Multi-dimensional optimization method for precision control of wire arranging at wire collecting end of diamond wire

Abstract

The application provides a multi-dimensional optimization diamond wire winding end wire arranging precision control method, and belongs to the technical field of diamond wire production and processing. The application predicts and identifies potential conflicts among multiple control targets such as wire arranging speed matching, wire tension stability and equipment vibration suppression, and resolves the conflicts. Based on a dynamic priority mediation collaborative optimization decision mechanism, the application avoids negative effects caused by a single control action on other system states from the root, realizes systematic stability under complex working conditions, and essentially improves the final wire arranging precision and winding uniformity. Through continuous comparison of actual feedback data and model prediction data, the system can not only finely calibrate internal parameters of the existing model, but also independently learn and generate new feature sub-models to describe unknown interference modes. The double evolution mechanism enables the core model of the control system to independently adapt to long-term or sudden working condition changes such as equipment wear and material property changes.

Description

Technical Field

[0001] This invention relates to the field of diamond wire production and processing technology, and in particular to a multi-dimensional optimization method for controlling the accuracy of diamond wire take-up end wiring. Background Technology

[0002] Diamond wire, or simply diamond wire, is a key consumable used in precision machining fields such as photovoltaics and semiconductors. In the production or use of diamond wire, take-up and winding is a core step. Its purpose is to wind long and thin diamond wires tightly and neatly onto the take-up spool. The quality of winding directly affects the storage, transportation, and subsequent processing of diamond wire, as well as the stability and product qualification rate of the subsequent processing steps.

[0003] In existing technologies, the control of diamond wire laying typically relies on computer-based servo control systems. A common approach is to use a closed-loop feedback system based on a proportional-integral-derivative (PID) control algorithm. This system obtains the rotational speed of the take-up spool and the actual position of the laying mechanism through an encoder. The computer calculates the theoretical lateral speed of the laying mechanism based on the take-up spool's rotational speed and compares it with the actual speed of the laying mechanism. By adjusting the output of the servo motor, speed or position errors are reduced. Some more complex systems introduce an additional independent tension control loop, which adjusts the torque of the take-up and untake-up motors based on the feedback signal from the tension sensor to maintain the wire tension within a certain range.

[0004] Existing technical solutions have obvious shortcomings in practical applications. Their control models are usually based on fixed parameters and cannot adapt to dynamic changes caused by mechanical wear, assembly tolerances, or differences in the physical properties of wires from different batches. Their control logic is essentially reactive, meaning that compensation adjustments are only made after an error is detected. For high-speed operation or conditions prone to errors, such as reversal points, this lag adjustment cannot fundamentally prevent wire overlap or gaps. Each control loop, such as speed control and tension control, is usually calculated and executed independently, failing to fully consider the complex coupling effects between multi-dimensional variables. This often results in some aspects being neglected while others are addressed, making it difficult to achieve the optimal overall control effect of the system. Summary of the Invention

[0005] This invention provides a multi-dimensional optimization method for controlling the accuracy of diamond wire take-up end wiring. It employs a calculation method that uses a dynamic evolution model to perform forward-looking conflict prediction and collaborative optimization decision-making, thereby achieving global closed-loop control of multiple variables in the wiring process.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a multi-dimensional optimization method for controlling the precision of diamond wire take-up end wiring is provided, specifically including the following steps: Acquire real-time operating status data of the cable receiving equipment; Based on the real-time operating status data, a dynamic mirror model representing the current operating characteristics of the device is dynamically generated; The dynamic mirror model is used to perform predictive simulations of the future cabling process, and potential cabling physical errors and potential conflicts between multiple control objectives are identified from the simulation results. Based on a production stage objective that defines the current core production requirements, and in conjunction with the identified potential conflicts, the optimization priorities of the multiple control objectives are dynamically adjusted to generate a dynamic priority configuration. Using the aforementioned dynamic priority configuration as the optimization guide, multi-objective optimization is performed to generate collaborative optimization control instructions; Obtain the actual operational response data and cable quality data generated after executing the collaborative optimization control command; Based on the actual operational response data and cable quality data, an evolution update operation is performed on the dynamic mirror model.

[0007] Optionally, the step of dynamically generating a dynamic mirror model representing the current operating characteristics of the device based on the real-time operating status data includes: Call a model library that contains a baseline sub-model and multiple feature sub-models; Analyze the characteristic patterns of the real-time operating status data, and select at least one target sub-model from the model library based on the characteristic patterns; Assign a dynamic weight to each of the selected target sub-models; The target sub-model is weighted and fused according to the dynamic weights to generate the dynamic mirror model.

[0008] Optionally, the step of performing predictive simulation of the future cabling process using the dynamic mirror model and identifying potential cabling physical errors and potential conflicts between multiple control objectives from the simulation results includes: Input the current control parameters into the dynamic mirror model, perform a short-time-domain wiring process simulation calculation, and extract the predicted wiring physical error data from the simulation results; Calculate a corrective control action to eliminate the predicted wiring physical error data, and evaluate the negative impact of the corrective control action on other control objectives in the dynamic mirror model; When the negative impact exceeds a threshold used to define an acceptable range of disturbances, the potential conflict is determined to exist.

[0009] Optionally, the potential conflicts between the plurality of control objectives include at least: The conflict between the corrective control action generated to achieve the target of matching accuracy in wire winding speed and the target of stable wire tension control aimed at ensuring winding tightness; And / or, the conflict between the corrective control action generated to achieve the wire speed matching accuracy control target and the equipment vibration suppression control target aimed at ensuring long-term stable operation of the system.

[0010] Optionally, the potential conflicts between the plurality of control objectives include at least: The conflict between the corrective control action generated to achieve the target of matching accuracy in wire winding speed and the target of stable wire tension control aimed at ensuring winding tightness; And / or, the conflict between the corrective control action generated to achieve the wire speed matching accuracy control target and the equipment vibration suppression control target aimed at ensuring long-term stable operation of the system.

[0011] Optionally, the step of performing an evolutionary update operation on the dynamic mirror model includes: By comparing the actual operational response data with the prior predicted data of the dynamic mirror model, the first deviation data is obtained; Based on the first deviation data, the internal parameters of the dynamic mirror model are calibrated; Analyze the actual operational response data and cable quality data to determine whether there are any systematic deviations caused by unmodeled interference patterns; When the systematic deviation is determined to exist, a new feature sub-model is generated based on the data related to the systematic deviation, and the new feature sub-model is added to the model library that can provide components for the dynamic mirror model.

[0012] Optionally, after the step of obtaining the real-time operating status data, the method further includes: Spectral analysis is performed on the equipment vibration data in the real-time operating status data to obtain the dominant vibration frequency and amplitude characteristics; The step of selecting at least one target sub-model from the model library based on the feature pattern is specifically as follows: Based on the dominant vibration frequency and amplitude characteristics, one or more of the feature sub-models with the highest correlation to the current vibration mode are selected from the model library as the target sub-model.

[0013] Optionally, the step of obtaining the actual operating response data and cable quality data generated after executing the collaborative optimization control command includes: Images of the fabricated cabling layers are acquired using a machine vision system, and the images are processed and analyzed to extract the actual line spacing data and cabling straightness data, which are used as the cabling quality data. The actual vibration change data and wire tension fluctuation data of the take-up device are recorded synchronously during the execution of the collaborative optimization control command, and are used as the actual operation response data.

[0014] Optionally, the step of calibrating the internal parameters of the dynamic mirror model has a synergistic effect with the step of adding the new feature sub-model to the model library; The calibration step corrects the model parameters to make the dynamic mirror model fit the known characteristics of the current device more accurately. The addition step expands the model structure, enabling the dynamic mirror model to describe new interference patterns. The combination of the two enhances both the accuracy and breadth of the dynamic mirror model, with the enhancement effect being superior to the sum of the effects that could be achieved by performing either step alone, thereby improving the overall effect of subsequent prediction simulation and co-optimization.

[0015] Secondly, a diamond wire take-up and lay-up coordinated control system is provided, including: The data sensing module is configured to acquire real-time operating status data of the receiving equipment; The dynamic modeling module is configured to dynamically generate a dynamic mirror model based on the real-time running status data. The prediction and conflict identification module is configured to perform predictive simulations using the dynamic mirror model and identify potential conflicts. The collaborative optimization decision-making module is configured to dynamically adjust the priority of control targets and generate collaborative optimization control instructions. The feedback acquisition module is configured to collect actual operational response data and cable quality data. The model evolution module is configured to perform evolution update operations on the dynamic mirror model based on the actual running response data and the cable quality data.

[0016] Thirdly, an electronic device is provided, comprising: a processor and a memory; the memory is used to store a computer program, which, when executed by the processor, causes the electronic device to perform the multi-dimensional optimized diamond wire take-up end wiring accuracy control method described in the first aspect.

[0017] In one possible design, the electronic device described in the third aspect may further include a transceiver. This transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the electronic device described in the third aspect and other electronic devices.

[0018] In the embodiments of the present invention, the electronic device described in the third aspect may be a terminal, or a chip (system) or other component or assembly disposed in the terminal, or a system containing the terminal.

[0019] Fourthly, a computer-readable storage medium is provided, comprising: a computer program or instructions; when the computer program or instructions are executed on a computer, the computer causes the computer to perform the multi-dimensional optimized diamond wire take-up end wiring accuracy control method described in the first aspect.

[0020] In summary, the above methods and systems have the following technical effects: This invention predicts and identifies potential conflicts between multiple control objectives, such as wire speed matching, wire tension stability, and equipment vibration suppression, and resolves them. Based on a collaborative optimization decision-making mechanism with dynamic priority adjustment, it fundamentally avoids the negative impact of a single control action on other system states, achieving system stability under complex operating conditions. This fundamentally improves the final wire laying accuracy and winding uniformity. By continuously comparing actual feedback data with model prediction data, the system can not only finely calibrate the internal parameters of the existing model but also autonomously learn and generate new feature sub-models to describe unknown disturbance patterns. This dual evolution mechanism enables the core module of the control system to... This system can autonomously adapt to long-term or sudden changes in operating conditions such as equipment wear and material properties, reducing the need for manual intervention and readjustment, and ensuring the long-term stability of the production process and the consistency of product quality. By deeply integrating multi-dimensional real-time data, dynamically evolving predictive models, and globally collaborative optimization decision-making algorithms, an intelligent closed-loop control system is constructed. This system achieves intelligent control of the entire wiring process from perception, prediction, decision-making to learning. Its overall control performance far exceeds the simple sum of the effects of individual technical units. While significantly improving the quality of diamond wire winding, it also provides a solid technical foundation for improving the operating speed and automation level of the production line. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the multi-dimensional optimization method for controlling the wire take-up precision of diamond wire provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0023] In this embodiment of the invention, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In specific implementation, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a correlation between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. Simultaneously, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0024] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be elaborated upon here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In specific implementation, the required indication method can be selected according to specific needs. This embodiment of the invention does not limit the selected indication method; therefore, the indication methods involved in this embodiment of the invention should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0025] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this embodiment of the invention. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0026] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This embodiment of the invention does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or electronic device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or electronic device. The type of memory can be any form of storage medium, and this embodiment of the invention does not limit this.

[0027] In the embodiments of this invention, the “protocol” may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to a future multi-dimensional optimization method system for controlling the accuracy of diamond wire take-up end wiring. The embodiments of this invention do not specifically limit this.

[0028] In this embodiment of the invention, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0029] In the description of the embodiments of the present invention, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present invention is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of the present invention, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this invention, words such as "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this invention should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0030] The network architecture and business scenarios described in the embodiments of this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0031] Figure 1 This is a flowchart illustrating the method provided in an embodiment of the present invention. The multi-dimensional optimization method for controlling the wire take-up precision of diamond wire specifically includes the following steps: Acquire real-time operating status data of the cable receiving equipment; Based on the real-time operating status data, a dynamic mirror model representing the current operating characteristics of the device is dynamically generated; The dynamic mirror model is used to perform predictive simulations of the future cabling process, and potential cabling physical errors and potential conflicts between multiple control objectives are identified from the simulation results. Based on a production stage objective that defines the current core production requirements, and in conjunction with the identified potential conflicts, the optimization priorities of the multiple control objectives are dynamically adjusted to generate a dynamic priority configuration. Using the aforementioned dynamic priority configuration as the optimization guide, multi-objective optimization is performed to generate collaborative optimization control instructions; Obtain the actual operational response data and cable quality data generated after executing the collaborative optimization control command; Based on the actual operational response data and cable quality data, an evolutionary update operation is performed on the dynamic mirror model: This embodiment provides an intelligent closed-loop control method with self-evolution capabilities. It acquires real-time state data through multi-dimensional sensors and immediately generates a dynamic mirror model reflecting the current characteristics of the equipment. Before outputting control commands, the system uses this model to perform short-time domain forward simulation, quantitatively identify systemic conflicts such as tension fluctuations or vibration aggravation that may be caused by correction actions, dynamically adjust the priority of each control objective and perform multi-objective solution to output the globally optimal control command. Finally, by comparing the deviation between the actual operation feedback and the model prediction data, the system parameters and model structure achieve dual autonomous evolution.

[0032] Specifically, the step of performing multi-objective optimization with dynamic priority configuration as the optimization guide is implemented by introducing a particle swarm optimization (PSO) algorithm that is deeply integrated with the dynamic mirror model, and includes the following steps: Construct and initialize a control command particle swarm, define a population of N particles, and encode the position vector of each particle as a combination of line motion parameters in the future short time domain. ; in Peak acceleration, For maximum jerk, To provide feedforward compensation torque, the initial positions and velocities of each particle are randomly initialized within the physical limit constraint space of the wiring mechanism.

[0033] Fitness calculation based on a dynamic mirror model involves the system calculating the position vectors of each particle during the iteration process. As a control input, the currently generated dynamic mirror model is invoked to perform predictive simulation, and the corresponding cable position prediction error is extracted. Tension prediction fluctuation With vibration prediction amplitude Based on the currently set dynamic priority configuration, calculate the particle's fitness value, i.e., the comprehensive cost function J: ; Extreme value tracking and optimization iteration compare the fitness value J of an individual with that of the population, and update the historical best position of each particle in real time. and the global optimal position of the population The particle velocity V and position X are updated for the next iteration based on the following dynamic equations: ; ; In the formula, For inertial weights, The acceleration constant, It is a random number.

[0034] Convergence determination and control command output: When the number of iterations reaches a preset upper limit (e.g., 20 times), or When the change in the corresponding fitness value is less than the convergence threshold, the optimization iteration stops. The final global optimum position is then extracted. And decoded into specific The parameter combinations are then used to generate the final collaborative optimization control commands, which are then issued and executed.

[0035] The step of dynamically generating a dynamic mirror model representing the current operating characteristics of the device based on the real-time operating status data includes: Call a model library that contains a baseline sub-model and multiple feature sub-models; Analyze the characteristic patterns of the real-time operating status data, and select at least one target sub-model from the model library based on the characteristic patterns; Assign a dynamic weight to each of the selected target sub-models; The target sub-model is weighted and fused according to the dynamic weights to generate the dynamic mirror model; After the step of obtaining the real-time operating status data, the method further includes: Spectral analysis is performed on the equipment vibration data in the real-time operating status data to obtain the dominant vibration frequency and amplitude characteristics; The step of selecting at least one target sub-model from the model library based on the feature pattern is specifically as follows: Based on the dominant vibration frequency and amplitude characteristics, one or more of the feature sub-models with the highest correlation to the current vibration mode are selected from the model library as the target sub-model.

[0036] Specifically: The generation of the dynamic mirror model relies on a pre-set model library, which contains a baseline sub-model representing ideal working conditions and multiple feature sub-models representing specific non-ideal working conditions, such as resonance in a specific frequency band. First, feature patterns such as dominant vibration frequency and amplitude are extracted from real-time data. The correlation is calculated using a Gaussian similarity function for quantification, as shown in the formula: ; in, The correlation score between the current vibration feature and the $i$-th feature sub-model is given. and These are the actual measured vibration amplitude and frequency, respectively. and Given the preset model center frequency and bandwidth parameters, the system selects the model with the highest correlation as the target sub-model, and then assigns normalized dynamic weights based on feature strength. Finally, a dynamic mirror model is generated through weighted fusion, and the fusion formula is: Where Y is the final predicted output. , The weights and outputs of the baseline sub-model. , Let $i$ be the weights and outputs of the $i$-th feature sub-model.

[0037] The steps of performing predictive simulations of the future cabling process using the dynamic mirror model, and identifying potential cabling physical errors and potential conflicts between multiple control objectives from the simulation results, include: Input the current control parameters into the dynamic mirror model, perform a short-time-domain wiring process simulation calculation, and extract the predicted wiring physical error data from the simulation results; Calculate a corrective control action to eliminate the predicted wiring physical error data, and evaluate the negative impact of the corrective control action on other control objectives in the dynamic mirror model; When the negative impact exceeds a threshold used to define an acceptable range of disturbances, the potential conflict is determined to exist. The potential conflicts among the multiple control objectives include at least the following: The conflict between the corrective control action generated to achieve the target of matching accuracy in wire winding speed and the target of stable wire tension control aimed at ensuring winding tightness; And / or, the conflict between the corrective control action generated to achieve the control target of the wiring speed matching accuracy and the control target of equipment vibration suppression aimed at ensuring the long-term stable operation of the system; The step of dynamically adjusting the optimization priorities of the multiple control objectives based on a production stage objective that defines the current core production needs and in conjunction with the identified potential conflicts, to generate a dynamic priority configuration includes: Based on the production phase objectives, an initial priority configuration is set; Based on the severity and type of the potential conflict, the weights of the corresponding control targets in the initial priority configuration are adjusted to form the dynamic priority configuration.

[0038] To identify potential conflicts, the system inputs the theoretically optimal corrected control action into the dynamic mirror model for re-simulation, extracting the predicted tension and vibration increments. Conflict determination is quantified based on a comprehensive conflict metric C. ; in, and These are the normalized tension influence factor and vibration influence factor, respectively. and The preset weighting coefficients are used. When C > 1, a potential conflict is identified. During the generation of collaborative optimization control instructions, the system dynamically adjusts the target weights based on the identified conflict metric and constructs a comprehensive cost function J. ; in, , , These are the real-time dynamically updated cable alignment accuracy, tension stability, and vibration suppression weights; , , For the corresponding prediction deviation quantization value, the solver minimizes the cost function J and outputs a comprehensive instruction containing the smooth velocity planning point and torque feedforward compensation value, thereby suppressing the tension and vibration deterioration caused by high acceleration impact from the source.

[0039] The steps of performing evolutionary update operations on the dynamic mirror model include: By comparing the actual operational response data with the prior predicted data of the dynamic mirror model, the first deviation data is obtained; Based on the first deviation data, the internal parameters of the dynamic mirror model are calibrated; Analyze the actual operational response data and cable quality data to determine whether there are any systematic deviations caused by unmodeled interference patterns; When the systematic deviation is determined to exist, a new feature sub-model is generated based on the data related to the systematic deviation, and the new feature sub-model is added to the model library that can provide components for the dynamic mirror model; The step of calibrating the internal parameters of the dynamic mirror model has a synergistic effect with the step of adding the new feature sub-model to the model library; The calibration step corrects the model parameters to make the dynamic mirror model fit the known characteristics of the current device more accurately. The addition step expands the model structure, enabling the dynamic mirror model to describe new interference patterns. The combination of the two enhances both the accuracy and breadth of the dynamic mirror model, with the enhancement effect being superior to the sum of the effects that could be achieved by performing either step alone, thereby improving the overall effect of subsequent prediction simulation and co-optimization.

[0040] The evolutionary mechanism has two synergistic levels. Shallow evolution (parameter calibration): By comparing the small residuals between measured feedback and predicted data, algorithms such as recursive least squares are used to fine-tune the internal physical parameters of the mirror model (such as equivalent moment of inertia and friction coefficient) online, improving the fitting accuracy of known characteristics. Deep evolution (structural expansion): When the residual error after parameter calibration exhibits a stable non-random pattern under specific operating conditions, it is determined that there is unmodeled interference. The system automatically extracts the data for this operating condition and trains to generate new mathematical function relationships. After verification, these are added to the model library as new feature sub-models. The two levels mutually promote each other: parameter calibration reduces basis noise, making the extraction of new patterns purer; the addition of new models strips away complex nonlinear terms, accelerating the convergence of basic parameter calibration.

[0041] The steps of obtaining the actual operational response data and cable quality data generated after executing the collaborative optimization control command include: Images of the fabricated cabling layers are acquired using a machine vision system, and the images are processed and analyzed to extract the actual line spacing data and cabling straightness data, which are used as the cabling quality data. The actual vibration change data and wire tension fluctuation data of the take-up device are recorded synchronously during the execution of the collaborative optimization control command, and are used as the actual operation response data.

[0042] The acquisition of actual data is carried out using dual synchronous channels: the cable quality channel extracts actual cable spacing and straightness data through an industrial camera and image processing algorithms (such as Canny operator and Hough transform); the operation response channel uses a high-frequency data recorder to synchronously acquire high-frequency signals (not less than 1kHz) from accelerometers and tension sensors that are strictly aligned with the timestamps of control commands, ensuring a precise correspondence between control commands and physical responses.

[0043] In another embodiment, a diamond wire take-up and lay-up coordinated control system is also included, comprising: The data sensing module is configured to acquire real-time operating status data of the receiving equipment; The dynamic modeling module is configured to dynamically generate a dynamic mirror model based on the real-time running status data. The prediction and conflict identification module is configured to perform predictive simulations using the dynamic mirror model and identify potential conflicts. The collaborative optimization decision-making module is configured to dynamically adjust the priority of control targets and generate collaborative optimization control instructions. The feedback acquisition module is configured to collect actual operational response data and cable quality data. The model evolution module is configured to perform evolution update operations on the dynamic mirror model based on the actual running response data and the cable quality data.

[0044] The electronic device provided in this embodiment of the invention, exemplarily, can be a network device, or a chip (system) or other component or assembly that can be disposed in a network device. The electronic device may include a processor. Optionally, the electronic device may also include a memory and / or a transceiver. The processor is coupled to the memory and transceiver, for example, by means of a communication bus connection.

[0045] The following is a detailed introduction to the various components of the electronic device: In this context, the processor is the control center of the electronic device. It can be a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0046] Alternatively, the processor can perform various functions of the electronic device, such as the methods described above, by running or executing software programs stored in memory and by calling data stored in memory.

[0047] In a specific implementation, as one example, the processor may include one or more CPUs, such as CPU0 and CPU1.

[0048] In a specific implementation, as one example, the electronic device may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0049] The memory is used to store the software program that executes the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0050] Optionally, the memory can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device; the embodiments of the present invention do not specifically limit this.

[0051] A transceiver is used for communication with other electronic devices. For example, if the electronic device is a terminal, the transceiver can be used to communicate with a network device or with another terminal device. Similarly, if the electronic device is a network device, the transceiver can be used to communicate with a terminal or with another network device.

[0052] Optionally, the transceiver may include a receiver and a transmitter. The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0053] Optionally, the transceiver can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device. This embodiment of the invention does not specifically limit this.

[0054] It is understood that the structure of the electronic device in this embodiment does not constitute a limitation on the electronic device. The actual electronic device may include more or fewer components, or combine certain components, or have different component arrangements.

[0055] Furthermore, the technical effects of the electronic device can be referred to the technical effects of the method described in the above method embodiments, and will not be repeated here.

[0056] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0057] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0058] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0059] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0060] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0061] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0062] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0063] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0064] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0067] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0068] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-dimensional optimization method for controlling the wire take-up precision of diamond wire, characterized in that, Specifically, the following steps are included: Acquire real-time operating status data of the cable receiving equipment; Based on the real-time operating status data, a dynamic mirror model representing the current operating characteristics of the device is dynamically generated; The dynamic mirror model is used to perform predictive simulations of the future cabling process, and potential cabling physical errors and potential conflicts between multiple control objectives are identified from the simulation results. Based on a production stage objective that defines the current core production requirements, and in conjunction with the identified potential conflicts, the optimization priorities of the multiple control objectives are dynamically adjusted to generate a dynamic priority configuration. Using the aforementioned dynamic priority configuration as the optimization guide, multi-objective optimization is performed to generate collaborative optimization control instructions; Obtain the actual operational response data and cable quality data generated after executing the collaborative optimization control command; Based on the actual operational response data and cable quality data, an evolution update operation is performed on the dynamic mirror model.

2. The multi-dimensional optimized diamond wire take-up end wire laying accuracy control method according to claim 1, characterized in that, The step of dynamically generating a dynamic mirror model representing the current operating characteristics of the device based on the real-time operating status data includes: Call a model library that contains a baseline sub-model and multiple feature sub-models; Analyze the characteristic patterns of the real-time operating status data, and select at least one target sub-model from the model library based on the characteristic patterns; Assign a dynamic weight to each of the selected target sub-models; The target sub-model is weighted and fused according to the dynamic weights to generate the dynamic mirror model.

3. The multi-dimensional optimized diamond wire take-up end wiring accuracy control method according to claim 1, characterized in that, The steps of performing predictive simulations of the future cabling process using the dynamic mirror model, and identifying potential cabling physical errors and potential conflicts between multiple control objectives from the simulation results, include: Input the current control parameters into the dynamic mirror model, perform a short-time-domain wiring process simulation calculation, and extract the predicted wiring physical error data from the simulation results; Calculate a corrective control action to eliminate the predicted wiring physical error data, and evaluate the negative impact of the corrective control action on other control objectives in the dynamic mirror model; When the negative impact exceeds a threshold used to define an acceptable range of disturbances, the potential conflict is determined to exist.

4. The multi-dimensional optimization method for controlling the wire take-up accuracy of diamond wire according to claim 3, characterized in that, The potential conflicts among the multiple control objectives include at least the following: The conflict between the corrective control action generated to achieve the target of matching accuracy in wire winding speed and the target of stable wire tension control aimed at ensuring winding tightness; And / or, the conflict between the corrective control action generated to achieve the wire speed matching accuracy control target and the equipment vibration suppression control target aimed at ensuring long-term stable operation of the system.

5. The multi-dimensional optimized diamond wire take-up end wiring accuracy control method according to claim 1, characterized in that, The step of dynamically adjusting the optimization priorities of the multiple control objectives based on a production stage objective that defines the current core production needs and in conjunction with the identified potential conflicts, to generate a dynamic priority configuration includes: Based on the production phase objectives, an initial priority configuration is set; Based on the severity and type of the potential conflict, the weights of the corresponding control targets in the initial priority configuration are adjusted to form the dynamic priority configuration.

6. The multi-dimensional optimized diamond wire take-up end wiring accuracy control method according to claim 1, characterized in that, The steps of performing evolutionary update operations on the dynamic mirror model include: By comparing the actual operational response data with the prior predicted data of the dynamic mirror model, the first deviation data is obtained; Based on the first deviation data, the internal parameters of the dynamic mirror model are calibrated; Analyze the actual operational response data and cable quality data to determine whether there are any systematic deviations caused by unmodeled interference patterns; When the systematic deviation is determined to exist, a new feature sub-model is generated based on the data related to the systematic deviation, and the new feature sub-model is added to the model library that can provide components for the dynamic mirror model.

7. The multi-dimensional optimized diamond wire take-up end wiring accuracy control method according to claim 2, characterized in that, After the step of acquiring the real-time operating status data, the method further includes: Spectral analysis is performed on the equipment vibration data in the real-time operating status data to obtain the dominant vibration frequency and amplitude characteristics; The step of selecting at least one target sub-model from the model library based on the feature pattern is specifically as follows: Based on the dominant vibration frequency and amplitude characteristics, one or more of the feature sub-models with the highest correlation to the current vibration mode are selected from the model library as the target sub-model.

8. The multi-dimensional optimized diamond wire take-up end wire laying accuracy control method according to claim 7, characterized in that, The steps of obtaining the actual operational response data and cable quality data generated after executing the collaborative optimization control command include: Images of the fabricated cabling layers are acquired using a machine vision system, and the images are processed and analyzed to extract the actual line spacing data and cabling straightness data, which are used as the cabling quality data. The actual vibration change data and wire tension fluctuation data of the take-up device are recorded synchronously during the execution of the collaborative optimization control command, and are used as the actual operation response data.

9. The multi-dimensional optimized diamond wire take-up end wiring accuracy control method according to claim 6, characterized in that, The step of calibrating the internal parameters of the dynamic mirror model has a synergistic effect with the step of adding the new feature sub-model to the model library; The calibration step corrects the model parameters to make the dynamic mirror model fit the known characteristics of the current device more accurately. The addition step expands the model structure, enabling the dynamic mirror model to describe new interference patterns. The combination of the two enhances both the accuracy and breadth of the dynamic mirror model, with the enhancement effect being superior to the sum of the effects that could be achieved by performing either step alone, thereby improving the overall effect of subsequent prediction simulation and co-optimization.

10. A diamond wire take-up and wire laying coordinated control system according to any one of claims 1 to 9, characterized in that, include: The data sensing module is configured to acquire real-time operating status data of the receiving equipment; The dynamic modeling module is configured to dynamically generate a dynamic mirror model based on the real-time running status data. The prediction and conflict identification module is configured to perform predictive simulations using the dynamic mirror model and identify potential conflicts. The collaborative optimization decision-making module is configured to dynamically adjust the priority of control targets and generate collaborative optimization control instructions. The feedback acquisition module is configured to collect actual operational response data and cable quality data. The model evolution module is configured to perform evolution update operations on the dynamic mirror model based on the actual running response data and the cable quality data.

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