Abstract

This paper presents the design of a methodology for distributed detection and isolation of multiple sensor faults in heating, ventilation and air-conditioning (HVAC) systems. The proposed methodology is developed in a distributed framework with the HVAC system modeled as a set of interconnected, nonlinear subsystems. A local sensor fault diagnosis (LSFD) agent is designed for each of the interconnected subsystems. The LSFD agent uses input and sensor output data of its underlying subsystem and it may exchange information with the neighboring agents. The distributed sensor fault detection is conducted using robust analytical redundancy relations, formulated by estimation-based residuals and adaptive thresholds. The distributed sensor fault isolation is carried out by combining the decisions of the LSFD agents and applying a reasoning-based decision logic. Simulation results are used for illustrating the effectiveness of the proposed methodology applied to a two-zone HVAC system.

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