Design And Research On Wireless Data Acquisition System Of Air-conditioning Fault Prediction And Diagnosis

Building,as the fundamental place of human activity, is also the major consumer of energy and resource. With the advancement of urbanization process in China, there are now more than 40 billions square meter buildings which are energy intensive, the amount of these buildings is so huge, and so tremendous energy-crisis is latent. By the end of 2000, the annual consumption of building on commercial energy amounts to 3.76 millions tons of standard coal, accounting for 27.6% of the total the social terminal energy consumption in China, thus, the "contribution rate" of building-energy-consumption to the greenhouse-gas-emissions-increase has reached 25%. It is expected that until 2020 years, the building-power-consumption of our country will reach 1089 billion tons of standard coal. Neglect of the building energy-saving design will directly aggravate the energy crisis. Therefore, we need to control energy consumption in the process of building heating ventilation, air conditioning, lighting, transportation, etc, especially air-conditioning system whose energy-saving potential is the biggest.Air-conditioning equipment have a high coefficient of performance(COP), and the running air-conditioning system "with fault" will cause a significant drop of COP .The increase of energy consumption caused by various faults of air-conditioning system is very considerable.And so is the impact of faults on system performance, which will seriously affect indoor environmental quality and system equipment life, increase maintenance costs and unforeseen equipment downtime. Therefore, the timely and accurate prediction and diagnosis of the various faults in the air-conditioning system have an important significance to ensure the normal operation of air-conditioning system, improve energy efficiency of air-conditioning system.Via analyzingon the status of data collection in the existing air-conditioning system, researching on the trend of wireless sensor network, and combing the structural characteristics of air-conditioning system, the thesis presents a low-cost, low power consumption, immunity to interference, scalable wireless data acquisition system of prediction and diagnosis of air-conditioning faults. The thesis designs the architecture of wireless data acquisition system, in which the hardware development platform is based on telosb from the University of California Berkeley and the CC2430 from TI . In the thesis TinyOS, the operation system of wireless sensor networks, is embeded into the hardware platform. The lightweight operating system threads, active message communication technologies, event-driven model, component-based programming of the TinyOS operating system make the system a good portability, give a full access to the hard ware features and sensor network performance, and reduce system power consumption. Meanwhile, using efficient ICEM-ZigBee protocol, flexible self-organizing wireless communication networks to continuously acquire multi-measuring-point, multi-factor parameters in the air-conditioning system, and display accurate and real-time acquire system operation status. The thesis makes for a timely prediction of the air-conditioning fault to ensure that air-conditioning system operates in the energy-efficient status with the usage of appropriate expert system for real-time analysis of the progressive trend of the parameters. Through intensive study of TinyOS operating system and Zigbee protocols, the practical application shows that the stable performance, which has important practical significance for improving energy efficiency of air-conditioning system and lay a good foundation for further research and the practical application.