在AHU单元中使用降维技术进行故障检测和诊断:对其可靠性的关键评估

IF 2.2 4区工程技术 Q2 CONSTRUCTION & BUILDING TECHNOLOGY

Journal of Building Performance Simulation Pub Date : 2022-07-15 DOI:10.1080/19401493.2022.2080864

Hugo Geoffroy, J. Berger, Benoît Colange, S. Lespinats, D. Dutykh

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引用次数: 2

摘要

故障检测和诊断(FDD)是对系统进行持续监测和协助进行楼宇调试的重要工具。研究了一种基于数据驱动和知识驱动相结合的创新方法。本文介绍了这种方法。在第一阶段，使用降维方法和数值或实验数据集构建所谓的系统操作图。这张地图由几个区域组成，对应于名义操作和特定的断层。第二阶段的重点是FDD。监测到的数据被投影在地图上。根据位置，可携带清晰精确的FDD。该方法应用于空气处理机组。这张地图是用建筑模拟程序生成的数据绘制的。通过产生的标称运行和故障运行的实验数据，验证了该方法的可靠性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The use of dimensionality reduction techniques for fault detection and diagnosis in a AHU unit: critical assessment of its reliability

Fault detection and diagnosis (FDD) are important tools to perform on-going monitoring of the systems and help in their building commissioning. An innovative method is investigated based on combined data-driven and knowledge-based approaches. This article presents the method. In the first phase, a so-called operating map of the system is built using a dimension reduction method and numerical or experimental dataset. This map is composed of several regions corresponding to nominal operation and to specific faults. The second phase focuses on the FDD. The monitored data are projected on the map. According to the position, a clear and precise FDD can be carried. The method is applied to an air handling unit. The map is built using data generated with a building simulation programme. The reliability of the method is proven using experimental data of nominal and fault operation generated.

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来源期刊

Journal of Building Performance Simulation CONSTRUCTION & BUILDING TECHNOLOGY-

CiteScore

5.50

自引率

12.00%

发文量

审稿时长

12 months

期刊介绍： The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies We welcome building performance simulation contributions that explore the following topics related to buildings and communities: -Theoretical aspects related to modelling and simulating the physical processes (thermal, air flow, moisture, lighting, acoustics). -Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems. -Theoretical aspects related to occupants, weather data, and other boundary conditions. -Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid. -Uncertainty, sensitivity analysis, and calibration. -Methods and algorithms for validating models and for verifying solution methods and tools. -Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics. -Techniques for educating and training tool users. -Software development techniques and interoperability issues with direct applicability to building performance simulation. -Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the knowledge base.