摘要
单一的室内环境温度作为被控变量的控制系统,难以满足人们对室内环境舒适性以及节能的要求。开发了基于TinyOS操作系统的无线热舒适度测量系统,无线传感网络节点组成多跳网络,用以采集温湿度等室内环境参数,并实时计算热舒适度PMV(Predicted Mean Vote)指标值。分析了测量误差产生的主要原因,并利用超闭球CMAC(Hyperball CMAC,HCMAC)神经网络进行了误差补偿,实验结果表明,补偿后的PMV精度得到了明显的改善。该系统可为热环境舒适度实时控制提供便捷的无线数据采集和有效的PMV指标测量方法。
A control system with only one controlled variable like environmental temperature can not satisfy the requirement of indoor environmental comfort and energy efficiency. A wireless comfort measurement system based on TinyOS operating system has been developed. The measurement system is a muti-hop network comprising many wireless sensor network nodes acquiring indoor environmental variables such as temperature and relative humidity. The PMV （Predicted Mean Vote） index is calculated according to the above thermal variables. Measurement error is analyzed and error compensation based on Hyperball CMAC （HCMAC） neural network is carried out. The experimental results demonstrate that the PMV measurement accuracy has been improved markedly after compensation. The developed system can facilitate convenient and fast wireless data acquisition and effective PMV calculation for real-time control of indoor thermal environments.
出处
《山东建筑大学学报》
2012年第5期451-454,460,共5页
Journal of Shandong Jianzhu University
基金
国家自然科学基金项目(61074070
61004005)
山东省科技攻关项目(2009GG10001029)
