Scalable distributed sensor fault diagnosis for smart buildings

Abstract

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.

Joint State and Fault Estimation of Complex Networks Under Measurement Saturations and Stochastic Nonlinearities

“…where Φ i,s+1 and F are given in (33) and (35), respectively. When (32) holds, it is obvious that (74) is solvable and the solution satisfies…”

“…In [4], [5], the distributed fault detection problem has been studied for a class of complex networks by resorting to the concept of Plug-and-Play [37], [41], where Schur stability of the estimation and detection strategy has been discussed in details as well. In the presence of bounded disturbances and unmodeled dynamics, [23], [35] have analyzed the FD and fault-tolerant control problems in distributed systems, where the conditions guaranteeing the detection and isolation of faults have been quantitatively established. The fault estimation and fault-tolerant control issues have been considered in distributed multi-agent systems in [26], [27] via sliding-mode and hierarchical-structure approaches, respectively.…”

A Digital Twin Architecture for Smart Buildings

“…The first use case investigates how a temperature sensor fault can affect the indoor air quality and energy consumption. An operational fault (e.g., offset fault) of the temperature sensor of the thermostat can lead to a poor energy performance and can create inconvenient environmental conditions for the occupants according to [14]. After investigating the effect of such failures on the building operation, the plan for future work includes the design of intelligent fault diagnosis and accommodation schemes to compensate the undesired impact.…”

SA1D-CNN: A Separable and Attention Based Lightweight Sensor Fault Diagnosis Method for Solar Insecticidal Lamp Internet of Things

“…However, the performance of sensors in SIL-IoTs nodes is affected by burn-in, damage, low quality, and improper maintenance [2]- [4]. When sensors become faulty, data unreliability can be a major drawback for the functions of SIL-IoTs (e.g., energy management, counting of killed pests, and monitoring components of SIL-IoTs) [5].…”