It addresses the issues of low operational efficiency and excessive energy consumption in current heat treatment furnaces by proposing a design for a heat treatment furnace temperature control system based on multi-agent technology.The system employs a fully automated control approach,integrating artificial intelligence and utilizing machine learning to achieve effective control of the furnace temperature.Specifically,the system leverages multi-agent technology,including key components such as distributed power sources,temperature controllers,and gate-ways for data exchange through communication pathways,to optimize control structures,improve operational efficiency,enhance processing quality,and achieve energy savings and emissions reduction.The system design includes multiple agents,each responsible for different func-tions,such as sensor agents,actuator agents,temperature controller agents,and relay agents.These agents work together through data collec-tion,analysis,and execution of commands to precisely control the furnace temperature.To achieve this goal,the system uses machine learn-ing techniques to analyze processing data and monitor process variables,detecting anomalies through pattern recognition and making necessary adjustments.Additionally,intelligent control technology automatically adjusts temperature and holding time to meet preset targets,while Inter-net of Things(IoT)technology connects devices,collects operational data,product attributes,and temperature data.
万方数据
维普
