Intelligent energy consumption management system for copper foil production process

Abstract

The invention discloses an intelligent energy consumption management system for a copper foil production process. The intelligent energy consumption management system comprises a data acquisition module, a data processing module, a model construction module, a data evaluation module and a plan making module, the data acquisition module is used for acquiring equipment energy consumption data in a copper foil production process in real time; the data processing module is used for processing the equipment energy consumption data; the model construction module is used for constructing a copper foil production process energy consumption evaluation model; the data evaluation module is used for evaluating the processed equipment energy consumption data by using the copper foil production process energy consumption evaluation model; and the plan making module is used for making a production plan according to the energy consumption evaluation result. According to the invention, the energy cost in copper foil production can be greatly reduced.

Description

Technical Field

[0001] The invention belongs to the field of information technology, and in particular relates to an intelligent energy consumption management system for a copper foil production process. Background Art

[0002] With the adjustment of my country's energy structure and the increasing proportion of natural gas in energy utilization, as well as the rise of wind power, solar energy, and bioenergy power generation, distributed power supply systems have attracted widespread attention in my country. At present, my country's construction of distributed energy systems fueled by solar energy and natural gas has entered the substantive development and implementation stage. In particular, the production process of copper foil requires the consumption of electricity, steam and other energy sources. The construction of a comprehensive system of natural gas, solar energy, peak-shaving and valley-filling energy storage power stations combined with distributed energy stations is a new direction for future development. It will definitely improve the comprehensive utilization efficiency of copper foil production energy and greatly reduce the cost of energy in copper foil production.

[0003] The processing cost of electronic copper foil is mainly composed of energy consumption, processing auxiliary materials, employee wages and equipment depreciation. With the sharp rise in energy prices, the proportion of energy consumption in the copper foil industry in the production cost of copper foil is increasing. In 2017, energy consumption (mainly including electricity, steam and water) accounted for more than 50% of the processing cost of our copper foil. For high-energy consumption industries including the copper foil industry, the state advocates the establishment of an energy-saving and emission-reduction investment mechanism guided by the government, dominated by enterprises and participated by the society, focusing on energy-saving and emission-reduction in key enterprises, promoting enterprises to increase structural adjustment and technological transformation, and improving the management level of energy-saving and emission-reduction. As an electronic copper foil manufacturer, the issues we are concerned about are no longer just safety, output and quality, but have turned into economic indicators and energy efficiency levels of processes, products and even the entire enterprise. The existing energy consumption management system is not stable enough, has poor compatibility, low accuracy of data collection, limited analysis capabilities, and high energy costs in copper foil production. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes an intelligent energy consumption management system for the copper foil production process, which can greatly reduce the energy cost in copper foil production.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] An intelligent energy consumption management system for a copper foil production process, comprising: a data acquisition module, a data processing module, a model building module, a data evaluation module and a plan making module;

[0007] The data acquisition module is used to collect equipment energy consumption data in the copper foil production process in real time;

[0008] The data processing module is used to process the energy consumption data of the equipment;

[0009] The model building module is used to build an energy consumption assessment model for the copper foil production process;

[0010] The data evaluation module is used to evaluate the processed equipment energy consumption data using the copper foil production process energy consumption evaluation model;

[0011] The plan making module is used to make a production plan according to the energy consumption evaluation result.

[0012] Preferably, the equipment energy consumption data includes: resource data, production information data, cost data and equipment operation data.

[0013] Preferably, the data processing module comprises: a decomposition unit and an analysis unit;

[0014] The decomposition unit is used to decompose the equipment energy consumption data into data of a preset scale by using an STL time series decomposition method;

[0015] The analysis unit is used to analyze the decomposed equipment energy consumption data.

[0016] Preferably, the energy consumption assessment model for the copper foil production process is divided into two parts: a basic learning model and a meta-learning model.

[0017] Preferably, the process of constructing the energy consumption assessment model for the copper foil production process includes:

[0018] By establishing support vector regression models SVR and multi-layer perceptron models MLP with different input structures;

[0019] The particle swarm algorithm is used to determine the optimal values ​​of SVR parameters and the optimal weights of MLP by minimizing the mean absolute percentage error MAPE;

[0020] Multivariate linear regression is used as the meta-learning machine for the final evaluation.

[0021] Preferably, the data evaluation module includes: an evaluation index obtaining unit, a normalization unit, a conversion unit, a trend model building unit and an energy consumption evaluation unit;

[0022] The evaluation index obtaining unit is used to convert the decomposed equipment energy consumption data into an evaluation result based on the energy consumption evaluation model of the copper foil production process, so as to obtain the energy consumption evaluation index of the copper foil production process;

[0023] The normalization unit is used to normalize the membership vector of the energy consumption evaluation index of the copper foil production process;

[0024] The conversion unit is used to convert the normalized membership vector into a five-element connection number corresponding to the energy consumption evaluation index based on the characterization principle;

[0025] The trend model building unit is used to build a trend model of energy consumption in the copper foil production process based on the five-element connection number;

[0026] The energy consumption evaluation unit is used to complete the evaluation of the energy consumption of the copper foil production process based on the trend model.

[0027] Preferably, the planning module includes: a resource management unit, a safety management unit and a production management unit;

[0028] The resource management unit is used to perform resource management based on the resource data;

[0029] The safety management unit is used to evaluate and predict production energy consumption based on the production information data and the equipment operation data;

[0030] The production management unit is used to formulate and control the production plan based on cost data, production energy consumption evaluation and prediction results, and resource management results.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] Through real-time monitoring and data analysis, the present invention can accurately identify energy waste links in the copper foil production process, and adjust and optimize the production process accordingly to reduce unnecessary energy consumption. At the same time, the application of intelligent control algorithms enables the equipment to operate in the best state, further reducing energy consumption, thereby significantly reducing carbon emissions, which is in line with the green production concept of modern enterprises.

[0033] The intelligent energy consumption management system of the present invention not only focuses on energy use, but also provides decision support for the optimization of production processes through data analysis. By adjusting equipment parameters, optimizing production scheduling, etc., the production cycle can be shortened and production efficiency can be improved. At the same time, stable energy supply and precise environmental control can also help improve the product quality of copper foil and meet the market demand for high-quality copper foil.

[0034] By reducing energy waste, lowering equipment failure rates and improving production efficiency, the intelligent energy management system for copper foil production can significantly reduce the operating costs of enterprises. This includes not only direct energy cost reduction, but also indirect cost reduction due to equipment maintenance, reduced downtime, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0036] Figure 1 The present invention is a schematic diagram of the structure of an intelligent energy consumption management system for a copper foil production process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] Embodiment 1

[0040] like Figure 1 As shown, the present invention provides an intelligent energy consumption management system for copper foil production process, including: a data acquisition module, a data processing module, a model building module, a data evaluation module and a plan making module;

[0041] The data acquisition module is used to collect equipment energy consumption data in the copper foil production process in real time;

[0042] The data processing module is used to process the energy consumption data of the equipment;

[0043] The model building module is used to build an energy consumption assessment model for the copper foil production process;

[0044] The data evaluation module is used to evaluate the processed energy consumption data of the equipment using the energy consumption evaluation model of the copper foil production process;

[0045] The planning module is used to formulate production plans based on energy consumption assessment results.

[0046] In this embodiment, the equipment energy consumption data includes: resource data, production information data, cost data and equipment operation data.

[0047] In this embodiment, the data processing module includes: a decomposition unit and an analysis unit;

[0048] The decomposition unit is used to decompose the energy consumption data of the equipment into data of a preset scale by using an STL time series decomposition method;

[0049] The analysis unit is used to analyze the decomposed equipment energy consumption data.

[0050] Specifically, the process of analyzing the decomposed equipment energy consumption data includes:

[0051] Raw material supply analysis: Through data analysis, we can identify areas of raw material waste, optimize production formulas and process flows, and improve the efficiency of raw material use.

[0052] Energy consumption and emission analysis: 1. Energy consumption monitoring: Real-time monitoring of the consumption of electricity, steam, water and other energy sources during the copper foil production process, and establishment of an energy consumption database. 2. Emission monitoring and control: Analyze the types, quantities and emission standards of waste gas, wastewater, solid waste and other emissions generated during the production process, and take effective control measures to reduce environmental impact. 3. Energy efficiency improvement strategy: Based on energy consumption data, formulate and implement energy efficiency improvement plans, such as using energy-saving equipment, optimizing production scheduling, strengthening energy management, etc., to achieve energy conservation and emission reduction goals.

[0053] Production efficiency evaluation: 1. Production cycle analysis: Analyze the entire production cycle of copper foil from raw material input to finished product output, identify bottlenecks, and propose improvement measures. 2. Equipment utilization: Evaluate the operating efficiency and capacity utilization of production equipment, optimize equipment configuration and scheduling, and improve overall production efficiency. 3. Capacity utilization: Through data analysis, evaluate the capacity utilization of the production line, rationally plan production plans and capacity expansion, and avoid overcapacity or undercapacity.

[0054] Quality control and testing: 1. Quality monitoring system: Establish a complete quality monitoring system to conduct strict quality testing and control on all aspects of copper foil production. 2. Data analysis and feedback: Use statistical process control (SPC) and other data analysis tools to analyze the stability and change trend of product quality, and timely discover and solve quality problems. 3. Quality improvement plan: Based on the results of quality data analysis, formulate and implement quality improvement plans to continuously improve product quality and customer satisfaction.

[0055] Financial data analysis: 1. Cost structure analysis: Detailed analysis of various costs in the copper foil production process (such as raw material costs, manufacturing costs, labor costs, logistics costs, etc.), clarify the cost structure and change trends. 2. Profitability assessment: By calculating financial indicators such as gross profit margin and net profit margin, the profitability of the copper foil production business is assessed to provide a basis for formulating business strategies.

[0056] In this embodiment, the energy consumption assessment model of the copper foil production process is divided into two parts: a basic learning model and a meta-learning model, which is a hybrid learning model PSVR-PMLP-MLR.

[0057] Specifically, the process of constructing the energy consumption assessment model for the copper foil production process includes:

[0058] By establishing support vector regression models SVR and multi-layer perceptron models MLP with different input structures;

[0059] The particle swarm algorithm is used to determine the optimal values ​​of SVR parameters and the optimal weights of MLP by minimizing the mean absolute percentage error MAPE;

[0060] Multivariate linear regression is used as the meta-learning machine for the final evaluation.

[0061] Among them, the energy consumption evaluation model of electrolytic copper foil production based on PSVR: The present invention uses Gaussian kernel function RBF to construct SVR regression model. In order to determine the penalty coefficient C and ε-insensitive loss parameter so that SVR can obtain better prediction results, the present invention uses PSO for optimization. At the same time, the mean absolute percentage error (MAPE) of the predicted data is used as the adaptation function.

[0062] Energy consumption evaluation model for electrolytic copper foil production based on PMLP: (1) Initialize the structure of MLP. At the same time, the number of neurons in the input layer and the output layer should be set together with the network parameters. Through trial calculation, the optimal number of neurons in the hidden layer can be calculated. (2) Set the operating parameters of the particle swarm optimization algorithm and randomly initialize the position and velocity of the particles in a certain way. After knowing the population size and dimension of the particle swarm, map the particles to the corresponding weights. (3) According to the MAPE value, calculate the fitness value of each particle to find the individual and global extreme values. (4) Update the speed, position and fitness of each particle accordingly until they meet the conditions. Then update the individual extreme value and the global extreme value according to the new fitness value. (5) Use the optimal individual position as the weight of the MLP for training and evaluating the research object.

[0063] Multiple Linear Regression (MLR) Model:

[0064]

[0065] Where Y is the output, x i is the input variable, a is the intercept, b i is the regression coefficient, and ε is the error term. i As the predicted value of PSVR and PMLP models, Y is the final prediction result.

[0066] In this embodiment, the data evaluation module includes: an evaluation index obtaining unit, a normalization unit, a conversion unit, a trend model building unit and an energy consumption evaluation unit;

[0067] The evaluation index obtaining unit is used to convert the decomposed equipment energy consumption data into an evaluation result based on the energy consumption evaluation model of the copper foil production process, and obtain the energy consumption evaluation index of the copper foil production process;

[0068] Specifically, an energy consumption evaluation index system for the copper foil production process is established. Based on the forward cloud generator, the qualitative concept is converted into membership. Based on the reverse cloud generator, the membership is converted into a membership cloud represented by cloud model characteristic parameters, that is, the production process evaluation state cloud. The preprocessed production information data is processed by the reverse cloud generator algorithm to obtain the model parameters, and then processed by the forward cloud generator to generate a preset number of cloud droplets to obtain the production process evaluation index cloud. The cloud similarity is calculated for the state cloud and the index cloud to obtain the membership vector of the state level corresponding to the evaluation index.

[0069] The normalization unit is used to normalize the membership vector of the energy consumption evaluation index of the copper foil production process;

[0070] The conversion unit is used to convert the normalized membership vector into a five-element connection number corresponding to the energy consumption evaluation index based on the characterization principle;

[0071] The trend model building unit is used to build a trend model of energy consumption in the copper foil production process based on the five-element connection number;

[0072] The energy consumption evaluation unit is used to complete the evaluation of the energy consumption of the copper foil production process based on the trend model.

[0073] In this embodiment, the planning module includes: a resource management unit, a safety management unit, and a production management unit;

[0074] The resource management unit is used to perform resource management based on the resource data;

[0075] The safety management unit is used to evaluate and predict production energy consumption based on the production information data and the equipment operation data;

[0076] The production management unit is used to formulate and control production plans based on cost data, production energy consumption assessment and forecast results, and resource management results.

[0077] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. An intelligent energy consumption management system for copper foil production process, characterized in that: include: Data collection module, data processing module, model building module, data evaluation module and plan making module; The data acquisition module is used to collect equipment energy consumption data in the copper foil production process in real time; The data processing module is used to process the energy consumption data of the equipment; The model building module is used to build an energy consumption assessment model for the copper foil production process; The data evaluation module is used to evaluate the processed equipment energy consumption data using the copper foil production process energy consumption evaluation model; The plan making module is used to make a production plan according to the energy consumption evaluation result.

2. The intelligent energy consumption management system for copper foil production process according to claim 1 is characterized in that: The equipment energy consumption data includes: resource data, production information data, cost data and equipment operation data.

3. The intelligent energy consumption management system for copper foil production process according to claim 1 is characterized in that: The data processing module includes: a decomposition unit and an analysis unit; The decomposition unit is used to decompose the equipment energy consumption data into data of a preset scale by using an STL time series decomposition method; The analysis unit is used to analyze the decomposed equipment energy consumption data.

4. The intelligent energy consumption management system for copper foil production process according to claim 1 is characterized in that: The energy consumption evaluation model of the copper foil production process is divided into two parts: a basic learning model and a meta-learning model.

5. The intelligent energy consumption management system for copper foil production process according to claim 4 is characterized in that: The process of constructing the energy consumption assessment model of the copper foil production process includes: By establishing support vector regression models SVR and multi-layer perceptron models MLP with different input structures; The particle swarm algorithm is used to determine the optimal values ​​of SVR parameters and the optimal weights of MLP by minimizing the mean absolute percentage error MAPE; Multivariate linear regression is used as the meta-learning machine for the final evaluation.

6. The intelligent energy consumption management system for copper foil production process according to claim 1, characterized in that: The data evaluation module includes: an evaluation index obtaining unit, a normalization unit, a conversion unit, a trend model building unit and an energy consumption evaluation unit; The evaluation index obtaining unit is used to convert the decomposed equipment energy consumption data into an evaluation result based on the energy consumption evaluation model of the copper foil production process, so as to obtain the energy consumption evaluation index of the copper foil production process; The normalization unit is used to normalize the membership vector of the energy consumption evaluation index of the copper foil production process; The conversion unit is used to convert the normalized membership vector into a five-element connection number corresponding to the energy consumption evaluation index based on the characterization principle; The trend model building unit is used to build a trend model of energy consumption in the copper foil production process based on the five-element connection number; The energy consumption evaluation unit is used to complete the evaluation of the energy consumption of the copper foil production process based on the trend model.

7. The intelligent energy consumption management system for copper foil production process according to claim 1, characterized in that: The plan making module includes: a resource management unit, a safety management unit and a production management unit; The resource management unit is used to perform resource management based on the resource data; The safety management unit is used to evaluate and predict production energy consumption based on the production information data and the equipment operation data; The production management unit is used to formulate and control the production plan based on cost data, production energy consumption evaluation and prediction results, and resource management results.

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