基于改进PMV指数的室内环境舒适性研究

Fuzhong Nian, Ke Wang
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引用次数: 6

摘要

室内环境舒适性的研究是以保证人体感觉舒适为目标,同时满足节能降耗的要求。本文是在Fanger教授提出的PMV指标的基础上,对两个环境参数进行改进和增加,即室内视频数和室内CO2浓度参数。提出了室内环境舒适性的研究方法。通过BP神经网络建立改进PMV指数的计算模型,通过多传感器对室内环境参数的监测数据,并进行室内环境舒适性实验。实验结果表明,改进后的PMV指数比传统的PMV指数更能实时、准确地反映室内环境舒适度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on indoor environmental comfort based on improved PMV index
The study of indoor environmental comfort is to ensure that the human body feel comfortable as the goal, while meeting the requirements of energy saving and consumption reduction. The paper is based on the index of PMV was proposed by Professor Fanger, and to be improved and increased two environmental parameters, as indoor video and the number of indoor CO2 concentration parameter., The research method of indoor environmental comfort is put forward in the paper. The improved PMV index by BP neural network established calculation model, through multi sensors on the indoor environment parameters of monitoring data, and indoor environment comfort experiment. The experimental results show that the improved PMV index is more real-time and accurate to reflect the indoor environmental comfort than traditional PMV index.
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