An internal weld control system

Abstract

The application relates to an internal welding control system for welding the inside of a workpiece, comprising a moving module for moving horizontally in the inside of the workpiece, a cleaning module for cleaning the moving path of the moving module, the moving module having one end provided with the cleaning module as a moving front end and the other end as a moving rear end, a guiding module for guiding the movement of the moving module in the inside of the workpiece, a welding module for welding processing the inside of the workpiece, and a wire feeding module for feeding welding wire to the welding module, wherein the moving module, the cleaning module, the guiding module, the welding module and the wire feeding module are signal-connected with a control module. The cleaning module is arranged at the moving front end of the moving module, so that the cleaning module can pre-clean the impurities such as particles, stains and dust on the path during the movement of the moving module in the inside of the workpiece, the impurities are prevented from affecting the smooth movement of the moving module, and the moving module can move smoothly.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of welding technology, in particular to an internal welding control system. BACKGROUND

[0002] Internal welding is a kind of practical problem often encountered in welding production, especially in the welding process of large bridges, pressure vessels, oil and gas pipelines, etc. Since it is difficult for construction personnel to enter the internal structure, internal welding is more often completed by using a dedicated internal welding mobile device. At present, such welding platforms mostly use wheels with magnetism to firmly adhere to the workpiece surface during welding.

[0003] However, a large amount of spatter metal is inevitably generated during welding. These liquid metal spatters from the molten pool quickly cool down in the air to form irregular metal particles, and the spattered metal particles will be adsorbed on the surface of the wheel, thereby seriously hindering the stable rolling of the wheel, and even causing the wheel to completely separate from the workpiece surface, making it difficult to maintain the precision of internal welding. SUMMARY

[0004] In order to solve the problems existing in the prior art, the present application aims to provide an internal welding control system. The internal welding control system sets a cleaning module at the moving front end of the moving module, so that the cleaning module can pre-clean the impurities such as particles, stains and dust on the path during the movement of the moving module inside the workpiece, avoid the influence of impurities on the smooth movement of the moving module, and then the moving module can move smoothly according to the predetermined route, and the subsequent welding can be continuous and stable.

[0005] The internal welding control system provided by the present application comprises:

[0006] A moving module for moving horizontally inside the workpiece;

[0007] A cleaning module arranged at one end of the moving module for cleaning the moving path of the moving module, the moving module taking the end with the cleaning module as the moving front end and the other end as the moving rear end;

[0008] A guide module arranged on the moving module for guiding the movement of the moving module inside the workpiece;

[0009] A welding module arranged at the moving rear end of the moving module for welding processing inside the workpiece;

[0010] A wire feeding module is arranged on the moving module and connected with the welding module to feed welding wire to the welding module;

[0011] A control module is signal connected with the moving module, the cleaning module, the guiding module, the welding module and the wire feeding module.

[0012] Preferably, the guiding module comprises two oppositely arranged moving guiding mechanisms, which are arranged close to the two sides of the moving module respectively, so that the two moving guiding mechanisms are in contact with the two inner side walls of the workpiece respectively.

[0013] Preferably, the control module controls the moving module, the cleaning module, the guiding module, the welding module and the wire feeding module according to a welding control strategy to complete welding processing.

[0014] The welding control strategy comprises the following steps:

[0015] S1. Selecting and setting welding process parameters according to parameter information of a required welding workpiece;

[0016] S2. Arranging an image acquisition assembly on the moving module to acquire image data of an internal path of the workpiece in real time, and selecting a moving speed of the moving module according to impurity density on the internal path of the workpiece;

[0017] S3. Guiding movement of the moving module according to the guiding module;

[0018] S4. Constructing a weld seam identification model, moving the moving module to a required welding position, and dynamically adjusting welding current and welding speed according to a weld seam type.

[0019] Preferably, the step S1 specifically comprises:

[0020] The parameter information comprises workpiece thickness and workpiece material type coefficient;

[0021] The welding process parameters comprise welding initial current and welding initial speed;

[0022] Obtaining workpiece thickness D and workpiece material type coefficient K of the workpiece ω and calculating welding initial current I0 and welding initial speed V0 of the workpiece:

[0023] I0 = I L *K ω *D*α

[0024]

[0025] wherein, I L represents a theoretical welding current value; a represents a current adjustment coefficient; V L represents a theoretical welding speed value; K V represents a speed comprehensive influence coefficient; β represents a speed adjustment coefficient.

[0026] Preferably, the step S1 further comprises:

[0027] The workpiece material type coefficient K ω is selected according to the workpiece material type:

[0028] If the workpiece material type is carbon steel, the workpiece material type coefficient K ω is 1.0-1.3;

[0029] If the workpiece material type is stainless steel, the workpiece material type coefficient K ω is 1.4-1.7;

[0030] If the workpiece material type is alloy material, the workpiece material type coefficient K ω is 1.8-2.0.

[0031] Preferably, the step S2 specifically comprises:

[0032] The moving module moves forward inside the workpiece with the moving front end, and the image acquisition assembly acquires images in real time of the path of the moving module to obtain a path image;

[0033] The path image is transmitted to an edge computing gateway, and the path image data is processed by a weighted average method to obtain a gray image;

[0034] The gray image is denoised by a median filter algorithm to obtain a first path image;

[0035] The first path image is enhanced by a histogram equalization technique to obtain a second path image;

[0036] The second path image is sequentially subjected to image segmentation and morphological processing to obtain a third path image, the number of pixel points of impurity parts in the third path image is counted, and an image analysis algorithm is used to calculate an impurity area S, and the impurity density M is calculated according to the following formula:

[0037]

[0038] wherein, the number of pixel points N is in units of pieces; the impurity area S is in units of square pixels; and the impurity density M is in units of pieces / square pixel.

[0039] Preferably, step S2 further includes:

[0040] The moving speed of the moving module is selected based on the impurity density M. Y ;

[0041] Based on the pre-established mapping relationship between impurity density and moving speed range, a moving speed adjustment coefficient C is selected, and the moving speed V is dynamically adjusted according to the moving speed adjustment coefficient C. Y ;

[0042] If 0 ≤ M < 2, then the value of the moving speed adjustment coefficient C is:

[0043]

[0044] If 2 ≤ M < 10, then the value of the moving speed adjustment coefficient C is:

[0045]

[0046] If M ≥ 10, then the value of the moving speed adjustment coefficient C is:

[0047]

[0048] The moving speed V Y Calculate using the following formula:

[0049] V Y =V YL *C

[0050] Among them, V YL This represents the theoretical initial moving speed.

[0051] Preferably, step S3 specifically includes:

[0052] Pressure sensors are installed at the contact points between the two moving guide mechanisms and the inner sidewall of the workpiece, and the pressure values ​​of the two moving guide mechanisms are monitored in real time to obtain the real-time guide pressure value F. DX1 and F DX2 ;

[0053] If F DX1 =[F Dmin F Dmax And F DX2 =[F Dmin F Dmax If the movement trajectory of the mobile module is normal, it is determined that the original movement state is maintained.

[0054] If F DX1 ≠[F Dmin, F Dmax ] and / or F DX2 ≠ [F Dmin , F Dmax ], it is determined that the motion trajectory of the mobile module is abnormal, an alarm information is sent out, and a motion adjustment operation is performed.

[0055] wherein F Dmin represents a preset minimum guiding pressure; and F Dmax represents a preset maximum guiding pressure.

[0056] Preferably, the step S4 specifically comprises:

[0057] acquiring historical weld image data and corresponding weld type label data, wherein the weld type label of the weld type label data comprises butt weld, fillet weld, T-shaped weld, lap weld, plug weld and slot weld;

[0058] performing grayscale processing, denoising processing and image enhancement processing on the historical weld image data to obtain processed first historical weld image data;

[0059] extracting edge features, geometric features and texture features of the first historical weld image data by using a Canny algorithm and a gray level co-occurrence matrix method to obtain a weld feature vector;

[0060] using a support vector machine, taking the weld feature vector as input and taking a weld type label as output, performing model training and testing on the historical weld image data and the weld type label data to obtain a trained weld recognition model;

[0061] the mobile module moves to a required welding position, the image acquisition assembly acquires a weld image of the required welding position, and inputs the weld image into the weld recognition model to identify a weld type of the required welding position, and adjusts the welding current and the welding speed according to the weld type.

[0062] Preferably, the step S4 further comprises:

[0063] selecting a welding adjustment coefficient P according to the weld type, and adjusting the welding initial current I0 and the welding initial speed V0 according to the welding adjustment coefficient P to obtain an adjusted welding actual current I S and a welding actual speed V S , and the adjustment mode is as follows:

[0064] I S = I0*P

[0065] V S = V0*P

[0066] If the weld type is butt joint, the welding adjustment coefficient P is 1.0-1.2;

[0067] If the weld type is fillet joint, the welding adjustment coefficient P is 0.9-1.1;

[0068] If the weld type is T-shaped joint, the welding adjustment coefficient P is 1.2-1.4;

[0069] If the weld type is lap joint, the welding adjustment coefficient P is 0.8-1.0;

[0070] If the weld type is plug joint, the welding adjustment coefficient P is 1.3-1.5;

[0071] If the weld type is slot joint, the welding adjustment coefficient P is 1.1-1.3.

[0072] The internal welding control system has the advantages that:

[0073] The internal welding control system can clean the impurities such as particles, stains and dust on the path in advance when the mobile module moves in the workpiece, so that the mobile module can move stably according to the predetermined route, and the subsequent welding can be continuous and stable. BRIEF DESCRIPTION OF DRAWINGS

[0074] Figure 1 is a structural schematic diagram of the internal welding control system;

[0075] Figure 2 is a structural schematic diagram of the internal welding control system;

[0076] Figure 3 is a structural schematic diagram of the internal welding control system;

[0077] Figure 4 is a structural schematic diagram of the internal welding control system;

[0078] Figure 5 is a structural schematic diagram of the internal welding control system;

[0079] Figure 6is a method flow chart of a welding control strategy in an internal welding control system described in the present application.

[0080] BRIEF DESCRIPTION OF DRAWINGS

[0081] 10 - moving module; 101 - base; 102 - moving wheel; 103 - handle;

[0082] 20 - cleaning module; 201 - cleaning scraper mechanism; 202 - pressure spring piece;

[0083] 30 - guiding module; 301 - moving guiding mechanism; 3011 - support plate 3011; 3012 - first rotating plate; 3013 - second rotating plate; 3014 - first guiding ball; 3015 - second guiding ball;

[0084] 40 - welding module;

[0085] 50 - wire feeding module;

[0086] 60 - T-shaped support column. DETAILED DESCRIPTION

[0087] As shown in Figure 1 - Figure 6 The internal welding control system described in the present application comprises:

[0088] The moving module 10 is used for horizontal movement in the interior of the workpiece. Specifically, the moving module 10 comprises a base 101, moving wheels 102, a handle 103, and a driving motor arranged in the base 101. The driving motor is used to drive the moving module 10 to move. The moving wheels 102 are respectively rotatably connected to the two sides of the base 101. The moving wheels 102 are rotatably connected to the two sides near the front end and the rear end of the base 101, i.e., the moving wheels 102 are arranged on the two sides of the front end and the rear end of the base 101.

[0089] The handle 103 is arranged at the front end of the base 101. When the driving motor is not used, the base 101 can be pulled or pushed in the horizontal direction by applying an external force to the handle 103.

[0090] The cleaning module 20 is arranged at one end of the moving module 10 and is used for cleaning the moving path of the moving module 10. The moving module 10 takes the end provided with the cleaning module 20 as the moving front end and the other end as the moving rear end. Specifically, the cleaning module 20 comprises a cleaning scraper mechanism 201 and a pressure spring piece 202.

[0091] One end of the pressure spring piece 202 is connected to the moving module 10, and the other end is connected to the cleaning scraper mechanism 201.

[0092] The cleaning scraper mechanism 201 is slidingly connected to the front end of the moving module 10, and the cleaning scraper mechanism 201 moves upward or downward along the vertical direction on the moving module 10 by the elastic force of the pressure spring sheet 202; that is, the pressure spring sheet 202 has a downward elastic force in the vertical direction, when the cleaning scraper mechanism 201 is subjected to an external force in the vertical direction, the cleaning scraper mechanism 201 is pressed against the pressure spring sheet 202, so that the cleaning scraper mechanism 201 moves upward along the vertical direction, after no external force acts on the cleaning scraper mechanism 201, the cleaning scraper mechanism 201 moves downward along the vertical direction by the elastic force of the pressure spring sheet 202, so that when passing through uneven road conditions, the cleaning scraper mechanism 201 can be adjusted along the vertical direction, avoiding the influence of the moving module 10;

[0093] The guide module 30 is arranged on the moving module 10 and is used for guiding the movement of the moving module 10 inside the workpiece;

[0094] The welding module 40 is arranged at the moving rear end of the moving module 10 and is used for welding the inside of the workpiece; the welding module 40 includes two groups of oppositely arranged welding gun assemblies, the welding ends of the welding gun assemblies extend away from the moving rear end of the moving module 10, and the wire feeding ends of the welding gun assemblies are close to the moving rear end of the moving module 10;

[0095] The wire feeding module 50 is arranged on the moving module 10 and is connected with the welding module 40, and is used for feeding welding wire to the welding module 40; the wire feeding module 50 includes a wire feeding motor and a wire feeding mechanism, the output end of the wire feeding motor is rotationally connected with the wire feeding mechanism, the wire feeding end of the wire feeding mechanism is connected with the wire feeding end of the welding gun assembly, and the wire feeding mechanism feeds the welding wire to the welding gun assembly through the driving of the wire feeding motor;

[0096] The welding module 40 and the wire feeding module 50 are connected on the moving module 10 through the T-shaped support column 60;

[0097] The control module is signal-connected with the moving module 10, the cleaning module 20, the guide module 30, the welding module 40 and the wire feeding module 50;

[0098] The internal welding control system sets the cleaning module 20 at the moving front end of the moving module 10, so that the cleaning module 20 can pre-clean the impurities such as particles, stains and dust on the path during the movement of the moving module 10 inside the workpiece, avoiding the influence of the impurities on the smooth movement of the moving module 10, and then the moving module 10 can move smoothly according to the predetermined route, and the subsequent welding can be continuous and stable; the guide module 30 can guide the movement of the moving module 10, so that the moving module 10 can move according to the predetermined path inside the workpiece, and can accurately reach the position required for welding, effectively improving the accuracy and reliability of the subsequent welding.

[0099] Further, in the embodiment, the guiding module 30 comprises two oppositely arranged moving guiding mechanisms 301, and the two moving guiding mechanisms 301 are arranged close to the two sides of the moving module 10 respectively, so that the two moving guiding mechanisms 301 are in contact with the two side walls inside the workpiece respectively;

[0100] Each moving guiding mechanism 301 comprises a support plate 3011, a first rotating plate 3012, a second rotating plate 3013, a first guiding ball 3014 and a second guiding ball 3015;

[0101] The middle part of the support plate 3011 is connected with the T-shaped support column 60 through a connecting rod, and the two ends of the support plate 3011 extend to the moving front end and the moving rear end of the moving module 10 respectively; one end of the connecting rod is connected to the middle part of the lower surface of the support plate 3011, and the other end of the connecting rod is connected to the upper surface of the T-shaped support column 60;

[0102] One end of the first rotating plate 3012 and one end of the second rotating plate 3013 are rotatably connected to the two ends of the support plate 3011 respectively, and the first rotating plate 3012 is close to the moving front end of the moving module 10, and the second rotating plate 3013 is close to the moving rear end of the moving module 10, and the first rotating plate 3042 and the second rotating plate 3043 both rotate in the horizontal direction around the support plate 3041;

[0103] The end of the first rotating plate 3012 away from the support plate 3011 is rotatably connected with the first guiding ball 3014, and the end of the second rotating plate 3013 away from the support plate 3011 is rotatably connected with the second guiding ball 3015;

[0104] In use, the moving guiding mechanism 301 located on the moving module 10 adjusts the position of the moving guiding mechanism 301 by rotating the first rotating plate 3042 and the second rotating plate 3043 in the horizontal direction around the support plate 3041, so as to adapt to the width of the workpiece;

[0105] The rotating connection between the first rotating plate 3012 and the support plate 3011, and the rotating connection between the second rotating plate 3013 and the support plate 3011 are both provided with a spring, and the first rotating plate 3012 and the second rotating plate 3013 can both rotate to the initial position by the rebound force of the spring, i.e. rotate in the direction away from the moving module 10, so that when inside the workpiece, the first guiding ball 3014 and the second guiding ball 3015 on the same moving guiding mechanism 301 are in contact with the side walls inside the workpiece and have a certain pressure, and the pressure is the force generated by the side walls inside the workpiece on the first guiding ball 3014 and the second guiding ball 3015; when guiding the moving module 10, if the pressure suddenly changes or becomes 0, it indicates that the moving module 10 deviates or moves abnormally;

[0106] During the movement of the movement module 10, the first guide ball 3014 and the second guide ball 3015 will rotate to avoid the first guide ball 3014 and the second guide ball 3015 not moving and generating friction with the inner side wall of the workpiece to hinder the movement of the movement module 10.

[0107] Further, in the embodiment, the control module controls the movement module 10, the cleaning module 20, the guide module 30, the welding module 40 and the wire feeding module 50 according to the welding control strategy to complete the welding process.

[0108] The welding control strategy includes the following steps:

[0109] S1, selecting and setting welding process parameters according to the parameter information of the required welding workpiece;

[0110] S2, setting an image acquisition assembly on the movement module 10, acquiring image data of the internal path of the workpiece in real time through the image acquisition assembly, and selecting the movement speed of the movement module 10 according to the impurity density on the internal path of the workpiece; the image acquisition assembly can be selected to be multiple industrial cameras arranged on the movement module 10, which are distributed to shoot the path image in front of the movement module 10 and the weld image of the subsequent required welding position;

[0111] S3, guiding the movement of the movement module 10 according to the guide module 30;

[0112] S4, constructing a weld recognition model, moving the movement module 10 to the required welding position, and dynamically adjusting the welding current and the welding speed according to the weld type.

[0113] Further, in the embodiment, step S1 specifically includes:

[0114] The parameter information includes the workpiece thickness and the workpiece material type coefficient;

[0115] The welding process parameters include the welding initial current and the welding initial speed;

[0116] The workpiece thickness D and the workpiece material type coefficient K of the workpiece are obtained ω , and the welding initial current I0 and the welding initial speed V0 of the workpiece are calculated:

[0117] I0 = I L *K ω *D*α

[0118]

[0119] Wherein, I L represents the theoretical welding current value; α represents the current adjustment coefficient; V L represents the theoretical welding speed value; K VWherein, β represents the speed adjustment coefficient.

[0120] Further, in the embodiment, the step S1 further comprises:

[0121] The workpiece material type coefficient K ω is selected according to the workpiece material type:

[0122] If the workpiece material type is carbon steel, the workpiece material type coefficient K ω is selected as 1.0-1.3; and the optimal value of K ω is 1.2 when the workpiece material type is carbon steel.

[0123] If the workpiece material type is stainless steel, the workpiece material type coefficient K ω is selected as 1.4-1.7; and the optimal value of K ω is 1.5 when the workpiece material type is stainless steel.

[0124] If the workpiece material type is alloy material, the workpiece material type coefficient K ω is selected as 1.8-2.0; and the optimal value of K ω is 1.9 when the workpiece material type is alloy material.

[0125] The step S1 is exemplified as follows:

[0126] The workpiece thickness D is 20mm, the theoretical welding current value I L is 10A, the current adjustment coefficient a is 0.05A / mm, the theoretical welding speed value V L is 20mm / min, the speed comprehensive influence coefficient K V is 10, and the speed adjustment coefficient β is 2.5mm / min.

[0127] If the workpiece material type is carbon steel, the workpiece material type coefficient K ω is selected as K ω =1.2.

[0128] The initial current I0 is calculated as 10*0.05*20*1.2=12A.

[0129] The welding initial speed

[0130] Further, in the embodiment, the step S2 specifically comprises:

[0131] The moving module 10 moves forward to the inside of the workpiece, and the image acquisition assembly acquires the path image in real time.

[0132] The path image is transmitted to the edge computing gateway, and the path image data is grayed by a weighted average method to obtain a gray image;

[0133] The gray image is denoised by a median filtering algorithm to obtain a first path image;

[0134] The first path image is subjected to image enhancement processing by a histogram equalization technique to obtain a second path image;

[0135] The second path image is subjected to image segmentation processing and morphological processing in sequence to obtain a third path image, the number of pixel points of the impurity part in the third path image is counted, and an image analysis algorithm is used to calculate the area S of the impurity region, and the impurity density M is calculated according to the following formula:

[0136]

[0137] The unit of the number of pixel points N is piece; the unit of the area S of the impurity region is square pixel; and the unit of the impurity density M is piece / square pixel;

[0138] An example is as follows:

[0139] The image acquisition component can be an industrial camera, and the mobile module 10 moves from the workpiece port to the inside of the workpiece at a theoretical initial moving speed, the industrial camera collects images of the moving path of the mobile module 10 in real time at 30 frames per second, and the real-time collected path images are transmitted to the edge computing gateway;

[0140] After the edge computing gateway receives the real-time transmitted path images, the gray scale is processed by a weighted average method, for example, for a certain frame of real-time collected color image, the RGB value of a pixel point is (190, 160, 130), and the gray value of the pixel point is calculated according to the weighted coefficients W R = 0.299, W G = 0.587, and W B = 0.114, that is, Gray = 0.299*190 + 0.587*160 + 0.114*130 = 164.23, and the same calculation is performed on all pixel points of the whole frame of image to obtain a gray image;

[0141] The gray image is denoised by a median filtering algorithm, for example, a 3*3 filtering window is selected, if the pixel values in the window are 150, 155, 145, 140, 160, 165, 135, 170, and 175, the values are sorted from small to large as 135, 140, 145, 150, 155, 160, 165, 170, and 175, the median value 155 is used to replace the original value of the center pixel of the window, and the whole frame of gray image is traversed to obtain the first path image after denoising;

[0142] The first path image is enhanced by using histogram equalization technology, the number of pixels of each gray level of the frame image is counted, the cumulative distribution function is calculated, and the pixel gray value is redistributed, for example, the original gray level of 120 pixels is changed to 140 after processing, and the second path image is obtained, so that the impurity details are more clear in the image;

[0143] The second path image is subjected to real-time image segmentation, the U-Net model based on machine learning is adopted to quickly and accurately distinguish the impurity region and the background region, then morphological processing is performed, the impurity region profile is further optimized through erosion and expansion operation, then the number of pixel points N of the impurity part is counted in real time, and the area S of the impurity region is calculated, for example, the number of pixel points N of the impurity part is counted in real time as 300, the area S of the impurity region is calculated as 120 square pixels, and the impurity density M is:

[0144]

[0145] Therefore, the impurity density M is 2.4 per square pixel.

[0146] Further, in the embodiment, the step S2 further comprises:

[0147] The moving speed of the moving module 10 is selected according to the impurity density M Y ;

[0148] According to the pre-established mapping relationship between the impurity density and the moving speed range, the moving speed adjustment coefficient C is selected, and the moving speed V Y is dynamically adjusted according to the moving speed adjustment coefficient C.

[0149] If 0≤M<2, the value of the moving speed adjustment coefficient C is:

[0150]

[0151] If 2≤M<10, the value of the moving speed adjustment coefficient C is:

[0152]

[0153] If M≥10, the value of the moving speed adjustment coefficient C is:

[0154]

[0155] The moving speed V Y is calculated according to the following formula:

[0156] V Y =V YL *C

[0157] Wherein, V YLtheoretical initial moving speed;

[0158] For example, as follows:

[0159] According to the above example, the impurity density M = 2.4 per pixel, so 2 ≤ M < 10, and the value of the moving speed adjustment coefficient C is:

[0160]

[0161] Theoretical initial moving speed V YL = 2 mm / s, then the moving speed V Y = 2 * 1.1 = 2.2 mm / s.

[0162] Further, in the embodiment, step S3 specifically comprises:

[0163] The positions where the two moving guide mechanisms 301 contact the inner side wall of the workpiece are provided with pressure sensors, and the pressure values of the two moving guide mechanisms 301 are monitored in real time to obtain real-time guide pressure values F DX1 and F DX2 ; According to the structure of the moving guide mechanism 301, the collected pressure values are the sum of the pressures of the first guide ball 3014 and the second guide ball 3015 on the same moving guide mechanism 301 and the inner side wall of the workpiece;

[0164] If F DX1 = [F Dmin , F Dmax ] and F DX2 = [F Dmin , F Dmax ], it is determined that the movement trajectory of the moving module 10 is normal, and the original movement state is maintained;

[0165] If F DX1 ≠ [F Dmin , F Dmax ] and / or F DX2 ≠ [F Dmin , F Dmax ], it is determined that the movement trajectory of the moving module 10 is abnormal, an alarm information is issued, and a movement adjustment operation is performed;

[0166] Wherein, F Dmin represents the preset minimum guide pressure; F Dmax represents the preset maximum guide pressure;

[0167] For example, as follows:

[0168] According to the historical welding data and test data, the preset minimum guide pressure F Dmin = 5N, and the preset maximum guide pressure F Dmax = 10N;

[0169] Since the two mobile guide mechanisms 301 are arranged near the two sides of the mobile module 10, i.e. the left side and the right side of the mobile module 10, the pressure values of the two mobile guide mechanisms 301 are F DX1 The pressure value of the mobile guide mechanism 301 corresponding to the left side of the mobile module 10 is F DX2 The pressure value of the mobile guide mechanism 301 corresponding to the right side of the mobile module 10 is F

[0170] The pressure values of the two mobile guide mechanisms 301 are monitored in real time, and the pressure values of the two mobile guide mechanisms 301 at a certain moment are F DX1 = 7N, F DX2 = 8N, F DX1 = [F Dmin , F Dmax ] and F DX2 = [F Dmin , F Dmax ], it is determined that the motion trajectory of the mobile module 10 is normal, and the original motion state is maintained.

[0171] If at a subsequent moment, the pressure values of the two mobile guide mechanisms 301 are monitored in real time, and the pressure values of the two mobile guide mechanisms 301 at a certain moment are F DX1 = 12N, F DX2 = 3N, F DX1 ≠ [F Dmin , F Dmax ] and F DX2 ≠ [F Dmin , F Dmax ], it is determined that the motion trajectory of the mobile module 10 is abnormal, an alarm information is sent out, and the motion trajectory of the mobile module 10 is adjusted through the control module so as to satisfy F DX1 = [F Dmin , F Dmax ] and F DX2 = [F Dmin , F Dmax ].

[0172] Further, in the embodiment, step S4 specifically comprises:

[0173] The historical weld image data and the corresponding weld type label data are obtained, and the weld type label of the weld type label data includes butt weld, fillet weld, T-shaped weld, lap weld, plug weld and slot weld;

[0174] The historical weld image data is subjected to grayscale processing, denoising processing and image enhancement processing to obtain the first historical weld image data after processing;

[0175] The edge features, geometric features and texture features of the first historical weld image data are extracted by using Canny algorithm and gray level co-occurrence matrix method to obtain a weld feature vector;

[0176] The support vector machine is adopted, the weld feature vector is taken as the input, and the weld type label is taken as the output, model training and testing are carried out on historical weld image data and weld type label data, and a trained weld recognition model is obtained;

[0177] The mobile module 10 moves to the required welding position, the image acquisition component acquires the weld image of the required welding position, and inputs the weld image into the weld recognition model, and the weld type of the required welding position is recognized, and the welding current and welding speed are adjusted according to the weld type;

[0178] The example is as follows:

[0179] 1000 historical weld image data are acquired from an existing welding database, and corresponding weld type label data includes 300 butt welds, 250 fillet welds, 200 T-shaped welds, 150 lap welds, 50 plug welds and 50 slot welds;

[0180] For a historical butt weld color image, the pixel point RGB value is (200, 180, 160), and the weighted coefficients W R =0.299, W G =0.587, W B =0.114 are calculated. The gray value Gray=0.299*200+0.587*180+0.114*160=178.28, and the same operation is performed on all pixel points of the 1000 historical weld images to realize the gray scale of each image;

[0181] The median filtering algorithm is adopted, a 3*3 filtering window is taken for the gray-scale image, for example, the pixel values in the window are 160, 165, 155, 150, 170, 175, 145, 180, 185, the median value 165 is taken after sorting to replace the center pixel value of the window, the noise is removed by traversing the whole image, and the histogram equalization technology is used to count the pixel number of each gray level of the image, and the pixel gray value is redistributed to enhance the contrast of the image, and the first historical weld image data is obtained;

[0182] The Canny algorithm is used, the low threshold is set to 50, and the high threshold is set to 150, a processed T-shaped weld image is processed, and the weld edge is detected;

[0183] The geometric feature extraction includes analyzing the shape, length and width geometric information of the weld, for example, for the lap weld, the length and width of the lap part are measured;

[0184] The texture feature extraction is obtained by using the gray level co-occurrence matrix method to calculate the contrast and entropy texture parameters, and the weld feature vector of all images is obtained;

[0185] The weld type label is output, and the support vector machine is used for model training. After multiple rounds of training and parameter adjustment, 800 image data are used for training, and 200 image data are used for testing, so as to obtain the trained weld recognition model;

[0186] The mobile module 10 moves to the required welding position, the image acquisition component acquires the weld image of the required welding position, and inputs the weld image into the weld recognition model. For example, when the first required welding position is reached, the acquired image is identified as a butt weld by the weld recognition model, and the welding current and welding speed are adjusted according to the butt weld.

[0187] Further, in the embodiment, step S4 further comprises:

[0188] The welding adjustment coefficient P is selected according to the weld type, and the welding initial current I0 and the welding initial speed V0 are adjusted according to the welding adjustment coefficient P, to obtain the adjusted welding actual current I S and the welding actual speed V S , and the adjustment mode is as follows:

[0189] I S = I0*P

[0190] V S = V0*P

[0191] If the weld type is a butt weld, the welding adjustment coefficient P is 1.0-1.2; and when the weld type is a butt weld, the optimal value of the welding adjustment coefficient P is 1.1.

[0192] If the weld type is a fillet weld, the welding adjustment coefficient P is 0.9-1.1; and when the weld type is a fillet weld, the optimal value of the welding adjustment coefficient P is 1.0.

[0193] If the weld type is a T-shaped weld, the welding adjustment coefficient P is 1.2-1.4; and when the weld type is a T-shaped weld, the optimal value of the welding adjustment coefficient P is 1.3.

[0194] If the weld type is a lap weld, the welding adjustment coefficient P is 0.8-1.0; and when the weld type is a lap weld, the optimal value of the welding adjustment coefficient P is 0.9.

[0195] If the weld type is a plug weld, the welding adjustment coefficient P is 1.3-1.5; and when the weld type is a plug weld, the optimal value of the welding adjustment coefficient P is 1.4.

[0196] If the weld type is a slot weld, the welding adjustment coefficient P is 1.1-1.3; and when the weld type is a slot weld, the optimal value of the welding adjustment coefficient P is 1.2.

[0197] For example:

[0198] According to the above example, the welding adjustment coefficient P is 1.0-1.2, and P=1.1 is selected, if the butt weld is identified by the weld identification model;

[0199] The welding initial current I0=12A, and the welding initial speed V0=21mm / min;

[0200] The welding actual current I S =12*1.1=13.2A;

[0201] The welding actual speed V S =21*1.1=23.1mm / min.

[0202] In the description of the present application, it should be understood that the orientation words such as "front, back, up, down, left, right", "transverse, vertical, horizontal" and "top, bottom" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, without the opposite description, these orientation words do not indicate and imply that the indicated device or element must have a specific orientation or be constructed and operated in a specific orientation, therefore it cannot be understood as a limitation on the protection scope of the present application.

[0203] For those skilled in the art, other various corresponding changes and deformations can be made according to the above described technical solutions and concepts, and all these changes and deformations should belong to the protection scope of the claims of the present application.

Claims

1. An internal welding control system for welding the interior of a workpiece, characterized in that, include: A moving module (10) is used to move horizontally inside the workpiece; A cleaning module (20) is disposed at one end of the moving module (10) and is used to clean the moving path of the moving module (10). The moving module (10) has one end with the cleaning module (20) as the moving front end and the other end as the moving rear end. A guide module (30) is disposed on the moving module (10) and is used to guide the movement of the moving module (10) inside the workpiece. Welding module (40), which is located at the moving rear end of the moving module (10), is used to perform welding processing on the inside of the workpiece; A wire feeding module (50) is disposed on the moving module (10) and connected to the welding module (40) for feeding welding wire to the welding module (40); The control module, the moving module (10), the cleaning module (20), the guiding module (30), the welding module (40) and the wire feeding module (50) are all signal connected to the control module; The moving speed of the moving module (10) is based on the impurity density on the moving path inside the workpiece. Select movement speed ; Based on the pre-established mapping relationship between impurity density and moving speed range, a moving speed adjustment coefficient is selected. And adjust the coefficient according to the moving speed. Dynamically adjust the movement speed ; If 0≤ If the moving speed adjustment coefficient is less than 2, then... The value can be: ， If 2≤ If the moving speed adjustment coefficient is less than 10, then... The value can be: ， like If the moving speed adjustment coefficient is ≥10, then... The value can be: ， The speed of movement Calculate using the following formula: ， in, This represents the theoretical initial moving speed; impurity density The method of obtaining it is: An image acquisition component is provided on the moving module (10). The moving module (10) moves forward into the workpiece with the moving front end. The image acquisition component acquires images of the path of the moving module (10) in real time to obtain the path image. The path image is transmitted to the edge computing gateway, and the path image data is converted to grayscale using a weighted average method to obtain a grayscale image. The grayscale image is denoised using a median filtering algorithm to obtain a first path image; The first path image is enhanced using histogram equalization to obtain the second path image. The second path image is sequentially processed through image segmentation and morphological processing to obtain the third path image. The number of pixels in the impurity region of the third path image is counted, and the area of ​​the impurity region is calculated using an image analysis algorithm. Calculate the impurity density using the following formula. : ， Wherein, the number of pixels The unit is "unit"; the area of ​​the impurity region The unit is square pixels; the impurity density The unit is pixels per square meter.

2. The internal welding control system according to claim 1, characterized in that, The guide module (30) includes two opposing movable guide mechanisms (301). The two movable guide mechanisms (301) are respectively arranged close to the two sides of the movable module (10), so that the two movable guide mechanisms (301) contact the two side walls inside the workpiece.

3. The internal welding control system according to claim 2, characterized in that, The control module controls the moving module (10), the cleaning module (20), the guiding module (30), the welding module (40), and the wire feeding module (50) respectively according to the welding control strategy to complete the welding process; The welding control strategy includes the following steps: S1. Select and set the welding process parameters according to the parameter information of the workpiece to be welded; S2. An image acquisition component is set on the moving module (10). The image acquisition component is used to acquire image data of the internal path of the workpiece in real time. The moving speed of the moving module (10) is selected according to the density of impurities on the internal path of the workpiece. S3. Guide the movement of the moving module (10) according to the guiding module (30); S4. Construct a weld identification model. The moving module (10) moves to the required welding location and dynamically adjusts the welding current and welding speed according to the weld type.

4. The internal welding control system according to claim 3, characterized in that, Step S1 specifically includes: The parameter information includes workpiece thickness and workpiece material type coefficient; The welding process parameters include the initial welding current and the initial welding speed; Obtain the workpiece thickness and workpiece material type coefficient And calculate the initial welding current of the workpiece. and initial welding speed : ， ， in, This represents the theoretical welding current value; Indicates the current adjustment coefficient; This represents the theoretical welding speed value; Indicates the overall influence coefficient of speed; This indicates the speed adjustment coefficient.

5. The internal welding control system according to claim 4, characterized in that, Step S1 further includes: The workpiece material type coefficient The value is selected based on the workpiece material type: If the workpiece material type is carbon steel, then the workpiece material type coefficient The value ranges from 1.0 to 1.3; If the workpiece material type is stainless steel, then the workpiece material type coefficient The value ranges from 1.4 to 1.7; If the workpiece material type is an alloy material, then the workpiece material type coefficient The value ranges from 1.8 to 2.

0.

6. The internal welding control system according to claim 3, characterized in that, Step S3 specifically includes: Pressure sensors are installed at the positions where the two moving guide mechanisms (301) contact the inner sidewall of the workpiece, and the pressure values ​​of the two moving guide mechanisms (301) are monitored in real time to obtain the real-time guide pressure value. and ; like = and = If the motion trajectory of the moving module (10) is normal, it will maintain its original motion state. like ≠ and / or ≠ If the motion trajectory of the mobile module (10) is abnormal, an alarm message is issued and a motion adjustment operation is performed. in, This indicates the preset minimum guide pressure. This indicates the maximum preset guide pressure.

7. The internal welding control system according to claim 5, characterized in that, Step S4 specifically includes: Acquire historical weld image data and corresponding weld type label data. The weld type labels in the weld type label data include butt welds, fillet welds, T-welds, lap welds, plug welds, and slot welds. The historical weld seam image data is subjected to grayscale processing, noise reduction processing, and image enhancement processing to obtain the processed first historical weld seam image data. The edge features, geometric features, and texture features of the first historical weld seam image data are extracted using the Canny algorithm and the gray-level co-occurrence matrix method to obtain the weld seam feature vector; A support vector machine is used, with the weld feature vector as input and the weld type label as output, to train and test the model on the historical weld image data and the weld type label data, so as to obtain the trained weld recognition model. The moving module (10) moves to the required welding location, the image acquisition component acquires the weld image of the required welding location, and inputs the weld image into the weld recognition model to identify the weld type of the required welding location. The welding current and the welding speed are adjusted according to the weld type.

8. The internal welding control system according to claim 7, characterized in that, Step S4 further includes: Select the welding adjustment coefficient according to the weld type. And according to the welding adjustment coefficient For the initial welding current and the initial welding speed Adjustments were made to obtain the adjusted actual welding current. and actual welding speed The adjustment method is as follows: ， ， If the weld type is a butt weld, then the welding adjustment coefficient The value ranges from 1.0 to 1.2; If the weld type is a fillet weld, then the welding adjustment coefficient The value ranges from 0.9 to 1.1; If the weld type is a T-weld, then the welding adjustment coefficient The value ranges from 1.2 to 1.4; If the weld type is a lap weld, then the welding adjustment coefficient The value ranges from 0.8 to 1.0; If the weld type is a plug weld, then the welding adjustment coefficient The value ranges from 1.3 to 1.5; If the weld type is a groove weld, then the welding adjustment coefficient The value ranges from 1.1 to 1.3.

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