Automatic deviation rectification regulation and control method and device of hydraulic pipe bending machine for metal processing

Abstract

The invention discloses an automatic deviation rectification regulation and control method and device for a hydraulic pipe bending machine for metal processing, and relates to the technical field of metal processing, and the method comprises the step of obtaining a built-in sensor group, a control data processing module and a deviation rectification regulation mechanism of the hydraulic automatic pipe bending machine for metal processing. And the hydraulic pipe bending control database and the target pipe machining feature information are obtained through a hydraulic pipe bending machine production system, and matching analysis is conducted to obtain a target pipe bending control parameter scheme. And pipe machining control is conducted, the control data processing module constructs multiple channels to conduct offset recognition on data flow to obtain bent pipe offset characteristic parameters, then deviation correction analysis is conducted to obtain bent pipe deviation correction control parameters, and automatic deviation correction machining control is conducted on the target pipe through the deviation correction adjusting mechanism. The technical problems that the machining precision is difficult to guarantee and the quality is unstable due to the fact that different pipe requirements cannot be met in existing hydraulic pipe bending machining are solved, and the technical effect of improving the machining precision and stability is achieved.

Description

Technical Field

[0001] This application relates to the field of metal processing technology, and in particular to an automatic correction and control method and device for hydraulic pipe bending machines used in metal processing. Background Technology

[0002] In metal processing scenarios, the requirements for precision, quality, and efficiency in metal pipe processing are increasingly stringent. This is especially true when dealing with diverse pipe characteristics and processing requirements, where the challenges are more pronounced. Developing efficient automatic correction and control methods for hydraulic pipe bending machines has become crucial for solving metal processing problems. Traditional hydraulic pipe bending machines for metal processing often suffer from numerous issues. They rely heavily on manual experience for parameter setting, lack effective real-time monitoring methods, and struggle to accurately grasp changes in the pipe's condition during processing. This leads to problems such as positional and angular deviations, making it difficult to guarantee processing accuracy. Furthermore, they have poor adaptability to the processing requirements and characteristics of different pipe materials, failing to provide personalized parameter settings and correction control for diverse needs. Resource allocation is also often inefficient, unable to effectively address different processing scenarios, and safety management plans are often simplistic and fixed, unable to adequately respond to the ever-changing realities of metal processing.

[0003] At present, there are technical problems in the related technologies, such as difficulty in ensuring processing accuracy and unstable quality in hydraulic pipe bending processing due to the inability to adapt to the needs of different pipe materials. Summary of the Invention

[0004] This application provides an automatic deviation correction and control method and device for a hydraulic pipe bending machine used in metal processing. It employs a hydraulic automatic pipe bending machine with a built-in sensor group (including position, angle, and pressure sensors), a control data processing module, and a deviation correction and adjustment mechanism. The hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and target pipe processing characteristic information, performs matching analysis and optimization, and obtains a target pipe bending control parameter scheme. Based on the scheme, pipe processing control is implemented, and the sensor group monitors and acquires data streams in real time. The control data processing module constructs multi-channel deviation identification parameters for pipe bending, and then performs deviation correction analysis to obtain pipe bending deviation correction control parameters. The deviation correction and adjustment mechanism automatically corrects the deviation of the target pipe during processing. Through automatic and accurate deviation correction, it adapts to different pipe processing requirements and characteristics, achieving the technical effect of improving processing accuracy and stability.

[0005] This application provides an automatic correction and control method for a hydraulic pipe bending machine used in metal processing, including: A hydraulic automatic pipe bending machine for metal processing is acquired. This machine incorporates a sensor array, a control data processing module, and a correction and adjustment mechanism. The sensor array includes position sensors, angle sensors, and pressure sensors. The hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and processing characteristic information of the target pipe. Based on this processing characteristic information and the hydraulic pipe bending control database, matching analysis and optimization are performed to obtain a target pipe bending control parameter scheme. Based on this target pipe bending control parameter scheme, pipe processing control is implemented. Simultaneously, the sensor array monitors the pipe processing control process in real time, acquiring a pipe processing status monitoring data stream. The control data processing module constructs a multi-channel data deviation analysis system. Based on this multi-channel data deviation analysis, offset identification processing is performed on the pipe processing status monitoring data stream to obtain pipe bending offset characteristic parameters. Correction analysis is performed on these pipe bending offset characteristic parameters to obtain pipe bending correction control parameters. The correction and adjustment mechanism then performs automatic correction processing control on the target pipe according to these correction control parameters.

[0006] This application also provides an automatic correction and control device for a hydraulic pipe bending machine used in metal processing, including: The system includes: a pipe bending machine acquisition module, which acquires information about a hydraulic automatic pipe bending machine for metal processing. The hydraulic automatic pipe bending machine has a built-in sensor group, a control data processing module, and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor, and a pressure sensor. A processing feature information acquisition module acquires processing feature information from a hydraulic pipe bending control database and the processing feature information of the target pipe material through the hydraulic pipe bending machine production system. Based on the processing feature information and the hydraulic pipe bending control database, it performs matching analysis and optimization to obtain a target pipe bending control parameter scheme. A pipe processing control module is used to obtain the target pipe bending control parameter scheme. The system controls pipe processing and monitors the process in real time using the sensor array to acquire pipe processing status monitoring data streams. An offset identification processing module is used to construct a multi-channel data deviation analysis based on the control data processing module. Based on this multi-channel analysis, the system performs offset identification processing on the pipe processing status monitoring data streams to obtain bend offset characteristic parameters. A bend correction control parameter acquisition module is used to perform correction analysis on the bend offset characteristic parameters to obtain bend correction control parameters. The correction adjustment mechanism then performs automatic correction processing control on the target pipe according to these parameters.

[0007] The proposed automatic deviation correction and control method and device for a hydraulic pipe bending machine for metal processing, as described in this application, first acquires a hydraulic automatic pipe bending machine for metal processing with a built-in sensor group (including position, angle, and pressure sensors), a control data processing module, and a deviation correction and adjustment mechanism. The hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and target pipe processing characteristic information, and performs matching analysis and optimization to obtain a target pipe bending control parameter scheme. According to the scheme, pipe processing control is performed, and the sensor group monitors and acquires the data stream in real time. The control data processing module constructs multi-channel deviation identification parameters for pipe bending, and then performs deviation correction analysis to obtain pipe bending deviation correction control parameters. The deviation correction and adjustment mechanism then automatically corrects the deviation of the target pipe during processing. Through automatic and accurate deviation correction, it adapts to different pipe processing requirements and characteristics, achieving the technical effect of improving processing accuracy and stability. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0009] Figure 1 A schematic flowchart illustrating the automatic correction and control method for a hydraulic pipe bending machine for metal processing provided in this application embodiment; Figure 2 This is a schematic diagram of the automatic correction and control device for a hydraulic pipe bending machine for metal processing provided in an embodiment of this application.

[0010] Explanation of reference numerals in the attached diagram: Pipe bending machine acquisition module 10, processing feature information acquisition module 20, pipe processing control module 30, offset identification and processing module 40, and pipe bending correction control parameter acquisition module 50. Detailed Implementation

[0011] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or apparatuses. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0014] This application provides an automatic correction and control method for a hydraulic pipe bending machine used in metal processing, such as... Figure 1 As shown, the method includes: Step S100: Obtain a hydraulic automatic pipe bending machine for metal processing. This machine has a built-in sensor group, a control data processing module, and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor, and a pressure sensor. Specifically, the hydraulic automatic pipe bending machine is first acquired. This machine has a built-in sensor group, a control data processing module, and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor, and a pressure sensor. The position sensor monitors the position change of the pipe in the bending machine in real time, ensuring it is in the correct processing position. If a position deviation occurs, it provides timely feedback. The angle sensor mainly monitors the angle change of the pipe, ensuring the bending angle meets the preset requirements. It also provides immediate feedback when an angle deviation occurs. The pressure sensor monitors the pressure on the pipe during processing. The pressure affects the degree of pipe deformation and quality, and the real-time pressure data is transmitted to the control data processing module. The three sensors work together to monitor the pipe processing process in all directions in real time, providing a basis for subsequent processing control and correction adjustments. The sensor group transmits the monitoring data to the control data processing module. After receiving the information, the module analyzes and processes it to determine whether the processing status meets the requirements and whether there are any deviations. If any deviations in position, angle, or pressure are detected during pipe processing, the control data processing module will send instructions to the correction and adjustment mechanism. The mechanism will then adjust the processing parameters of the pipe bending machine according to the instructions, thereby achieving automatic correction processing control and ensuring the accuracy and quality of pipe processing.

[0015] Step S200: The hydraulic pipe bending machine production system acquires the hydraulic pipe bending control database and the processing characteristic information of the target pipe. Based on the processing characteristic information and the hydraulic pipe bending control database, a matching analysis and optimization are performed to obtain a target pipe bending control parameter scheme. Specifically, firstly, the hydraulic pipe bending control database and the processing characteristic information of the target pipe are acquired through the hydraulic pipe bending machine production system. The processing characteristic information includes processing requirements such as pipe precision requirements and allowable error range, as well as pipe characteristics such as material, size, and wall thickness. Next, the processing characteristic information of the target pipe is matched and analyzed with the hydraulic pipe bending control database for optimization. The system will select similar cases and parameter settings from the database based on the target pipe's material, size, and wall thickness, and further refine the parameter selection based on the precision requirements and error range. Optimization is performed through methods such as simulated processing, establishing mathematical model prediction, or conducting small-scale experiments to finally obtain a target pipe bending control parameter scheme customized for the target pipe. This ensures the precision, quality, and stability of pipe processing, improves production efficiency, reduces scrap rate, and provides a scientific and efficient solution for hydraulic pipe bending in the metal processing industry.

[0016] In one possible implementation, the hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and the processing characteristic information of the target pipe. Based on the processing characteristic information and the hydraulic pipe bending control database, matching analysis and optimization are performed to obtain a target pipe bending control parameter scheme. Step S200 further includes step S210, which involves matching and dividing the specification attribute information of the metal processing hydraulic automatic pipe bending machine with the hydraulic pipe bending control database to construct a hydraulic pipe bending control scheme space. Specifically, firstly, the specification attribute information of the metal processing hydraulic automatic pipe bending machine is analyzed. Attributes include the maximum bending capacity of the pipe bending machine, the applicable pipe size range, and the pressure range it can withstand. The hydraulic pipe bending control database stores a large amount of processing data and control schemes for different types of pipe bending machines under various conditions. By matching and dividing the specification attributes of the pipe bending machine with the information in the database, a set of control schemes suitable for the performance of the pipe bending machine can be selected, thereby constructing a preliminary hydraulic pipe bending control scheme space. For example, if the maximum bending capacity of the pipe bending machine is for pipes with a specific angle and diameter, then control schemes suitable for this capacity range will be selected from the database and included in the scheme space.

[0017] Step S220: The processing characteristic information of the target pipe is used as a constraint parameter and associated with the hydraulic pipe bending control scheme space to obtain a selection set of pipe bending control schemes. Specifically, the processing characteristic information of the target pipe includes processing requirements and pipe characteristics. Processing requirements, such as the pipe's precision requirements and allowable error range, determine the quality standard of the final product. Pipe characteristics include factors affecting the processing, such as material, size, and wall thickness. The processing characteristic information is used as a constraint parameter and associated with the previously constructed hydraulic pipe bending control scheme space. Specifically, based on the material of the target pipe, schemes suitable for processing that material are selected from the scheme space; based on the size and wall thickness, the range of schemes is further narrowed to obtain a selection set of pipe bending control schemes that conforms to the processing characteristics of the target pipe. For example, if the target pipe is a special material with a large size and thick wall, then schemes that are suitable for this material and can adapt to the processing of large-size and thick-walled pipes will be selected from the scheme space to form the selection set.

[0018] Step S230: The bending control schemes in the selected set are evaluated and optimized according to the bending effect evaluation rules to obtain the initial bending control parameter scheme. Specifically, bending effect evaluation rules are formulated. These rules can consider multiple aspects, such as whether the processed pipe meets the precision requirements, whether it is stable during processing, energy consumption, processing time, etc. Each control scheme in the selected set is evaluated. By simulating the processing process or conducting small-scale experiments, the performance of each scheme in different aspects is observed. Based on the evaluation results, the scheme with the best performance is selected as the initial bending control parameter scheme. For example, if a scheme can achieve high-precision bending processing in the shortest time with the lowest energy consumption and the processing process is stable, then this scheme may be selected as the initial scheme.

[0019] Step S240 involves performing characteristic deviation analysis and adaptive optimization on the initial pipe bending control parameter scheme to obtain the target pipe bending control parameter scheme. Specifically, in practical applications, the initial pipe bending control parameter scheme may deviate due to various factors, such as changes in the processing environment and differences in pipe batches. Characteristic deviation analysis is performed on the initial scheme to identify potential problems, and then adaptive optimization is performed based on the actual situation. The adaptability and accuracy of the scheme can be improved by adjusting parameter values, changing the processing sequence, or adopting other optimization measures. After repeated analysis and adjustments, the target pipe bending control parameter scheme is finally obtained. This scheme can maximally meet the processing requirements of the target pipe, ensuring the stability and efficiency of the processing process. For example, if it is found in actual processing that the initial scheme causes uneven stress on the pipe, parameters such as bending force or bending angle can be adjusted to achieve better processing results, thereby obtaining the target scheme.

[0020] In one possible implementation, the initial pipe bending control parameter scheme is subjected to feature deviation analysis and adaptive optimization to obtain the target pipe bending control parameter scheme. Step S240 further includes step S241, which determines the initial pipe bending processing feature information based on the initial pipe bending control parameter scheme, and performs processing feature deviation analysis on the initial pipe bending processing feature information to obtain pipe processing feature deviation parameters. Specifically, firstly, based on the determined initial pipe bending control parameter scheme, the initial pipe bending processing feature information under this scheme can be derived. The feature information includes the expected bending angle, bending radius, pressure distribution during processing, etc. The initial pipe bending processing feature information is subjected to processing feature deviation analysis. In the actual processing process, due to the influence of various factors, the actual processing result may differ from the expected feature information. By comparing the actual processing situation with the expected features, these differences are identified, thereby obtaining the pipe processing feature deviation parameters. For example, if the initial scheme expects a specific bending angle, but the actual processed pipe angle deviates from the expected angle, this angle deviation value is one of the processing feature deviation parameters.

[0021] Step S242: Obtain the bending control element parameters and pipe processing characteristic parameters. Based on the hydraulic bending control scheme space, perform correlation fitting between each element parameter in the bending control element parameters and the pipe processing characteristic parameters to obtain a set of processing characteristic parameter-control element parameter functions. Specifically, obtain the bending control element parameters, which include, but are not limited to, bending pressure, bending angle, and processing speed. Simultaneously, obtain the pipe processing characteristic parameters, such as the pipe material, size, and wall thickness. Based on the hydraulic bending control scheme space, perform correlation fitting between each element parameter in the bending control element parameters and the pipe processing characteristic parameters. For example, according to the interpretation of "correlation fitting," perform data fitting between each element parameter, such as bending control pressure and angle, and the pipe processing characteristic parameters. Through fitting, the influence relationship of different bending control element parameters on the pipe processing characteristics can be understood. Each element parameter's fitting with the pipe processing characteristic parameters will yield a correlation function. Combining these correlation functions yields the set of processing characteristic parameter-control element parameter functions.

[0022] Step S243 involves fusing the processing feature parameter-control element parameter function set to generate a processing feature parameter-control element parameter function model. Specifically, the previously obtained processing feature parameter-control element parameter function set is fused. The fusion process can employ various methods, such as weighted average or principal component analysis. Through fusion, the individual functions are integrated into a comprehensive function model. This model can more comprehensively reflect the complex relationship between the pipe bending control element parameters and the pipe processing feature parameters. The generated processing feature parameter-control element parameter function model can be used to predict the processing characteristics of the pipe under different control parameters and can also provide a basis for subsequent adjustments.

[0023] Step S244: Based on the processing feature parameter-control element parameter function model, adaptively adjust the pipe processing feature deviation parameters to obtain the target pipe bending control parameter scheme. Specifically, using the generated processing feature parameter-control element parameter function model, adaptively adjust the previously obtained pipe processing feature deviation parameters. Based on the relationship between the control element parameters and processing feature parameters revealed by the model, determine how to adjust the bending control parameters to reduce processing feature deviation. Through continuous adjustment and optimization, the actual processing characteristics of the pipe gradually approach the expected target characteristics. After repeated adjustments and verifications, the target pipe bending control parameter scheme is finally obtained. This scheme can better adapt to actual processing conditions, ensuring that the processing quality and accuracy of the pipe meet the requirements.

[0024] Step S300: Pipe processing control is performed based on the target bending control parameter scheme. Simultaneously, the pipe processing control process is monitored in real time using the sensor group to acquire a pipe processing status monitoring data stream. Specifically, firstly, pipe processing is controlled based on the target bending control parameter scheme, which includes the optimal combination of processing parameters such as bending angle, bending force, and processing speed. The hydraulic pipe bending machine strictly adjusts its working state according to these parameters to ensure the accuracy and quality of pipe processing. Simultaneously, during the pipe processing control process, the sensor group built into the hydraulic pipe bending machine, including position sensors, angle sensors, and pressure sensors, monitors the processing process in real time. The position sensor determines the pipe position, the angle sensor monitors changes in the bending angle, and the pressure sensor monitors the pressure on the pipe. The data continuously generated by the sensor group forms a pipe processing status monitoring data stream, providing a basis for subsequent offset identification and correction analysis. It can also be used to evaluate the stability and quality of the processing process, providing data support for further optimization and adjustment.

[0025] Step S400: A multi-channel data deviation analysis is constructed using the control data processing module. Based on this multi-channel, the pipe processing status monitoring data stream is processed for offset identification to obtain pipe bending offset characteristic parameters. Specifically, the control data processing module, as the core component of the hydraulic pipe bending machine's automatic correction and control system, first designs a multi-data processing channel architecture based on the sensor group type information. Then, it performs data processing requirement analysis to determine preprocessing and deviation feature identification requirements. Following these requirements, it analyzes the processing flow of each data channel to obtain a multi-channel data preprocessing process set and a deviation feature identification algorithm set. These are then mapped and configured with the multi-data processing channel architecture information to construct the multi-channel data deviation analysis. After construction, the pipe processing status monitoring data stream is matched and mapped with the multi-channel. The data stream is analyzed and processed according to the associated information to obtain multiple offset feature identification parameters. Next, information on pipe bending offset influencing factors is obtained to determine the offset degree discrimination rule. Based on this rule, the multiple offset feature identification parameters are fused to determine the offset degree, ultimately obtaining the pipe bending offset characteristic parameters, providing an accurate basis for subsequent correction analysis.

[0026] In one possible implementation, the control data processing module constructs a multi-channel data deviation analysis system. Based on this system, the pipe processing status monitoring data stream is processed for offset identification to obtain bend offset characteristic parameters. Step S400 further includes step S410, whereby the control data processing module designs a multi-data processing channel architecture based on the sensor group type information. Specifically, firstly, the control data processing module needs to design a multi-data processing channel architecture based on the sensor group type information. The sensor group includes different types of sensors such as position sensors, angle sensors, and pressure sensors. Each type of sensor collects data with different characteristics and properties. For example, position sensors mainly provide the position information of the pipe during processing, and their data may require precise spatial positioning and tracking processing; angle sensors focus on measuring the angle change of the bend, and their data is crucial for the analysis of angle accuracy and change trends; pressure sensors monitor the pressure on the pipe, and their data reflects the mechanical state during processing. Based on the characteristics of different types of sensors, the control data processing module designs a corresponding multi-data processing channel architecture, allocating independent processing channels for the data from each sensor to better perform targeted data processing.

[0027] Step S420: Based on the multi-data processing channel architecture information, data processing requirements are analyzed sequentially to determine data preprocessing requirements and deviation feature identification requirements. Specifically, after designing the multi-data processing channel architecture, data processing requirements are analyzed sequentially based on this architecture. To determine the specific requirements for processing data from different sensors, for data preprocessing, considering that the data collected by the sensors may contain noise, interference, or non-standard conditions, corresponding processing is required to improve data quality. For example, for position sensor data, filtering is required to remove spatial clutter interference, making its position information more accurate; for angle sensor data, data normalization is required for better angle deviation analysis. Deviation feature identification requirements need to be determined, as different types of sensor data reflect different deviation characteristics. For position sensors, it may be necessary to identify whether the position offset exceeds the allowable range; for angle sensors, it is necessary to determine whether the angle deviation is within the acceptable range; for pressure sensors, it is necessary to pay attention to whether pressure changes are abnormal and whether they indicate problems in the processing process. Through this analysis, the specific requirements for processing different sensor data are clarified.

[0028] Step S430: Analyze the processing flow of each data channel in the multi-data processing channel architecture information according to the data preprocessing requirements and deviation feature identification requirements to obtain a multi-channel data preprocessing process set and a deviation feature identification algorithm set. Specifically, based on the determined data preprocessing requirements and deviation feature identification requirements, analyze the processing flow of each data channel in the multi-data processing channel architecture information. Specifically, analyze the data preprocessing process and corresponding deviation feature identification algorithm for each sensor's corresponding data processing channel. For the data preprocessing process analysis, for example, for the position sensor's data channel, determine the specific filtering algorithm and data smoothing steps to ensure the accuracy and stability of the position data. For the deviation feature identification algorithm analysis, for the angle sensor's data channel, design an algorithm based on the angle change rate to identify the characteristics of angle deviation. Through analysis, obtain the multi-channel data preprocessing process set, which includes the specific preprocessing steps and methods for each data channel; also obtain the deviation feature identification algorithm set, which includes specific deviation identification algorithms for different sensor data.

[0029] Step S440: Based on the multi-channel data preprocessing process set and the deviation feature identification algorithm set, map and configure them with the multi-data processing channel architecture information to construct the multi-channel data deviation analysis system. Specifically, based on the multi-channel data preprocessing process set and the deviation feature identification algorithm set, map and configure them with the multi-data processing channel architecture information to correspond and integrate the preprocessing processes and deviation feature identification algorithms with the corresponding data channels. For example, a specific preprocessing process and deviation identification algorithm for a position sensor are mapped to the position sensor's data channel to ensure that the channel can effectively preprocess and identify deviation features from the position sensor data. Through this mapping configuration, a multi-channel data deviation analysis system is constructed. This multi-channel system can perform specialized data processing for different types of sensor data, achieving comprehensive monitoring and deviation analysis of the pipe processing status, and providing accurate data support for subsequent correction control.

[0030] In one possible implementation, a multi-channel data deviation analysis is constructed through the control data processing module. Based on this multi-channel, offset identification processing is performed on the pipe processing status monitoring data stream to obtain bend offset characteristic parameters. Step S400 further includes step S450, matching and mapping the pipe processing status monitoring data stream and the multi-channel data deviation analysis to obtain associated data deviation analysis channel information. Specifically, firstly, the pipe processing status monitoring data stream is obtained in real-time through sensor arrays during pipe processing, containing various data information such as position, angle, and pressure. The multi-channel data deviation analysis is constructed by the control data processing module, with different processing channels for different types of sensor data. The purpose of matching and mapping the two is to determine which specific data deviation analysis channel each data point should enter for processing. For example, position data collected by a position sensor will be mapped to a channel specifically for processing position data. Through matching and mapping, associated data deviation analysis channel information can be obtained, clarifying the processing path for each data point and providing a basis for subsequent analysis and processing.

[0031] Step S460: The pipe processing status monitoring data stream is analyzed and processed according to the associated data deviation analysis channel information to obtain multi-offset feature identification parameters, including position deviation, angle deviation, and uneven stress. Specifically, the pipe processing status monitoring data stream is analyzed and processed based on the obtained associated data deviation analysis channel information. Different channels analyze different types of parameters. For the position data channel, the position change of the pipe during processing is analyzed to determine if there is a position deviation. If the actual position does not match the expected position, the position deviation parameter is determined. For the angle data channel, the angle deviation parameter is determined by comparing the actual bending angle with the target angle. For the pressure data channel, the pressure distribution on the pipe is analyzed to determine if there is uneven stress. Through the analysis and processing of each channel, multi-offset feature identification parameters are obtained, including position deviation, angle deviation, and uneven stress. These parameters reflect various offset situations that may occur during pipe processing.

[0032] Step S470: Obtain information on factors influencing pipe bending offset. This information includes processing requirements, pipe material characteristics, and the performance of the pipe bending machine. Specifically, the information includes processing requirements, pipe material characteristics, and the performance of the pipe bending machine. Processing requirements, such as the pipe's precision requirements and allowable error range, determine the tolerance for offset. For example, for pipes with high precision requirements, even a small deviation may be considered unacceptable. Pipe material characteristics include material, size, and wall thickness. Different materials have different physical properties, which affect the deformation and stress of the pipe during processing, thus affecting the degree of offset. Size and wall thickness also affect the processing. The performance of the pipe bending machine, such as stability and precision, also affects the offset. If the equipment performance is unstable, it may lead to large deviations during processing.

[0033] Step S480: Determine the offset degree discrimination rule based on the information on the influencing factors of pipe offset. Specifically, based on the acquired information on the influencing factors of pipe offset, the offset degree discrimination rule is determined. For example, if the processing requirements are very high, the tolerance for positional and angular deviations will be very low. Once a small deviation occurs, it is considered a serious offset. For pipes of different materials, the discrimination standard for uneven stress is determined based on their hardness, toughness, and other characteristics. For pipe bending machines with different performance, their accuracy and stability are considered to determine the corresponding offset discrimination rule. In this way, appropriate offset degree discrimination standards are formulated for different situations in order to accurately assess the severity of the offset.

[0034] Step S490: Based on the offset degree discrimination rule, the multiple offset feature identification parameters are fused to obtain the pipe offset feature parameters. Specifically, based on the determined offset degree discrimination rule, the multiple offset feature identification parameters are fused to determine the offset degree. Parameters such as position deviation, angle deviation, and uneven force are comprehensively evaluated according to the discrimination rule. For example, if the position deviation and angle deviation are within a certain range, but the uneven force is more serious, the overall offset degree is determined according to the discrimination rule. Through the fusion processing of the parameters, the pipe offset feature parameters are obtained. The parameters comprehensively reflect the offset of the pipe during the processing, including the type and severity of the offset, providing an accurate basis for subsequent correction analysis and control.

[0035] Step S500 involves performing a correction analysis on the bend offset characteristic parameters to obtain bend correction control parameters. The correction adjustment mechanism then performs automatic correction processing control on the target pipe according to these parameters. Specifically, firstly, the bend offset characteristic parameters are analyzed, which involves constructing a correction control strategy library. Correction strategies are analyzed on the parameters to determine suitable strategies. These strategies are then used to further analyze and determine the fine-tuning threshold for the correction strategy parameters. Within this threshold, multiple correction strategy parameters are randomly selected and simulated to generate simulation effects for multiple correction parameters. Based on the simulation effects, the threshold is locally optimized to obtain the bend correction control parameters. The correction and adjustment mechanism automatically corrects the deviation of the target pipe according to the control parameters. If the parameters indicate that the position needs to be adjusted, the mechanism will precisely move the position of the pipe. For angular deviations, it will adjust the bending angle setting of the pipe bending machine or use auxiliary tools for fine adjustment. For uneven force, it will adjust the pressure distribution or processing speed. Throughout the process, it continuously adjusts in real time according to the control parameters to ensure that the pipe processing is within the accuracy requirements and error range, improves processing quality and efficiency, reduces scrap rate, and provides an efficient and accurate hydraulic pipe bending solution for the metal processing industry.

[0036] In one possible implementation, the pipe offset characteristic parameters are analyzed to obtain pipe offset control parameters. The offset adjustment mechanism performs automatic offset processing control on the target pipe according to the pipe offset control parameters. Step S500 further includes step S510, constructing an offset control strategy library, and performing offset strategy analysis on the pipe offset characteristic parameters based on the offset control strategy library to obtain a pipe offset control adaptation strategy. Specifically, the first step is to construct a correction control strategy library. This library is the foundational resource for the entire correction process, containing various correction methods and strategies for different types of pipe deviation. For example, for positional deviations, strategies might include adjusting the pipe position or changing the direction of the bending force; for angular deviations, strategies might include adjusting the angle setting of the pipe bending machine or using auxiliary tools to correct the angle; and for uneven stress, strategies might include optimizing pressure distribution or adjusting the processing speed. After obtaining the characteristic parameters of the pipe deviation, correction strategies are analyzed based on these parameters using the correction control strategy library. During the analysis, based on the specific type and degree of pipe deviation, potentially applicable correction strategies are selected from the strategy library. If the characteristic parameters of the pipe deviation indicate that the positional deviation is the main issue, then strategies targeting positional deviations are selected from the strategy library for evaluation. By analyzing and comparing various possible strategies, the most suitable correction strategy for the current pipe deviation situation is determined, thus obtaining the pipe deviation correction control adaptation strategy.

[0037] Step S520: The bending pipe offset characteristic parameters are analyzed using the bending pipe correction control adaptation strategy to determine the fine-tuning threshold of the correction strategy parameters. Specifically, after determining the bending pipe correction control adaptation strategy, this strategy is used to further analyze the bending pipe offset characteristic parameters. During this process, it is necessary to determine the fine-tuning threshold of the correction strategy parameters. The threshold limits the adjustment range of the correction parameters to ensure that over-adjustment does not lead to other problems during correction. For example, if the adaptation strategy uses bending force to correct positional deviation, then the adjustment range of the bending force needs to be determined; this range is the fine-tuning threshold of the correction strategy parameters. Through in-depth analysis of the adaptation strategy and understanding of the bending pipe offset characteristic parameters, a reasonable fine-tuning threshold is determined, providing boundary conditions for subsequent parameter selection and adjustment.

[0038] Step S530: Randomly select multiple correction strategy parameters within the fine-tuning threshold of the correction strategy parameters, and perform simulation evaluation on the multiple correction strategy parameters to generate multiple correction parameter simulation effects. Specifically, after determining the fine-tuning threshold of the correction strategy parameters, multiple correction strategy parameters are randomly selected within the threshold range. The parameters represent different correction scheme possibilities. For example, if the fine-tuning threshold is the adjustment of the bending force within a certain range, then different bending force values ​​are randomly selected as correction strategy parameters. Simulation evaluation is performed on the multiple correction strategy parameters. By establishing a mathematical model or using simulation software to simulate the bending process under different parameters, the correction effect on the bending deviation is predicted. Through simulation evaluation, the correction effect corresponding to each correction strategy parameter is obtained, that is, multiple correction parameter simulation effects are generated. These simulation effects may include information such as the degree of reduction in position deviation, the correction of angle deviation, and the degree of improvement in uneven force distribution.

[0039] Step S540: Based on the simulation effects of the multiple correction parameters, locally optimize the fine-tuning threshold of the correction strategy parameters to obtain the pipe bending correction control parameters. Specifically, the local optimization of the fine-tuning threshold of the correction strategy parameters based on the simulation effects of multiple correction parameters can employ optimization algorithms, such as gradient ascent or genetic algorithms. By analyzing the simulation effects of multiple correction parameters, it is determined which parameters can bring better correction effects. Within the fine-tuning threshold range, the parameter selection is continuously adjusted according to the optimization algorithm to find the optimal combination of correction strategy parameters. After repeated optimization processes, the parameters that can correct the pipe bending offset to the greatest extent are finally obtained, i.e., the pipe bending correction control parameters. These parameters will be used in the actual pipe bending process, where the correction adjustment mechanism automatically controls the correction processing of the target pipe to ensure the accuracy and quality of pipe processing.

[0040] In one possible implementation, the fine-tuning threshold of the correction strategy parameters is locally optimized based on the simulation effect of the multiple correction parameters to obtain the correction control parameters of the bend pipe. Step S540 further includes step S541, which calculates the gradient ascent and divides the interval comparison based on the simulation effect of the multiple correction parameters to determine the local optimization interval of the parameters. Specifically, firstly, the simulation effects of multiple correction parameters are obtained by simulating and evaluating multiple correction strategy parameters randomly selected within the fine-tuning threshold of the correction strategy parameters. The simulation effects reflect the correction effect on the pipe deviation under different parameter combinations. When performing gradient ascent calculation, the influence trend of each correction parameter on the correction effect is analyzed. If the change of a certain parameter leads to a better correction effect, then further exploration is carried out along this direction. For example, if increasing a certain bending force value makes the position deviation decrease faster, then it indicates that there is an upward trend in the direction of this parameter. Next, interval comparison and division are performed. Since the faster the gradient ascent, the faster the parameter effect improvement efficiency, the parameter interval is further divided according to the direction of the fastest gradient ascent. For example, if the analysis finds that the gradient ascent in a certain parameter interval is significantly faster than that in other intervals, then this interval is taken as the key focus area and divided more finely. In this way, the local optimization interval of the parameter is determined, the range of subsequent parameter search is narrowed, and the optimization efficiency is improved.

[0041] Step S542 involves iterative parameter selection and effect evaluation within the local parameter optimization interval, continuing until a preset number of iterations is reached to obtain the parameter optimization approximation interval. Specifically, after determining the local parameter optimization interval, iterative parameter selection and effect evaluation are performed within the interval. First, a set of correction strategy parameters is randomly selected within the local parameter optimization interval. Then, the parameters are evaluated for their effects, similar to the previous simulation evaluation of multiple correction parameters, to determine the corrective effect of the parameters on the pipe deviation. Next, gradient ascent calculation and interval comparison are performed. Based on the evaluation results, the local parameter optimization interval is further divided according to the direction of the fastest gradient ascent, narrowing the parameter search range. The above steps are repeated, performing random parameter selection, effect evaluation optimization, gradient ascent calculation, and interval comparison within the local parameter optimization interval until a preset number of iterations is reached. With each iteration, the parameter interval is continuously refined and optimized, gradually approaching the region where the optimal parameter combination is located. By continuously iterating and approximating, the parameter optimization efficiency is improved, ultimately obtaining the parameter optimization approximation interval. This interval is closer to the optimal pipe deviation correction control parameters than the initial local parameter optimization interval.

[0042] Step S543: Parameters are compared and optimized within the parameter optimization approximation interval according to a preset local step size to obtain the bend correction control parameters. Specifically, after obtaining the parameter optimization approximation interval, the parameters within this interval are compared and optimized according to a preset local step size. The preset local step size determines the precision of the parameter search. For example, if the step size is small, the parameter search will be more detailed, but it may require more computation time; if the step size is large, the search speed will be faster, but some better parameter combinations may be missed. Within the parameter optimization approximation interval, the parameters are gradually adjusted with the preset local step size, and each parameter combination is evaluated. The correction effect of different parameter combinations is compared, and the parameter combination with the best effect is selected. Through continuous comparison and adjustment, the bend correction control parameters are finally obtained. The parameters are the optimal solution obtained after a series of calculations, divisions, and optimization processes, which can correct the bend offset to the greatest extent and ensure the accuracy and quality of pipe processing.

[0043] This application embodiment employs a hydraulic automatic pipe bending machine for metal processing, which acquires a built-in sensor group (including position, angle, and pressure sensors), a control data processing module, and a correction and adjustment mechanism. The hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and target pipe processing characteristic information, performs matching analysis and optimization, and obtains a target pipe bending control parameter scheme. Based on the scheme, pipe processing control is performed, and the sensor group monitors and acquires data streams in real time. The control data processing module constructs multi-channel pipe bending offset characteristic parameters to identify offsets in the data stream, and then performs correction analysis to obtain pipe bending correction control parameters. The correction and adjustment mechanism automatically corrects the processing of the target pipe. Through automatic and accurate correction, it adapts to different pipe processing requirements and characteristics, achieving the technical effect of improving processing accuracy and stability.

[0044] In the above text, refer to Figure 1 The automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 An automatic correction and control device for a hydraulic pipe bending machine for metal processing according to an embodiment of the present invention is described.

[0045] The automatic deviation correction and control device for a hydraulic pipe bending machine according to an embodiment of the present invention solves the technical problems of inconsistent processing accuracy and quality caused by the inability to adapt to different pipe material requirements in existing hydraulic pipe bending processes. By automatically and accurately correcting deviations, it adapts to the processing requirements and characteristics of different pipe materials, achieving the technical effect of improving processing accuracy and stability. The automatic deviation correction and control device for a hydraulic pipe bending machine includes: a pipe bending machine acquisition module 10, a processing feature information acquisition module 20, a pipe processing control module 30, an offset identification and processing module 40, and a pipe bending deviation control parameter acquisition module 50.

[0046] The pipe bending machine acquisition module 10 is used to acquire a hydraulic automatic pipe bending machine for metal processing. The hydraulic automatic pipe bending machine for metal processing has a built-in sensor group, a control data processing module, and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor, and a pressure sensor.

[0047] The processing feature information acquisition module 20 is used to acquire the hydraulic pipe bending control database and the processing feature information of the target pipe through the hydraulic pipe bending machine production system, and to perform matching analysis and optimization based on the processing feature information and the hydraulic pipe bending control database to obtain the target pipe bending control parameter scheme.

[0048] The pipe processing control module 30 is used to control the pipe processing based on the target bend control parameter scheme, and at the same time, it monitors the pipe processing control process in real time through the sensor group to obtain the pipe processing status monitoring data stream.

[0049] The offset identification and processing module 40 is used to construct a multi-channel data deviation analysis through the control data processing module, and perform offset identification processing on the pipe processing status monitoring data stream based on the multi-channel data deviation analysis to obtain the pipe offset characteristic parameters.

[0050] The pipe bending correction control parameter acquisition module 50 is used to perform correction analysis on the pipe bending offset characteristic parameters to obtain pipe bending correction control parameters. The correction adjustment mechanism performs automatic correction processing control on the target pipe according to the pipe bending correction control parameters.

[0051] The specific configuration of the processing feature information acquisition module 20 will be described in detail below. As described above, the hydraulic pipe bending machine production system acquires a hydraulic pipe bending control database and processing feature information of the target pipe. Based on the processing feature information and the hydraulic pipe bending control database, matching analysis and optimization are performed to obtain a target pipe bending control parameter scheme. The processing feature information acquisition module 20 further includes: an attribute matching and partitioning unit, which is used to perform attribute matching and partitioning based on the specification attribute information of the hydraulic automatic pipe bending machine for metal processing and the hydraulic pipe bending control database to construct a hydraulic pipe bending control scheme space; a constraint feature association unit, which uses the processing feature information of the target pipe as constraint parameters and performs constraint feature association with the hydraulic pipe bending control scheme space to obtain a set of pipe bending control schemes; an effect evaluation and optimization unit, which performs effect evaluation and optimization on each control scheme in the set of pipe bending control schemes according to the pipe bending effect evaluation rules to obtain an initial pipe bending control parameter scheme; and a control parameter scheme acquisition unit, which performs feature deviation analysis and adaptive optimization on the initial pipe bending control parameter scheme to obtain the target pipe bending control parameter scheme.

[0052] The initial pipe bending control parameter scheme is subjected to feature deviation analysis and adaptive optimization to obtain the target pipe bending control parameter scheme. The control parameter scheme acquisition unit further includes: an initial pipe bending processing feature information determination subunit, which determines initial pipe bending processing feature information based on the initial pipe bending control parameter scheme, performs processing feature deviation analysis on the initial pipe bending processing feature information, and obtains pipe processing feature deviation parameters; and a function set acquisition subunit, which acquires pipe bending control element parameters and pipe processing feature parameters based on the liquid... The bending pipe control scheme space correlates and fits each element parameter in the bending pipe control element parameters with the pipe processing characteristic parameters to obtain a set of processing characteristic parameters-control element parameter functions; the element fusion subunit is used to fuse the set of processing characteristic parameters-control element parameter functions to generate a processing characteristic parameter-control element parameter function model; the adaptive adjustment subunit is used to adaptively adjust the pipe processing characteristic deviation parameters based on the processing characteristic parameter-control element parameter function model to obtain the target bending pipe control parameter scheme.

[0053] The specific configuration of the offset identification processing module 40 will be described in detail below. As mentioned above, the control data processing module constructs a multi-channel data deviation analysis system. Based on the multi-channel data deviation analysis, the pipe processing status monitoring data stream is subjected to offset identification processing to obtain the pipe offset characteristic parameters. The offset identification processing module 40 further includes: a channel architecture information design unit, which is used by the control data processing module to design multi-data processing channel architecture information according to the type information of the sensor group; a data processing requirement analysis unit, which is used to perform data processing requirement analysis sequentially based on the multi-data processing channel architecture information to determine data preprocessing requirements and deviation feature identification requirements; a processing flow analysis unit, which is used to perform processing flow analysis on each data channel in the multi-data processing channel architecture information according to the data preprocessing requirements and deviation feature identification requirements to obtain a multi-channel data preprocessing process set and a deviation feature identification algorithm set; and a mapping configuration unit, which is used to map and configure the multi-channel data deviation analysis system with the multi-data processing channel architecture information based on the multi-channel data preprocessing process set and the deviation feature identification algorithm set, respectively, to construct the multi-channel data deviation analysis system.

[0054] The offset recognition and processing module 40 may further include: a deviation analysis channel information acquisition unit, which is used to match and map the pipe processing status monitoring data stream and the data deviation analysis multi-channel to obtain associated data deviation analysis channel information; a multi-offset feature recognition parameter acquisition unit, which is used to analyze and process the pipe processing status monitoring data stream according to the associated data deviation analysis channel information to obtain multi-offset feature recognition parameters, including position deviation, angle deviation, and uneven force; an offset influencing factor information acquisition unit, which is used to acquire bending offset influencing factor information, including processing requirements, pipe characteristics, and bending machine equipment performance; an offset degree discrimination rule determination unit, which is used to determine the offset degree discrimination rule based on the bending offset influencing factor information; and an offset degree discrimination fusion unit, which is used to perform offset degree discrimination fusion on the multi-offset feature recognition parameters based on the offset degree discrimination rule to obtain the bending offset feature parameters.

[0055] The specific configuration of the pipe bending correction control parameter acquisition module 50 will be described in detail below. As mentioned above, the pipe bending offset characteristic parameters are analyzed to obtain pipe bending correction control parameters. The correction adjustment mechanism performs automatic correction processing control on the target pipe according to the pipe bending correction control parameters. The pipe bending correction control parameter acquisition module 50 further includes: a correction control strategy library construction unit, which is used to construct a correction control strategy library and perform correction strategy analysis on the pipe bending offset characteristic parameters based on the correction control strategy library to obtain a pipe bending correction control adaptation strategy; and a correction strategy parameter fine-tuning threshold determination unit, which determines the correction strategy... The parameter fine-tuning threshold determination unit is used to perform correction analysis on the bend offset characteristic parameters using the bend correction control adaptation strategy to determine the fine-tuning threshold of the correction strategy parameters; the simulation evaluation unit is used to randomly select multiple correction strategy parameters within the fine-tuning threshold of the correction strategy parameters and perform simulation evaluation on the multiple correction strategy parameters to generate multiple correction parameter simulation effects; the local optimization unit is used to perform local optimization on the fine-tuning threshold of the correction strategy parameters based on the simulation effects of the multiple correction parameters to obtain the bend correction control parameters.

[0056] The process involves locally optimizing the fine-tuning threshold of the correction strategy parameters based on the simulation results of the multiple correction parameters to obtain the pipe correction control parameters. The local optimization unit further includes: an optimization interval determination subunit, used to perform gradient ascent calculation and interval comparison division on the fine-tuning threshold of the correction strategy parameters based on the simulation results of the multiple correction parameters to determine the local optimization interval for the parameters; an optimization approximation interval acquisition subunit, used to perform iterative parameter selection and effect evaluation division within the local optimization interval for the parameters until a preset number of iterations is reached to obtain the parameter optimization approximation interval; and a pipe correction control parameter acquisition subunit, used to perform parameter comparison and optimization within the parameter optimization approximation interval according to a preset local step size to obtain the pipe correction control parameters.

[0057] The automatic correction and control device for a hydraulic pipe bending machine for metal processing provided in this embodiment of the invention can execute the automatic correction and control method for a hydraulic pipe bending machine for metal processing provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0058] Although this application makes various references to certain modules in the apparatus according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to 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 each functional unit are only for easy distinction between each other and are not intended to limit the scope of protection of this invention.

[0059] The specific embodiments described above do not constitute a limitation on the scope of protection 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 principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An automatic deviation correction and control method for a hydraulic pipe bending machine used in metal processing, characterized in that, The method includes: A hydraulic automatic pipe bending machine for metal processing is obtained. The hydraulic automatic pipe bending machine for metal processing has a built-in sensor group, a control data processing module and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor and a pressure sensor. The hydraulic pipe bending machine production system acquires the hydraulic pipe bending control database and the processing feature information of the target pipe. Based on the processing feature information and the hydraulic pipe bending control database, a matching analysis and optimization are performed to obtain the target pipe bending control parameter scheme. Pipe processing control is performed based on the target bend control parameter scheme, and the pipe processing control process is monitored in real time through the sensor group to obtain pipe processing status monitoring data stream; The control data processing module constructs a multi-channel data deviation analysis system, and performs offset identification processing on the pipe processing status monitoring data stream based on the multi-channel data deviation analysis system to obtain the pipe offset characteristic parameters. The deviation characteristic parameters of the bend are analyzed to obtain the bend correction control parameters. The correction adjustment mechanism performs automatic correction processing control on the target pipe according to the bend correction control parameters.

2. The automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 1, characterized in that, The scheme for obtaining the target bend control parameters includes: Based on the specification and attribute information of the hydraulic automatic pipe bending machine for metal processing, attribute matching and division are performed with the hydraulic pipe bending control database to construct a hydraulic pipe bending control scheme space. The processing characteristics of the target pipe are used as constraint parameters and associated with the constraint characteristics of the hydraulic pipe bending control scheme space to obtain a set of pipe bending control schemes. According to the pipe bending effect evaluation rules, the effect of each control scheme in the selected set of pipe bending control schemes is evaluated and optimized to obtain the initial pipe bending control parameter scheme. The initial pipe bending control parameter scheme is subjected to characteristic deviation analysis and adaptive optimization to obtain the target pipe bending control parameter scheme.

3. The automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 2, characterized in that, The scheme for obtaining the target bend control parameters includes: Based on the initial pipe bending control parameter scheme, the initial pipe bending processing characteristic information is determined, and the processing characteristic deviation analysis is performed on the initial pipe bending processing characteristic information to obtain the pipe processing characteristic deviation parameters. Obtain the pipe bending control element parameters and pipe processing characteristic parameters. Based on the hydraulic pipe bending control scheme space, perform correlation fitting between each element parameter in the pipe bending control element parameters and the pipe processing characteristic parameters to obtain the processing characteristic parameter-control element parameter function set. The set of processing feature parameters and control element parameter functions is fused to generate a processing feature parameter and control element parameter function model. Based on the processing characteristic parameter-control element parameter function model, the pipe processing characteristic deviation parameters are adaptively adjusted to obtain the target bend pipe control parameter scheme.

4. The automatic correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 1, characterized in that, The construction of the multi-channel data deviation analysis includes: The control data processing module designs a multi-data processing channel architecture based on the type information of the sensor group. Based on the multi-data processing channel architecture information, data processing requirements are analyzed sequentially to determine data preprocessing requirements and deviation feature identification requirements. Based on the data preprocessing requirements and deviation feature identification requirements, the processing flow of each data channel in the multi-data processing channel architecture information is analyzed to obtain a multi-channel data preprocessing process set and a deviation feature identification algorithm set. Based on the set of multi-channel data preprocessing processes and the set of deviation feature identification algorithms, the data deviation analysis multi-channel is constructed by mapping and configuring them with the multi-data processing channel architecture information.

5. The automatic correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 1, characterized in that, The obtained bend offset characteristic parameters include: The pipe processing status monitoring data stream and the data deviation analysis multi-channel are matched and mapped to obtain the associated data deviation analysis channel information; The pipe processing status monitoring data stream is analyzed and processed according to the associated data deviation analysis channel information to obtain multi-offset feature identification parameters, which include position deviation, angle deviation and uneven force. Obtain information on factors influencing pipe offset, including processing requirements, pipe material characteristics, and pipe bending machine performance. Based on the information on factors affecting pipe offset, determine the offset degree discrimination rules; Based on the offset degree discrimination rule, the offset degree discrimination and fusion of the multiple offset feature recognition parameters are performed to obtain the pipe offset feature parameters.

6. The automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 1, characterized in that, The obtained pipe bending correction control parameters include: A correction control strategy library is constructed, and the correction strategy analysis is performed on the bend offset characteristic parameters based on the correction control strategy library to obtain the bend correction control adaptation strategy. The aforementioned pipe correction control adaptation strategy is used to perform correction analysis on the pipe offset characteristic parameters to determine the fine-tuning threshold of the correction strategy parameters. Multiple correction strategy parameters are randomly selected within the fine-tuning threshold of the correction strategy parameters, and the multiple correction strategy parameters are simulated and evaluated to generate multiple correction parameter simulation effects. Based on the simulation results of the multiple correction parameters, the threshold for fine-tuning the correction strategy parameters is locally optimized to obtain the correction control parameters for the bend pipe.

7. The automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing as described in claim 6, characterized in that, Obtaining the bending pipe correction control parameters includes: Based on the simulation results of the multiple correction parameters, the gradient ascent calculation and interval comparison division of the fine-tuning threshold of the correction strategy parameters are performed to determine the local optimization interval of the parameters. Within the local optimization interval of the parameters, iterative parameter selection and effect evaluation are performed until a preset number of iterations are reached to obtain the parameter optimization approximation interval. The parameters are compared and optimized within the parameter optimization approximation interval according to a preset local step size to obtain the bending pipe correction control parameters.

8. An automatic deviation correction and control device for a hydraulic pipe bending machine used in metal processing, characterized in that, The device is used to implement the automatic deviation correction and control method for a hydraulic pipe bending machine for metal processing according to any one of claims 1-7, and the device comprises: A pipe bending machine acquisition module is used to acquire a hydraulic automatic pipe bending machine for metal processing. The hydraulic automatic pipe bending machine for metal processing has a built-in sensor group, a control data processing module, and a correction and adjustment mechanism. The sensor group includes a position sensor, an angle sensor, and a pressure sensor. The processing feature information acquisition module is used to acquire the processing feature information of the hydraulic pipe bending control database and the target pipe through the hydraulic pipe bending machine production system, and to perform matching analysis and optimization based on the processing feature information and the hydraulic pipe bending control database to obtain the target pipe bending control parameter scheme. The pipe processing control module is used to control the pipe processing based on the target bend control parameter scheme, and at the same time, it monitors the pipe processing control process in real time through the sensor group to obtain the pipe processing status monitoring data stream; Offset recognition and processing module, which is used to construct a data deviation analysis multi-channel through the control data processing module, and perform offset recognition processing on the pipe processing status monitoring data stream based on the data deviation analysis multi-channel to obtain the bend offset characteristic parameters; A bend correction control parameter acquisition module is used to perform correction analysis on the bend offset characteristic parameters to obtain bend correction control parameters. The correction adjustment mechanism performs automatic correction processing control on the target pipe according to the bend correction control parameters.

Images