A systematic fault diagnosis strategy for building HVAC systems.

摘要

The building energy use accounts for a large portion of energy end use of commercial sectors. The performance of HVAC systems is very important in terms of energy saving and energy efficiency. However, the HVAC systems may suffer various faults. The thesis presents a three-level FDD strategy for the building HVAC systems, i.e. the building load estimation/forecast scheme for overall building performance, the system-level FDD scheme for the HVAC systems and the component-level scheme for the chiller.;The building-level diagnosis scheme adopts a simplified building load estimation model as the benchmark to characterize the overall performance of the entire building system. The building load estimation scheme using monitoring weather information via building management systems (BMS) as the input of the building thermal network model is applied in the building-level diagnosis. The building load forecast scheme using the weather forecast information from the observatory as the input of the building thermal network model is applied in the optimal control strategies.;The system-level FDD scheme for the HVAC systems has two steps. The first step is to detect, diagnose the sensor, and to estimate the fault (i.e. sensor fault detection, diagnosis and bias estimation (FDD&E)) prior to the use of the system FDD method. The second step is to diagnose the system (i.e., system FDD) by using the sensor FDD&E as the guarantee of measurement health.;As chillers take the largest part of the power consumption in HVAC systems, the component-level FDD scheme for the chiller is developed using fuzzy modeling and artificial neural network (ANN). All the PI residuals are fuzzified into a series of standardized quantitative PIs (SQPs) using membership functions. SQP is very effective to distinguish the faults, even to the faults having the same qualitative rule patterns. Then, ANN is used to identify the chiller fault by matching the SQPs with the fault category.;The three-level building HVAC system diagnosis strategy is developed into a software package implemented on IBmanager, which is an open integration and management platform for intelligent building systems based on the middleware technologies.