Fault Diagnosis in Air-Conditioning Systems: A Multi-Step Fuzzy Model-Based Approach

Model-based Fault Detection and Diagnosis of HVAC systems using Support Vector Machine method

“…Furthermore, several studies were also presented to deal with the faults in the air handling unit (AHU) [14e18] and sensors [19,20], respectively. At the same time, some advanced algorithms, such as transient pattern analysis [21], multi-step fuzzy model-based approach [14], general regression neural networks [15], and feedforward control scheme [22], etc. were also utilized to detect and diagnose the faults in the HVAC systems.…”

Online sensor fault diagnosis for robust chiller sequencing control

“…Generally, sensor fault diagnosis methods can be grouped into two categories: model-based methods [9][10][11][12][13][14] and model-free methods [15][16][17]. The model-based diagnosis methods usually use an explicit model, such as physical models, data-driven models (black-box models) or semi-physical models (grey-box models), to describe the behaviors of the target systems or measurement tools.…”

Fault tolerant control of outdoor air and AHU supply air temperature in VAV air conditioning systems using PCA method

“…The knowledge based approaches, such as expert systems [5], neural net [6] and fuzzy theory [7], are widely used to detect and diagnosis faults. To some simple systems, it is easy to detect and diagnosis faults using these methods.…”