be abnormal, the color is uneven or obvious color difference appears, the color anomaly reflects the stability and quality of the welding structure, and the strength and compactness of the welding part may be affected.
According to the invention, the three-dimensional laser scanning technology is introduced to identify the internal structure image of each welding seam of the hydroelectric generator, so that the internal structure image of each welding seam is subjected to data analysis processing, the visual display of welding defects is realized, the problem of the internal structure of the welding seam is more intuitively presented, and the judgment and decision making of operators are facilitated. Meanwhile, high-precision data can be obtained, and tiny internal structural defects of the welding line can be captured, so that potential problems possibly causing faults or accidents can be found early, and corresponding repair measures can be taken.
B5, flatness analysis: and analyzing the post-welding flatness of the hydroelectric generator by combining the deformation degree of each surface welding seam, the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure anomaly degree of each welding point position, so as to judge the post-welding flatness grade of the hydroelectric generator, wherein the post-welding flatness grade comprises a high grade, a medium grade and a low grade.
In a specific embodiment of the present invention, the post-welding flatness corresponding analysis formula for analyzing the hydro-electric generator is as followsIn/>The flatness balance factors corresponding to the deformation degree of the surface welding seam, the influence coefficient of the internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure abnormality of the welding point position are respectively obtained.
And comparing the post-welding flatness of the hydroelectric generator with a preset post-welding flatness range corresponding to each post-welding flatness grade, and identifying the post-welding flatness grade of the hydroelectric generator.
B6, fixed-point early warning: and carrying out early warning display on the post-welding leveling grade of the hydroelectric generator, extracting flatness evaluation indexes corresponding to each defect type when the post-welding leveling grade is displayed as a low grade, further identifying each defect welding position of the hydroelectric generator, and carrying out early warning feedback on each defect welding position.
In a specific embodiment of the present invention, each defect type includes a surface weld defect type, an internal weld defect type, and a welding defect type, and the flatness evaluation index corresponding to each defect type specifically refers to a deformation degree of the surface weld corresponding to the surface weld defect type, a welding structure anomaly degree of the welding defect corresponding to the welding point position corresponding to the welding defect type, and an influence coefficient of the internal weld structure defect corresponding to the internal weld defect type on the hydroelectric generator operation.
In another embodiment of the present invention, the identifying the corresponding content of each defective welding position of the hydroelectric generator includes: and identifying an image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line through an image identification technology, and counting to obtain each welding slag position to be cleaned in the hydroelectric generator when foreign matters exist in a certain position in the image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line, wherein welding slag exists between the left side contour line and the right side contour line corresponding to each surface welding seam contour line, and further the positions of the surface welding seam contour lines are marked as welding slag positions to be cleaned.
And comparing the deformation degree of each surface welding seam with a preset deformation degree threshold value, screening out the positions of each surface welding seam with the deformation degree exceeding the preset deformation degree threshold value, marking the positions as the positions to be processed of the surface forms of each welding seam, and summarizing and de-duplicating the positions to be cleaned of each welding slag and the positions to be processed of the surface forms of each welding seam in the hydroelectric generator to obtain the early warning positions of the defect types of the surface welding seam.
Comparing the running influence coefficient of each internal weld joint structural defect on the hydroelectric generator with a preset running influence coefficient threshold value of the hydroelectric generator, screening out the position of each internal weld joint structural defect, of which the running influence coefficient exceeds the preset running influence coefficient threshold value of the hydroelectric generator, marking the position as each early warning position of the internal weld joint defect type, and obtaining each early warning position of the welding defect type in the same way.
And counting all early warning positions of the surface weld defect type, all early warning positions of the internal weld defect type and all early warning positions of the welding defect type, namely all defect welding positions of the hydroelectric generator.
According to the invention, the welding positions of the defects of the hydroelectric generator can be accurately positioned by analyzing the flatness evaluation indexes corresponding to the defect types, an important basis can be provided for the establishment of a maintenance plan, and the maintenance priority positions can be determined by analyzing the distribution conditions of different defect positions, so that the maintenance work is more efficient and effective, and unnecessary maintenance cost and time waste are avoided. Meanwhile, an inspector can intensively inspect the welding defect position, so that the condition of missing inspection or misjudgment is avoided, and the accuracy and reliability of the detection result are improved.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (7)
1. A flatness inspection method for cleaning after welding is characterized by comprising the following steps: b1, weld joint statistics of the hydroelectric generator: scanning the hydroelectric generator by using three-dimensional laser scanning, identifying the corresponding surface welding seams and the internal welding seams of the hydroelectric generator, and marking the serial numbers of the surface welding seams asThe number of each internal weld is also denoted/>；
B2, detecting the flatness of the surface welding seam: identifying each surface weld contour line, wherein each surface weld contour line comprises a left side contour line and a right side contour line, extracting the torsion degree of each surface weld contour line, and further analyzing the deformation degree of each surface weld；
B3, detecting internal weld defects: obtaining structural images of all internal welding seams by using a flaw detection technology, further evaluating the welding roughness of all internal welding seams, and analyzing the influence coefficient of structural defects of all internal welding seams on the operation of the hydroelectric generator according to the structural images；
B4, detecting the flatness of the welding piece: obtaining standard connection shapes of welding parts corresponding to the positions of all welding points of the hydroelectric generator, identifying welding colors of the connecting parts of the welding parts corresponding to the positions of all the welding points, and accordingly evaluating the abnormal degree of the welding parts corresponding to the positions of all the welding points;
B5, flatness analysis: analyzing the post-welding flatness of the hydroelectric generator by combining the deformation degree of each surface welding seam, the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure anomaly degree of each welding point position, so as to judge the post-welding flatness grade of the hydroelectric generator, wherein the post-welding flatness grade comprises a high grade, a medium grade and a low grade;
B6, fixed-point early warning: performing early warning display on the post-welding leveling grade of the hydroelectric generator, extracting corresponding leveling evaluation indexes of each defect type when the post-welding leveling grade is displayed as a low grade, further identifying each defect welding position of the hydroelectric generator, and performing early warning feedback on each defect welding position;
the welding structure anomaly degree of each welding point position is evaluated, and the process is as follows:
extracting the connection shape of the welding parts corresponding to the positions of the welding points, and comparing the connection shape with the standard connection shape of the welding parts corresponding to the positions of the corresponding welding points of the hydroelectric generator to obtain the deviation area of the welding parts corresponding to the positions of the welding points ，/>Indicates the position number of the welding point,/>；
Extracting standard welding color of the welding position from the web data end, comparing the standard welding color with the welding color of the connecting part of the welding piece corresponding to each welding point position, and obtaining color anomaly of each welding point position；
Analyzing abnormality degree of welding piece corresponding to each welding point positionWherein/>Indicating the set deviation area contrast value of the welding piece,/>Indicating the degree of anomaly of the set color reference,/>A setting deviation allowable value corresponding to the color anomaly degree is represented;
The post-welding flatness corresponding analysis formula for the analysis hydroelectric generator is as follows In/>The flatness balance factors corresponding to the deformation degree of the surface welding seam, the influence coefficient of the internal welding seam structural defect on the operation of the hydroelectric generator and the welding structure abnormality degree of the welding point position are respectively obtained;
and comparing the post-welding flatness of the hydroelectric generator with a preset post-welding flatness range corresponding to each post-welding flatness grade, and identifying the post-welding flatness grade of the hydroelectric generator.
2. A post-weld clean flatness inspection method according to claim 1, characterized in that: the corresponding analysis mode for analyzing the deformation degree of each surface weld joint is as follows:
Obtaining standard contour lines of base materials corresponding to the positions of welding seams on each surface of the hydroelectric generator, comparing the standard contour lines with the contour lines of the welding seams on the surfaces of the corresponding positions, identifying the gap area and the overflow area of the contour lines of the welding seams on each surface, and summing to obtain residual areas of the contour lines of the welding seams on each surface ；
Obtaining the torsion degree of the contour line of each surface welding seamFrom the calculation formula/>Obtaining the deformation degree of each surface welding seam, wherein/>、/>Corresponding allowable values are respectively set for residual areas and torsion degrees of the surface weld contour lines,The set residual area and the corresponding deformation degree influence duty ratio of the torsion degree are respectively set.
3. A post-weld clean flatness inspection method according to claim 2, characterized in that: the specific method for acquiring the torsion degree of each surface weld contour line comprises the following steps:
Each bending point is distributed on each surface welding seam contour line, each bending point comprises a left bending point and a right bending point, each adjacent left bending point on each surface welding seam contour line corresponding to each left bending point on each left bending point is connected to obtain each left connecting line segment of each surface welding seam contour line, each right connecting line segment of each surface welding seam contour line is obtained in the same way, and further, the left connecting line segments and the right connecting line segments of each surface welding seam contour line at the same bending point positions are subjected to contour comparison to obtain welding seam included angles of each surface welding seam contour line at the same bending point positions ,/>Number indicating the position of the bending point,/>；
Comparing the left bending point and the right bending point of each surface welding seam contour line at each same bending point position to obtain the welding seam width of each surface welding seam contour line at each same bending point position；
Calculating to obtain the torsion degree of each surface welding seam contour lineWhereinRepresenting the set surface weld contour line corresponding to the reference weld included angle,/>Weld width error tolerance value representing preset two bending point positions,/>Represents the/>The outline of each surface weld is at the/>The weld widths at the same bending point locations,Representing the number of bending point positions,/>And representing the set corresponding deviation correction factor of the weld torsion degree.
4. A post-weld clean flatness inspection method according to claim 1, characterized in that: the corresponding evaluation method of the welding roughness of each internal welding seam comprises the following steps:
Uniformly distributing each monitoring point on each internal welding line, identifying the fusion depth of each internal welding line corresponding to each monitoring point from the structural image of each internal welding line, acquiring the position of each monitoring point in each internal welding line which is smaller than the set safe fusion depth, marking the position as the position of each internal welding line corresponding to each melting point, and extracting the fusion area of each internal welding line corresponding to each melting point position ，/>Indicates the melting point position number,/>；
Identifying whether bubbles exist at each melting point position in each internal welding line, and counting to obtain the bubble area of each melting point position in each internal welding line；
Calculating the weld roughness of each internal weldWherein/>Representing the setting of safe fusion depth,/>The set melting point position is indicated as a bubble area reference value.
5. A post-weld clean flatness inspection method according to claim 4, characterized in that: the analysis process for analyzing the influence coefficient of each internal weld joint structural defect on the operation of the hydroelectric generator comprises the following steps:
obtaining vibration amplitude of vibration motor of hydroelectric generator under rated power generation Distance/>, vibration motor position from each interior weld positionAssessment of the importance specific gravity/>, of each internal weld positionWhereinIndicating the corresponding reference vibration amplitude of the set vibration motor,/>A set reference distance between the position of the vibration motor and the position of the internal weld joint is represented, and e is a natural constant;
Identifying whether each internal weld position is in the cable protection area, and if so, marking the structural risk factor of the internal weld position as Otherwise, it is denoted as/>Counting structural risk factors/>, of each internal weld position；
Identifying whether cracks exist in each internal welding seam position, and when cracks exist in a certain internal welding seam position, acquiring the crack length of the internal welding seam position, and further analyzing the influence coefficient of each internal welding seam structural defect on the operation of the hydroelectric generatorWherein/>Represents the/>Crack length at each internal weld location,/>Represents the set fracture length contrast value,/>Representing the correction proportion of the floating influence corresponding to the set internal weld structure defect,/>Indicating that the internal weld location is within the cable protected area,/>Indicating that the interior weld location is not within the cable protected area.
6. A post-weld clean flatness inspection method according to claim 1, characterized in that: the defect types include a surface weld defect type, an internal weld defect type and a welding defect type.
7. The post-weld clean flatness inspection method of claim 6, wherein: the corresponding content of the defect welding positions of the identified hydroelectric generator comprises the following steps:
Identifying an image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line through an image identification technology, and counting to obtain each welding slag position to be cleaned in the hydroelectric generator when foreign matters exist in the image area between the left side contour line and the right side contour line corresponding to each surface welding seam contour line at a certain position;
Comparing the deformation degree of each surface welding seam with a preset deformation degree threshold value, screening out each surface welding seam position with the deformation degree exceeding the preset deformation degree threshold value, marking the position as each welding seam surface form to-be-processed position, summarizing and de-duplicating each welding slag to-be-cleaned position and each welding seam surface form to-be-processed position in the hydroelectric generator, and obtaining each early warning position of the surface welding seam defect type;
Comparing the running influence coefficient of each internal weld joint structural defect on the hydroelectric generator with a preset hydroelectric generator running influence coefficient threshold value, screening out each internal weld joint structural defect position of which the running influence coefficient exceeds the preset hydroelectric generator running influence coefficient threshold value, marking the internal weld joint structural defect position as each early warning position of the internal weld joint defect type, and obtaining each early warning position of the welding defect type in the same way;
and counting all early warning positions of the surface weld defect type, all early warning positions of the internal weld defect type and all early warning positions of the welding defect type, namely all defect welding positions of the hydroelectric generator.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311782095.2A CN117760343B (en) | 2023-12-22 | 2023-12-22 | Flatness inspection method for cleaning after welding |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311782095.2A CN117760343B (en) | 2023-12-22 | 2023-12-22 | Flatness inspection method for cleaning after welding |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117760343A CN117760343A (en) | 2024-03-26 |
| CN117760343B true CN117760343B (en) | 2024-06-07 |
Family
ID=90324954
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311782095.2A Active CN117760343B (en) | 2023-12-22 | 2023-12-22 | Flatness inspection method for cleaning after welding |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117760343B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0972851A (en) * | 1995-09-04 | 1997-03-18 | Sumitomo Metal Ind Ltd | Method and apparatus for detection of welding bead for steel pipe |
| JP2005014026A (en) * | 2003-06-24 | 2005-01-20 | Enshu Ltd | Weld zone inspection method, and welding support system |
| DE102005027342A1 (en) * | 2005-06-13 | 2006-12-14 | Abb Research Ltd. | Troubleshooting system for detecting weld faults |
| KR20190124452A (en) * | 2018-04-26 | 2019-11-05 | 오토아이티(주) | Apparatus for weld bead detecting and method for detecting welding defects of the same |
| CN110987944A (en) * | 2019-12-19 | 2020-04-10 | 武汉新耐视智能科技有限责任公司 | Laser brazing weld surface defect detection method based on envelope line identification |
| CN111721768A (en) * | 2020-06-04 | 2020-09-29 | 江苏弘冉智能科技有限公司 | Multi-information fusion weld defect detection system and method |
| CN112232400A (en) * | 2020-10-12 | 2021-01-15 | 太原科技大学 | Stainless steel weld ultrasonic defect detection method based on depth feature fusion |
| CN112666248A (en) * | 2020-12-16 | 2021-04-16 | 上海交通大学 | Weld defect automatic detection method and system based on deep learning |
| CN114354639A (en) * | 2022-03-21 | 2022-04-15 | 苏芯物联技术(南京)有限公司 | Weld defect real-time detection method and system based on 3D point cloud |
| CN115290656A (en) * | 2022-07-15 | 2022-11-04 | 中车青岛四方机车车辆股份有限公司 | Welding seam surface defect detection and classification method based on line structured light |
-
2023
- 2023-12-22 CN CN202311782095.2A patent/CN117760343B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0972851A (en) * | 1995-09-04 | 1997-03-18 | Sumitomo Metal Ind Ltd | Method and apparatus for detection of welding bead for steel pipe |
| JP2005014026A (en) * | 2003-06-24 | 2005-01-20 | Enshu Ltd | Weld zone inspection method, and welding support system |
| DE102005027342A1 (en) * | 2005-06-13 | 2006-12-14 | Abb Research Ltd. | Troubleshooting system for detecting weld faults |
| KR20190124452A (en) * | 2018-04-26 | 2019-11-05 | 오토아이티(주) | Apparatus for weld bead detecting and method for detecting welding defects of the same |
| CN110987944A (en) * | 2019-12-19 | 2020-04-10 | 武汉新耐视智能科技有限责任公司 | Laser brazing weld surface defect detection method based on envelope line identification |
| CN111721768A (en) * | 2020-06-04 | 2020-09-29 | 江苏弘冉智能科技有限公司 | Multi-information fusion weld defect detection system and method |
| CN112232400A (en) * | 2020-10-12 | 2021-01-15 | 太原科技大学 | Stainless steel weld ultrasonic defect detection method based on depth feature fusion |
| CN112666248A (en) * | 2020-12-16 | 2021-04-16 | 上海交通大学 | Weld defect automatic detection method and system based on deep learning |
| CN114354639A (en) * | 2022-03-21 | 2022-04-15 | 苏芯物联技术(南京)有限公司 | Weld defect real-time detection method and system based on 3D point cloud |
| CN115290656A (en) * | 2022-07-15 | 2022-11-04 | 中车青岛四方机车车辆股份有限公司 | Welding seam surface defect detection and classification method based on line structured light |
Non-Patent Citations (1)
| Title |
|---|
| 基于视差照相法的小直径管焊缝内缺陷深度定位技术;孙朝明;汤光平;王增勇;;无损检测;20101010(第10期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117760343A (en) | 2024-03-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107367682B (en) | Printed circuit board repair method and system | |
| CN101402159B (en) | Device and method for testing weldability for rolled steel for vessel | |
| CN113588692B (en) | Computer vision-based weld defect nondestructive testing method | |
| CN114216915B (en) | Method for detecting and classifying class levels based on stains and defect types of circuit board | |
| CN105115802B (en) | CTOD experimental methods are reprocessed in a kind of welding | |
| CN107081503A (en) | The infrared nondestructive detection device and its Infrared Non-destructive Testing method of a kind of arc-welding quality | |
| WO2021251064A1 (en) | Information processing device, determination method, and information processing program | |
| CN112453751B (en) | Pipeline all-position welding back surface online monitoring method based on visual sensing | |
| CN112091472B (en) | Welding process quality fusion judgment method and device | |
| KR20150038693A (en) | Method and device for inspecting an object for the detection of surface damage | |
| CN111430055B (en) | Reuse method of MOX fuel cladding tube | |
| JP2023514753A (en) | Method and apparatus for testing bipolar plates of electrochemical cells, in particular fuel cells | |
| CN111948002B (en) | Weld joint characteristic region deformation damage evolution rule experimental method | |
| CN117760343B (en) | Flatness inspection method for cleaning after welding | |
| CN116976757B (en) | High-precision circuit board tracing system and method | |
| CN112008195A (en) | Research and development of construction process for controlling welding cracks of composite board | |
| CN117236756A (en) | Intelligent control system for pipe fitting welding forming based on machine vision | |
| CN116460495A (en) | Welding processing method | |
| JPH11248638A (en) | Automatic detection method for surface of press-molded product | |
| CN217528325U (en) | Chemical fiber paper tube flaw detection device based on laser ranging | |
| Inspection | Repair | |
| Setiyana et al. | Analysis of Welding Results on Stringer Tertiary Screen Using NDT Magnetic Particle Test Method at PT. PAL Indonesia | |
| CN116958076A (en) | Weld quality assessment method | |
| Maass | Demonstration of Closed-Loop Control for Laser Powder Bed Fusion (LPBF) | |
| WO2021127761A1 (en) | Passive monocular image-based method for visual inspection of weld beads for butt joints |
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 |