Development and alpha testing of a cloud based automated fault detection and diagnosis tool for Air Handling Units

• Expansion of the APAR rule based approach to AFDD
• Development of a data access layer for the extraction of BMS data
• Development of a new AHU AFDD tool as part of an industry partnered research project
• Demonstration of an automated FDD tool in large commercial and industrial sites
• Alpha test results from online testing of an AFDD tool

Heating Ventilation and Air Conditioning (HVAC) system energy consumption on average accounts for 40% of an industrial sites total energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning Air Handling Units (AHUs) in HVAC systems to rectify faulty operation. Studies have also demonstrated that on-going commissioning of building systems for optimum efficiency can yield savings of an average of over 20% of total energy cost. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with automating the detection of faults and their causes in physical systems. AFDD can be used to assist the commissioning process at multiple stages. This paper outlines the development of an AFDD tool for AHUs using expert rules. It outlines the results of the alpha testing phase of the tool on 18 AHUs across four commercial & industrial sites with over €104,000 annual energy savings detected by the AFDD tool.