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由于不带恒温阀的常规采暖系统在一定时期内还会大量存在 ,而现有的质量并调方案建立在“静态”基础上 ,忽略了系统的热惰性 ,使系统逐时供热量与需热量不一致 ,造成系统热用户室温偏高或偏低 ,即降低了供热品质 ,又浪费能源。本文利用神经网络理论 ,建立了一种常规采暖系统的自适应控制方案。模拟结果显示 ,这种“动态”运行方案克服了常规“静态”运行方案的缺点
As the conventional heating system without thermostatic valve will still exist in a certain period of time, and the existing quality adjustment program is based on “static”, ignoring the thermal inertia of the system, enabling the system to supply heat on time and on demand Inconsistent with the heat, resulting in high heat system users or low room temperature, which reduces the quality of heating, but also a waste of energy. In this paper, neural network theory is used to establish an adaptive control scheme for a conventional heating system. The simulation results show that this “dynamic” operation solution overcomes the disadvantages of the conventional “static” operation solution