Edge computing based energy consumption data real-time acquisition system of injection molding machine

Abstract

The application discloses an injection molding machine energy consumption data real-time acquisition system based on edge computing and relates to the technical field of data acquisition, comprising the following steps: firstly, obtaining multiple operating conditions of an injection molding machine and corresponding high fluctuation discrimination stages and low fluctuation constant value stages of each operating condition; acquiring energy consumption data acquisition values corresponding to all injection operating stages based on real-time reference conditions and taking the values as real-time acquisition results of injection molding machine energy consumption data; and the application is used for solving the problem that, in the prior art, there is a lack of low-invasion and few-acquisition-point sub-energy consumption analysis method in the aspect of energy consumption acquisition of injection molding machine process stages, resulting in the need for multi-loop installation of metering devices or reliance on private communication protocols of equipment, high batch deployment implementation cost, easy interference with original process operation of equipment and difficulty in giving consideration to acquisition accuracy and on-site landing feasibility.

Description

Technical Field

[0001] This invention relates to the field of data acquisition technology, specifically to a real-time data acquisition system for injection molding machine energy consumption based on edge computing. Background Technology

[0002] Injection molding machines, also known as injection molding machines, are core industrial molding equipment that uses molds to form various shapes of plastic products from thermoplastic or thermosetting plastics. Real-time energy consumption data collection for injection molding machines is a digital technology that uses hardware sensors and industrial gateways to acquire energy consumption data such as electricity consumption of each energy-consuming unit of the injection molding machine in real time and upload it to the management platform. This is the core foundation for achieving energy conservation and cost reduction in injection molding workshops.

[0003] Existing methods for real-time energy consumption data acquisition in injection molding machines typically involve deploying a multi-module collaborative data acquisition architecture to collect multi-source data throughout the equipment's production cycle. This data is then analyzed in real-time to achieve real-time monitoring of the injection molding machine's energy consumption and production status. However, for energy consumption acquisition at different stages of the injection molding process, there is a lack of low-intrusion, low-sampling-point segmented energy consumption analysis methods. This necessitates the installation of multiple metering devices or reliance on proprietary communication protocols, resulting in significant on-site electrical modifications, high costs for large-scale deployment, and potential interference with existing equipment processes. Furthermore, it is difficult to balance acquisition accuracy with on-site feasibility. For example, patent application CN116811171A discloses an injection molding machine data acquisition system, which addresses this issue. By collecting operational data from the injection molding machine during the current production cycle, the corresponding operating status, production reports, and production cycle duration can be obtained, and warning information can be generated, thus achieving the collection of injection molding machine operation data. However, other improvements to real-time energy consumption data collection methods for injection molding machines are usually improvements in multi-machine energy consumption analysis. In terms of energy consumption acquisition at each stage of the injection molding process, there is still a lack of low-intrusion and low-collection-point sub-item energy consumption analysis methods. This results in the need to install metering devices in multiple loops or rely on equipment proprietary communication protocols, leading to a large amount of on-site electrical modification work, high batch deployment costs, and easy interference with the original process operation of the equipment. It is also difficult to balance the issues of collection accuracy and on-site feasibility. In view of this, it is necessary to improve the existing real-time energy consumption data collection methods for injection molding machines. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by proposing a real-time energy consumption data acquisition system for injection molding machines based on edge computing. This system addresses the lack of low-intrusion and limited-collection-point methods for analyzing energy consumption during the injection molding process, which necessitates the installation of metering devices in multiple loops or reliance on proprietary communication protocols. This results in significant on-site electrical modifications, high costs for mass deployment, potential interference with existing equipment processes, and difficulty in balancing acquisition accuracy with on-site feasibility.

[0005] To achieve the above objectives, this application provides a real-time energy consumption data acquisition system for injection molding machines based on edge computing, including a multi-condition stage acquisition module, a multi-condition stage analysis module, and a real-time energy consumption breakdown module. The multi-condition acquisition module is used to acquire various operating conditions of the injection molding machine, and based on edge computing, it acquires the total energy consumption data, operating time and total operating energy consumption for each operating condition. The multi-condition stage analysis module is used to analyze the energy consumption data corresponding to all operating conditions. Based on the analysis results, it obtains the high fluctuation discrimination stage and low fluctuation setpoint stage corresponding to each operating condition, and obtains the discrimination interval and setpoint interval corresponding to the high fluctuation discrimination stage and low fluctuation setpoint stage respectively. The real-time energy consumption breakdown module is used to obtain real-time reference operating conditions based on the actual operating conditions, running time, and total energy consumption of the injection molding machine. Based on the operating time, total operating energy consumption, high fluctuation judgment stage, and low fluctuation set value stage of the real-time reference operating conditions, it obtains the energy consumption data collection values ​​corresponding to all injection operation stages of the actual operation of the injection molding machine, and uses them as the real-time collection results of the injection molding machine's energy consumption data.

[0006] Furthermore, the multi-condition phase acquisition module includes a multi-condition phase acquisition unit, which is configured with a multi-condition phase acquisition strategy. The multi-condition phase acquisition strategy includes: Based on the environmental data acquisition equipment within the workshop where the injection molding machine is located, all operating conditions of the injection molding machine during operation are acquired and recorded as operating condition YG1 to operating condition YG. n Among them, at least one environmental parameter is different between any two operating conditions; The full-stage simulation data acquisition method is executed for each operating condition, and the total energy consumption data, operating time and total operating energy consumption for each operating condition are obtained based on the full-stage simulation data acquisition method.

[0007] Furthermore, the full-stage simulation acquisition method includes: All operational stages of the injection molding machine during the entire process are obtained separately, and based on the execution time sequence of each stage during the entire process, all operational stages are denoted as injection molding operation stage ZY1 to injection molding operation stage ZY. t ; For any operating condition YG m When the workshop environment where the injection molding machine is located is operating condition YG m At that time, the injection molding machine is subjected to k full-process injection molding tests. The full-process injection molding test is: the injection molding machine is operated at rated power and a complete injection molding process is performed once, where m is a positive integer less than or equal to n and greater than 1.

[0008] Furthermore, the full-stage simulation acquisition method also includes: For any single full-process injection molding test: based on edge settlement, obtain the energy consumption data corresponding to each injection operation stage in the full-process injection molding test; After the full process operation test, the total time of the full process operation test and the total energy consumption of the injection molding machine are recorded as the working condition operation time and the total operating energy consumption, respectively, and the energy consumption data corresponding to all injection molding operation stages are recorded as the total energy consumption data. Obtain the operating conditions YG respectively m The total energy consumption data, operating time, and total operating energy consumption were obtained from k full-process injection molding tests.

[0009] Furthermore, the multi-condition stage analysis module includes a multi-condition stage analysis unit, which is configured with a multi-condition stage analysis strategy. The multi-condition stage analysis strategy includes: For any operating condition YG m : The operating condition YG m The total energy consumption data obtained from k full-process injection molding tests are denoted as data to be analyzed, DF1 to data to be analyzed, respectively. k ; For any injection molding operation stage ZY r The injection molding operation stage ZY r From the data to be analyzed DF1 to the data to be analyzed DF k The corresponding operating energy consumption values ​​are denoted as W1 to W2 respectively. k , where r is a positive integer less than or equal to t and greater than 1; Using a discrete algorithm to obtain the injection molding operation stage ZY r The stage fluctuation value; the discrete algorithm is: Where U is the stage fluctuation value, and W sq From W1 to W k The average value, W i From W1 to W kThe i-th value in the array, where i is a positive integer less than or equal to k and greater than or equal to 1; Obtain all stage fluctuation values ​​for all injection molding operation stages, and denote the injection molding operation stages corresponding to the largest and smallest stage fluctuation values ​​as operating conditions YG. m The high volatility discrimination stage and the low volatility settling stage; Furthermore, the multi-condition phase analysis strategy also includes: Operating condition YG m The high volatility discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding discrimination interval; Operating condition YG m The low-fluctuation discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding range of constant values; For operating condition YG m For any given full-process injection molding test: the ratio of the operating energy consumption values ​​corresponding to all injection molding operation stages in the total energy consumption test data corresponding to the full-process injection molding test is recorded as the stage ratio corresponding to the full-process injection molding test. Get operating status YG m The continuous ratio of all stages corresponding to k full-process injection molding tests.

[0010] Furthermore, the real-time energy consumption dismantling module includes a real-time energy consumption dismantling unit, which is configured with a real-time energy consumption dismantling strategy. The real-time energy consumption dismantling strategy includes: When collecting energy consumption data for an injection molding machine during actual operation, the machine's operating conditions are obtained from environmental data collection equipment within the workshop where the machine is located, and recorded as real-time operating conditions. Based on data comparison, operating conditions YG1 to YG are obtained. n The operating condition that is most similar to the real-time operating condition is recorded as the real-time reference operating condition. The high-fluctuation discrimination stage and the low-fluctuation settling stage corresponding to the real-time reference working condition are recorded as the collectable stage; based on edge settlement, the energy consumption data of the collectable stage is collected during the actual operation of the injection molding machine and recorded as the actual operating energy consumption data of the collectable stage.

[0011] Furthermore, the real-time energy consumption breakdown strategy also includes: When the injection molding machine completes a complete injection molding process, the total time of the complete injection molding process and the total energy consumption of the injection molding machine are recorded as the actual running time and the actual running energy consumption, respectively. Among the k groups of full-process injection molding tests corresponding to the real-time reference operating conditions, the full-process injection molding test with the smallest difference between the operating time and the actual operating time is recorded as the first-level screening test; among all the first-level screening tests, the first-level screening test with the smallest difference between the total operating energy consumption and the actual operating energy consumption is recorded as the disassembly analysis test, and the stage ratio of the disassembly analysis test is recorded as the energy consumption disassembly ratio.

[0012] Furthermore, the real-time energy consumption breakdown strategy also includes: In the actual energy consumption data of the collectable stage, the values ​​of the operating energy consumption corresponding to the high fluctuation discrimination stage and the low fluctuation settling stage are denoted as β1 and β2, respectively. When β1 is within the discrimination range corresponding to the real-time reference working condition and β2 is within the set value range corresponding to the real-time reference working condition, β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption decomposition ratio. After proportionally converting the values ​​in the energy consumption decomposition ratio based on β2, the operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the energy consumption data collection values ​​of all injection molding operation stages corresponding to the injection molding machine in the complete injection molding process.

[0013] Furthermore, the real-time energy consumption breakdown strategy also includes: When β1 is outside the discrimination range corresponding to the real-time reference operating condition, or when β2 is outside the set value range corresponding to the real-time reference operating condition, β1 is substituted into the ratio corresponding to the high fluctuation set value stage within the energy consumption decomposition ratio. After proportionally converting the values ​​in the energy consumption decomposition ratio based on β1, the resulting operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the first reference value. When β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption decomposition ratio, after proportionally converting the values ​​in the energy consumption decomposition ratio based on β2, the resulting operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the second reference value. For any injection molding operation stage in the complete injection molding process, the average value of the corresponding values ​​in the first reference value and the second reference value for the injection molding operation stage is recorded as the energy consumption data collection value corresponding to the injection molding operation stage.

[0014] The beneficial effects of this invention are as follows: This application first obtains various operating conditions of the injection molding machine, and then obtains the total energy consumption data, operating time, and total operating energy consumption corresponding to each operating condition based on edge computing; then, it analyzes the energy consumption data corresponding to all operating conditions, and obtains the high fluctuation discrimination stage and low fluctuation settling stage corresponding to each operating condition based on the analysis results, and obtains the discrimination interval and settling interval corresponding to the high fluctuation discrimination stage and the low fluctuation settling stage respectively. The advantage of this is that by performing edge analysis on the energy consumption and operating time under various operating conditions, dividing the high fluctuation discrimination stage and the low fluctuation settling stage and determining the corresponding interval, it can get rid of the dependence on multi-loop metering devices and equipment private protocols, reduce on-site electrical modification work, avoid the interference of modification on equipment process operation, provide statistical benchmarks for data collection at a few points, reduce the hardware investment for subsequent batch deployment, and improve the data collection accuracy and on-site implementation feasibility. This application also obtains real-time reference operating conditions based on the actual operating conditions, running time, and total energy consumption of the injection molding machine. Based on the operating time, total operating energy consumption, high fluctuation judgment stage, and low fluctuation settling stage of the real-time reference operating conditions, it obtains the energy consumption data collection values ​​corresponding to all injection molding operation stages during the actual operation of the injection molding machine, and uses them as the real-time collection results of the injection molding machine's energy consumption data. The advantage of this is that by relying on the real-time reference operating conditions to match the actual operating state, energy consumption collection results are only obtained for characteristic stages, eliminating the need to deploy collection units for all process stages, significantly reducing the number of collection points, reducing on-site construction costs, and enabling the energy consumption analysis of each stage without interfering with the original equipment operating logic, thus balancing data analysis capabilities and on-site feasibility. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a flowchart illustrating the full-stage simulation acquisition method of the present invention; Figure 3 This is a flowchart illustrating the real-time energy consumption breakdown strategy of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1As shown, this application provides a real-time energy consumption data acquisition system for injection molding machines based on edge computing, characterized in that it includes a multi-condition stage acquisition module, a multi-condition stage analysis module, and a real-time energy consumption breakdown module. The multi-condition acquisition module is used to acquire various operating conditions of the injection molding machine, and based on edge computing, it acquires the total energy consumption data, operating time and total operating energy consumption for each operating condition. The multi-condition phase acquisition module includes a multi-condition phase acquisition unit, which is configured with a multi-condition phase acquisition strategy. The multi-condition phase acquisition strategy includes: Based on the environmental data acquisition equipment within the workshop where the injection molding machine is located, all operating conditions of the injection molding machine during operation are acquired and recorded as operating condition YG1 to operating condition YG. n Among them, at least one environmental parameter is different between any two operating conditions; In the specific implementation process, environmental parameters may include air humidity, temperature and dust concentration in the workshop. In order to avoid the impact of environmental factors on the energy consumption generated during the actual operation of the injection molding machine, this embodiment distinguishes and analyzes the working conditions composed of different environmental factors to ensure that the energy consumption of the injection molding machine under different working conditions is accurately collected. The full-stage simulation data acquisition method is executed for each operating condition, and the total energy consumption data, operating time and total operating energy consumption for each operating condition are obtained based on the full-stage simulation data acquisition method.

[0018] Please see Figure 2 As shown, the full-stage simulation acquisition method includes: acquiring all operating stages of the injection molding machine during the entire process, and based on the execution time sequence of all operating stages during the entire process, recording all operating stages as injection molding operation stage ZY1 to injection molding operation stage ZY. t ; In the data analysis of this embodiment, for example, if all the operating stages of the injection molding machine during the entire process are obtained in one analysis, and the order obtained after sorting based on the execution time sequence is: mold clamping stage, injection stage, pressure holding stage, pre-plasticizing stage, cooling stage, mold opening stage, ejection stage, and standby stage, then through analysis, the value of t can be obtained as 8. All the above stages can be substituted into the injection operation stages ZY1 to ZY8 in sequence and then analyzed. For any operating condition YG m When the workshop environment where the injection molding machine is located is operating condition YG m At that time, the injection molding machine is subjected to k full-process injection molding tests. The full-process injection molding test is: the injection molding machine is run at rated power and a complete injection molding process is executed once, where m is a positive integer less than or equal to n and greater than 1. In the specific implementation process, the value of k can be determined according to the number of times the full-process injection molding test can be performed in the actual data analysis. The purpose is to obtain the energy consumption data corresponding to all injection molding operation stages under the same working condition when performing the full-process injection molding test, and to fully acquire the differentiated data generated therefrom. In the data analysis of this embodiment, the value of k is set to 10.

[0019] The full-stage simulation data acquisition method also includes: for any full-process injection molding test: acquiring the energy consumption data corresponding to each injection molding operation stage in the full-process injection molding test based on edge settlement; After the full process operation test, the total time of the full process operation test and the total energy consumption of the injection molding machine are recorded as the working condition operation time and the total operating energy consumption, respectively, and the energy consumption data corresponding to all injection molding operation stages are recorded as the total energy consumption data. In the data analysis of this embodiment, for example, in a single data analysis, the operating time and total operating energy consumption corresponding to a single full-process injection molding test are 25s and 0.11kWh, respectively. Obtain the operating conditions YG respectively m The total energy consumption data, operating time, and total operating energy consumption were obtained from k full-process injection molding tests.

[0020] The multi-condition stage analysis module is used to analyze the energy consumption data corresponding to all operating conditions. Based on the analysis results, it obtains the high fluctuation discrimination stage and low fluctuation setpoint stage corresponding to each operating condition, and obtains the discrimination interval and setpoint interval corresponding to the high fluctuation discrimination stage and low fluctuation setpoint stage respectively. The multi-condition stage analysis module includes a multi-condition stage analysis unit, which is configured with multi-condition stage analysis strategies. These strategies include: For any operating condition YG m : The operating condition YG m The total energy consumption data obtained from k full-process injection molding tests are denoted as data to be analyzed, DF1 to data to be analyzed, respectively. k ; For any injection molding operation stage ZY r The injection molding operation stage ZY r From the data to be analyzed DF1 to the data to be analyzed DF k The corresponding operating energy consumption values ​​are denoted as W1 to W2 respectively. k , where r is a positive integer less than or equal to t and greater than 1; In the data analysis of this embodiment, for example, the injection molding operation stage analyzed in a single data analysis is the "injection stage". After acquiring all the data to be analyzed, the energy consumption values ​​corresponding to the "injection stage" are as follows: 0.0231kWh, 0.0224kWh, 0.0253kWh, 0.0237kWh, 0.0261kWh, 0.0218kWh, 0.0268kWh, 0.0245kWh, 0.0242kWh, and 0.0257kWh. By substituting these values ​​into a discrete algorithm, the W value is obtained. sq The value is 0.02436, and the stage fluctuation value is 0.00132. By obtaining the stage fluctuation value, we can obtain the value corresponding to the fluctuation state of energy consumption generated by the "injection stage" in the whole injection molding process. The larger the stage fluctuation value, the greater the fluctuation of energy consumption generated by the "injection stage" in the whole injection molding process. Using a discrete algorithm to obtain the injection molding operation stage ZY r The stage fluctuation value; the discrete algorithm is: Where U is the stage fluctuation value, and W sq From W1 to W k The average value, W i From W1 to W k The i-th value in the array, where i is a positive integer less than or equal to k and greater than or equal to 1; Obtain all stage fluctuation values ​​for all injection molding operation stages, and denote the injection molding operation stages corresponding to the largest and smallest stage fluctuation values ​​as operating conditions YG. m The high volatility discrimination stage and the low volatility settling stage; The multi-condition phase analysis strategy also includes: including the operating condition YG m The high volatility discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding discrimination interval; In the data analysis of this embodiment, for example, after the above analysis, the high fluctuation discrimination stage and the low fluctuation setting stage are respectively the "injection stage" and the "cooling stage". Then, W1 to W1 corresponding to the "injection stage" and the "cooling stage" can be obtained respectively. k0 Thus, the judgment interval and the fixed value interval are obtained; through the above analysis, the judgment interval is [0.0218kWh, 0.0268kWh]; Operating condition YG m The low-fluctuation discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding range of constant values; In the specific implementation process, since the high-fluctuation discrimination stage corresponding to the discrimination interval is the stage with the largest energy consumption fluctuation in the entire injection molding process, by obtaining the discrimination interval, the overall energy consumption fluctuation of the entire injection molding process can be judged based on the relationship between the energy consumption generated in the high-fluctuation discrimination stage and the discrimination interval. If the energy consumption generated in the high-fluctuation discrimination stage is within the discrimination interval, it means that the energy consumption of the entire injection molding process is within the normal fluctuation range, and the energy consumption of each operating stage in the entire injection molding process can be directly calculated based on the subsequent stage ratio. If the energy consumption generated in the high-fluctuation discrimination stage is outside the discrimination interval, it means that the energy consumption of the entire injection molding process may have large fluctuations. Therefore, in actual analysis, multiple sets of data should be obtained and calculated to determine the energy consumption of each operating stage. That is, the first reference value and the second reference value should be obtained in the real-time energy consumption decomposition strategy to determine the energy consumption data collection value. For any full-process injection molding test corresponding to operating condition YGm: the continuous ratio of the operating energy consumption values ​​corresponding to all injection molding stages in the total energy consumption test data corresponding to the full-process injection molding test is recorded as the stage continuous ratio corresponding to the full-process injection molding test. In the data analysis of this embodiment, for example, in a single data analysis, the energy consumption corresponding to all process stages in the full-process injection molding test is 0.0165kWh, 0.0242kWh, 0.0187kWh, 0.0330kWh, 0.0066kWh, 0.0055kWh, 0.0055kWh, and 0.0066kWh, respectively. Through analysis, it can be found that the continuous ratio of the operating energy consumption values ​​corresponding to all the above process stages is 15:22:17:30:6:5:5:6. Therefore, the stage continuous ratio can be recorded as 15:22:17:30:6:5:5:6. Get operating status YG m The continuous ratio of all stages corresponding to k full-process injection molding tests.

[0021] The real-time energy consumption breakdown module is used to obtain real-time reference operating conditions based on the actual operating conditions, running time, and total energy consumption of the injection molding machine. Based on the operating time, total operating energy consumption, high fluctuation judgment stage, and low fluctuation set value stage of the real-time reference operating conditions, the module obtains the energy consumption data collection values ​​corresponding to all injection operation stages of the actual operation of the injection molding machine, and uses them as the real-time collection results of the injection molding machine's energy consumption data. The real-time energy consumption breakdown module includes a real-time energy consumption breakdown unit, which is configured with a real-time energy consumption breakdown strategy. Please refer to [link / reference]. Figure 3 As shown, the real-time energy consumption breakdown strategy includes: When collecting energy consumption data for an injection molding machine during actual operation, the machine's operating conditions are obtained from environmental data collection equipment within the workshop where the machine is located, and recorded as real-time operating conditions. Based on data comparison, operating conditions YG1 to YG are obtained. nThe operating condition that is most similar to the real-time operating condition is recorded as the real-time reference operating condition. The high-fluctuation discrimination stage and the low-fluctuation settling stage corresponding to the real-time reference working condition are recorded as the collectable stage; based on edge settlement, the energy consumption data of the collectable stage is collected during the actual operation of the injection molding machine and recorded as the actual operating energy consumption data of the collectable stage.

[0022] The real-time energy consumption breakdown strategy also includes: when the injection molding machine completes a complete injection molding process, the total time of the complete injection molding process and the total energy consumption consumed by the injection molding machine are recorded as the actual running time and the actual running energy consumption, respectively. Among the k groups of full-process injection molding tests corresponding to the real-time reference operating conditions, the full-process injection molding test with the smallest difference between the operating time and the actual operating time is recorded as the first-level screening test; among all the first-level screening tests, the first-level screening test with the smallest difference between the total operating energy consumption and the actual operating energy consumption is recorded as the disassembly analysis test, and the stage ratio of the disassembly analysis test is recorded as the energy consumption disassembly ratio.

[0023] The real-time energy consumption breakdown strategy also includes: when the actual energy consumption data in the collectable stage is used, the values ​​of the operating energy consumption corresponding to the high fluctuation discrimination stage and the low fluctuation set value stage are recorded as β1 and β2, respectively. When β1 is within the discrimination range corresponding to the real-time reference working condition and β2 is within the set value range corresponding to the real-time reference working condition, β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption decomposition ratio. After proportionally converting the values ​​in the energy consumption decomposition ratio based on β2, the operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the energy consumption data collection values ​​of all injection molding operation stages in the complete injection molding process. In specific implementation, for example, in a data analysis, the real-time energy consumption data shows that the operating energy consumption value corresponding to the high-fluctuation discrimination stage "injection stage" is 0.0224 kWh, which is within the discrimination range [0.0218 kWh, 0.0268 kWh] corresponding to the operating condition. Furthermore, the operating energy consumption value corresponding to the low-fluctuation settling stage "cooling stage" is 0.0066 kWh, which is within the settling range [0.0050 kWh, 0.0069 kWh] corresponding to the operating condition. Since the energy consumption breakdown ratio is 15:22:17:30:6:5:5:6, the 0.0066 kWh value can be considered... Substituting the values ​​into 15:22:17:30:6:5:5:6, we perform a proportional conversion. Since the "cooling stage" is the fifth stage in all injection molding operations, 0.0066 kWh should be substituted into the 6 in 15:22:17:30:6:5:5:6 and converted accordingly. From the above analysis, the energy consumption for each injection molding stage is as follows: 0.0165 kWh, 0.0242 kWh, 0.0187 kWh, 0.0330 kWh, 0.0066 kWh, 0.0055 kWh, 0.0055 kWh, and 0.0066 kWh.

[0024] The real-time energy consumption breakdown strategy also includes: when β1 is outside the discrimination range corresponding to the real-time reference operating condition, or when β2 is outside the set value range corresponding to the real-time reference operating condition, β1 is substituted into the ratio corresponding to the high fluctuation set value stage within the energy consumption breakdown ratio, and the values ​​in the energy consumption breakdown ratio based on β1 are proportionally converted to obtain the operating energy consumption values ​​corresponding to all injection molding operation stages, which are recorded as the first reference value; β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption breakdown ratio, and the values ​​in the energy consumption breakdown ratio based on β2 are proportionally converted to obtain the operating energy consumption values ​​corresponding to all injection molding operation stages, which are recorded as the second reference value. For any injection molding operation stage in the complete injection molding process, the average value of the corresponding values ​​in the first reference value and the second reference value for the injection molding operation stage is recorded as the energy consumption data collection value corresponding to the injection molding operation stage.

[0025] Working principle: First, the system acquires multiple operating conditions of the injection molding machine and, based on edge computing, obtains the total energy consumption data, operating time, and total energy consumption for each operating condition. Then, it analyzes the energy consumption data for all operating conditions, and based on the analysis results, obtains the high-fluctuation discrimination stage and low-fluctuation settling stage for each operating condition, and obtains the discrimination interval and settling interval for each stage. Finally, based on the actual operating conditions, operating time, and total energy consumption of the injection molding machine, a real-time reference operating condition is obtained. Based on the operating time, total energy consumption, high-fluctuation discrimination stage, and low-fluctuation settling stage of the real-time reference operating condition, the system acquires the energy consumption data for all injection molding stages during actual operation of the injection molding machine, and uses this as the real-time acquisition result of the injection molding machine's energy consumption data.

[0026] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0027] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0028] 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. A real-time energy consumption data acquisition system for injection molding machines based on edge computing, characterized in that, It includes a multi-condition stage acquisition module, a multi-condition stage analysis module, and a real-time energy consumption breakdown module; The multi-condition acquisition module is used to acquire various operating conditions of the injection molding machine, and based on edge computing, it acquires the total energy consumption data, operating time and total operating energy consumption for each operating condition. The multi-condition stage analysis module is used to analyze the energy consumption data corresponding to all operating conditions. Based on the analysis results, it obtains the high fluctuation discrimination stage and low fluctuation setpoint stage corresponding to each operating condition, and obtains the discrimination interval and setpoint interval corresponding to the high fluctuation discrimination stage and low fluctuation setpoint stage respectively. The real-time energy consumption breakdown module is used to obtain real-time reference operating conditions based on the actual operating conditions, running time, and total energy consumption of the injection molding machine. Based on the real-time reference operating conditions, including operating time, total operating energy consumption, high fluctuation judgment stage, and low fluctuation setpoint stage, the energy consumption data collection values ​​corresponding to all injection molding operation stages during the actual operation of the injection molding machine are obtained and used as the real-time collection results of the injection molding machine's energy consumption data.

2. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 1, characterized in that, The multi-condition phase acquisition module includes a multi-condition phase acquisition unit, which is configured with a multi-condition phase acquisition strategy. The multi-condition phase acquisition strategy includes: Based on the environmental data acquisition equipment within the workshop where the injection molding machine is located, all operating conditions of the injection molding machine during operation are acquired and recorded as operating condition YG1 to operating condition YG. n Among them, at least one environmental parameter is different between any two operating conditions; The full-stage simulation data acquisition method is executed for each operating condition, and the total energy consumption data, operating time and total operating energy consumption for each operating condition are obtained based on the full-stage simulation data acquisition method.

3. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 2, characterized in that, The full-stage simulation acquisition method includes: All operational stages of the injection molding machine during the entire process are obtained separately, and based on the execution time sequence of each stage during the entire process, all operational stages are denoted as injection molding operation stage ZY1 to injection molding operation stage ZY. t ; For any operating condition YG m When the workshop environment where the injection molding machine is located is under operating condition YG m At that time, the injection molding machine is subjected to k full-process injection molding tests. The full-process injection molding test is: the injection molding machine is operated at rated power and a complete injection molding process is performed once, where m is a positive integer less than or equal to n and greater than 1.

4. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 3, characterized in that, The full-stage simulation acquisition method also includes: For any single full-process injection molding test: based on edge settlement, obtain the energy consumption data corresponding to each injection operation stage in the full-process injection molding test; After the full process operation test, the total time of the full process operation test and the total energy consumption of the injection molding machine are recorded as the working condition operation time and the total operating energy consumption, respectively, and the energy consumption data corresponding to all injection molding operation stages are recorded as the total energy consumption data. Obtain the operating conditions YG respectively m The total energy consumption data, operating time, and total operating energy consumption were obtained from k full-process injection molding tests.

5. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 4, characterized in that, The multi-condition stage analysis module includes a multi-condition stage analysis unit, which is configured with multi-condition stage analysis strategies. These strategies include: For any operating condition YG m : The operating condition YG m The total energy consumption data obtained from k full-process injection molding tests are denoted as data to be analyzed, DF1 to data to be analyzed, respectively. k ; For any injection molding operation stage ZY r The injection molding operation stage ZY r From the data to be analyzed DF1 to the data to be analyzed DF k The corresponding operating energy consumption values ​​are denoted as W1 to W2 respectively. k , where r is a positive integer less than or equal to t and greater than 1; Using a discrete algorithm to obtain the injection molding operation stage ZY r The stage fluctuation value; the discrete algorithm is: Where U is the stage fluctuation value, and W sq From W1 to W k The average value, W i From W1 to W k The i-th value in the array, where i is a positive integer less than or equal to k and greater than or equal to 1; Obtain all stage fluctuation values ​​for all injection molding operation stages, and denote the injection molding operation stages corresponding to the largest and smallest stage fluctuation values ​​as operating conditions YG. m The high volatility discrimination stage and the low volatility settling stage.

6. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 5, characterized in that, Multi-condition phase analysis strategies also include: Operating condition YG m The high volatility discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding discrimination interval; Operating condition YG m The low volatility discrimination stage corresponds to W1 to W k In this context, the closed interval formed by the minimum and maximum values ​​is denoted as operating condition YG. m The corresponding range of constant values; For operating condition YG m For any given full-process injection molding test: the ratio of the operating energy consumption values ​​corresponding to all injection molding operation stages in the total energy consumption test data corresponding to the full-process injection molding test is recorded as the stage ratio corresponding to the full-process injection molding test. Get operating status YG m The continuous ratio of all stages corresponding to k full-process injection molding tests.

7. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 6, characterized in that, The real-time energy consumption dismantling module includes a real-time energy consumption dismantling unit, which is configured with a real-time energy consumption dismantling strategy. The real-time energy consumption dismantling strategy includes: When collecting energy consumption data for an injection molding machine during actual operation, the machine's operating conditions are obtained from environmental data collection equipment within the workshop where the machine is located, and recorded as real-time operating conditions. Based on data comparison, operating conditions YG1 to YG are obtained. n The operating condition that is most similar to the real-time operating condition is recorded as the real-time reference operating condition. The high-fluctuation discrimination stage and the low-fluctuation settling stage corresponding to the real-time reference working condition are recorded as the collectable stage; based on edge settlement, the energy consumption data of the collectable stage is collected during the actual operation of the injection molding machine and recorded as the actual operating energy consumption data of the collectable stage.

8. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 7, characterized in that, Real-time energy consumption breakdown strategies also include: When the injection molding machine completes a complete injection molding process, the total time of the complete injection molding process and the total energy consumption of the injection molding machine are recorded as the actual running time and the actual running energy consumption, respectively. Among the k groups of full-process injection molding tests corresponding to the real-time reference operating conditions, the full-process injection molding test with the smallest difference between the operating time and the actual operating time is recorded as the first-level screening test; among all the first-level screening tests, the first-level screening test with the smallest difference between the total operating energy consumption and the actual operating energy consumption is recorded as the disassembly analysis test, and the stage ratio of the disassembly analysis test is recorded as the energy consumption disassembly ratio.

9. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 8, characterized in that, Real-time energy consumption breakdown strategies also include: In the actual energy consumption data of the collectable stage, the values ​​of the operating energy consumption corresponding to the high fluctuation discrimination stage and the low fluctuation settling stage are denoted as β1 and β2, respectively. When β1 is within the discrimination range corresponding to the real-time reference working condition and β2 is within the set value range corresponding to the real-time reference working condition, β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption decomposition ratio. After proportionally converting the values ​​in the energy consumption decomposition ratio based on β2, the operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the energy consumption data collection values ​​of all injection molding operation stages corresponding to the injection molding machine in the complete injection molding process.

10. The real-time energy consumption data acquisition system for injection molding machines based on edge computing according to claim 9, characterized in that, Real-time energy consumption breakdown strategies also include: When β1 is outside the discrimination range corresponding to the real-time reference operating condition, or when β2 is outside the set value range corresponding to the real-time reference operating condition, β1 is substituted into the ratio corresponding to the high fluctuation set value stage within the energy consumption decomposition ratio. After proportionally converting the values ​​in the energy consumption decomposition ratio based on β1, the resulting operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the first reference value. When β2 is substituted into the ratio corresponding to the low fluctuation set value stage within the energy consumption decomposition ratio, after proportionally converting the values ​​in the energy consumption decomposition ratio based on β2, the resulting operating energy consumption values ​​corresponding to all injection molding operation stages are recorded as the second reference value. For any injection molding operation stage in the complete injection molding process, the average value of the corresponding values ​​in the first reference value and the second reference value for the injection molding operation stage is recorded as the energy consumption data collection value corresponding to the injection molding operation stage.

Images