Abstract
In this paper, we proposed the infrared camera method to diagnose wall thermal insulation performance of existing houses with simple and adequately accurate methods. This method separately obtains the heat transfer density of the surface of a building element, combining the result with the infrared thermography to calculate the heat flow rate passing through the building element, finding the thermal transmittance from the environmental temperature difference, and thus enabling quantitative assessment of the thermal insulation properties. The important point of this measurement method is to measure the local heat transfer coefficient of the indoor wall surface, indoor temperature and wall temperature using a heat transfer coefficient sensor and an environmental temperature sensor. Because the sensitivity of sensors significantly affects the accuracy of measurement of thermal transmittance, this paper describes experiment and numerical simulation study with the heat transfer coefficient sensor and the environmental temperature sensor to evaluate the measurement accuracy. First, we evaluate the environmental temperature with the thickness of copper plate on the sensor. Second, we compare the theoretical result and numerical simulation result of the heat transfer coefficient using the 2-dimensional plate model to validate the correctness of the simulation approach to evaluate the sensitivity of heat transfer coefficient sensor. After the validation, the sensitivity of the heat transfer coefficient sensor is evaluated in detail by numerical simulation at several cases. Although the measurement error of environmental temperature sensor was small with the thickness of copper plate, the numerical results of heat transfer coefficient sensor show that it is necessary to calibrate the local heat transfer coefficient by measurement environments. The local heat transfer coefficient of the indoor wall surface became higher as a linear approximation by the thickness of the sensor and air velocity around the sensor. Therefore, we suggested the linear calibration method according to the sensor thickness and air velocity around the sensor.
