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Design of Energy-saving Optimized Remote Control System of Chiller Based on Improved Particle Swarm Optimization

机译:基于改进粒子群优化的冷却器节能优化遥控系统设计

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The traditional chiller system in pharmaceutical plants is facing many problems. Such as low water energy and power utilization, serious energy consumption problems. Manual detection of water chiller parameters has low efficiency and low accuracy. Water chiller failures occur frequently. relying solely on manual detection to find the fault is not timely, can not be real-time remote monitoring and control of water chiller. In order to solve these problems, this paper proposes the design of a chiller energy-saving optimization remote control system based on an improved particle swarm optimization (PSO) algorithm. First of all, this paper builds a hardware detection and remote monitoring control system to detect various parameters of the chiller system. Through the TCP protocol and the MODBUS protocol for data interaction, the collected data can be transmitted to the upper computer in real time. Not only can the webcam monitor real-time monitoring of chiller changes, but it can also detect chiller failures timely. The use of remote monitoring and early warning devices enables the system to have the ability to monitor and control chiller systems in real time. Secondly, a mathematical model is established based on the parameters of the chiller being detected, and the improved PSO algorithm is optimized. Finally, data analysis is performed to achieve optimal energy-saving control. Through the analysis of pharmaceutical factory data, we can draw a conclusion that the system we design not only has good use value, but also has a very broad development prospects.
机译:制药厂的传统冷水机构面临着许多问题。如低水能和电力利用,严重的能量消耗问题。手动检测水冷却器参数具有低效率和低精度。饮水冷却失败频繁发生。仅仅依靠手动检测来找到故障并不及时,不能是实时远程监控和控制水冷杯。为了解决这些问题,本文提出了基于改进粒子群优化(PSO)算法的冷却器节能优化遥控系统的设计。首先,本文建立了硬件检测和远程监控控制系统,以检测冷却器系统的各种参数。通过TCP协议和用于数据交互的Modbus协议,收集的数据可以实时将其发送到上部计算机。网络摄像头不仅可以监控冷却器的实时监控,但它还可以及时检测冷却器故障。使用远程监控和预警设备使系统能够实时监控和控制冷却系统。其次,基于被检测到的冷却器的参数建立数学模型,并且优化了改进的PSO算法。最后,执行数据分析以实现最佳节能控制。通过对药品厂数据的分析,我们可以得出一个结论,我们设计的系统不仅具有良好的使用价值,而且还有一个非常广泛的发展前景。

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