Intelligent production line material distribution method based on welding digitization

Abstract

The invention discloses an intelligent production line material distribution method based on welding digitization, and relates to the field of material distribution, and the method comprises the steps: collecting topographic data in a workshop through a laser radar technology, generating point cloud data, drawing a workshop state model, and scanning a tool vehicle after material sorting is completed to generate a beat code; a material delivery priority model is constructed based on the beat code, a material delivery priority is obtained in combination with a workshop state model, and a delivery transfer vehicle delivery path is generated by using an optimal scheduling algorithm; identifying the state information of the material storage rack by using an image processing technology, analyzing the driving state of the distribution transfer trolley according to the state information, and generating an angle height adjustment instruction of the distribution transfer trolley based on the driving state; and the distribution transfer trolley executes material distribution operation according to the distribution transfer trolley distribution path, and the operation state of the distribution transfer trolley is adjusted through the angle and height adjusting instruction. The state of the material storage rack can be detected, and an accurate unloading target position is provided for the distribution transfer trolley.

Description

Technical Field

[0001] The present invention relates to the field of material distribution, and in particular to a material distribution method based on a welding digital intelligent production line. Background Art

[0002] Material distribution is one of the key links in manufacturing and supply chain management. It refers to the process of transporting materials from storage locations (such as production lines or assembly areas) to designated usage locations (such as warehouses or storage racks) according to production needs. Material distribution is an important part of smart manufacturing and flexible production. By integrating advanced technologies (such as AGV, path optimization algorithms, the Internet of Things, etc.), it can significantly improve efficiency, reduce costs and enhance system adaptability.

[0003] With the transformation of manufacturing industry towards intelligence, traditional material distribution methods have gradually exposed problems such as low efficiency, high waste of resources and slow response speed. Optimizing the material distribution process through intelligent means can cope with these challenges and achieve improvements in production efficiency and quality. The necessity of intelligence in the material distribution process is mainly reflected in improving efficiency, reducing costs, enhancing flexibility and the ability to adapt to industrial needs.

[0004] However, the material distribution method in the prior art cannot adaptively generate the optimal distribution path for the transport vehicle according to the status of the storage location during the distribution process, which may increase the distribution time and energy consumption. At the same time, it is unable to analyze the status of the designated location in real time and adjust the status of the transport vehicle accordingly, thereby reducing the distribution efficiency. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a material distribution method based on a welding digital intelligent production line to achieve the purpose of reducing distribution time and energy consumption.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] The present invention provides a material distribution method based on a welding digital intelligent production line, and the intelligent production line material distribution method includes:

[0008] S1. Use laser radar technology to collect terrain data in the workshop, generate point cloud data to draw the workshop status model, and scan the tooling vehicle after material picking to generate beat code;

[0009] S2. Build a material distribution priority model based on the beat code, combine it with the workshop status model to obtain the material distribution priority, and use the optimization scheduling algorithm to generate the distribution path of the distribution transfer vehicle;

[0010] S3. Using image processing technology to identify the status information of the material storage rack, analyzing the driving status of the delivery transfer vehicle according to the status information, and generating an angle height adjustment instruction for the delivery transfer vehicle based on the driving status;

[0011] S4. The delivery transfer vehicle performs material delivery operations according to the delivery route of the delivery transfer vehicle, and when delivering to the material storage rack, uses the angle height adjustment command to adjust the running state of the delivery transfer vehicle to unload the materials to the material storage rack.

[0012] Preferably, building a material distribution priority model based on the beat code, obtaining the material distribution priority in combination with the workshop status model, and using the optimization scheduling algorithm to generate the distribution path of the distribution transfer vehicle include:

[0013] S21. Obtain the original distribution task of the material, extract the hierarchical demand index from the obtained original demand information, and construct a field information architecture table according to the hierarchical demand index and the beat code. The field information architecture table includes the planned delivery date, the delivery vehicle type and the beat code;

[0014] S22, performing an initial priority sorting of the beat codes according to the planned delivery date, building a material delivery priority model using the planned delivery date, and obtaining the importance sorting weight of the field information;

[0015] S23, combining the initial priority ranking with the importance ranking weight to obtain the material distribution priority, obtaining the distribution transfer vehicle location information and introducing it into the workshop status model, and generating the distribution path in combination with the material distribution priority;

[0016] S24. Optimize the delivery path based on the optimization scheduling algorithm and the optimization objective function, and select the optimal delivery method as the delivery path of the delivery transfer vehicle according to the optimization result.

[0017] Preferably, the beat codes are initially prioritized according to the planned delivery date, and a material delivery priority model is constructed using the planned delivery date. Obtaining the importance ranking weight of the field information includes:

[0018] S221, calculating the time interval between the current time and the planned delivery date, obtaining the urgency weight of the time interval, analyzing the beat weight of the beat code, and outputting the initial sorting result by combining the urgency weight and the beat weight;

[0019] S222. Based on the initial sorting result and the hierarchical structure of the analytic hierarchy process, a material distribution priority model is obtained to obtain the importance sorting weight of the field information.

[0020] Preferably, based on the initial sorting results and the hierarchical structure of the analytic hierarchy process, a material distribution priority model is obtained, and the importance sorting weights of the field information are obtained, including:

[0021] S2221. Establish a target layer, a criterion layer, and an indicator layer from top to bottom according to the structure of the field information structure table, and fill the planned delivery date, the beat code, and the initial sorting result into the target layer, the criterion layer, and the indicator layer respectively;

[0022] S2222, respectively compare the demand indicators in the criterion layer and the indicator layer with the demand indicators in the corresponding upper layer, obtain the importance comparison elements of each layer, and construct the judgment matrix of each layer using the importance comparison elements;

[0023] S2223. Scale and assign values ​​to the field information in the judgment matrix, and normalize the judgment matrices at each layer based on the assignment results to obtain ranking weight results of the relative importance of the field information.

[0024] Preferably, combining the initial priority sorting with the importance sorting weight to obtain the material distribution priority, obtaining the distribution transfer vehicle location information and introducing it into the workshop status model, and generating the distribution path in combination with the material distribution priority includes:

[0025] S231, calculating the comprehensive priority of each group of beat codes by using the initial ranking of comprehensive priorities and the weight of importance ranking, and ranking the comprehensive priorities in order to obtain the material distribution priority result;

[0026] S232. Based on the material distribution priority result, use wireless positioning technology to obtain the current position and operating status of the corresponding distribution vehicle model, and update the position and operating status to the workshop status model;

[0027] S233. Use the workshop status model to dynamically generate path points for the delivery transfer vehicle from the current position to the tooling vehicle and the material storage rack, and connect the path points to form a delivery path for the delivery transfer vehicle.

[0028] Preferably, using image processing technology to identify the status information of the material storage rack, analyzing the driving status of the delivery transfer vehicle according to the status information, and generating an angle height adjustment instruction of the delivery transfer vehicle based on the driving status includes:

[0029] S31. Using an industrial camera to collect images of material storage racks in real time, and performing denoising and binarization processing on the images of the material storage racks;

[0030] S32, performing morphological processing on the material storage rack image, and combining it with a descent optimization algorithm to obtain a curve of the material storage rack, and comparing the difference between the material storage rack curve and the standard curve;

[0031] S33. Analyze the status information of the material storage rack based on the difference results, analyze the placement position of the material according to the status information, analyze the driving status of the delivery transfer vehicle, and generate an angle height adjustment instruction for the delivery transfer vehicle based on the driving status.

[0032] Preferably, the material storage rack image is subjected to morphological processing, and a descent optimization algorithm is used to obtain a curve of the material storage rack, and the difference between the material storage rack curve and the standard curve is compared, including:

[0033] S321. After dilation and corrosion processing is performed on the material storage rack image based on morphological operation technology, edge point coordinates are extracted, and equidistant sampling technology is used to perform redundant processing on the edge point coordinates;

[0034] S322, initializing the curve shape of the material storage rack based on the edge point coordinates and polynomial fitting technology, and performing error optimization processing on the curve shape, and obtaining the optimal curve according to the processing result to obtain the contour curve of the material storage rack;

[0035] S323, obtaining the slope of the curve where the left and right end points of the contour curve are located, and analyzing the difference between the material storage rack contour curve and the standard curve based on the slope result.

[0036] Preferably, obtaining the slope of the curve where the left and right end points of the contour curve are located, and analyzing the difference between the material storage rack contour curve and the standard curve based on the slope result includes:

[0037] S3231. Analyze the slope of the curve where the left and right end points of the contour curve are located, and use similarity analysis technology to calculate the similarity between the material storage rack contour curve and the standard curve;

[0038] S3232. Analyze the characteristic function of the material storage rack contour curve based on the similarity and the set threshold value, and analyze the difference between the material storage rack contour curve and the standard curve based on the characteristic function value.

[0039] Preferably, the calculation formula for the similarity is:

[0040]

[0041] In the formula, S(a,b) represents the similarity between the material storage rack profile curve point a and the standard curve point b, k represents the slope, p a The contour vector representing the contour curve point a of the material storage rack, p b represents the contour vector of the standard curve point b, and x represents the xth item in the material storage rack contour curve set.

[0042] Preferably, the expression of the characteristic function is:

[0043]

[0044] In the formula, T(a,b) represents the characteristic function of the material storage rack contour curve point a and the standard curve point b, S(a,b) represents the similarity between the material storage rack contour curve point a and the standard curve point b, and scon It represents the vector similarity between the contour vector of the material storage rack contour curve point a and the contour vector of the standard curve point b, α represents the weight of the similarity, and β represents the weight of the vector similarity.

[0045] The beneficial effects of the present invention are:

[0046] 1. The present invention uses laser radar to collect point cloud data, which can highly accurately reflect the terrain, layout and obstacle locations of the workshop, providing a reliable data basis for subsequent path planning. At the same time, the priority model is constructed through the beat code and combined with the optimization scheduling algorithm to generate the optimal distribution path while considering the priority, thereby reducing the distribution time and energy consumption. The image processing technology is used to identify the status information of the material storage rack, and the driving status of the distribution transfer vehicle is analyzed according to the status information to generate the angle height adjustment instructions of the distribution transfer vehicle. The status of the material storage rack (such as empty space, material stacking status) can be detected to provide the distribution transfer vehicle with an accurate unloading target location.

[0047] 2. The present invention constructs a material distribution priority model based on the beat code and generates an optimized distribution path to convert the complex original distribution task into a hierarchical demand indicator. At the same time, the planned delivery date is used to initially sort the beat code to ensure that time-critical materials are processed first, and the material distribution priority is combined with the workshop status model to ensure that the path planning can take into account the urgency of the distribution task and the actual situation of the workshop. Finally, the optimized scheduling algorithm is used to globally optimize the path to ensure the lowest cost distribution plan, reduce the driving time and energy consumption of the distribution transfer vehicle, and improve overall efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0049] Figure 1 It is a flow chart of a material distribution method based on a welding digital intelligent production line according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0051] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0052] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0054] See also Figure 1 The present invention provides a material distribution method based on a welding digital intelligent production line, and the intelligent production line material distribution method includes:

[0055] S1. Use LiDAR technology to collect terrain data in the workshop, generate point cloud data to draw the workshop status model, and scan the tooling vehicle after material picking to generate beat code.

[0056] In this embodiment, when using laser radar technology to collect terrain data in the workshop, generate point cloud data to draw a workshop status model, and scan the tooling vehicle after material picking to generate a beat code, you can choose a laser radar device suitable for the workshop environment, such as a 2D or 3D laser radar, determine the installation position of the laser radar to ensure that it can cover the entire workshop area, set the scanning range of the laser radar to ensure that it can cover all key areas of the workshop, set the frequency of data collection, and adjust it according to the needs of dynamic changes in the workshop. The collected point cloud data is stored in a local or cloud server, and the point cloud data is removed. Noise points, improve data quality, use filtering algorithms (such as voxel filtering, statistical filtering, etc.) to filter the point cloud data; separate the ground point cloud data from the non-ground point cloud data to facilitate subsequent obstacle detection and path planning, segment different objects in the point cloud data (such as equipment, tooling vehicles, material storage racks, etc.), use the point cloud data to generate a three-dimensional model of the workshop, including equipment layout, obstacle location, etc., optimize the generated three-dimensional model to ensure the accuracy and practicality of the model; convert the processed point cloud data into a workshop status model, including the physical layout and dynamic changes of the workshop.

[0057] It needs to be explained that, in specific applications, distribution documents can be prepared according to the existing rhythmic production method of the workstation system and the list of materials divided out in each project. The distribution documents include: station name, material code, material Chinese name, quantity, distribution method, form of transport tooling, material picture, and material placement method. Based on this, the materials required for each production station, the model of the tooling vehicle (material handling vehicle) for distributing materials at each station, and the material placement method of each tooling vehicle are confirmed, and the prepared distribution documents are imported into the distribution system; planners formulate production plans on the distribution system. The production plans include: project name, planned production date, rhythm, vehicle model, and the distribution system automatically generates distribution tasks based on the project, rhythm, vehicle model and other fields in the production plan and the background tooling information. When there are spare distribution tooling, the system automatically generates picking tasks based on the distribution tasks and pushes them to the sorting personnel.

[0058] The sorting personnel determine the delivery tooling according to the picking task and pick according to the platform material list, correctly place the materials on the tooling pad of the customized tooling vehicle, ensure that the type and quantity, placement and direction of the placed materials meet the requirements of the logistics list, and scan the tooling vehicle and materials after the picking is completed to bind them together and finally generate the beat code; the workshop will call the required tooling according to the production situation. After receiving the call task, the material handling vehicle will transport the full tooling with the specified tooling frame code to the full material rack at the access port of the bogie workshop to complete the delivery; when the workshop has empty tooling that needs to be taken back to the warehouse, the workshop clicks the empty frame button through the system to issue an instruction to generate an empty frame task. After receiving the task instruction, the material handling vehicle automatically retrieves the empty frame at the empty frame placement position in the workshop and transports it to the designated location in the warehouse.

[0059] At the same time, when the system automatically generates a task code label according to the list content, the task code label is a unique identifier, and the task code is associated with the tool vehicle type. Therefore, the sorting task directly generates the tool vehicle type, which is convenient for the sorting personnel to quickly identify and sort, determine the material list, and correspond the material list of each station to the tool vehicle type. A material list card is attached to each tool vehicle, and the three-dimensional view of the material tooling, the material picture, and the material quantity are marked on the card to facilitate the sorting personnel to sort and avoid material placement errors; at the same time, the materials are placed according to the workpiece placement diagram to facilitate the workshop production personnel to take the materials and improve the workshop operation efficiency. When using a handheld terminal to bind the tool vehicle to the material, the system has an automatic judgment function. If the material is placed in the wrong place or the tool vehicle is taken by the wrong place, there will be an error prompt, and the binding function can trace the distribution of materials and the use of the tool vehicle.

[0060] The workshop issues tasks to generate delivery tasks, and the material handling vehicle carries out delivery upon receiving the tasks. The delivery time is reasonably allocated, and materials are delivered on demand to avoid material congestion in the workshop. The transportation of materials by automated transfer devices effectively reduces the workload of delivery personnel. The entire transportation route adopts mixed traffic of people and vehicles, and the safety factor of delivery operations is improved by stopping obstacles. The overall transportation and sorting materials are large pieces with a high weight, which can be successfully transported and delivered unmanned, laying the foundation for improving the level of automated logistics distribution.

[0061] Furthermore, the material distribution purpose of the welding digital intelligent production line with the lean management and lean production line concepts can be realized. When picking materials in the warehouse, the material requirements of the production stations are subdivided, and the materials required for each station are placed on the material handling vehicle, which supplies them accurately according to the beat, and the tooling vehicle is delivered to the production workshop. This is truly unmanned distribution, which is convenient for workshop production operations, reduces material anomalies in the production process, and improves production efficiency. Information technology is used throughout the process to effectively control every process of material picking and every state of the tooling vehicle.

[0062] S2. Build a material distribution priority model based on the beat code, combine it with the workshop status model to obtain the material distribution priority, and use the optimization scheduling algorithm to generate the distribution path of the distribution transfer vehicle.

[0063] In this embodiment, a material distribution priority model is constructed based on the beat code, the material distribution priority is obtained in combination with the workshop status model, and the distribution path of the distribution transfer vehicle is generated by using the optimization scheduling algorithm, including:

[0064] S21. Obtain the original distribution task of the material, extract the hierarchical demand index from the obtained original demand information, and construct a field information architecture table according to the hierarchical demand index and the beat code. The field information architecture table includes the planned delivery date, the delivery vehicle type and the beat code;

[0065] S22, performing an initial priority sorting of the beat codes according to the planned delivery date, building a material delivery priority model using the planned delivery date, and obtaining the importance sorting weight of the field information;

[0066] S23, combining the initial priority ranking with the importance ranking weight to obtain the material distribution priority, obtaining the distribution transfer vehicle location information and introducing it into the workshop status model, and generating the distribution path in combination with the material distribution priority;

[0067] S24. Optimize the delivery path based on the optimization scheduling algorithm and the optimization objective function, and select the optimal delivery method as the delivery path of the delivery transfer vehicle according to the optimization result.

[0068] Specifically, the beat codes are initially prioritized according to the planned delivery date, and the material delivery priority model is constructed using the planned delivery date. The importance ranking weights of the field information are obtained, including:

[0069] S221, calculating the time interval between the current time and the planned delivery date, obtaining the urgency weight of the time interval, analyzing the beat weight of the beat code, and outputting the initial sorting result by combining the urgency weight and the beat weight;

[0070] S222. Based on the initial sorting result and the hierarchical structure of the analytic hierarchy process, a material distribution priority model is obtained to obtain the importance sorting weight of the field information.

[0071] Among them, based on the initial sorting results and the hierarchical structure of the hierarchical analysis technology, the material distribution priority model is obtained, and the importance sorting weights of the field information are obtained, including:

[0072] S2221. Establish a target layer, a criterion layer, and an indicator layer from top to bottom according to the structure of the field information structure table, and fill the planned delivery date, the beat code, and the initial sorting result into the target layer, the criterion layer, and the indicator layer respectively;

[0073] S2222, respectively compare the demand indicators in the criterion layer and the indicator layer with the demand indicators in the corresponding upper layer, obtain the importance comparison elements of each layer, and construct the judgment matrix of each layer using the importance comparison elements;

[0074] S2223. Scale and assign values ​​to the field information in the judgment matrix, and normalize the judgment matrices at each layer based on the assignment results to obtain ranking weight results of the relative importance of the field information.

[0075] Specifically, the initial priority ranking is combined with the importance ranking weight to obtain the material distribution priority, the distribution transfer vehicle location information is obtained and introduced into the workshop status model, and the distribution path is generated in combination with the material distribution priority, including:

[0076] S231, calculating the comprehensive priority of each group of beat codes by using the initial ranking of comprehensive priorities and the weight of importance ranking, and ranking the comprehensive priorities in order to obtain the material distribution priority result;

[0077] S232. Based on the material distribution priority result, use wireless positioning technology to obtain the current position and operating status of the corresponding distribution vehicle model, and update the position and operating status to the workshop status model;

[0078] S233. Use the workshop status model to dynamically generate path points for the delivery transfer vehicle from the current position to the tooling vehicle and the material storage rack, and connect the path points to form a delivery path for the delivery transfer vehicle.

[0079] Specifically, the distribution path is optimized based on the optimization scheduling algorithm and the optimization objective function, and the optimal distribution method is selected as the distribution path of the distribution transfer vehicle according to the optimization results, including:

[0080] S241, generating location information of the pickup points and placement points of the delivery transfer vehicle based on the delivery path, generating a corresponding point matrix, using the point matrix to generate an initial population, and calling the delivery path a chromosome;

[0081] S242, using the optimization scheduling algorithm to perform crossover and mutation operations on the initial population and chromosomes, and compare the optimal chromosome of the current population with the optimal chromosome of the previous populations, and retain the optimal chromosome as the final population;

[0082] S243. The minimum transfer path distance is used as the optimization objective function and combined with the final population to model and generate a path optimization function with priority. The optimal point matrix is ​​obtained based on the output of the path optimization function to obtain the path points, and the path points are connected to obtain the delivery path of the delivery transfer vehicle.

[0083] Therefore, building a material distribution priority model based on the beat code and generating an optimized distribution path converts the complex original distribution task into a hierarchical demand indicator, which can ensure that time-critical materials are processed first. Combining the material distribution priority with the workshop status model ensures that the path planning can take into account the urgency of the distribution task and the actual situation of the workshop. Finally, the optimization scheduling algorithm is used to globally optimize the path to ensure the lowest cost distribution plan, reduce the driving time and energy consumption of the distribution transfer vehicle, and improve overall efficiency.

[0084] S3. Use image processing technology to identify the status information of the material storage rack, analyze the driving status of the distribution transfer vehicle according to the status information, and generate angle height adjustment instructions for the distribution transfer vehicle based on the driving status.

[0085] In this embodiment, the state information of the material storage rack is identified by using image processing technology, the driving state of the delivery transfer vehicle is analyzed according to the state information, and the angle height adjustment instruction of the delivery transfer vehicle is generated based on the driving state, including:

[0086] S31. Using an industrial camera to collect images of material storage racks in real time, and performing denoising and binarization processing on the images of the material storage racks;

[0087] S32, performing morphological processing on the material storage rack image, and combining it with a descent optimization algorithm to obtain a curve of the material storage rack, and comparing the difference between the material storage rack curve and the standard curve;

[0088] S33. Analyze the status information of the material storage rack based on the difference results, analyze the placement position of the material according to the status information, analyze the driving status of the delivery transfer vehicle, and generate an angle height adjustment instruction for the delivery transfer vehicle based on the driving status.

[0089] Specifically, the material storage rack image is morphologically processed, and the material storage rack curve is obtained by combining the descent optimization algorithm, and the difference between the material storage rack curve and the standard curve is compared, including:

[0090] S321. After dilation and corrosion processing is performed on the material storage rack image based on morphological operation technology, edge point coordinates are extracted, and equidistant sampling technology is used to perform redundant processing on the edge point coordinates;

[0091] S322, initializing the curve shape of the material storage rack based on the edge point coordinates and polynomial fitting technology, and performing error optimization processing on the curve shape, and obtaining the optimal curve according to the processing result to obtain the contour curve of the material storage rack;

[0092] S323, obtaining the slope of the curve where the left and right end points of the contour curve are located, and analyzing the difference between the material storage rack contour curve and the standard curve based on the slope result.

[0093] Specifically, the slope of the curve where the left and right end points of the contour curve are located is obtained, and the difference between the material storage rack contour curve and the standard curve is analyzed based on the slope result, including:

[0094] S3231. Analyze the slope of the curve where the left and right end points of the contour curve are located, and use similarity analysis technology to calculate the similarity between the material storage rack contour curve and the standard curve;

[0095] S3232. Analyze the characteristic function of the material storage rack contour curve based on the similarity and the set threshold value, and analyze the difference between the material storage rack contour curve and the standard curve based on the characteristic function value.

[0096] The calculation formula for similarity is:

[0097]

[0098] In the formula, S(a,b) represents the similarity between the material storage rack profile curve point a and the standard curve point b, k represents the slope, p a The contour vector representing the contour curve point a of the material storage rack, p b represents the contour vector of the standard curve point b, and x represents the xth item in the material storage rack contour curve set.

[0099] The expression of the characteristic function is:

[0100]

[0101] In the formula, T(a,b) represents the characteristic function of the material storage rack contour curve point a and the standard curve point b, S(a,b) represents the similarity between the material storage rack contour curve point a and the standard curve point b, and s con It represents the degree of vector similarity between the contour vector of the material storage rack contour curve point a and the contour vector of the standard curve point b, α represents the weight of the similarity, and β represents the weight of the vector similarity.

[0102] Among them, analyzing the status information of the material storage rack based on the difference result, analyzing the placement position of the material according to the status information, analyzing the driving status of the distribution transfer vehicle, and generating the angle height adjustment instruction of the distribution transfer vehicle based on the driving status include:

[0103] S331, analyzing the status information of the material storage rack based on the difference result, analyzing the placement position of the material according to the status information, and predicting the head direction of the delivery transfer vehicle by using the placement position and the delivery path of the delivery transfer vehicle;

[0104] S332. Analyze the front angle adjustment requirements of the delivery transfer vehicle according to the vehicle front direction, and analyze the height adjustment requirements of the delivery transfer vehicle based on the placement position and the height information of the delivery transfer vehicle, and generate angle height adjustment instructions for the delivery transfer vehicle in combination with the front angle adjustment requirements.

[0105] S4. The delivery transfer vehicle performs material delivery operations according to the delivery route of the delivery transfer vehicle, and when delivering to the material storage rack, uses the angle height adjustment command to adjust the running state of the delivery transfer vehicle to unload the materials to the material storage rack.

[0106] In summary, with the help of the above technical scheme of the present invention, the present invention uses laser radar to collect point cloud data to highly accurately reflect the terrain, layout and obstacle location of the workshop, and provides a reliable data basis for subsequent path planning. At the same time, the priority model is constructed by the beat code and combined with the optimization scheduling algorithm to generate the optimal distribution path while considering the priority, reducing the distribution time and energy consumption, and using image processing technology to identify the status information of the material storage rack, and analyze the driving state of the distribution transfer vehicle according to the status information to generate the angle height adjustment instruction of the distribution transfer vehicle, which can detect the state of the material storage rack (such as empty space, material stacking situation), and provide the distribution transfer vehicle with an accurate unloading target position. The present invention constructs a material distribution priority model based on the beat code and generates an optimized distribution path to convert the complex original distribution task into a hierarchical demand indicator, and at the same time uses the planned distribution date to perform initial sorting of the beat code to ensure that time-critical materials are processed first, and the material distribution priority is combined with the workshop status model to ensure that the path planning can take into account the urgency of the distribution task and the actual situation of the workshop, and finally uses the optimization scheduling algorithm to globally optimize the path to ensure the lowest cost distribution plan, reduce the driving time and energy consumption of the distribution transfer vehicle, and improve the overall efficiency.

[0107] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0108] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A material distribution method based on welding digital intelligent production line, characterized in that: The intelligent production line material distribution method includes: S1. Use laser radar technology to collect terrain data in the workshop, generate point cloud data to draw the workshop status model, and scan the tooling vehicle after material picking to generate beat code; S2. Build a material distribution priority model based on the beat code, combine it with the workshop status model to obtain the material distribution priority, and use the optimization scheduling algorithm to generate the distribution path of the distribution transfer vehicle; S3, using image processing technology to identify the status information of the material storage rack, analyzing the driving status of the delivery transfer vehicle according to the status information, and generating an angle height adjustment instruction for the delivery transfer vehicle based on the driving status; S4. The delivery transfer vehicle performs material delivery operations according to the delivery route of the delivery transfer vehicle, and when delivering to the material storage rack, uses the angle height adjustment command to adjust the running state of the delivery transfer vehicle to unload the materials to the material storage rack.

2. A material distribution method based on welding digital intelligent production line according to claim 1, characterized in that: The material distribution priority model is constructed based on the beat code, the material distribution priority is obtained in combination with the workshop status model, and the distribution path of the distribution transfer vehicle is generated by using the optimization scheduling algorithm, including: S21, obtaining the original distribution task of the material, extracting the hierarchical demand index from the obtained original demand information, and constructing a field information architecture table according to the hierarchical demand index and the beat code, wherein the field information architecture table includes the planned distribution date, distribution vehicle type and beat code; S22, performing an initial priority sorting of the beat codes according to the planned delivery date, building a material delivery priority model using the planned delivery date, and obtaining the importance sorting weight of the field information; S23, combining the initial priority ranking with the importance ranking weight to obtain the material distribution priority, obtaining the distribution transfer vehicle location information and introducing it into the workshop status model, and generating the distribution path in combination with the material distribution priority; S24. Optimize the delivery path based on the optimization scheduling algorithm and the optimization objective function, and select the optimal delivery method as the delivery path of the delivery transfer vehicle according to the optimization result.

3. A material distribution method based on welding digital intelligent production line according to claim 2, characterized in that: The initial priority sorting of the beat codes according to the planned delivery date, building a material delivery priority model using the planned delivery date, and obtaining the importance sorting weight of the field information include: S221, calculating the time interval between the current time and the planned delivery date, obtaining the urgency weight of the time interval, analyzing the beat weight of the beat code, and outputting the initial sorting result by combining the urgency weight and the beat weight; S222. Based on the initial sorting result and the hierarchical structure of the analytic hierarchy process, a material distribution priority model is obtained to obtain the importance sorting weight of the field information.

4. A material distribution method based on welding digital intelligent production line according to claim 3, characterized in that: Based on the initial sorting results and the hierarchical structure of the analytic hierarchy process, the material distribution priority model is obtained, and the importance sorting weights of the field information are obtained, including: S2221. Establish a target layer, a criterion layer, and an indicator layer from top to bottom according to the structure of the field information structure table, and fill the planned delivery date, the beat code, and the initial sorting result into the target layer, the criterion layer, and the indicator layer respectively; S2222, respectively compare the demand indicators in the criterion layer and the indicator layer with the demand indicators in the corresponding upper layer, obtain the importance comparison elements of each layer, and construct the judgment matrix of each layer using the importance comparison elements; S2223. Scale and assign values ​​to the field information in the judgment matrix, and normalize the judgment matrices at each layer based on the assignment results to obtain ranking weight results of the relative importance of the field information.

5. A material distribution method based on welding digital intelligent production line according to claim 4, characterized in that: The method of combining the initial priority sorting with the importance sorting weight to obtain the material distribution priority, obtaining the distribution transfer vehicle location information and introducing it into the workshop status model, and generating the distribution path in combination with the material distribution priority includes: S231, calculating the comprehensive priority of each group of beat codes by using the initial ranking of comprehensive priorities and the weight of importance ranking, and ranking the comprehensive priorities in order to obtain the material distribution priority result; S232. Based on the material distribution priority result, use wireless positioning technology to obtain the current position and operating status of the corresponding distribution vehicle model, and update the position and operating status to the workshop status model; S233. Use the workshop status model to dynamically generate path points for the delivery transfer vehicle from the current position to the tooling vehicle and the material storage rack, and connect the path points to form a delivery path for the delivery transfer vehicle.

6. The material distribution method based on welding digital intelligent production line according to claim 1 is characterized in that: The method of using image processing technology to identify the status information of the material storage rack, analyzing the driving status of the delivery transfer vehicle according to the status information, and generating an angle height adjustment instruction for the delivery transfer vehicle based on the driving status includes: S31. Using an industrial camera to collect images of material storage racks in real time, and performing denoising and binarization processing on the images of the material storage racks; S32, performing morphological processing on the material storage rack image, and combining it with a descent optimization algorithm to obtain a curve of the material storage rack, and comparing the difference between the material storage rack curve and the standard curve; S33. Analyze the status information of the material storage rack based on the difference results, analyze the placement position of the material according to the status information, analyze the driving status of the delivery transfer vehicle, and generate an angle height adjustment instruction for the delivery transfer vehicle based on the driving status.

7. A material distribution method based on welding digital intelligent production line according to claim 6, characterized in that: The morphological processing of the material storage rack image and the processing combined with the descent optimization algorithm to obtain the curve of the material storage rack and compare the difference between the material storage rack curve and the standard curve include: S321. After dilation and corrosion processing is performed on the material storage rack image based on morphological operation technology, edge point coordinates are extracted, and equidistant sampling technology is used to perform redundant processing on the edge point coordinates; S322, initializing the curve shape of the material storage rack based on the edge point coordinates and polynomial fitting technology, and performing error optimization processing on the curve shape, and obtaining the optimal curve according to the processing result to obtain the contour curve of the material storage rack; S323, obtaining the slope of the curve where the left and right end points of the contour curve are located, and analyzing the difference between the material storage rack contour curve and the standard curve based on the slope result.

8. The material distribution method based on welding digital intelligent production line according to claim 7 is characterized in that: The step of obtaining the slope of the curve at the left and right end points of the contour curve and analyzing the difference between the material storage rack contour curve and the standard curve based on the slope result includes: S3231. Analyze the slope of the curve where the left and right end points of the contour curve are located, and use similarity analysis technology to calculate the similarity between the material storage rack contour curve and the standard curve; S3232. Analyze the characteristic function of the material storage rack contour curve based on the similarity and the set threshold value, and analyze the difference between the material storage rack contour curve and the standard curve based on the characteristic function value.

9. A material distribution method based on welding digital intelligent production line according to claim 8, characterized in that: The calculation formula of the similarity is: In the formula, S(a,b) represents the similarity between the material storage rack profile curve point a and the standard curve point b, k represents the slope, p a The contour vector representing the contour curve point a of the material storage rack, p b represents the contour vector of the standard curve point b, and x represents the xth item in the material storage rack contour curve set.

10. A material distribution method based on welding digital intelligent production line according to claim 9, characterized in that: The expression of the characteristic function is: In the formula, T(a,b) represents the characteristic function of the material storage rack contour curve point a and the standard curve point b, S(a,b) represents the similarity between the material storage rack contour curve point a and the standard curve point b, and s con It represents the vector similarity between the contour vector of the material storage rack contour curve point a and the contour vector of the standard curve point b, α represents the weight of the similarity, and β represents the weight of the vector similarity.

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