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Heat Mapping Drones: An Autonomous Computer-Vision-Based Procedure for Building Envelope Inspection Using Unmanned Aerial Systems (UAS)

机译:热图无人机:基于自动计算机视觉的使用无人机系统(UAS)进行建筑围护检查的程序

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摘要

The building sector accounts for about 76% of electricity use and 40% of primary energy use and associated greenhouse gas (GHG) emissions in the United States (US DOE 2015). Research conducted in metropolitan Boston, Massachusetts, found that in 135 residential houses surveyed with infrared (IR) technology, heat transfer and air leaks through cracks were the reason behind about 40% of energy loss (Shao 2011). More than half of all US commercial buildings in operation today were built before 1970 and this large existing building stock performs with general lower efficiency (US DOE 2015). Heating, ventilation, and air conditioning (HVAC) and lighting loads in existing residential and commercial buildings consume 35% and 11% of total building energy, respectively, which totals more than 17 quads of residential and commercial building's primary energy use (US DOE 2015). In order to achieve substantial energy savings in existing and deteriorating built environments, retrofitting strategies that respond to accurate and reliable energy audits should be implemented. To identify compromises in the building envelope, energy auditors traditionally use tools such as blower door tests to detect infiltration/exfiltration regions and thermal bridges (US DOE 2012). Unfortunately, predicted savings and delivered savings typically do not match. This can be attributed to imprecise energy audits, which may lead to lower than expected energy savings, no energy savings, or in some cases occasional increase in energy use. Myriad negative effects follow, including unaccounted for environmental impacts, discrediting energy efficiency retrofits and causing a loss of investment funds. This is typically a result of many challenges that energy auditors face, including insufficient building information that leads to misrepresentation in energy models, overestimated savings, ineffective selection of improvement strategies, and incomprehensive improvement scopes that result in missed opportunities (Shapiro 2011). In large commercial buildings energy auditors typically emphasize exciting technical challenges that focus on HVAC systems or the integration of renewable energy in the form of solar panels while ignoring less attractive building envelope issues such as window performance, thermal bridges, air sealing, and insulation deterioration. This can also be coupled with situations that are considered uneasy, dangerous, or inaccessible to the auditor, including high-rise or large-span structure envelope inspections as well as building roofs (Shapiro 2009). In this paper, a methodology is presented to address these critical challenges by employing an Unmanned Aerial Systems (UAS) platform.
机译:在美国,建筑行业约占电力使用量的76%,占一次能源使用量和相关温室气体(GHG)排放量的40%(US DOE 2015)。在马萨诸塞州大都会波士顿进行的研究发现,在使用红外线(IR)技术进行调查的135栋住宅中,传热和通过裂缝漏气是造成约40%能量损失的原因(Shao 2011)。如今,美国运营中的所有商用建筑物中,有一半以上是在1970年之前建成的,而这种现有的大型建筑物的效率通常较低(US DOE 2015)。现有住宅和商业建筑中的供暖,通风和空调(HVAC)和照明负荷分别消耗建筑总能源的35%和11%,占住宅和商业建筑一次能源使用总量的17倍以上(美国能源部,2015年) )。为了在现有和不断恶化的建筑环境中实现大量节能,应实施对准确而可靠的能源审核做出响应的改造策略。为了确定建筑物围护结构中的妥协之处,能源审计师传统上使用诸如鼓风机门测试之类的工具来检测渗透/渗透区域和热桥(US DOE 2012)。不幸的是,预期的节省和交付的节省通常不匹配。这可能归因于不准确的能源审核,这可能导致低于预期的节能量,没有节能量,或者在某些情况下偶尔增加能耗。随之而来的是各种各样的负面影响,包括无法计算的环境影响,使能效改造失去信誉并造成投资资金损失。这通常是能源审计师面临的许多挑战的结果,其中包括建筑信息不足,导致能源模型表述失误,过高地节省了成本,对改进策略的选择不力以及导致错过机会的不完整的改进范围(Shapiro 2011)。在大型商业建筑中,能源审计师通常会强调激动人心的技术挑战,这些挑战侧重于HVAC系统或以太阳能电池板形式集成可再生能源,而忽略了吸引力较小的建筑围护结构问题,例如窗户性能,热桥,空气密封和隔热性能下降。这还可能伴随着审计人员认为不舒服,危险或难以到达的情况,包括高层或大跨度结构围护结构检查以及建筑物屋顶(Shapiro 2009)。在本文中,提出了一种通过采用无人机系统(UAS)平台解决这些关键挑战的方法。

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