Research On Energy Consumption Prediction And Optimization Method Of Hydraulic System Of Injection Molding Machine

Injection moulding machine is the core production equipment,which is widely used in Chinese enterprises.According to statistics,the actual energy consumption of injection moulding machine is more than twice the theoretical energy consumption,and it's production efficiency is much lower than the international advanced level.Therefore,reducing the energy consumption of injection moulding machine and improving the production efficiency of injection moulding machine are the new requirements for energy consumption of Chinese enterprises.put forward in the 14th Five-Year Plan.It is also an urgent problem for enterprises to solve at present.The energy consumed by the injection molding machine consists of three modules:energy consumption of the hydraulic system,energy consumption of circulating cooling water and energy consumption of the heater.The energy consumption of hydraulic system accounts for 75%?80%of the total energy consumption,so it is of great significance to construct the energy prediction and optimization model of injection moulder.Firstly,the power bond graph is used to build the energy consumption analysis model of the hydraulic system of the injection molding machine;Then,the improved fruit fly algorithm is used to optimize SVM to establish the energy consumption prediction model of hydraulic system.Finally,through the improved multi-objective PSO algorithm,the process parameters of the main influencing factors are optimized to achieve the purpose of reducing energy consumption and improving production efficiency,The specific work arrangement is as follows:1.The current energy flow analysis does not consider the energy consumption,power flow direction,conversion efficiency,power loss and dynamic characteristics of hydraulic impact.This paper uses the power bond graph method to dynamically build the analysis model of the hydraulic system of the injection molding machine,analyzes the energy consumption characteristics of the hydraulic system of the injection molding machine,and Research out the main factors affecting the energy consumption.2.The process flow of injection moulding machine production is complicated,and the reasons affecting energy consumption and production efficiency can be influenced by a multiplicity of different factors.Affected by uncertain factors such as process parameters,structural parameters,equipment operation status and production environment,it is difficult to predict by mechanism analysis.Based on production data of enterprises,this paper builds a short-term energy consumption prediction model.The method of SVM optimization based on improved fruit fly algorithm,improved adaptive step size of fruit fly algorithm and set chaos agitation mechanism,effectively improved forecast accuracy,solved the problem of high randomness of short-term forecast data occasionally,and was of great significance to guide scheduling and cost budget of actual production process of enterprises.3.The improved multi-objective PSO algorithm is used to optimize the injection pressure,sol temperature and holding time with the energy consumption and production efficiency of the injection molding machine as the optimization objective.After the product quality is up to standard,the optimum combination of process parameters is obtained with the lowest energy consumption and the highest production efficiency.4.Based on the actual production demand of the enterprise and the original energy management system of the enterprise,the analysis,prediction and optimization module of injection moulding machine is built by Python language.The visual call of the system module is realized by external service call,which facilitates the production management of the enterprise.