An automatic production system for welding H-shaped steel in assembled steel structure houses

Abstract

The present invention discloses an automatic production system for welding H-shaped steel in assembled steel structure houses, which belongs to the technical field of H-shaped steel production, and includes: an automatic welding module, which automatically welds H-shaped steel according to a set initial moving speed; a data acquisition module, which is used to obtain image information of H-shaped steel before and after welding; an analysis and processing module, which is used to analyze and process the acquired image information to obtain a weld gap value, and generate an adjustment instruction according to the weld gap value; an adjustment module, which adjusts the moving speed of the automatic welding machine according to the adjustment instruction. The present invention can obtain the image information of the weld before welding, analyze and generate the weld gap value, and judge whether the moving speed of the automatic welding machine needs to be adjusted according to the size of the weld gap value, so that the speed of the automatic welding machine can be adjusted accordingly according to the size of the weld in each segmented contour and the thickness of the steel plate to ensure the welding quality is qualified.

Description

Technical Field

[0001] The invention belongs to the technical field of H-beam production, and in particular relates to an automatic production system for assembly and welding H-beams for assembled steel structure houses. Background Art

[0002] Prefabricated steel structure housing is a building system made of steel parts. It transfers the traditional construction method to the factory. The factory manufactures and processes the components, then transports them to the construction site and installs them through bolt connections. As prefabricated steel structure housing has significant advantages in improving building quality, saving labor, shortening construction period, improving earthquake resistance, flexible space layout, energy saving and environmental protection, it is becoming more and more widely used.

[0003] Prefabricated steel structure houses require a large number of H-shaped steels in production. During the production of existing H-shaped steels, the cut steel plates are generally set into an H shape, and then the corresponding automatic welding machines are moved at a specified speed for automatic welding. However, due to the differences between different steel plates during production, the weld gaps at the joints of the steel plates will also be different during welding. If welding is performed at a uniform welding speed, it is easy for the welding area to be over-welded or under-welded, thereby affecting the quality of welding. Summary of the invention

[0004] The purpose of the present invention is to provide an automatic production system for assembling and welding H-shaped steel for assembled steel structure houses, so as to solve the problems faced by the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An automatic production system for welding H-shaped steel for assembled steel structure housing, the system comprising:

[0007] An automatic welding module, wherein the automatic welding module drives the automatic welding machine to move according to a set initial moving speed to automatically weld the H-beam;

[0008] A data acquisition module, wherein the data acquisition module is used to obtain image information of the H-beam before and after welding;

[0009] An analysis and processing module, the analysis and processing module is used to analyze and process the acquired image information, thereby obtaining a weld gap value, and generating an adjustment instruction according to the weld gap value of the H-beam;

[0010] An adjustment module is used to adjust the moving speed of the automatic welding machine according to the generated adjustment instruction.

[0011] Furthermore, the method for the analysis and processing module to obtain the weld gap value is:

[0012] Collect the image of the H-beam weld before welding, and perform grayscale processing on it to obtain a grayscale image;

[0013] The edge detection algorithm is used to detect the edges in the image, and the binarization method is used to extract the contour of the weld;

[0014] According to the length of the H-beam, the extracted profile is equally divided into m segmented profiles, and the same initial moving speed v is set in each segmented profile;

[0015] Get the distance between the edges of each segmented contour , through the formula Find the weld gap value ,in is the standard weld distance corresponding to the initial moving speed v.

[0016] Furthermore, the method for generating the adjustment instruction is:

[0017] The weld gap value will be obtained The gap between the weld seam and the preset weld seam threshold For comparison:

[0018] when When , no adjustment instruction is generated, otherwise, an adjustment instruction is generated.

[0019] Furthermore, the adjustment instruction includes an increase instruction and a decrease instruction:

[0020] when When , an increase instruction is generated;

[0021] when When , a decrease instruction is generated.

[0022] Furthermore, the adjustment module performs adjustment in the following manner:

[0023] When the instruction is to increase, the formula is used within the segmented contour Adjust the moving speed of the automatic welding machine to ;

[0024] When it is a lowering instruction, the formula is used within the segmented contour Adjust the moving speed of the automatic welding machine to ;

[0025] in is the maximum speed that the system allows to adjust. is the conversion coefficient, L is the average thickness of the steel plate within the segmented profile, Standard steel plate thickness preset for the system.

[0026] Furthermore, the analysis and processing module is also used to rate the welding quality according to the change of the welding speed, and the rating method is as follows:

[0027] Get the number of times the welding speed changes during welding, and the speed change amount each time the speed changes ;

[0028] By formula Calculate the welding condition value K;

[0029] when When the quality is rated as level one;

[0030] when When the quality is rated as level 2;

[0031] when When the quality is rated as level 3;

[0032] Where K 1 and K 2 is the preset rating threshold.

[0033] Furthermore, the analysis and processing module is also used to analyze the image after welding, so as to determine whether welding abnormality occurs, and the determination method is:

[0034] Obtain the image information of each segmented contour after welding and compare it with the standard image information preset by the system:

[0035] If the similarity between the two is greater than 95%, the welding is normal, otherwise there is a welding defect;

[0036] The segmented contour information judged as welding defects is input into the model trained with the convolutional neural network to determine the type of welding defects.

[0037] Beneficial effects of the present invention:

[0038] The present invention can obtain the image information of the weld before welding, analyze and generate the weld gap value, and judge whether it is necessary to adjust the moving speed of the automatic welding machine according to the size of the weld gap value. In this way, the speed of the automatic welding machine can be adjusted accordingly according to the size of the weld in each segmented contour and the thickness of the steel plate to ensure the welding quality is qualified.

[0039] The present invention can also judge and grade the welding quality according to the number of times the welding speed changes during welding and the magnitude of the speed change each time the speed changes after welding, so as to facilitate the subsequent analysis and evaluation of the quality of the H-beam.

[0040] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0042] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] In one embodiment, Figure 1 As shown, an automatic production system for welding H-shaped steel for assembled steel structure residential buildings is disclosed, and the system comprises:

[0045] An automatic welding module, wherein the automatic welding module drives the automatic welding machine to move according to a set initial moving speed to automatically weld the H-beam;

[0046] A data acquisition module, wherein the data acquisition module is used to obtain image information of the H-beam before and after welding;

[0047] An analysis and processing module, the analysis and processing module is used to analyze and process the acquired image information, thereby obtaining a weld gap value, and generating an adjustment instruction according to the weld gap value of the H-beam;

[0048] An adjustment module is used to adjust the moving speed of the automatic welding machine according to the generated adjustment instruction.

[0049] Through the above technical solution, the present application obtains the image information of the weld before welding through the data acquisition module, and analyzes and processes the obtained image through the analysis and processing module to obtain the weld gap value, thereby adjusting the welding speed of the automatic welding machine accordingly according to the size of the weld gap value to ensure the welding quality of the H-beam. Through this method, the weld required for the H-beam can be divided into multiple small sections, and the welding speed of the welding machine can be adjusted according to the weld conditions in each small section, so that the welding speed can be adjusted in real time according to the size of the weld to ensure the quality of welding.

[0050] As an implementation of the present invention, the method for the analysis and processing module to obtain the weld gap value is:

[0051] Collect the image of the H-beam weld before welding, and perform grayscale processing on it to obtain a grayscale image;

[0052] The edge detection algorithm is used to detect the edges in the image, and the binarization method is used to extract the contour of the weld;

[0053] According to the length of the H-beam, the extracted profile is equally divided into m segmented profiles, and the same initial moving speed v is set in each segmented profile;

[0054] Get the distance between the edges of each segmented contour , through the formula Find the weld gap value ,in is the standard weld distance corresponding to the initial moving speed v.

[0055] Through the above technical scheme, this embodiment provides a specific method for obtaining the weld gap value. First, an image of the H-beam weld before welding is collected and grayscale processed to obtain a grayscale image. Then, an edge detection algorithm is used to detect the edge in the image, and a binarization method is used to extract the weld contour. Then, according to the length of the H-beam, the extracted contour is equidistantly divided into m segmented contours, each segmented contour corresponds to the actual weld position one by one, and each segmented contour is set with the same initial moving speed v. The initial moving speed v of the automatic welding machine can be set by the operator according to the historical welding data, and then the distance between the edges on both sides of each segmented contour is obtained. , that is, the size of the weld within each segment contour, and the distance between the two side edges The size can be determined based on the maximum distance within the segmented contour, thus using the formula Find the weld gap value ,in is the standard weld distance corresponding to the initial moving speed v. In this way, the obtained weld size is compared with the standard weld size corresponding to the initial moving speed to obtain the weld gap value for subsequent judgment.

[0056] As an implementation mode of the present invention, the method for generating the adjustment instruction is:

[0057] The weld gap value will be obtained The gap between the weld seam and the preset weld seam threshold For comparison:

[0058] when When , no adjustment instruction is generated, otherwise, an adjustment instruction is generated, and the adjustment instruction includes an increase instruction and a decrease instruction:

[0059] when When , an increase instruction is generated;

[0060] when When the lowering instruction is generated

[0061] The method of adjusting the module is: when adding instructions, the formula is used within the segmented contour Adjust the moving speed of the automatic welding machine to ;

[0062] When it is a lowering instruction, the formula is used within the segmented contour Adjust the moving speed of the automatic welding machine to ;

[0063] in is the maximum speed that the system allows to adjust. is the conversion coefficient, L is the average thickness of the steel plate within the segmented profile, Standard steel plate thickness preset for the system.

[0064] Through the above technical solution, this embodiment provides a specific method for adjusting the moving speed of the automatic welding machine according to the obtained weld gap value. First, the weld gap value is obtained. The gap between the weld seam and the preset weld seam threshold For comparison, When , it means that the difference between the weld size obtained at this time and the preset weld size is within the allowable error range, indicating that the weld is normal, and no adjustment instruction is generated. Otherwise, it means that the weld difference is too large, and an adjustment instruction is generated to adjust the moving speed of the automatic welding machine. The adjustment instruction includes an increase instruction and a decrease instruction. When , it means that the obtained weld size is smaller than the preset weld size. If welding is performed at the normal preset speed, too much heat will be input to the steel plate, causing welding abnormality. Therefore, in order to ensure normal welding, an increase instruction is generated at this time to speed up the welding speed of the automatic welding machine at this point to reduce heat input. The specific formula is Adjust the moving speed of the automatic welding machine to , it can be seen from the formula that when The larger the difference, that is, the narrower the weld, the faster the speed needs to be. Or when L is smaller, that is, the thinner the steel plate is, the faster the speed needs to be. The speed cannot be adjusted unlimitedly. Too much adjustment will also affect the quality and effect of welding. Therefore, a maximum speed allowed by the system is set. To restrict, finally through the formula Adjust the moving speed of the automatic welding machine in this area to . Similarly, when , it means that the obtained weld size is larger than the preset weld size. If welding is performed at the normal preset speed, some welds may not be welded completely. Therefore, in order to ensure normal welding, a reduction instruction is generated to reduce the welding speed of the automatic welding machine at this point. The specific formula is Adjust the moving speed of the automatic welding machine to , it can be seen from the formula that when The larger the value, the wider the weld, the more the speed needs to be reduced, or when the thickness of the steel plate is thicker, the more the speed needs to be reduced. Finally, through the formula Adjust the moving speed of the automatic welding machine to Through this solution, the speed of the automatic welding machine within each segmented contour can be adjusted accordingly according to the size of the weld within the segmented contour and the thickness of the steel plate to ensure the welding quality.

[0065] In the above technical solution, the weld gap threshold interval preset by the system is It can be set according to the allowable deviation value during actual welding. The mean thickness L of the steel plate within the segmented contour can be obtained according to the corresponding image processing algorithm. And the standard steel plate thickness preset by the system The maximum speed that the system allows to adjust can be obtained based on empirical data. It is formulated after comprehensive analysis of the relevant plate welding data in big data and the performance parameters of the welding machine, which will not be described in detail here.

[0066] As an embodiment of the present invention, the analysis and processing module is also used to rate the welding quality according to the speed change during welding, and the rating method is as follows:

[0067] Get the number of times the welding speed changes during welding, and the speed change amount each time the speed changes ;

[0068] By formula Calculate the welding condition value K;

[0069] when When the quality is rated as level one;

[0070] when When the quality is rated as level 2;

[0071] when When the quality is rated as level 3;

[0072] Where K 1 and K 2 is the preset rating threshold.

[0073] Through the above technical solution, this embodiment provides a specific method for rating welding quality. Since the moving speed of the automatic welding machine will not stop when it is moving and welding, each time the moving speed is adjusted, the change in speed is an adjustment process. If the adjustment process is long and long, it will also affect the welding quality. For example, when the weld is more uniform, the frequency of automatic welding machine speed adjustment is smaller, so that the automatic welding machine can weld at the specified speed, the quality of the welded H-beam will be better. If the speed needs to be changed more during welding, the overall welding quality will be worse. Therefore, this embodiment first obtains the number of times the welding speed changes during welding, n, and the speed change amount each time the speed changes , and then through the formula Calculate the welding condition value K. From the formula, we can see that when The smaller the value is, that is, the smaller the speed change is during the entire welding process, or the fewer times n the speed is adjusted during the welding process, the smaller the corresponding welding condition value K is, indicating that the welding quality is better. Therefore, the obtained welding condition value K is compared with the preset rating threshold K 1 , K 2 For comparison, the preset rating threshold can be obtained based on historical data. When When When the quality is good, it will be rated into three levels, among which the quality of level one is better than level two, and the quality of level two is better than level three. In this way, the welding quality is rated to facilitate the subsequent analysis and evaluation of the quality of H-beam.

[0074] As an embodiment of the present invention, the analysis and processing module is also used to analyze the image after welding, so as to determine whether welding abnormality occurs, and the determination method is:

[0075] Obtain the image information of each segmented contour after welding and compare it with the standard image information preset by the system:

[0076] If the similarity between the two is greater than 95%, the welding is normal, otherwise there is a welding defect;

[0077] The segmented contour information judged as welding defects is input into the model trained with the convolutional neural network to determine the type of welding defects.

[0078] Through the above technical scheme, this embodiment provides a specific method for the analysis and processing module to determine whether welding abnormalities occur after welding. First, the image information of each segmented contour after welding is obtained, and it is compared with the standard image information preset by the system: if the similarity between the two is greater than 95%, it means that the welding is normal, otherwise, a welding defect occurs, and the welding defect can be further judged to determine the type of defect. Specifically, the segmented contour information determined to be a welding defect is input into a model trained with a convolutional neural network. There are a large number of trained defect classification libraries in the model, which are compared and output to determine the type of welding defects. In this way, the operator can quickly understand what kind of defects appear in which position of the H-beam, so as to facilitate the subsequent timely repair and fine-tuning of the defective parts.

[0079] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An automatic production system for welding H-shaped steel for assembled steel structure houses. It is characterized in that The system comprises: An automatic welding module, wherein the automatic welding module drives the automatic welding machine to move according to a set initial moving speed to automatically weld the H-beam; A data acquisition module, wherein the data acquisition module is used to obtain image information of the H-beam before and after welding; An analysis and processing module, the analysis and processing module is used to analyze and process the acquired image information, thereby obtaining a weld gap value, and generating an adjustment instruction according to the weld gap value of the H-beam; An adjustment module, wherein the adjustment module adjusts the moving speed of the automatic welding machine according to the generated adjustment instruction; The method for the analysis and processing module to obtain the weld gap value is: Collect the image of the H-beam weld before welding, and perform grayscale processing on it to obtain a grayscale image; The edge detection algorithm is used to detect the edges in the image, and the binarization method is used to extract the contour of the weld; According to the length of the H-beam, the extracted profile is equally divided into m segmented profiles, and the same initial moving speed v is set in each segmented profile; Get the distance between the edges of each segmented contour , through the formula Find the weld gap value ,in is the standard weld distance corresponding to the initial moving speed v; The weld gap value will be obtained The gap between the weld seam and the preset weld seam threshold For comparison: when When , no adjustment instruction is generated, otherwise, an adjustment instruction is generated; The adjustment instructions include increase instructions and decrease instructions: when When , an increase instruction is generated; when When , a lowering instruction is generated; The method for the adjustment module to perform adjustment is: When the instruction is to increase, the formula is used within the segmented contour Adjust the moving speed of the automatic welding machine to ; When the instruction is to be lowered, the formula Adjust the moving speed of the automatic welding machine to ; in is the maximum speed that the system allows to adjust, is the conversion coefficient, L is the average thickness of the steel plate within the segmented profile, Standard steel plate thickness preset for the system; The analysis and processing module is also used to rate the welding quality according to the change of the welding speed, and the rating method is as follows: Get the number of times the welding speed changes during welding, and the speed change amount each time the speed changes ; By formula Calculate the welding condition value K; when When the quality is rated as level one; when When the quality is rated as level 2; when When the quality is rated as level 3; in as well as is the preset rating threshold.

2. According to claim 1, an automatic production system for welding H-beams for assembled steel structure houses, It is characterized in that The analysis and processing module is also used to analyze the image after welding, so as to determine whether welding abnormality occurs, and the determination method is: Obtain the image information of each segmented contour after welding and compare it with the standard image information preset by the system: If the similarity between the two is greater than 95%, the welding is normal, otherwise there is a welding defect; The segmented contour information judged as welding defects is input into the model trained with the convolutional neural network to determine the type of welding defects.

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