A processing control method for a sheet production line

Abstract

The present invention discloses a processing control method for a sheet production line, which relates to the technical field of control systems. The method includes: collecting noise data at multiple positions in the rolling production line of the sheet, constructing noise sound field information, performing roll vibration traceability analysis, and obtaining a traceability analysis result. Performing an impact analysis on the rolling dimensional accuracy of the sheet to obtain multiple basic dimension impact information. According to the noise sound field information, performing an impact analysis on the noise processing yield to obtain multiple yield impact information, performing supplementary processing on the multiple basic dimension impact information to obtain multiple adjusted dimension impact information, combining with the sheet characteristic data, performing an impact analysis on the processing quality to obtain multiple processing quality impact information, and performing noise control optimization processing at multiple positions. It solves the technical problem in the prior art that it is difficult to improve the processing accuracy and reliability of sheet products due to the influence of processing noise during the processing of the sheet production line.

Description

Technical Field

[0001] This application relates to the field of control system technologies, and particularly to a processing control method for a sheet metal production line. Background Art

[0002] In modern industrial production, sheet metal processing is a key link and is widely used in multiple fields such as construction, automotive, shipbuilding, and household appliances. A sheet metal production line usually includes multiple processes such as cutting, stamping, and rolling. Among them, the rolling process is an important step in determining the quality and performance of sheet metal. However, the noise problem generated during the rolling process has always been a challenge in industrial production. It not only affects the working environment of the production line but also affects the processing operations of the operators, and ultimately affects the processing accuracy and reliability of the sheet metal products.

[0003] Therefore, in the prior art, due to the influence of processing noise during the processing of a sheet metal production line, there are technical problems that it is difficult to improve the processing accuracy and reliability of sheet metal products. Summary of the Invention

[0004] This application provides a processing control method for a sheet metal production line, which solves the technical problem in the prior art that due to the influence of processing noise during the processing of a sheet metal production line, it is difficult to improve the processing accuracy and reliability of sheet metal products. It realizes the suppression of production noise during the processing of the sheet metal production line, reduces the influence of processing noise on the working environment and the processing operations of workers, improves the processing accuracy and reliability of products, and optimizes production efficiency.

[0005] This application provides a processing control method for a sheet metal production line. The method includes: in the rolling production line of sheet metal, collecting noise data at multiple positions and constructing noise sound field information; according to the noise sound field information, performing roll vibration traceability analysis to obtain vibration traceability analysis results at multiple roll positions; according to the multiple vibration traceability analysis results, performing an influence analysis on the rolling dimensional accuracy of the sheet metal to obtain multiple basic dimension influence information at multiple rolling positions, where the multiple positions, multiple roll positions, and multiple rolling positions correspond one by one; according to the noise sound field information, combining historical processing data, performing an influence analysis on the noise processing yield of manual processing control at multiple rolling positions to obtain multiple yield influence information; according to the multiple yield influence information, performing supplementary processing on the multiple basic dimension influence information to obtain multiple adjusted dimension influence information, combining the sheet metal characteristic data of the sheet metal, performing a processing quality influence analysis to obtain multiple processing quality influence information; according to the multiple processing quality influence information, performing noise control optimization processing on the multiple positions to obtain multiple optimal noise control solutions for noise control during processing.

[0006] In a possible implementation, in the rolling production line of the sheet material, noise data at multiple positions are collected, and noise sound field information is constructed, including: in the rolling production line of the sheet material, at multiple noise collection positions, multiple noise data are collected, where each noise data includes noise magnitude data; based on the position coordinates of the multiple noise collection positions and in combination with the multiple noise data, a basic noise sound field is constructed; the basic noise field is interpolated and rendered to obtain the noise sound field information.

[0007] In a possible implementation, based on the noise sound field information, roll vibration traceability analysis is performed to obtain vibration traceability analysis results at multiple roll positions, including: according to the sheet material rolling vibration detection records, a sample noise sound field information set and multiple sample vibration detection result sets at multiple roll positions are obtained; using the sample noise sound field information set and multiple sample vibration detection result sets at multiple roll positions, a roll vibration traceability analyzer for performing roll vibration traceability analysis is constructed, and the roll vibration traceability analyzer includes multiple roll vibration traceability analysis branches; based on the roll vibration traceability analyzer, the noise sound field information is analyzed and processed to obtain multiple vibration traceability analysis results at multiple roll positions.

[0008] In a possible implementation, based on multiple vibration traceability analysis results, the influence analysis of the rolling dimensional accuracy of the sheet material is performed to obtain multiple basic dimension influence information at multiple rolling positions, including: according to the sheet material rolling data records at the multiple roll positions, multiple sample vibration traceability analysis result sets are obtained, and multiple sample basic dimension influence information sets at multiple positions of the rolled sheet material are obtained; using the multiple sample vibration traceability analysis result sets and multiple sample basic dimension influence information sets, multiple dimension influence classification branches are respectively constructed to obtain a dimension influence classifier; based on the dimension influence classifier, the multiple vibration traceability analysis results are classified and identified to obtain the multiple basic dimension influence information.

[0009] In a possible implementation, based on the noise sound field information and in combination with historical processing data, the influence analysis of the noise processing yield of manual processing control at multiple rolling positions is performed to obtain multiple yield influence information, including: according to the data records of manual processing control at multiple rolling positions, a sample noise sound field information set and multiple sample yield influence information sets are obtained; using the sample noise sound field information set and multiple sample yield influence information sets, multiple processing yield influence recognition branches are constructed to obtain a processing yield influence recognizer, and the noise sound field information is recognized to obtain multiple yield influence information.

[0010] In a possible implementation manner, based on the multiple yield influence information, supplementary processing is performed on the multiple basic dimension influence information to obtain multiple adjusted dimension influence information. Combining with the sheet characteristic data of the sheet, processing quality influence analysis is carried out, including: calculating the allowable processing dimension error according to the difference between the multiple yield influence information and the normal yield, to obtain multiple sheet dimension errors; performing supplementary calculation processing by combining the multiple sheet dimension errors and the multiple basic dimension influence information to obtain multiple adjusted dimension influence information; obtaining the component information of the sheet as the sheet characteristic data; according to the sheet rolling data record, obtaining the sample sheet characteristic data set, and obtaining the multiple sample adjusted dimension influence information sets at multiple rolling positions, and evaluating the performance influence level after different rolling dimension influence information to obtain multiple sample processing quality influence information sets; using the sample sheet characteristic data set, the multiple sample adjusted dimension influence information sets and the multiple sample processing quality influence information sets to construct a processing quality influence analyzer including multiple processing quality influence analysis branches, and performing processing quality influence identification on the sheet characteristic data and the multiple adjusted dimension influence information to obtain multiple processing quality influence information.

[0011] In a possible implementation manner, based on the multiple processing quality influence information, noise control optimization processing is performed on the multiple positions to obtain multiple optimal noise control solutions, including: obtaining multiple noise management solutions for the rolls, constructing a control solution library, where the control intensity levels of different noise control solutions are different; constructing a noise control function for optimizing the noise control of the multiple positions; randomly selecting the noise control solutions for the multiple positions in the control solution library to obtain multiple first noise control solutions; calculating the first noise control fitness of the multiple first noise control solutions according to the noise control function; randomly adjusting the noise control solutions for a random number of positions and calculating the second noise control fitness; determining whether the second noise control fitness is greater than the first noise control fitness. If so, continue to adjust and optimize the noise control solutions for a random number of positions. If not, re-adjust and optimize the noise control solutions for a random number of positions based on the multiple first noise control solutions; continue to optimize until convergence, and output the multiple noise control solutions with the maximum noise control fitness to obtain the multiple optimal noise control solutions. The noise control function for optimizing the noise control of the multiple positions is constructed as follows:

[0012] ;

[0013] where NCT is the noise control fitness, and The sum of is 1, which are the control weight and the cost weight respectively, M is the number of multiple positions, The weight of the i-th position allocated according to the magnitudes of multiple machining quality impact information The machining quality impact information of the i-th position The control intensity level of the noise control solution for the i-th position The total cost of multiple noise control solutions The preset cost

[0014] This application also provides a machining control system for a sheet production line, including:

[0015] A sound field information construction module, configured to collect noise data at multiple positions in the rolling production line of the sheet and construct noise sound field information;

[0016] A traceability analysis module, configured to perform roll vibration traceability analysis based on the noise sound field information to obtain vibration traceability analysis results at multiple roll positions;

[0017] An impact analysis module, configured to perform an impact analysis on the rolling dimension accuracy of the sheet based on multiple vibration traceability analysis results to obtain multiple basic dimension impact information at multiple rolling positions, where the multiple positions, multiple roll positions, and multiple rolling positions correspond one by one;

[0018] A yield impact acquisition module, configured to perform a noise machining yield impact analysis on manual machining control at multiple rolling positions based on the noise sound field information in combination with historical machining data to obtain multiple yield impact information;

[0019] An impact information acquisition module, configured to perform supplementary processing on the multiple basic dimension impact information according to the multiple yield impact information to obtain multiple adjusted dimension impact information, and perform a machining quality impact analysis in combination with the sheet feature data of the sheet to obtain multiple machining quality impact information;

[0020] A noise control module, configured to perform noise control optimization processing on the multiple positions according to the multiple machining quality impact information to obtain multiple optimal noise control solutions and perform noise control during machining.

[0021] A processing control method for a sheet production line proposed in this application. In the rolling production line of the sheet, noise data at multiple positions is collected to construct noise sound field information. According to the noise sound field information, roll vibration traceability analysis is carried out to obtain vibration traceability analysis results at multiple roll positions. According to the multiple vibration traceability analysis results, the influence analysis of the rolling dimension accuracy of the sheet is carried out to obtain multiple basic dimension influence information at multiple rolling positions, where the multiple positions, multiple roll positions, and multiple rolling positions correspond one by one. According to the noise sound field information, combined with historical processing data, the influence analysis of the noise processing yield of manual processing control at multiple rolling positions is carried out to obtain multiple yield influence information. According to the multiple yield influence information, the multiple basic dimension influence information is supplemented and processed to obtain multiple adjusted dimension influence information. Combined with the sheet feature data of the sheet, the influence analysis of the processing quality is carried out to obtain multiple processing quality influence information. According to the multiple processing quality influence information, the noise control optimization processing of the multiple positions is carried out to obtain multiple optimal noise control schemes for noise control during processing. This solves the technical problem in the prior art that it is difficult to improve the processing accuracy and reliability of sheet products due to the influence of processing noise during the processing of the sheet production line. It realizes the suppression of production noise during the processing of the sheet production line, reduces the influence of processing noise on the working environment and workers' processing operations, improves the processing accuracy and reliability of products, and optimizes production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the operations before or below do not necessarily need to be executed precisely in sequence. On the contrary, as needed, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0023] Figure 1 Schematic diagram of the process of a processing control method for a sheet production line provided by an embodiment of the present application;

[0024] Figure 2 Schematic diagram of the structure of a processing control system for a sheet production line provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The above description is only an overview of the technical solutions of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of this application more obvious and understandable, the following specifically gives the detailed implementation manners of this application.

[0026] To make the objectives, technical solutions and advantages of this application more clear, the following will further describe this application in detail with reference to the accompanying drawings. The described embodiments should not be regarded as limitations of this application. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0027] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first / second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0028] An embodiment of this application provides a processing control method for a sheet production line, as Figure 1 shown, the method includes:

[0029] Step S10: In the rolling production line of the sheet, collect noise data at multiple positions and construct noise sound field information;

[0030] Step S20: According to the noise sound field information, perform roll vibration traceability analysis to obtain vibration traceability analysis results at multiple roll positions;

[0031] Step S30: According to multiple vibration traceability analysis results, perform an impact analysis on the rolling dimensional accuracy of the sheet to obtain multiple basic dimension impact information at multiple rolling positions, and the multiple positions, multiple roll positions, and multiple rolling positions correspond one by one;

[0032] Specifically, in the rolling production line of a sheet, noise data at multiple positions are collected, and noise sound field information is constructed. Among them, the multiple positions correspond one-to-one to multiple roll positions and multiple rolling positions on the rolling production line. The roll position is the position on each roll in the rolling production line, and the rolling position is the contact position between the sheet and the roll. Generally, when the roll lubrication is poor, the roll vibrates abnormally during operation, generating noise. According to the noise sound field information, roll vibration traceability analysis is carried out to obtain the vibration traceability analysis results of multiple roll positions. According to the multiple vibration traceability analysis results, the influence analysis of the rolling dimension accuracy of the sheet is carried out to obtain multiple basic dimension influence information of multiple rolling positions, where the multiple positions, multiple roll positions, and multiple rolling positions correspond one-to-one.

[0033] The method provided by the embodiment of the present application further includes:

[0034] Step S11: In the rolling production line of a sheet, at multiple noise collection positions, collect multiple noise data, where each noise data includes noise magnitude data;

[0035] Step S12: According to the position coordinates of the multiple noise collection positions, combined with the multiple noise data, construct a basic noise sound field;

[0036] Step S13: Perform interpolation rendering on the basic noise field to obtain the noise sound field information.

[0037] Specifically, in the rolling production line of a sheet, at multiple noise collection positions, collect multiple noise data, where each noise data includes noise magnitude data. According to the position coordinates of the multiple noise collection positions, combined with the multiple noise data, construct a basic noise sound field, and the basic noise sound field includes the distribution of noise collection positions and the corresponding noise data collected. Further, perform interpolation rendering on the basic noise field to obtain the noise sound field information, and use the linear interpolation method in the prior art when performing interpolation rendering on the basic noise field.

[0038] The method provided by the embodiment of the present application further includes:

[0039] Step S21: According to the rolling vibration detection records of the sheet, obtain a sample noise sound field information set and a set of multiple sample vibration detection results of multiple roll positions;

[0040] Step S22: Use the sample noise sound field information set and the set of multiple sample vibration detection results of multiple roll positions to construct a roll vibration traceability analyzer for performing roll vibration traceability analysis. The roll vibration traceability analyzer includes multiple roll vibration traceability analysis branches;

[0041] Step S23: Based on the roll vibration traceability analyzer, analyze and process the noise sound field information to obtain multiple vibration traceability analysis results at multiple roll positions.

[0042] Specifically, according to multiple vibration traceability analysis results, analyze the influence on the rolling dimensional accuracy of the sheet metal, and obtain multiple basic dimension influence information at multiple rolling positions, including: according to the sheet metal rolling vibration detection records, obtain the sample noise sound field information set and the multiple sample vibration detection result sets at multiple roll positions, that is, perform vibration detection at each roll position on the sample noise sound field information set and multiple roll positions to obtain the corresponding vibration source positions. Subsequently, use the sample noise sound field information set and the multiple sample vibration detection result sets at multiple roll positions to construct a roll vibration traceability analyzer for roll vibration traceability analysis. The roll vibration traceability analyzer includes multiple roll vibration traceability analysis branches. When obtaining the roll vibration traceability analysis branches, use the sheet metal rolling vibration detection records as training data to perform supervised training on the neural network model until the accuracy of the vibration detection result set finally output by the model meets the preset threshold, complete the training, obtain the roll vibration traceability analysis branches, and link the multiple roll vibration traceability analysis branches in parallel to obtain the roll vibration traceability analyzer. Based on the roll vibration traceability analyzer, analyze and process the noise sound field information to obtain multiple vibration traceability analysis results at multiple roll positions.

[0043] The method provided by the embodiment of the present application further includes:

[0044] Step S31: According to the sheet metal rolling data records at the multiple roll positions, obtain multiple sample vibration traceability analysis result sets, and obtain multiple sample basic dimension influence information sets at multiple positions of the rolled sheet metal;

[0045] Step S32: Use the multiple sample vibration traceability analysis result sets and the multiple sample basic dimension influence information sets to respectively construct multiple dimension influence classification branches to obtain a dimension influence classifier;

[0046] Step S33: Based on the dimension influence classifier, classify and identify the multiple vibration traceability analysis results to obtain the multiple basic dimension influence information.

[0047] Specifically, based on multiple vibration source tracing analysis results, perform an impact analysis on the rolling dimensional accuracy of the sheet metal to obtain multiple basic dimension impact information for multiple rolling positions, including: obtaining multiple sample vibration source tracing analysis result sets according to the sheet metal rolling data records at the multiple roll positions, and obtaining multiple sample basic dimension impact information sets for multiple positions of the rolled sheet metal. The sample basic dimension impact information set is the dimensional impact deviation generated at the corresponding position of the rolled sheet metal by using the corresponding equipment in the sample vibration source tracing analysis result set. Subsequently, use the multiple sample vibration source tracing analysis result sets and multiple sample basic dimension impact information sets to respectively construct multiple dimension impact classification branches to obtain a dimension impact classifier, and the dimension impact classifier contains multiple parallel dimension impact classification branches. When constructing the dimension impact classification branches, use the multiple sample vibration source tracing analysis result sets and multiple sample basic dimension impact information sets as training data to perform supervised training on the classifier model to obtain a trained model and obtain the dimension impact classification branches. Finally, based on the dimension impact classifier, perform classification recognition on the multiple vibration source tracing analysis results to obtain the multiple basic dimension impact information.

[0048] Step S40: According to the noise sound field information and in combination with historical processing data, perform an impact analysis on the noise processing yield of manual processing control at multiple rolling positions to obtain multiple yield impact information;

[0049] Step S50: According to the multiple yield impact information, perform supplementary processing on the multiple basic dimension impact information to obtain multiple adjusted dimension impact information, and in combination with the sheet metal characteristic data of the sheet metal, perform an impact analysis on the processing quality to obtain multiple processing quality impact information;

[0050] Step S60: According to the multiple processing quality impact information, perform optimization processing on the noise control at the multiple positions to obtain multiple optimal noise control solutions and perform noise control during processing.

[0051] Specifically, since there is still manual processing control in plate rolling, noise will affect the accuracy of manual control, and thus affect the yield. By analyzing the influence information of the yield in the noise sound field, for the noise sound field information, combined with historical processing data, which includes noise record data and corresponding processing yield influence data at multiple rolling positions, an analysis of the influence of noise on the processing yield of manual processing control at multiple rolling positions is carried out to obtain multiple yield influence information. Further, according to the multiple yield influence information, supplementary processing is performed on the multiple basic dimension influence information to obtain multiple adjusted dimension influence information. Combined with the plate characteristic data of the plate, an analysis of the influence on processing quality is carried out to obtain multiple processing quality influence information. According to the multiple processing quality influence information, an optimization process of noise control at the multiple positions is carried out to obtain multiple optimal noise control schemes, and noise control during processing is performed. This realizes the suppression of production noise during the processing of the plate production line, reduces the influence of processing noise on the working environment and workers' processing operations, improves the processing accuracy and reliability of products, and optimizes production efficiency.

[0052] The method provided by the embodiment of the present application further includes:

[0053] Step S41: Obtain a sample noise sound field information set and multiple sample yield influence information sets according to the data records of manual processing control at multiple rolling positions;

[0054] Step S42: Use the sample noise sound field information set and multiple sample yield influence information sets to construct multiple processing yield influence recognition branches, obtain a processing yield influence recognizer, and recognize the noise sound field information to obtain multiple yield influence information.

[0055] Specifically, according to the noise sound field information, combined with historical processing data, an analysis of the influence of noise on the processing yield of manual processing control at multiple rolling positions is carried out to obtain multiple yield influence information, including: obtaining a sample noise sound field information set and multiple sample yield influence information sets according to the data records of manual processing control at multiple rolling positions, and the yield influence information set is the yield after being affected. Subsequently, use the sample noise sound field information set and multiple sample yield influence information sets to construct multiple processing yield influence recognition branches, obtain a processing yield influence recognizer, and recognize the noise sound field information to obtain multiple yield influence information, where each yield influence information corresponds to a processing position. The processing yield influence recognizer contains multiple processing yield influence recognition branches. When constructing the processing yield influence recognition branches, the sample noise sound field information set and multiple sample yield influence information sets are used as training data to perform supervised training on the neural network model until the output result of the model meets the preset accuracy rate, and then the training of the model is completed to obtain the processing yield influence recognition branches.

[0056] The method provided by the embodiment of the present application further includes:

[0057] Step S51: Calculate the allowable processing dimension error according to the difference between multiple yield influence information and the normal yield, and obtain multiple influence factors on the sheet metal dimension error;

[0058] Step S52: Perform supplementary calculation processing according to multiple influence factors on the sheet metal dimension error in combination with the multiple basic dimension influence information, and obtain multiple adjusted dimension influence information;

[0059] Step S53: Obtain the composition information of the sheet metal as the sheet metal characteristic data;

[0060] Step S54: According to the sheet metal rolling data record, obtain the sample sheet metal characteristic data set, and obtain the multiple sample adjusted dimension influence information sets at multiple rolling positions, and evaluate the performance influence level after different rolling dimension influence information, and obtain multiple sample processing quality influence information sets;

[0061] Step S55: Use the sample sheet metal characteristic data set, multiple sample adjusted dimension influence information sets and multiple sample processing quality influence information sets to construct a processing quality influence analyzer including multiple processing quality influence analysis branches, and perform processing quality influence identification on the sheet metal characteristic data and multiple adjusted dimension influence information to obtain multiple processing quality influence information.

[0062] Specifically, based on the multiple yield influence information, supplementary processing is performed on the multiple basic dimension influence information to obtain multiple adjusted dimension influence information. Combining with the sheet material characteristic data of the sheet, processing quality influence analysis is carried out, including: calculating the deviation value of the yield influence information and the normal yield at the corresponding position according to the difference between the multiple yield influence information and the normal yield, calculating the allowable processing dimension error, and obtaining multiple sheet dimension errors. For example, if the difference is 5% and the allowable processing dimension error is ±0.5 mm, then the sheet dimension error is calculated as ±0.5 * 105% and the absolute value of the final result is 0.525 mm. Subsequently, based on the multiple sheet dimension errors, supplementary calculation processing is carried out in combination with the multiple basic dimension influence information, that is, the average value of the obtained sheet dimension error and the basic dimension influence information at the corresponding position is calculated, so as to obtain multiple adjusted dimension influence information. Obtain the composition information of the sheet, such as aluminum alloy sheet, steel sheet, etc. and the corresponding dimension data of the sheet as the sheet material characteristic data. According to the sheet rolling data record, obtain the sample sheet material characteristic data set, and obtain the multiple sample adjusted dimension influence information sets at multiple rolling positions, and obtain the performance influence level after obtaining different rolling dimension influence information through manual evaluation, and obtain multiple sample processing quality influence information sets, that is, perform manual analysis on the sheet material characteristics of the sample and the corresponding sample adjusted dimension influence information to obtain the performance influence level. Using the sample sheet material characteristic data set, the multiple sample adjusted dimension influence information sets and the multiple sample processing quality influence information sets, construct a processing quality influence analyzer including multiple processing quality influence analysis branches. The processing quality influence analyzer contains multiple parallel processing quality influence analysis branches. When constructing the processing quality influence analysis branches, use the sample sheet material characteristic data set, the multiple sample adjusted dimension influence information sets and the multiple sample processing quality influence information sets as training data to perform supervised training on the neural network model until the output result of the model meets the preset accuracy rate to complete the training and obtain the processing quality influence analysis branches. Input the sheet material characteristic data and the multiple adjusted dimension influence information into the processing quality influence analyzer for processing quality influence identification to obtain multiple processing quality influence information.

[0063] The method provided by the embodiment of the present application further includes:

[0064] Step S61: Obtain multiple noise management schemes for the rolling mill, construct a control scheme library, and the control intensity levels of different noise control schemes are different;

[0065] Step S62: Construct a noise control function for optimizing the noise control at the multiple positions;

[0066] Step S63: Randomly select the noise control schemes at the multiple positions in the control scheme library to obtain multiple first noise control schemes;

[0067] Step S64: Calculate the first noise control fitness of multiple first noise control schemes according to the noise control function;

[0068] Step S65: Randomly adjust the noise control schemes at a random number of positions, and calculate the second noise control fitness;

[0069] Step S66: Determine whether the second noise control fitness is greater than the first noise control fitness. If so, continue to adjust and optimize the noise control schemes at a random number of positions. If not, re-adjust and optimize the noise control schemes at a random number of positions based on multiple first noise control schemes;

[0070] Step S67: Continue to optimize until convergence, output multiple noise control schemes with the maximum noise control fitness, and obtain the multiple optimal noise control schemes.

[0071] Specifically, obtain various noise management schemes for the roll, construct a control scheme library, and the control intensity levels of different noise control schemes are different. Among them, the roll noise management scheme is a pre-set control scheme, such as dynamic balancing of the roll, setting of shock absorbers and vibration isolation systems, installation of sound insulation screens or enclosures to reduce the transmission of noise to the working area, and use of sound absorption materials such as sound absorption boards and sound absorption curtains inside the workshop to absorb noise and reduce echoes, etc. Each control scheme corresponds to different control intensity levels and management cost parameters. Construct a noise control function for optimizing the noise control of the multiple positions. Randomly select the noise control schemes for the multiple positions in the control scheme library to obtain multiple first noise control schemes. Calculate the first noise control fitness of the multiple first noise control schemes according to the noise control function. Randomly adjust the noise control schemes at a random number of positions to obtain a second noise control scheme, and calculate the second noise control fitness. Determine whether the second noise control fitness is greater than the first noise control fitness. If so, continue to adjust and optimize the noise control schemes at a random number of positions. If not, re-adjust and optimize the noise control schemes at a random number of positions based on multiple first noise control schemes. Continue to optimize until convergence, output multiple noise control schemes with the maximum noise control fitness, and obtain the multiple optimal noise control schemes, realizing the corresponding setting of the optimal noise control scheme according to the specific situation of the rolling production line of the sheet metal.

[0072] Construct a noise control function for optimizing the noise control of the multiple positions, as shown in the following formula:

[0073] ;

[0074] where NCT is the noise control fitness, and Their sum is 1, which are the control weight and the cost weight respectively. M is the number of multiple positions. is the weight of the i-th position allocated according to the magnitudes of multiple machining quality influence information. The machining quality influence information of the i-th position. is the control strength level of the noise control solution for the i-th position. is the total cost of multiple noise control solutions. is the preset cost.

[0075] In the above text, with reference to Figure 1 A processing control method for a sheet production line according to an embodiment of the present invention is described in detail. Next, with reference to Figure 2 A processing control system for a sheet production line according to an embodiment of the present invention will be described.

[0076] A processing control system for a sheet production line according to an embodiment of the present invention solves the technical problem in the prior art that it is difficult to improve the processing accuracy and reliability of sheet products due to the influence of processing noise during the processing of the sheet production line. It realizes the suppression of production noise during the processing of the sheet production line, reduces the influence of processing noise on the working environment and the processing operations of workers, improves the processing accuracy and reliability of products, and optimizes production efficiency. A processing control system for a sheet production line includes: an acoustic field information construction module 11, a traceability analysis module 12, an influence analysis module 13, a yield influence acquisition module 14, an influence information acquisition module 15, and a noise control module 16.

[0077] The acoustic field information construction module 11 is used to collect noise data at multiple positions in the rolling production line of the sheet and construct noise acoustic field information.

[0078] The traceability analysis module 12 is used to perform roll vibration traceability analysis based on the noise acoustic field information and obtain vibration traceability analysis results at multiple roll positions.

[0079] The influence analysis module 13 is used to perform influence analysis on the rolling dimensional accuracy of the sheet based on multiple vibration traceability analysis results, and obtain multiple basic dimension influence information at multiple rolling positions. The multiple positions, multiple roll positions, and multiple rolling positions correspond one by one.

[0080] The yield influence acquisition module 14 is used to perform influence analysis on the noise processing yield of manual processing control at multiple rolling positions based on the noise acoustic field information in combination with historical processing data, and obtain multiple yield influence information.

[0081] The influence information acquisition module 15 is configured to supplementarily process the multiple basic dimension influence information according to the multiple yield influence information, obtain multiple adjusted dimension influence information, and combine with the sheet material characteristic data of the sheet material to perform machining quality influence analysis to obtain multiple machining quality influence information;

[0082] The noise control module 16 is configured to perform noise control optimization processing at the multiple positions according to the multiple machining quality influence information, obtain multiple optimal noise control solutions, and perform noise control during machining.

[0083] Next, the specific configuration of the sound field information construction module 11 will be described in detail. As described above, in the rolling production line of the sheet material, noise data at multiple positions are collected and a noise sound field information is constructed, including: in the rolling production line of the sheet material, at multiple noise collection positions, multiple noise data are collected, where each noise data includes noise magnitude data; according to the position coordinates of the multiple noise collection positions and in combination with the multiple noise data, a basic noise sound field is constructed; and the basic noise field is interpolated and rendered to obtain the noise sound field information.

[0084] Next, the specific configuration of the traceability analysis module 12 will be further described in detail. According to the noise sound field information, roll vibration traceability analysis is performed to obtain vibration traceability analysis results at multiple roll positions, including: according to the sheet material rolling vibration detection records, obtaining a sample noise sound field information set and multiple sample vibration detection result sets at multiple roll positions; using the sample noise sound field information set and multiple sample vibration detection result sets at multiple roll positions to construct a roll vibration traceability analyzer for performing roll vibration traceability analysis, the roll vibration traceability analyzer including multiple roll vibration traceability analysis branches; and based on the roll vibration traceability analyzer, analyzing and processing the noise sound field information to obtain multiple vibration traceability analysis results at multiple roll positions.

[0085] Next, the specific configuration of the influence analysis module 13 will be described in detail. As described above, according to multiple vibration traceability analysis results, rolling dimension accuracy influence analysis of the sheet material is performed to obtain multiple basic dimension influence information at multiple rolling positions, including: according to the sheet material rolling data records at the multiple roll positions, obtaining multiple sample vibration traceability analysis result sets and obtaining multiple sample basic dimension influence information sets at multiple positions of the rolled sheet material; using the multiple sample vibration traceability analysis result sets and multiple sample basic dimension influence information sets to respectively construct multiple dimension influence classification branches to obtain a dimension influence classifier; and based on the dimension influence classifier, classifying and identifying the multiple vibration traceability analysis results to obtain the multiple basic dimension influence information.

[0086] Next, the specific configuration of the yield impact acquisition module 14 will be described in detail. As described above, based on the noise sound field information and combined with historical processing data, a noise processing yield impact analysis of manual processing control at multiple rolling positions is performed to obtain multiple yield impact information, including: obtaining a sample noise sound field information set and multiple sample yield impact information sets according to the data records of manual processing control at multiple rolling positions; using the sample noise sound field information set and multiple sample yield impact information sets to construct multiple processing yield impact recognition branches, obtaining a processing yield impact recognizer, and recognizing the noise sound field information to obtain multiple yield impact information.

[0087] Next, the specific configuration of the impact information acquisition module 15 will be continued to be described in detail. As described above, based on the multiple yield impact information, supplementary processing is performed on the multiple basic dimension impact information to obtain multiple adjusted dimension impact information, and combined with the sheet material characteristic data of the sheet, a processing quality impact analysis is carried out, including: calculating the allowable processing dimension error according to the difference between the multiple yield impact information and the normal yield to obtain multiple impact sheet material dimension errors; performing supplementary calculation processing on the multiple impact sheet material dimension errors in combination with the multiple basic dimension impact information to obtain multiple adjusted dimension impact information; obtaining the component information of the sheet as the sheet material characteristic data; obtaining a sample sheet material characteristic data set according to the sheet rolling data record, and obtaining multiple sample adjusted dimension impact information sets at multiple rolling positions, and evaluating the performance impact level after different rolling dimension impact information to obtain multiple sample processing quality impact information sets; using the sample sheet material characteristic data set, multiple sample adjusted dimension impact information sets and multiple sample processing quality impact information sets to construct a processing quality impact analyzer including multiple processing quality impact analysis branches, and performing processing quality impact recognition on the sheet material characteristic data and multiple adjusted dimension impact information to obtain multiple processing quality impact information.

[0088] Next, the specific configuration of the noise control module 16 will be described in detail. As described above, various noise management solutions for the roll are obtained to build a control solution library, and the control strength levels of different noise control solutions are different; a noise control function for optimizing the noise control of the multiple positions is constructed; within the control solution library, the noise control solutions for the multiple positions are randomly selected to obtain multiple first noise control solutions; according to the noise control function, the first noise control fitness of the multiple first noise control solutions is calculated; the noise control solutions for a random number of positions are randomly adjusted, and the second noise control fitness is calculated; it is determined whether the second noise control fitness is greater than the first noise control fitness. If so, the adjustment and optimization of the noise control solutions for a random number of positions continue. If not, the adjustment and optimization of the noise control solutions for a random number of positions are re-performed based on the multiple first noise control solutions; continue to optimize until convergence, and output the multiple noise control solutions with the maximum noise control fitness to obtain the multiple optimal noise control solutions. A noise control function for optimizing the noise control of the multiple positions is constructed as follows:

[0089] ;

[0090] where NCT is the noise control fitness, and The sum of is 1, which are the control weight and the cost weight respectively, M is the number of multiple positions, is the weight of the i-th position allocated according to the magnitudes of the multiple processing quality impact information, The processing quality impact information of the i-th position, is the control strength level of the noise control solution for the i-th position, is the total cost of the multiple noise control solutions, is the preset cost.

[0091] The processing control system of a sheet production line provided by an embodiment of the present invention can execute the processing control method of a sheet production line provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0092] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The included individual units and modules are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0093] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims

1. A processing control method for a sheet production line, characterized in that, The method includes: In the rolling production line of the sheet material, noise data at multiple positions are collected, and noise sound field information is constructed; According to the noise sound field information, roll vibration traceability analysis is carried out to obtain vibration traceability analysis results at multiple roll positions; According to multiple vibration traceability analysis results, the influence analysis of the rolling dimensional accuracy of the sheet material is carried out to obtain multiple basic dimension influence information at multiple rolling positions, and the multiple positions, multiple roll positions and multiple rolling positions correspond one by one; According to the noise sound field information, combined with historical processing data, the influence analysis of the noise processing yield of manual processing control at multiple rolling positions is carried out to obtain multiple yield influence information; According to the multiple yield influence information, the multiple basic dimension influence information is supplemented and processed to obtain multiple adjusted dimension influence information. Combined with the sheet material characteristic data of the sheet material, the influence analysis of the processing quality is carried out to obtain multiple processing quality influence information, including: According to the difference between the multiple yield influence information and the normal yield, the allowable processing dimension error is calculated to obtain multiple sheet material dimension errors; According to the multiple sheet material dimension errors, combined with the multiple basic dimension influence information, supplementary calculation processing is carried out to obtain multiple adjusted dimension influence information; The component information of the sheet material is obtained as the sheet material characteristic data; According to the sheet material rolling data record, a sample sheet material characteristic data set is obtained, and a set of multiple sample adjusted dimension influence information at multiple rolling positions is obtained, and the performance influence level after evaluating different rolling dimension influence information is obtained to obtain a set of multiple sample processing quality influence information; Using the sample sheet material characteristic data set, the set of multiple sample adjusted dimension influence information and the set of multiple sample processing quality influence information, a processing quality influence analyzer including multiple processing quality influence analysis branches is constructed to identify the processing quality influence of the sheet material characteristic data and the multiple adjusted dimension influence information, and multiple processing quality influence information is obtained; According to the multiple processing quality influence information, the noise control optimization processing at the multiple positions is carried out to obtain multiple optimal noise control schemes for noise control during processing.

2. The method according to claim 1, wherein In the rolling production line of the sheet material, noise data at multiple positions are collected, and noise sound field information is constructed, including: In the rolling production line of the sheet material, at multiple noise collection positions, multiple noise data are collected, and each noise data includes noise magnitude data; According to the position coordinates of multiple noise collection positions, combined with the multiple noise data, a basic noise sound field is constructed; The basic noise field is interpolated and rendered to obtain the noise sound field information.

3. The method according to claim 1, wherein According to the noise sound field information, roll vibration traceability analysis is carried out to obtain vibration traceability analysis results at multiple roll positions, including: According to the sheet material rolling vibration detection record, a sample noise sound field information set and a set of multiple sample vibration detection results at multiple roll positions are obtained; Using the sample noise sound field information set and the set of multiple sample vibration detection results at multiple roll positions, a roll vibration traceability analyzer for carrying out roll vibration traceability analysis is constructed, and the roll vibration traceability analyzer includes multiple roll vibration traceability analysis branches; Based on the roll vibration traceability analyzer, analyze and process the noise sound field information to obtain multiple vibration traceability analysis results at multiple roll positions.

4. The method according to claim 1, wherein According to multiple vibration traceability analysis results, conduct an analysis on the influence of the rolling dimensional accuracy of the sheet metal, and obtain multiple basic dimension influence information at multiple rolling positions, including: According to the sheet metal rolling data records at the multiple roll positions, obtain multiple sets of sample vibration traceability analysis results, and obtain multiple sets of sample basic dimension influence information at multiple positions of the rolled sheet metal; Use the multiple sets of sample vibration traceability analysis results and multiple sets of sample basic dimension influence information to respectively construct multiple dimension influence classification branches to obtain a dimension influence classifier; Based on the dimension influence classifier, classify and identify the multiple vibration traceability analysis results to obtain the multiple basic dimension influence information.

5. The method according to claim 1, characterized in that According to the noise sound field information, combined with historical processing data, conduct an analysis on the influence of the noise processing yield of manual processing control at multiple rolling positions to obtain multiple yield influence information, including: According to the data records of manual processing control at multiple rolling positions, obtain a set of sample noise sound field information and multiple sets of sample yield influence information; Use the set of sample noise sound field information and multiple sets of sample yield influence information to construct multiple processing yield influence recognition branches to obtain a processing yield influence recognizer, and recognize the noise sound field information to obtain multiple yield influence information.

6. The method according to claim 1, characterized in that, According to the multiple processing quality influence information, conduct an optimization process on the noise control at the multiple positions to obtain multiple optimal noise control solutions, including: Obtain various noise management solutions for the rolls, construct a control solution library, and the control intensity levels of different noise control solutions are different; Construct a noise control function for optimizing the noise control at the multiple positions; Randomly select the noise control solutions at the multiple positions in the control solution library to obtain multiple first noise control solutions; According to the noise control function, calculate the first noise control fitness of the multiple first noise control solutions; Randomly adjust the noise control solutions at a random number of positions, and calculate to obtain a second noise control fitness; Judge whether the second noise control fitness is greater than the first noise control fitness. If so, continue to adjust and optimize the noise control solutions at a random number of positions. If not, re-adjust and optimize the noise control solutions at a random number of positions based on the multiple first noise control solutions; Continue to optimize until convergence, and output the multiple noise control solutions with the maximum noise control fitness to obtain the multiple optimal noise control solutions.

7. The method according to claim 6, characterized in that, Construct a noise control function for optimizing the noise control at the multiple positions, as shown in the following formula: ； Among them, NCT is the noise control fitness, and The sum of and is 1, which are the control weight and the cost weight respectively. M is the number of multiple positions, is the weight of the i-th position allocated according to the magnitude of multiple machining quality influence information, The machining quality influence information of the i-th position, is the control intensity level of the noise control plan for the i-th position, is the total cost of multiple noise control plans, is the preset cost.

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