An energy-saving control system and method for a profiled armor sheet stamping production line

Abstract

The present application relates to a kind of special-shaped armor piece stamping production line energy-saving control system and method, the industrial data processing presented in the present application belongs to program control system field.For the technical problems that the prediction error of general energy consumption prediction model in prior art is large for different models of special-shaped armor piece, it is difficult to efficiently optimize under the condition of multi-parameter coupling, and energy consumption prediction is disconnected with real-time control, the present application provides a kind of customized stamping energy consumption prediction model based on the curvature characteristics of standard three-dimensional surface, by traversing the four-parameter space of stamping speed, stamping depth, pressure holding time and stamping gap duration, determine the optimal energy-saving parameter combination with the goal of minimizing total energy consumption, and form the closed-loop energy-saving control of "collection-prediction-optimization-execution".The present application realizes the effective prediction and intelligent optimization of the total energy consumption of special-shaped armor piece, and the limitation of the value range of four parameters respectively ensures the forming quality of special-shaped armor piece, realizes the double optimization of energy saving and quality.

Description

Technical Field

[0001] The industrial data processing proposed in this invention belongs to the field of program control systems, and in particular relates to an energy-saving control system and method for a production line for stamping irregularly shaped armor plates. Background Technology

[0002] Irregularly shaped armor plates, as metal protective components with complex curved surface structures, are widely used in CNC machine tools, stone / glass machinery, electronic equipment production lines, servo motor drive equipment, automotive production lines, and the food industry. They are involved in the specific manufacturing of components for products such as bellows-style protective covers, chip conveyors, protective equipment series, and outer cover series. For irregularly shaped armor plate stamping production lines, even with slight energy savings per piece produced, the overall energy consumption under mass production demands becomes considerable. However, due to the complex curved surface structure and diverse models of irregularly shaped armor plates, stamping production lines using stamping components involve the coordinated consumption of multiple energy sources, including electrical, hydraulic, and pneumatic energy, during the stamping process, making energy consumption control quite challenging.

[0003] For example, Chinese invention patent publication CN117981934A proposes an improved armor component covering structure, including an edging and an inner lining. The edging is composed of two strips of leather or PU leather fixedly connected, positioned along the edge of the armor plate layer to secure it. A protruding ring is provided on the rear edge of the edging. The inner lining has through holes corresponding to the rings on its edge, through which the rings pass. This structure avoids the use of stitching in the prior art to separate the edging and inner lining. When the armor plate layer needs to be replaced, the edging and inner lining can be separated without removing the stitching. The edging and inner lining are secured with irregularly shaped pieces, resulting in a more stable connection.

[0004] For example, Chinese Utility Model Patent Publication CN223701035U discloses an armor strip cutting and assembly mechanism, comprising: a fixed structure, wherein the fixed structure is provided with a guide groove for conveying the armor strip; a linkage component, wherein the linkage component includes a sliding seat, the sliding seat being slidably connected to the fixed structure, the sliding seat being provided with an assembly structure and a cutting structure, the assembly structure being used to press the armor strip into a rubber core, the cutting structure being used to cut off the remaining waste strip of the armor strip; and a driving structure, wherein the driving structure includes a first driving member and a second driving member, the first driving member driving the armor strip to move within the guide groove, and the second driving member driving the sliding seat to move the sliding seat up and down. This utility model aims to improve cutting and assembly accuracy, and enhance overall production efficiency and quality.

[0005] Therefore, it is evident that the aforementioned technical solutions either only involve limitations on the armor structure or only involve limitations on the structure of the armor component production line, with little description of energy-saving control for the stamping production line of irregularly shaped armor pieces. This results in the following main deficiencies in energy consumption control during the stamping process of irregularly shaped armor pieces:

[0006] First, the generalized energy consumption prediction model has insufficient prediction accuracy: under conventional technology, a unified general energy consumption prediction model is usually used to predict the energy consumption of different types of irregular armor plates. This fails to fully consider the significant differences in curved structure and forming difficulty of different types of irregular armor plates, resulting in large prediction errors and failing to provide a reliable basis for energy-saving optimization.

[0007] Second, multi-parameter coupling optimization is difficult: there are complex nonlinear coupling relationships between process parameters such as stamping speed, stamping depth, holding time, and stamping gap duration. Traditional parameter setting methods based on manual experience are difficult to efficiently find the optimal in the huge parameter space, often getting stuck in local optima or causing energy waste.

[0008] Third, energy consumption prediction and real-time control are disconnected: In conventional technologies, energy consumption prediction and actual control execution are independent of each other. The prediction results cannot be fed back to the control system in real time, making it difficult to achieve automated energy-saving control from prediction to execution, resulting in a low level of intelligence.

[0009] Therefore, there is an urgent need for an energy-saving control technology that can establish accurate energy consumption prediction models for different types of irregularly shaped armor plates, achieve efficient optimization of multiple parameters, and form a prediction-control closed loop. Summary of the Invention

[0010] To address the technical problems in existing technologies, this invention provides an energy-saving control system and method for a stamping production line for irregularly shaped armor plates. By establishing a customized stamping energy consumption prediction model based on the three-dimensional surface curvature characteristics of standard irregularly shaped armor plates of different models, and employing a convolutional neural network trained multiple times with curvature values ​​at uniformly spaced points on the three-dimensional surface of the standard parts as forming characteristic inputs, the system achieves accurate prediction of the total energy consumption of electrical, hydraulic, and pneumatic energy during the stamping of irregularly shaped armor plates. Furthermore, by traversing parameter combinations within their respective ranges for stamping speed, stamping depth, holding time, and stamping gap duration, the system automatically determines the optimal energy-saving value set with the goal of minimizing the predicted total energy consumption. This avoids energy waste from manually set values ​​based on experience and forms a closed-loop energy control system of "collection-prediction-optimization-execution," significantly improving energy-saving effects and production efficiency.

[0011] According to one aspect of the present invention, an energy-saving control system for a stamping production line for irregularly shaped armor plates is provided, the system comprising:

[0012] The data acquisition module is used to collect multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model.

[0013] The energy efficiency optimization module is used to iterate through any set of four parameter values ​​for the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device as the current parameter value set. It also uses a stamping energy consumption intelligent prediction model designed for the customized structure of the irregular armor plate of the target model. Based on the current parameter value set, the forming characteristics of the irregular armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, it predicts the total energy consumption data of stamping electrical energy, hydraulic energy, and pneumatic energy under the current parameter value set.

[0014] The collaborative control module is connected to the energy efficiency optimization module and the data acquisition module respectively. It is used to acquire the total energy consumption data corresponding to each set of four-parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time and stamping gap duration of the stamping device, and take the set of four-parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy saving value set.

[0015] The execution module is connected to the collaborative control module and the stamping device respectively, and is used to configure the optimal energy-saving value set to the stamping device and start the stamping device to perform the current stamping forming operation of the target model of the irregular armor piece;

[0016] Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​corresponding to each point at a uniform interval on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

[0017] According to another aspect of the present invention, an energy-saving control method for a stamping production line for irregularly shaped armor plates is provided, the method comprising:

[0018] Multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters are collected as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model.

[0019] The system iterates through any set of four parameters—stamping speed, stamping depth, holding time, and stamping gap duration—of the stamping device to obtain the current set of parameter values. It then employs an intelligent prediction model for stamping energy consumption, designed specifically for the irregularly shaped armor plate of the target model. Based on the current set of parameter values, the forming characteristics of the irregularly shaped armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, the model predicts the total energy consumption of stamping electrical, hydraulic, and pneumatic energy under the current set of parameter values.

[0020] Obtain the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device, and take the set of four parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy-saving value set.

[0021] The optimal energy-saving value set is configured to the stamping device and the stamping device is started to perform the current stamping forming operation of the irregular armor piece of the target model;

[0022] Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​corresponding to each point at a uniform interval on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

[0023] The technical effects of this invention are as follows:

[0024] 1. Establish a customized energy consumption prediction model based on the curvature characteristics of the three-dimensional surface of standard parts:

[0025] This invention employs a convolutional neural network as an intelligent energy consumption prediction model, which uses the curvature values ​​at uniform intervals on the three-dimensional curved surface of a standard part as the forming characteristic input and is trained multiple times (the number of training times is adaptively adjusted according to the weight of the standard part). This enables accurate prediction of the total energy consumption of stamping of irregularly shaped armor plates, including electrical energy, hydraulic energy, and pneumatic energy.

[0026] 2. Achieve global optimization and optimal energy-saving parameter configuration in the four-parameter space:

[0027] This invention automatically determines the optimal set of energy-saving values ​​by iterating through the parameter combinations within their respective ranges for stamping speed, stamping depth, holding time, and stamping gap duration, with the goal of minimizing total energy consumption, thus avoiding energy waste caused by manual experience settings.

[0028] 3. Forming a closed-loop energy control system of "data acquisition-prediction-optimization-execution" significantly improves energy efficiency and production efficiency:

[0029] The data acquisition module in this invention acquires multiple stamping device operating parameters, mold status parameters, and material characteristic parameters in real time. After prediction by the energy efficiency optimization module and optimization by the collaborative control module, the execution module directly configures the optimal parameters and starts stamping, realizing intelligent and automated energy-saving control. Compared with the traditional fixed parameter control method, this technical solution can reduce the overall energy consumption by 15%-30% while ensuring the forming quality of irregular armor plates, achieving dual optimization of energy saving and quality. Attached Figure Description

[0030] The embodiments of the present invention will now be described with reference to the accompanying drawings, wherein:

[0031] Figure 1 A front view of a stamping production line for irregularly shaped armor plates according to the present invention;

[0032] Figure 2 A top view of a stamping production line for irregularly shaped armor plates according to the present invention;

[0033] Figure 3 This is a schematic diagram of the working scenario of an energy-saving control system and method for a stamping production line of irregularly shaped armor plates according to the present invention;

[0034] Figure 4 This is an internal structural diagram of an energy-saving control system for a stamping production line of irregularly shaped armor plates according to a first embodiment of the present invention.

[0035] Figure 5 This is an internal structural diagram of an energy-saving control system for a stamping production line of irregularly shaped armor plates, as shown in the second embodiment of the present invention.

[0036] Figure 6 This is an internal structural diagram of an energy-saving control system for a stamping production line for irregularly shaped armor plates, as shown in the third embodiment of the present invention.

[0037] Figure 7 This is an internal structural diagram of an energy-saving control system for a stamping production line of irregularly shaped armor plates, as shown in the fourth embodiment of the present invention.

[0038] Figure 8 This is an internal structural diagram of an energy-saving control system for a non-circular armor plate stamping production line according to a fifth embodiment of the present invention.

[0039] Figure 9 This is a flowchart illustrating the steps of an energy-saving control method for a stamping production line of irregularly shaped armor plates according to the sixth embodiment of the present invention. Detailed Implementation

[0040] like Figure 1-3 The diagram illustrates the working scenario of a stamping production line for irregularly shaped armor plates, and its energy-saving control system and method, according to the present invention. The industrial data processing proposed in this invention belongs to the field of program control systems.

[0041] The specific technical process of this invention is as follows:

[0042] Technical Process 1: To intelligently predict the total energy consumption of stamping electrical, hydraulic, and pneumatic energy for the stamping production line of the target model of irregularly shaped armor pieces under any set of parameter values, a special intelligent prediction model for stamping energy consumption of irregularly shaped armor pieces of the target model was designed, such as... Figure 3 As shown, in Figure 3 In the process, the stamping production line for the irregularly shaped armor plates of the target model includes its core component, namely the stamping device;

[0043] Specifically, the intelligent prediction model for stamping energy consumption of the irregularly shaped armor plates, which is specific to the target model, and the customized performance of each structure are as follows:

[0044] The first point: The intelligent prediction model for stamping energy consumption of the special-shaped armor plate for the target model is a convolutional neural network that has been trained multiple times, and the number of training times follows the numerical trend of the weight of the standard part of the special-shaped armor plate of the target model.

[0045] For example, the standard part of the target model's irregular armor plate weighs 5 kg, and the number of training sessions is 500; the standard part of the target model's irregular armor plate weighs 10 kg, and the number of training sessions is 1000; the standard part of the target model's irregular armor plate weighs 20 kg, and the number of training sessions is 2000; the standard part of the target model's irregular armor plate weighs 40 kg, and the number of training sessions is 4000, and so on.

[0046] The second point: The convolutional neural network used includes sequentially connected input layers, convolutional layers, pooling layers and fully connected layers, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the target model's irregular armor plate, and the number of convolutional layers is proportional to the three-dimensional volume of the standard part of the target model's irregular armor plate.

[0047] For example, the surface area of ​​the standard part of the irregular armor plate of the target model is 0.8 square meters and the number of pooling layers is 1; the surface area of ​​the standard part of the irregular armor plate of the target model is 1.6 square meters and the number of pooling layers is 2; the surface area of ​​the standard part of the irregular armor plate of the target model is 3.0 square meters and the number of pooling layers is 3, and so on.

[0048] For example, when the solid volume of the standard part of the irregular armor plate of the target model is 0.05 cubic meters, the number of convolutional layers selected is 1; when the solid volume of the standard part of the irregular armor plate of the target model is 0.1 cubic meters, the number of convolutional layers selected is 2; when the solid volume of the standard part of the irregular armor plate of the target model is 0.2 cubic meters, the number of convolutional layers selected is 4; when the solid volume of the standard part of the irregular armor plate of the target model is 0.4 cubic meters, the number of convolutional layers selected is 8, and so on.

[0049] Thirdly: In the convolutional neural network used, each convolutional layer uses the TanH function as the activation function, and each pooling layer uses the ReLU function as the activation function;

[0050] Fourthly: In each training iteration of the convolutional neural network, the total energy consumption data of a known finished product of a target model of irregularly shaped armor piece during the stamping process is used as the single output data of the convolutional neural network. The set of four parameter values ​​used for the finished product, the forming characteristics of the target model of irregularly shaped armor piece, the various parameters of the stamping process, and multiple environmental parameters of the stamping workshop during the stamping process of the finished product are used as the various input contents of the convolutional neural network to complete the training, thereby ensuring the training effect of the convolutional neural network in a single training iteration.

[0051] In this way, different customized structural designs were designed for stamping energy consumption intelligent prediction models for different types of irregular armor plates, ensuring the effectiveness and stability of the intelligent prediction results of total energy consumption data under any set of parameter values.

[0052] Technical Process 2: To intelligently predict the total energy consumption of stamping electrical energy, hydraulic energy and pneumatic energy of the stamping production line for the target model of irregular armor pieces under any parameter value set, a variety of basic data from different sources were introduced.

[0053] Specifically, the basic data from various sources includes the current set of parameter values ​​used, the forming characteristics of the irregular armor pieces of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop. Among them, the various parameters of the stamping process are multiple stamping device operating parameters, multiple mold status parameters, and multiple material property parameters.

[0054] More specifically, multiple sets of stamping device operating parameters include the motor speed, stamping force, stroke position, hydraulic mechanism pressure, and hydraulic mechanism temperature of the stamping device; multiple sets of mold status parameters include mold wear thickness, mold temperature, mold clearance, and mold vibration frequency; multiple sets of material property parameters include the thickness and hardness of the sheet metal to be stamped for the irregular armor plates of the target model; multiple sets of environmental parameters include the temperature, humidity, and air pressure of the stamping workshop; and the current parameter value set used is the specific value set of four parameters of the stamping device used: stamping speed, stamping depth, holding time, and stamping gap duration. This allows for the customized design of the data structure for the basic data from various sources used for intelligent prediction.

[0055] In this way, by comprehensively and fully selecting basic data from various sources, the effectiveness and stability of the intelligent prediction results of total energy consumption data under any set of parameter values ​​are further guaranteed.

[0056] Technical Process 3: Utilizing a customized stamping energy consumption intelligent prediction model designed for the target model's irregularly shaped armor plates in Technical Process 1, and based on comprehensive and fully selected basic data from various sources in Technical Process 2, the model intelligently predicts the total energy consumption (electrical, hydraulic, and pneumatic) required to produce a single irregularly shaped armor plate under specific value sets for each of the four parameters: stamping speed, stamping depth, holding time, and stamping gap duration. Figure 5 As shown;

[0057] Obviously, the quality of each irregularly shaped armor piece is guaranteed because the stamping speed, stamping depth, holding time, and stamping gap duration each have their own range of values.

[0058] However, since there are a large number of possible values ​​within the range of each parameter, there will be a massive set of multiple specific values ​​when matching the four specific values ​​of the four parameters. Thus, through the third technical process, it is possible to quickly complete the intelligent prediction of the total energy consumption data corresponding to the massive set of multiple specific values ​​in the context of big data computing.

[0059] Technical Process 4: Based on the massive set of specific values ​​obtained in Technical Process 3, which correspond to multiple sets of total energy consumption data, the optimal energy-saving value set is analyzed and actually configured to the stamping device to start the stamping device to perform this stamping operation;

[0060] Specifically, the set of values ​​corresponding to the total energy consumption data with the smallest value among multiple total energy consumption data is taken as the optimal energy-saving value set for this stamping operation;

[0061] Clearly, due to the continuous changes in the production environment, the mold condition, the properties of the production materials, and the environmental parameters of the production workshop where the stamping production line is located, obtaining the optimal energy-saving value set for each stamping operation is a continuous dynamic analysis result based on big data computation.

[0062] Therefore, through the coordinated operation of the above-mentioned technical processes, this invention, for a stamping production line for producing irregularly shaped armor pieces of a target model, intelligently predicts the total energy consumption data of stamping electrical energy, hydraulic energy, and pneumatic energy required to produce a single irregularly shaped armor piece under each parameter value set of the stamping device, including stamping speed, stamping depth, holding time, and stamping gap duration. Then, based on the multiple total energy consumption data corresponding to the massive number of parameter value sets, it selects the parameter value set corresponding to the minimum total energy consumption data as the optimal energy-saving value set. This optimal energy-saving value set is then actually configured to the stamping device, and the stamping device is started to perform the current stamping forming operation. This allows for the dynamic selection of the most energy-efficient production control mode for different stamping scenarios on any stamping production line. Simultaneously, the limitation of the value range of each of the four parameters ensures the forming quality of the irregularly shaped armor piece, achieving dual optimization of energy saving and quality.

[0063] The key points of this invention are: the directional customized structural design of intelligent prediction models for different stamping energy consumption of different types of irregular armor plates; the targeted selection of multi-source basic data including the three-dimensional surface curvature characteristics of the standard parts of irregular armor plates; the massive traversal of parameter combinations within the respective value ranges of stamping speed, stamping depth, holding time, and stamping gap duration; the dynamic analysis of the optimal energy-saving value set; and the closed-loop energy control of "collection-prediction-optimization-execution".

[0064] The following will describe in detail, by way of embodiments, an energy-saving control system and method for a production line for stamping irregularly shaped armor plates according to the present invention.

[0065] First Embodiment

[0066] like Figure 4-9 As shown, the energy-saving control system of the irregular armor plate stamping production line includes the following components:

[0067] The data acquisition module is used to collect multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model.

[0068] Specifically, stamping components are key parts of the irregular armor plate stamping production line. Multiple sets of stamping component operating parameters, multiple sets of mold state parameters, and multiple sets of material characteristic parameters respectively reflect the continuous changes in the production environment, the continuous changes in the mold state, and the continuous changes in the characteristics of the production materials.

[0069] The energy efficiency optimization module is used to iterate through any set of four parameter values ​​for the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device as the current parameter value set. It also uses a stamping energy consumption intelligent prediction model designed for the customized structure of the irregular armor plate of the target model. Based on the current parameter value set, the forming characteristics of the irregular armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, it predicts the total energy consumption data of stamping electrical energy, hydraulic energy, and pneumatic energy under the current parameter value set.

[0070] Here, stamping speed, stamping depth, holding time, and stamping gap duration are the four most critical stamping parameters of the stamping device. Since stamping speed, stamping depth, holding time, and stamping gap duration each have their own value range, the quality of each irregular armor piece is guaranteed.

[0071] The collaborative control module is connected to the energy efficiency optimization module and the data acquisition module respectively. It is used to acquire the total energy consumption data corresponding to each set of four-parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time and stamping gap duration of the stamping device, and take the set of four-parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy saving value set.

[0072] Obviously, since there are a large number of possible values ​​within the range of each parameter, the matching of the four specific values ​​of the four parameters will result in a massive set of multiple specific values. In this way, under the technical background of big data computing, it is possible to quickly complete the intelligent prediction of the total energy consumption data corresponding to the massive set of multiple specific values.

[0073] The execution module is connected to the collaborative control module and the stamping device respectively, and is used to configure the optimal energy-saving value set to the stamping device and start the stamping device to perform the current stamping forming operation of the target model of the irregular armor piece;

[0074] Thus, due to the continuous changes in the production environment, the mold state, the characteristics of the production materials, and the environmental parameters of the production workshop where the stamping production line is located, the acquisition of the optimal energy-saving value set for each stamping operation is a continuous dynamic analysis result based on big data calculation. Therefore, this invention enables each stamping operation of each type of irregular armor piece to achieve the best energy-saving effect.

[0075] Correspondingly, for the irregular armor plate stamping production line, if the energy consumption of producing each irregular armor plate is slightly reduced, the overall energy consumption of the irregular armor plate stamping production line under the demand of mass production will be extremely considerable.

[0076] Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​of each part at uniform intervals on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

[0077] Here, a three-dimensional model can be obtained by performing a three-dimensional modeling on the standard parts of the irregular armor plate of the target model. Then, numerical analysis can be performed on the three-dimensional model to obtain the curvature values ​​of each part at uniform intervals on the three-dimensional surface of the three-dimensional model, which can be used as the forming characteristics of the irregular armor plate of the target model.

[0078] Among them, the intelligent prediction model for stamping energy consumption designed for the customized structure of the irregular armor plate of the target model is a convolutional neural network that has been trained multiple times, and the number of training times follows the numerical trend of the weight of the standard part of the irregular armor plate of the target model.

[0079] For example, the numerical trend of the number of training sessions following the weight of the standard part of the target model's irregular armor plate includes: the standard part of the target model's irregular armor plate weighs 5 kg, and the number of training sessions is 500; the standard part of the target model's irregular armor plate weighs 10 kg, and the number of training sessions is 1000; the standard part of the target model's irregular armor plate weighs 20 kg, and the number of training sessions is 2000; the standard part of the target model's irregular armor plate weighs 40 kg, and the number of training sessions is 4000, and so on.

[0080] Among them, in the intelligent prediction model of stamping energy consumption for the customized structure of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model.

[0081] For example, the positive correlation between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model includes: the surface area of ​​the standard part of the irregular armor plate of the target model is 0.8 square meters, and the number of pooling layers selected is 1; the surface area of ​​the standard part of the irregular armor plate of the target model is 1.6 square meters, and the number of pooling layers selected is 2; the surface area of ​​the standard part of the irregular armor plate of the target model is 3.0 square meters, and the number of pooling layers selected is 3, and so on.

[0082] Among them, in the intelligent prediction model of stamping energy consumption for the customized structure design of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model. This includes: each convolutional layer of the convolutional neural network uses the TanH function as the activation function, and each pooling layer of the convolutional neural network uses the ReLU function as the activation function.

[0083] In each training iteration of the convolutional neural network, the total energy consumption data of a known finished product of a target model of irregularly shaped armor piece during the stamping process is used as the single output data of the convolutional neural network. The set of four parameter values ​​used for the finished product, the forming characteristics of the target model of irregularly shaped armor piece, the various parameters of the stamping process, and multiple environmental parameters of the stamping workshop during the stamping process of the finished product are used as the various input contents of the convolutional neural network to complete the training.

[0084] Specifically, an FPGA chip designed using VHDL language can be selected to perform testing and simulation of each training iteration of the convolutional neural network.

[0085] The multiple sets of stamping device operating parameters include the motor speed, stamping force, stroke position, hydraulic mechanism pressure, and hydraulic mechanism temperature of the stamping device; the multiple sets of mold status parameters include mold wear thickness, mold temperature, mold gap, and mold vibration frequency; the multiple sets of material characteristic parameters include the thickness and hardness of the sheet metal to be stamped for the irregular armor plate of the target model; and the multiple sets of environmental parameters include the temperature, humidity, and air pressure of the stamping workshop.

[0086] Specifically, multiple different parameter measurement components can be used to obtain the motor speed, stamping force, stroke position, hydraulic mechanism pressure and hydraulic mechanism temperature of the stamping device respectively;

[0087] The stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device each have their own numerical range.

[0088] Among them, any set of four parameters of the stamping device, namely stamping speed, stamping depth, holding time and stamping gap duration, is a set of numerical values ​​composed of the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration, and the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration are within their respective numerical value ranges.

[0089] Obviously, the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device each have their own numerical range, which ensures the production quality of each irregular armor piece. At the same time, the setting of the numerical value set composed of the specific values ​​of stamping depth, holding time, and stamping gap duration ensures that a large number of numerical value sets can be obtained before intelligent prediction, and after intelligent prediction, multiple total energy consumption data corresponding to the large number of numerical value sets can be obtained.

[0090] In addition, the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set is the cumulative value of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set.

[0091] Second Embodiment

[0092] The energy-saving control system of the irregular armor plate stamping production line also includes:

[0093] The workshop monitoring module is connected to the energy efficiency optimization module and is used to monitor the temperature, humidity and air pressure of the stamping workshop in real time so as to send multiple environmental parameters of the stamping workshop to the energy efficiency optimization module.

[0094] The workshop monitoring module, connected to the energy efficiency optimization module, is used to monitor the temperature, humidity, and air pressure of the stamping workshop in real time and send multiple environmental parameters of the stamping workshop to the energy efficiency optimization module. It includes: using a temperature sensing unit, a humidity sensing unit, and an air pressure sensing unit to monitor the temperature, humidity, and air pressure of the stamping workshop in real time respectively.

[0095] Specifically, the temperature sensing unit, humidity sensing unit, and air pressure sensing unit each have the same microcontroller unit and bus control interface, wherein the bus control interface is a 16-bit or 32-bit parallel control interface.

[0096] Third Embodiment

[0097] The energy-saving control system of the irregular armor plate stamping production line also includes:

[0098] An energy consumption early warning module, connected to the collaborative control module, is used to issue an energy consumption early warning signal when the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device are all greater than a set energy consumption threshold.

[0099] Conversely, the energy consumption early warning module is also used to issue an energy consumption reliability signal when the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time and stamping gap duration of the stamping device are all less than or equal to the set energy consumption threshold.

[0100] The energy consumption early warning module, connected to the collaborative control module, is used to issue an energy consumption early warning signal when the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device are all greater than a set energy consumption threshold. The energy consumption early warning module has built-in acoustic early warning module and optical early warning module, which are used to perform energy consumption early warning operations in acoustic early warning mode and optical early warning mode, respectively.

[0101] Fourth embodiment

[0102] The energy-saving control system of the irregular armor plate stamping production line also includes:

[0103] A range storage module, connected to the energy efficiency optimization module, is used to store the respective value ranges of the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device.

[0104] For example, an MMC memory chip or a TF memory chip can be selected to implement the range storage module, which is used to store the respective value ranges of the stamping speed, stamping depth, holding time and stamping gap duration of the stamping device.

[0105] The range storage modules use different physical storage addresses to store the respective value ranges of the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device.

[0106] Fifth Embodiment

[0107] The energy-saving control system of the irregular armor plate stamping production line also includes:

[0108] The mobile communication module is connected to the collaborative control module and the energy-saving control service network element respectively, and is used to bind the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set and send them together to the energy-saving control service network element.

[0109] Specifically, the mobile communication module uses frequency division duplex communication mode or time division duplex communication mode to bind the optimal energy saving value set and the total energy consumption data corresponding to the optimal energy saving value set and wirelessly send them to the energy saving control service network element.

[0110] The mobile communication module is connected to the collaborative control module and the energy-saving control service network element respectively. It is used to bind the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set and send them to the energy-saving control service network element. This includes binding the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set together and then sending the network data packet to the energy-saving control service network element.

[0111] For example, the energy-saving control service network element can be one of a cloud computing service network element, a blockchain service network element, or a big data service network element.

[0112] Next, various embodiments of the present invention will be further described.

[0113] Optionally, in the energy-saving control system of the irregular armor plate stamping production line described above:

[0114] Traverse any set of four parameters of the stamping device, namely stamping speed, stamping depth, holding time, and stamping gap duration, to form a set of numerical values ​​consisting of the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration. Within their respective numerical ranges, the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration are: in any set of four parameters, sequentially concatenate the binary values ​​of the same number of bits corresponding to the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration.

[0115] For example, in any set of four parameter values, the binary values ​​of the same number of bits corresponding to the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration are sequentially concatenated, including: the value of the same number of bits is 64 bits.

[0116] Among them, the intelligent prediction model for stamping energy consumption, which adopts a customized structure design for the special-shaped armor plate of the target model, predicts the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set based on the current parameter value set, the forming characteristics of the special-shaped armor plate of the target model, various parameters of the entire stamping process and multiple environmental parameters of the stamping workshop. This includes: synchronously inputting the current parameter value set, the forming characteristics of the special-shaped armor plate of the target model, various parameters of the entire stamping process and multiple environmental parameters of the stamping workshop into the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model, and running the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model to obtain the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set output by the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model.

[0117] Among them, the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set, the current parameter value set, the forming characteristics of the irregular armor plate of the target model, the various parameters of the entire stamping process, and the multiple environmental parameters of the stamping workshop are all in the form of binary numerical values.

[0118] Specifically, a numerical conversion unit can be used to convert non-binary numerical parameters into a binary numerical representation.

[0119] And, optionally, in the energy-saving control system of the irregular armor plate stamping production line in the above embodiments:

[0120] The numerical trend of the number of training sessions following the weight change of the standard part of the non-standard armor plate of the target model includes: using a weight change curve to represent the numerical trend of the weight change of the standard part of the non-standard armor plate of the target model, and using a number of training sessions change curve to represent the numerical trend of the number of training sessions.

[0121] Among them, the weight change curve is used to represent the trend of the weight change of the standard part of the non-shaped armor plate of the target model, and the number of training cycles is used to represent the trend of the number of training cycles. The curvature values ​​at uniform intervals on the number of training cycles curve are equal to the curvature values ​​at uniform intervals on the weight change curve.

[0122] Specifically, the number of points at uniform intervals on the curve of frequency variation is equal to the number of points at uniform intervals on the curve of weight variation.

[0123] The positive correlation between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model includes: using a parameter transformation function to represent the parameter transformation relationship between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model.

[0124] For example, the MATLAB toolbox can be used to test and simulate the parameter transformation relationship that uses a parameter transformation function to represent the positive correlation between the number of pooling layers and the surface area of ​​the standard part of the target model of irregular armor plate;

[0125] The parameter transformation function, which expresses the positive correlation between the number of pooling layers and the surface area of ​​the standard part of the target model's irregular armor plate, includes the following: In the parameter transformation function, the surface area of ​​the standard part of the target model's irregular armor plate is the input parameter, and the number of pooling layers that is positively correlated with the surface area of ​​the standard part of the target model's irregular armor plate is the output parameter.

[0126] Sixth Embodiment

[0127] The energy-saving control method for the irregular armor plate stamping production line includes the following steps:

[0128] Multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters are collected as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model.

[0129] Specifically, stamping components are key parts of the irregular armor plate stamping production line. Multiple sets of stamping component operating parameters, multiple sets of mold state parameters, and multiple sets of material characteristic parameters respectively reflect the continuous changes in the production environment, the continuous changes in the mold state, and the continuous changes in the characteristics of the production materials.

[0130] The system iterates through any set of four parameters—stamping speed, stamping depth, holding time, and stamping gap duration—of the stamping device to obtain the current set of parameter values. It then employs an intelligent prediction model for stamping energy consumption, designed specifically for the irregularly shaped armor plate of the target model. Based on the current set of parameter values, the forming characteristics of the irregularly shaped armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, the model predicts the total energy consumption of stamping electrical, hydraulic, and pneumatic energy under the current set of parameter values.

[0131] Here, stamping speed, stamping depth, holding time, and stamping gap duration are the four most critical stamping parameters of the stamping device. Since stamping speed, stamping depth, holding time, and stamping gap duration each have their own value range, the quality of each irregular armor piece is guaranteed.

[0132] Obtain the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device, and take the set of four parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy-saving value set.

[0133] Obviously, since there are a large number of possible values ​​within the range of each parameter, the matching of the four specific values ​​of the four parameters will result in a massive set of multiple specific values. In this way, under the technical background of big data computing, it is possible to quickly complete the intelligent prediction of the total energy consumption data corresponding to the massive set of multiple specific values.

[0134] The optimal energy-saving value set is configured to the stamping device and the stamping device is started to perform the current stamping forming operation of the irregular armor piece of the target model;

[0135] Thus, due to the continuous changes in the production environment, the mold state, the characteristics of the production materials, and the environmental parameters of the production workshop where the stamping production line is located, the acquisition of the optimal energy-saving value set for each stamping operation is a continuous dynamic analysis result based on big data calculation. Therefore, this invention enables each stamping operation of each type of irregular armor piece to achieve the best energy-saving effect.

[0136] Correspondingly, for the irregular armor plate stamping production line, if the energy consumption of producing each irregular armor plate is slightly reduced, the overall energy consumption of the irregular armor plate stamping production line under the demand of mass production will be extremely considerable.

[0137] Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​of each part at uniform intervals on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

[0138] Here, a three-dimensional model can be obtained by performing a three-dimensional modeling on the standard parts of the irregular armor plate of the target model. Then, numerical analysis can be performed on the three-dimensional model to obtain the curvature values ​​of each part at uniform intervals on the three-dimensional surface of the three-dimensional model, which can be used as the forming characteristics of the irregular armor plate of the target model.

[0139] Among them, the intelligent prediction model for stamping energy consumption designed for the customized structure of the irregular armor plate of the target model is a convolutional neural network that has been trained multiple times, and the number of training times follows the numerical trend of the weight of the standard part of the irregular armor plate of the target model.

[0140] For example, the numerical trend of the number of training sessions following the weight of the standard part of the target model's irregular armor plate includes: the standard part of the target model's irregular armor plate weighs 5 kg, and the number of training sessions is 500; the standard part of the target model's irregular armor plate weighs 10 kg, and the number of training sessions is 1000; the standard part of the target model's irregular armor plate weighs 20 kg, and the number of training sessions is 2000; the standard part of the target model's irregular armor plate weighs 40 kg, and the number of training sessions is 4000, and so on.

[0141] Among them, in the intelligent prediction model of stamping energy consumption for the customized structure of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model.

[0142] For example, the positive correlation between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model includes: the surface area of ​​the standard part of the irregular armor plate of the target model is 0.8 square meters, and the number of pooling layers selected is 1; the surface area of ​​the standard part of the irregular armor plate of the target model is 1.6 square meters, and the number of pooling layers selected is 2; the surface area of ​​the standard part of the irregular armor plate of the target model is 3.0 square meters, and the number of pooling layers selected is 3, and so on.

[0143] Among them, in the intelligent prediction model of stamping energy consumption for the customized structure design of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model. This includes: each convolutional layer of the convolutional neural network uses the TanH function as the activation function, and each pooling layer of the convolutional neural network uses the ReLU function as the activation function.

[0144] In each training iteration of the convolutional neural network, the total energy consumption data of a known finished product of a target model of irregularly shaped armor piece during the stamping process is used as the single output data of the convolutional neural network. The set of four parameter values ​​used for the finished product, the forming characteristics of the target model of irregularly shaped armor piece, the various parameters of the stamping process, and multiple environmental parameters of the stamping workshop during the stamping process of the finished product are used as the various input contents of the convolutional neural network to complete the training.

[0145] Specifically, an FPGA chip designed using VHDL language can be selected to perform testing and simulation of each training iteration of the convolutional neural network.

[0146] The multiple sets of stamping device operating parameters include the motor speed, stamping force, stroke position, hydraulic mechanism pressure, and hydraulic mechanism temperature of the stamping device; the multiple sets of mold status parameters include mold wear thickness, mold temperature, mold gap, and mold vibration frequency; the multiple sets of material characteristic parameters include the thickness and hardness of the sheet metal to be stamped for the irregular armor plate of the target model; and the multiple sets of environmental parameters include the temperature, humidity, and air pressure of the stamping workshop.

[0147] Specifically, multiple different parameter measurement components can be used to obtain the motor speed, stamping force, stroke position, hydraulic mechanism pressure and hydraulic mechanism temperature of the stamping device respectively;

[0148] The stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device each have their own numerical range.

[0149] Among them, any set of four parameters of the stamping device, namely stamping speed, stamping depth, holding time and stamping gap duration, is a set of numerical values ​​composed of the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration, and the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration are within their respective numerical value ranges.

[0150] Obviously, the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device each have their own numerical range, which ensures the production quality of each irregular armor piece. At the same time, the setting of the numerical value set composed of the specific values ​​of stamping depth, holding time, and stamping gap duration ensures that a large number of numerical value sets can be obtained before intelligent prediction, and after intelligent prediction, multiple total energy consumption data corresponding to the large number of numerical value sets can be obtained.

[0151] In addition, the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set is the cumulative value of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set.

[0152] Furthermore, in an energy-saving control system and method for a non-circular armor plate stamping production line according to the present invention:

[0153] In the intelligent prediction model of stamping energy consumption for the customized structure design of the irregular armor plate of the target model, the convolutional neural network used includes various convolutional layers, and the number of convolutional layers is proportional to the three-dimensional volume of the standard part of the irregular armor plate of the target model.

[0154] For example, the number of convolutional layers being proportional to the solid volume of the standard part of the irregular armor plate of the target model includes: when the solid volume of the standard part of the irregular armor plate of the target model is 0.05 cubic meters, the number of convolutional layers selected is 1; when the solid volume of the standard part of the irregular armor plate of the target model is 0.1 cubic meters, the number of convolutional layers selected is 2; when the solid volume of the standard part of the irregular armor plate of the target model is 0.2 cubic meters, the number of convolutional layers selected is 4; when the solid volume of the standard part of the irregular armor plate of the target model is 0.4 cubic meters, the number of convolutional layers selected is 8, and so on.

[0155] Among them, in the intelligent prediction model of stamping energy consumption for the customized structure design of the irregular armor plate of the target model, the convolutional neural network used includes various convolutional layers, and the number of convolutional layers is proportional to the three-dimensional volume of the standard part of the irregular armor plate of the target model. This includes: using a content mapping function to represent the content mapping relationship that the number of convolutional layers is proportional to the three-dimensional volume of the standard part of the irregular armor plate of the target model.

[0156] For example, using a content mapping function to represent the content mapping relationship where the number of convolutional layers is proportional to the 3D volume of the standard part of the non-shaped armor plate of the target model includes: optionally using a programmable logic device to implement the simulation and testing of the content mapping function;

[0157] Furthermore, in the intelligent prediction model for stamping energy consumption designed for the customized structure of the irregular armor plate of the target model, the convolutional neural network used includes various convolutional layers, and the number of convolutional layers is proportional to the three-dimensional volume of the standard part of the irregular armor plate of the target model. It also includes: in the content mapping function, the three-dimensional volume of the standard part of the irregular armor plate of the target model is the input content, and the number of convolutional layers proportional to the three-dimensional volume of the standard part of the irregular armor plate of the target model is the output content.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An energy-saving control system for a stamping production line of irregularly shaped armor plates, characterized in that, The system includes: The data acquisition module is used to collect multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model. The energy efficiency optimization module is used to iterate through any set of four parameter values ​​for the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device as the current parameter value set. It also uses a stamping energy consumption intelligent prediction model designed for the customized structure of the irregular armor plate of the target model. Based on the current parameter value set, the forming characteristics of the irregular armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, it predicts the total energy consumption data of stamping electrical energy, hydraulic energy, and pneumatic energy under the current parameter value set. The collaborative control module is connected to the energy efficiency optimization module and the data acquisition module respectively. It is used to acquire the total energy consumption data corresponding to each set of four-parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time and stamping gap duration of the stamping device, and take the set of four-parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy saving value set. The execution module is connected to the collaborative control module and the stamping device respectively, and is used to configure the optimal energy-saving value set to the stamping device and start the stamping device to perform the current stamping forming operation of the target model of the irregular armor piece; Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​corresponding to each point at a uniform interval on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

2. The energy-saving control system of the irregular armor plate stamping production line as described in claim 1, characterized in that: The intelligent prediction model for stamping energy consumption designed for the customized structure of the irregular armor plate of the target model is a convolutional neural network that has been trained multiple times, and the number of training times follows the numerical trend of the weight of the standard part of the irregular armor plate of the target model. Among them, in the intelligent prediction model of stamping energy consumption for the customized structure of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model. Among them, in the intelligent prediction model of stamping energy consumption for the customized structure design of the irregular armor plate of the target model, the convolutional neural network used includes sequentially connected input layer, convolutional layer, pooling layer and fully connected layer, and the number of pooling layers is positively correlated with the surface area of ​​the standard part of the irregular armor plate of the target model. This includes: each convolutional layer of the convolutional neural network uses the TanH function as the activation function, and each pooling layer of the convolutional neural network uses the ReLU function as the activation function. In each training iteration of the convolutional neural network, the total energy consumption data of a known finished product of a target model of irregularly shaped armor piece during the stamping process is used as the single output data of the convolutional neural network. The set of four parameter values ​​used for the finished product, the forming characteristics of the target model of irregularly shaped armor piece, the various parameters of the stamping process, and multiple environmental parameters of the stamping workshop during the stamping process of the finished product are used as the various input contents of the convolutional neural network to complete the training.

3. The energy-saving control system of the irregular armor plate stamping production line as described in claim 2, characterized in that: The multiple sets of stamping device operating parameters include the motor speed, stamping force, stroke position, hydraulic mechanism pressure, and hydraulic mechanism temperature of the stamping device; the multiple sets of mold status parameters include mold wear thickness, mold temperature, mold clearance, and mold vibration frequency; the multiple sets of material characteristic parameters include the thickness and hardness of the sheet metal to be stamped for the irregular armor plate of the target model; and the multiple sets of environmental parameters include the temperature, humidity, and air pressure of the stamping workshop. The stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device each have their own numerical range. Among them, any set of four parameters of the stamping device, namely stamping speed, stamping depth, holding time and stamping gap duration, is a set of numerical values ​​composed of the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration, and the specific values ​​of stamping speed, stamping depth, holding time and stamping gap duration are within their respective numerical value ranges. The total energy consumption data for stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set is the cumulative value of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set.

4. The energy-saving control system of the irregular armor plate stamping production line as described in claim 3, characterized in that, The system also includes: The workshop monitoring module is connected to the energy efficiency optimization module and is used to monitor the temperature, humidity and air pressure of the stamping workshop in real time so as to send multiple environmental parameters of the stamping workshop to the energy efficiency optimization module. The workshop monitoring module, connected to the energy efficiency optimization module, is used to monitor the temperature, humidity, and air pressure of the stamping workshop in real time and send multiple environmental parameters of the stamping workshop to the energy efficiency optimization module. It includes temperature sensing unit, humidity sensing unit, and air pressure sensing unit, respectively, for real-time monitoring of the temperature, humidity, and air pressure of the stamping workshop.

5. The energy-saving control system of the irregular armor plate stamping production line as described in claim 3, characterized in that, The system also includes: An energy consumption early warning module, connected to the collaborative control module, is used to issue an energy consumption early warning signal when the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device are all greater than a set energy consumption threshold. The energy consumption early warning module, connected to the collaborative control module, is used to issue an energy consumption early warning signal when the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device are all greater than a set energy consumption threshold. The energy consumption early warning module has built-in acoustic early warning module and optical early warning module, which are used to perform energy consumption early warning operations in acoustic early warning mode and optical early warning mode, respectively.

6. The energy-saving control system of the irregular armor plate stamping production line as described in claim 3, characterized in that, The system also includes: A range storage module, connected to the energy efficiency optimization module, is used to store the respective value ranges of the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device. The range storage modules use different physical storage addresses to store the respective value ranges of the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device.

7. The energy-saving control system of the irregular armor plate stamping production line as described in claim 3, characterized in that, The system also includes: The mobile communication module is connected to the collaborative control module and the energy-saving control service network element respectively, and is used to bind the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set and send them together to the energy-saving control service network element. The mobile communication module is connected to the collaborative control module and the energy-saving control service network element, respectively. It is used to bind the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set and send them to the energy-saving control service network element. This includes binding the optimal energy-saving value set and the total energy consumption data corresponding to the optimal energy-saving value set and then including them in a network data packet, and then sending the network data packet to the energy-saving control service network element.

8. The energy-saving control system of the irregular armor plate stamping production line as described in any one of claims 3-7, characterized in that: Traverse any set of four parameters of the stamping device, namely stamping speed, stamping depth, holding time, and stamping gap duration, to form a set of numerical values ​​consisting of the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration. Within their respective numerical ranges, the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration are: in any set of four parameters, sequentially concatenate the binary values ​​of the same number of bits corresponding to the specific values ​​of stamping speed, stamping depth, holding time, and stamping gap duration. Among them, the intelligent prediction model for stamping energy consumption, which adopts a customized structure design for the special-shaped armor plate of the target model, predicts the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set based on the current parameter value set, the forming characteristics of the special-shaped armor plate of the target model, various parameters of the entire stamping process and multiple environmental parameters of the stamping workshop. This includes: synchronously inputting the current parameter value set, the forming characteristics of the special-shaped armor plate of the target model, various parameters of the entire stamping process and multiple environmental parameters of the stamping workshop into the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model, and running the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model to obtain the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set output by the intelligent prediction model for stamping energy consumption designed for the customized structure of the special-shaped armor plate of the target model. Among them, the total energy consumption data of stamping electrical energy, hydraulic energy and pneumatic energy under the current parameter value set, the current parameter value set, the forming characteristics of the target model's irregular armor plate, the various parameters of the entire stamping process, and the multiple environmental parameters of the stamping workshop are all represented in binary numerical form.

9. The energy-saving control system of the irregular armor plate stamping production line as described in any one of claims 3-7, characterized in that: The numerical trend of the number of training sessions following the weight change of the standard part of the non-standard armor plate of the target model includes: using a weight change curve to represent the numerical trend of the weight change of the standard part of the non-standard armor plate of the target model, and using a number of training sessions change curve to represent the numerical trend of the number of training sessions. Among them, the weight change curve is used to represent the trend of the weight change of the standard part of the non-shaped armor plate of the target model, and the number of training cycles is used to represent the trend of the number of training cycles. The curvature values ​​at uniform intervals on the number of training cycles curve are equal to the curvature values ​​at uniform intervals on the weight change curve. The positive correlation between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model includes: using a parameter transformation function to represent the parameter transformation relationship between the number of pooling layers and the surface area of ​​the standard part of the irregular armor plate of the target model. The parameter transformation function, which expresses the positive correlation between the number of pooling layers and the surface area of ​​the standard part of the target model's irregular armor plate, includes the following: In the parameter transformation function, the surface area of ​​the standard part of the target model's irregular armor plate is the input parameter, and the number of pooling layers that is positively correlated with the surface area of ​​the standard part of the target model's irregular armor plate is the output parameter.

10. An energy-saving control method for a stamping production line of irregularly shaped armor plates, characterized in that, The method includes: Multiple sets of stamping device operating parameters, multiple sets of mold status parameters, and multiple sets of material property parameters are collected as various parameters of the stamping process. The stamping device is used to stamp and form irregularly shaped armor pieces of the target model. The system iterates through any set of four parameters—stamping speed, stamping depth, holding time, and stamping gap duration—of the stamping device to obtain the current set of parameter values. It then employs an intelligent prediction model for stamping energy consumption, designed specifically for the irregularly shaped armor plate of the target model. Based on the current set of parameter values, the forming characteristics of the irregularly shaped armor plate of the target model, various parameters of the stamping process, and multiple environmental parameters of the stamping workshop, the model predicts the total energy consumption of stamping electrical, hydraulic, and pneumatic energy under the current set of parameter values. Obtain the total energy consumption data corresponding to each set of four parameter values ​​obtained by traversing the stamping speed, stamping depth, holding time, and stamping gap duration of the stamping device, and take the set of four parameter values ​​corresponding to the total energy consumption data with the smallest value as the optimal energy-saving value set. The optimal energy-saving value set is configured to the stamping device and the stamping device is started to perform the current stamping forming operation of the irregular armor piece of the target model; Among them, the forming characteristics of the irregular armor plate of the target model are the curvature values ​​corresponding to each point at a uniform interval on the three-dimensional curved surface of the standard part of the irregular armor plate of the target model.

Images