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Analysis of HVAC sensor characteristics for operation and maintenance of the indoor environment: A case research on public building HVAC

Zhang, Boyan, Wang, Jiaming, Shangguan, Liuyang, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400, Ghoroghi, Ali, Cao, Ximing, Song, Chengzhe, Ding, Menglin and Zhao, Tianyi 2025. Analysis of HVAC sensor characteristics for operation and maintenance of the indoor environment: A case research on public building HVAC. Building Simulation 10.1007/s12273-025-1254-6
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Abstract

Sensors are a crucial component in heating, ventilation, and air conditioning (HVAC) control systems, and the quality of them plays an important role in control accuracy. In the research of fault detection and control optimization, improving sensor data quality has inspiring potential in application. It has been largely limited to the application of signal processing methods in research focus, whereas a detailed analysis of the characteristics of signals from various sensors of the HVAC system has not been conducted. Therefore, this study analyzes the time-frequency domain characteristics of control sensors within HVAC systems through integrating the structural design and control logic of such systems. Additionally, the research examines the correlations between control sensors in HVAC systems. Based on statistical principles and the energy-mass dynamic laws of the equipment, this paper defines first-class (I) correlated sensors and second-class (II) correlated sensors. To sum up, the main contribution of this paper is conducting a fundamental study on the characteristics of control sensors within HVAC systems, providing theoretical reference for future research on HVAC system fault diagnosis and control optimization.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Schools > Engineering
Publisher: Springer
ISSN: 1996-3599
Date of First Compliant Deposit: 13 May 2025
Date of Acceptance: 9 February 2025
Last Modified: 13 May 2025 13:30
URI: https://orca.cardiff.ac.uk/id/eprint/177643

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