The Research Of The Survey Data Acquisition And Analysis System Of Building Thermal Comfort

With the outbreak of global environmental crisis, the realization of building energy conservation is imminent for the sustainable development of the society. Building thermal comfort is the basic prerequisite for building energy conservation. However, it needs to exhaust some harmful substances and consumes lots of natural resource. Therefore, the balance of building thermal comfort and building energy saving is an important development direction of construction industry in the future.The commonly used research method is to collect people’s subjective satisfaction evaluation about whether the thermal environment around is comfortable through paper questionnaire, and then set up a linear thermal comfort adaptive model combining with the theoretical formula to obtain the neutral temperature of indoor. However, the paper questionnaire survey has some problems: lots of information needs to collect; not easily to statistical analysis; low execution efficiency and not easily to save the information. In addition, due to the error of collection data, the neutral temperature accuracy will be affected. Therefore, this paper will design and implement a questionnaire system based on the i OS platform to collect data, and study the best building thermal comfort adaptive model. In this paper, the main research content is showing as follows:(1) Based on the impact factors of online survey summarizes, put forward several proposed methods to improve the quality of online survey(2) According to the online survey of assess the degree of application form, verified the applicability of online survey research in the field of building thermal comfort(3) Designing a completed structure, detail function and database based on Web server and the i OS platform of online survey system, and implement each function module of the system.(4) Applying the development of an online survey system to the actual building thermal comfort research project, and then based on the data collected to verify the on-line survey response rate and reliability of the empirical analysis.(5) According to the related parameters of building thermal comfort and statistical analysis of the collected data.(6) Aiming at the shortcomings of the traditional Bin algorithms to preprocess the original data,put forward the corresponding improvement measures.(7) Using the method of least squares linear fitting, B-spline curve fitting methods and polynomial curve fitting method respectively to build the relational model building thermal comfort indices. Finally, choosing the best fitting method through analyzing and comparing the simulation results of these types of models.In summary, this paper proposed a new method on the building thermal comfort of the data collection and analysis, and through practical projects to verify the if the method is correctness and feasibility, which will benefit for the studying of the build thermal comfort.