In situ quantitative diagnosis of insulated building walls using passive infrared thermography

IF 3.7 3区 工程技术 Q1 INSTRUMENTS & INSTRUMENTATION Quantitative Infrared Thermography Journal Pub Date : 2020-08-23 DOI:10.1080/17686733.2020.1805939
M. H. A. Larbi Youcef, V. Feuillet, L. Ibos, Y. Candau
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引用次数: 16

Abstract

ABSTRACT The research project DPE-IITI aims to carry out the in situ diagnosis of energy performance of buildings by quantifying the insulation level of walls. The on site monitoring method is based on the use of passive infrared thermography, meteorological measurements (air temperatures, solar flux), thermal modelling and identification algorithm. A measurement campaign was conducted in a school in the city of Noisiel (suburb of Paris, France). Experimental results based on a radiometric model and finite element simulation parameter identification approach show the potential of the method to quantify the thermal insulation level of a building wall. The structure of the wall is considered as known and the identification procedure estimates either the thermal conductivity or the thickness of the insulation layer. It is therefore a situation of control of the insulation. It shows that a satisfactory estimation could be reached for an analysis duration of one day. This prospective work could lead to the integration of infrared thermography into standard diagnosis procedures.
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被动红外热成像技术在绝热建筑墙体现场定量诊断中的应用
研究项目DPE-IITI旨在通过量化墙体的保温水平来对建筑的能源性能进行现场诊断。现场监测方法基于被动红外热像仪、气象测量(气温、太阳通量)、热建模和识别算法。在法国巴黎郊区诺伊塞尔市的一所学校开展了一项测量活动。基于辐射模型和有限元模拟参数识别方法的实验结果表明,该方法在量化建筑墙体保温水平方面具有潜力。墙体的结构被认为是已知的,识别程序估计导热性或保温层的厚度。因此,这是一种控制绝缘的情况。结果表明,在一天的分析时间内可以得到满意的估计。这项前瞻性的工作可能导致红外热成像集成到标准诊断程序。
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来源期刊
Quantitative Infrared Thermography Journal
Quantitative Infrared Thermography Journal Physics and Astronomy-Instrumentation
CiteScore
6.80
自引率
12.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: The Quantitative InfraRed Thermography Journal (QIRT) provides a forum for industry and academia to discuss the latest developments of instrumentation, theoretical and experimental practices, data reduction, and image processing related to infrared thermography.
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