基于模糊神经网络的保鲜冷库节能研究

Study on the Energy-saving of Cold Storage Based on Fuzzy Neural-Network

为了克服冷库空调系统的设备频繁启停和系统节能效率不高的问题,针对保鲜冷库制冷系统提出了基于Elman神经网络的模糊控制算法的优化改造,采用不同的温度偏差作为模糊控制系统的输入量,模糊控制规则由Elman神经网络在线学习实时生成,调控优化制冷系统的运行状态。试验数据表明,改进的保鲜冷库系统节能效果明显,提高了运行的平稳性,基本克服了压缩机频繁启动的问题。

In order to overcome the startup or shutdown frequently of cold air-conditioning systems and the inefficiencies of energy-saving, the optimizing and reforming about refrigerated air conditioning system for compressor based on Elman neural network fuzzy control algorithm were put forward, furthermore, using different amounts of temperature deviation as the input fuzzy control, fuzzy control rules were generated based on re- M-time online learning by Elman neural network to regulate, control and optimize the running status of refrigerating system. Test data showed that the efficiency of modified refreshing refrigerated system had obvious results, and the operating stability was improved, moreover, the problems a- bout frequent starting of compressor were overcome.