Scalable distributed sensor fault diagnosis for smart buildings

被引:19
作者
Papadopoulos, Panayiotis M. [1 ]
Reppa, Vasso [2 ]
Polycarpou, Marios M. [1 ]
Panayiotou, Christos G. [1 ]
机构
[1] Univ Cyprus, Dept Elect & Comp Engn, KIOS Res & Innovat Ctr Excellence, Nicosia 1678, Cyprus
[2] Delft Univ Technol, Dept Maritime & Transport Technol, Delft 2628 CD, Netherlands
关键词
Building automation; fault diagnosis; fault location; smart homes; AIR HANDLING UNIT; DETECTION STRATEGY; SYSTEMS; SCHEME; CLUSTER;
D O I
10.1109/JAS.2020.1003123
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The enormous energy use of the building sector and the requirements for indoor living quality that aim to improve occupants' productivity and health, prioritize Smart Buildings as an emerging technology. The Heating, Ventilation and Air-Conditioning (HVAC) system is considered one of the most critical and essential parts in buildings since it consumes the largest amount of energy and is responsible for humans comfort. Due to the intermittent operation of HVAC systems, faults are more likely to occur, possibly increasing eventually building's energy consumption and/or downgrading indoor living quality. The complexity and large scale nature of HVAC systems complicate the diagnosis of faults in a centralized framework. This paper presents a distributed intelligent fault diagnosis algorithm for detecting and isolating multiple sensor faults in large-scale HVAC systems. Modeling the HVAC system as a network of interconnected subsystems allows the design of a set of distributed sensor fault diagnosis agents capable of isolating multiple sensor faults by applying a combinatorial decision logic and diagnostic reasoning. The performance of the proposed method is investigated with respect to robustness, fault detectability and scalability. Simulations are used to illustrate the effectiveness of the proposed method in the presence of multiple sensor faults applied to a 83-zone HVAC system and to evaluate the sensitivity of the method with respect to sensor noise variance.
引用
收藏
页码:638 / 655
页数:18
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