A detection method for indoor thermal comfort

Abstract

The invention provides a detection method for an indoor thermal comfort degree. The detection method comprises the following steps: acquiring indoor environment parameters and human body thermal balance parameters, taking a PMV value as a measurement degree, defining the sensitivity of each measurement parameter to the thermal comfort degree, and selecting detection variables according to the sensitivity of each parameter; setting partition meeting the physical significance of each detection variable for the detection variable in the domain range of the detection variable, and extracting a fuzzy rule according to association rules under the domain ranges; establishing a hierarchical structure fuzzy self-adaptation model for the indoor thermal comfort degree according to the selected detection variables and the extracted fuzzy rule, and training each layer of sub-model in the hierarchical structure fuzzy self-adaptation model by virtue of a neural network until preset conditions are met. The detection method provided by the invention is capable of achieving a purpose of much timely and accurately detecting the condition of the thermal comfort degree under the current environment, and is capable of carrying out reasonable adjustment according to the changes of the environment. The detection method provided by the invention has an obvious effect in the aspect of reducing model complexity and a rule number, and has great practicability.

Description

technical field [0001] The invention relates to the technical field of detection, in particular to the technical field of detection, regulation and control of an indoor thermal environment, and specifically to a detection method for indoor thermal comfort. Background technique [0002] Comfort itself is a very vague concept. In order to accurately and timely reflect the current indoor thermal comfort and improve the efficiency of air conditioning, more efficient and reasonable thermal comfort detection and modeling technology is needed. At present, the methods of indoor thermal comfort detection and modeling are mainly divided into data-driven 'black box' detection modeling methods and fuzzy logic-based detection modeling methods. In the actual application process, it is difficult for designers to analyze the internal mechanism and causal relationship of the 'black box' detection method in detail, which makes the method lack of explanatory power and is difficult to promote i...

AI Technical Summary

Problems solved by technology

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a detection method for indoor thermal comfort, which is used to solve the problem of inaccurate and untimely detection of indoor thermal comfort in the prior art

Images