Wireless Sensor Technology Based Identification Research Of Indoor Air Quality System

As the complexity of the building structure and function increases, as well as building intelligent improves, indoor air quality is increasingly dependent on the control of the air-conditioning systems. In air-conditioning control systems, the effectiveness of indoor air parameters and the accuracy of indoor air quality model are key factors which effect the control result. At present, there are many problems in the detection of indoor air parameters, such as route complexity, small test range. And most indoor air quality models can not meet the qualification for control system. Therefore, the author of this paper developed a wireless sensor network based indoor air parameters detection system and identified a multivariable system identification based indoor air quality model. The research was supported by Beijing Municipal Natural Science Foundation. The main taks are listed as follows:1、In the wireless sensor network aspect1) Designed the JN5148based circuit of wireless sensor network node which include communication module’s peripheral circuit, power supply circuit and function module circuit.2) Designed the PIC based hardware timing control circuit which controls the make-break of load switch in a assigned time span.3) Developed the Zigbee PRO and JenOS based node software programs which realize the corresponding functions of coordinator, router and end device.4) Developed the ARM9and WinCE OS based main controller which improves the coordinator’s processing ability.2、In the indoor air quality identification aspect 1) Proposed a PSO-SMC (Particle Swarm Optimization-Slide Mode Variable Structure Control) based artificial neural network training algorithm. Comparing with SMC, this algorithm reduces training error and improves network’s generalization ability2) In order to determine indoor air quality model’structure, Guidorzi and neural network time delay identification algorithm were used to identify system’s order and time delay parameter.3) In order to determine indoor air quality model’coefficient, PSO-SMC algorithm was adopted to estimate model’paremeters. Finally, indoor air quality model is established with a high fitting degree.