A decentralized sensor fault detection and self-repair method for HVAC systems

Abstract

This study proposes a novel decentralized sensor fault detection and self-repair method for heating, ventilation and air-conditioning systems. From the perspective of network structure, sensor fault diagnosis in heating, ventilation and air-conditioning systems is distributed to the updated smart sensors without the monitoring host, which is necessary in the traditional centralized method. A fully distributed flat sensor network is established based on fundamental physical equations. Similar to the structure, mechanism and characteristics of biological communities, a smart sensor needs only to communicate with adjacent nodes and operate collaboratively to complete sensor fault detection and self-repair tasks. These tasks are formulated as a constrained optimization and are solved by a decentralized algorithm with a penalty function executed in all the sensor nodes in parallel. The diagnosis model introduces an exponential function method to determine the precise location and undertake self-repair of a fault node. Simulation results on a chilled water system illustrate the effectiveness of the proposed method.

Practical application : The traditional sensor fault detection and diagnosis methods for heating, ventilation and air-conditioning systems are based on a centralized structure with several deficiencies, such as high maintenance and labor costs, link congestion and operational lag. This study presents a decentralized sensor network structure and exponential-function-based method that possess the advantages of plug-and-play, rapid deployment, high flexibility and convenience for engineering implementation without having to build a central monitor. The efficiency and effectiveness of the proposed method are demonstrated via a case study.

Keywords

Heating ventilation and air-conditioning sensors fault detection and self-repair decentralized optimization penalty function

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