Experimental dataset for an AHU air-to-air heat exchanger with normal and simulated fault operations

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

Journal of Building Performance Simulation Pub Date : 2022-07-27 DOI:10.1080/19401493.2022.2097311

Hugo Geoffroy, J. Berger, E. Gonze, C. Buhé

引用次数: 2

Abstract

Fault Detection and Diagnosis (FDD) is an important tool in building commissioning. Providing a consolidated dataset for FDD benchmarking is necessary to accurately evaluate the FDD prediction accuracy and detect anomalies. In this study, we provide an experimental dataset for an air handling unit containing two ducts linked by an air-to-air heat exchanger. The dataset is composed of nominal and faulty operations of the system, including the ground truth in order to investigate various faults in 52 cases. The dataset was obtained by measuring a representative system with real climate variations like the ones obtained by Building Automation Systems. The transition between nominal and fault sequences was continuous, as in real operating conditions. An uncertainty evaluation was carried out to provide confidence bounds in the experimental dataset.

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AHU空气-空气换热器正常和模拟故障运行的实验数据集

故障检测与诊断(FDD)是楼宇调试中的重要工具。为FDD基准测试提供统一的数据集是准确评估FDD预测准确性和检测异常的必要条件。在这项研究中，我们提供了一个空气处理单元的实验数据集，该单元包含两个由空气对空气热交换器连接的管道。该数据集由系统的标称操作和错误操作组成，包括地面真相，以便调查52种情况下的各种故障。该数据集是通过测量具有真实气候变化的代表性系统获得的，就像楼宇自动化系统获得的那样。在标称序列和故障序列之间的转换是连续的，就像在实际运行条件下一样。进行了不确定度评估，以提供实验数据集的置信范围。

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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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.