A mobile measurement solution for fault detection and diagnosis in buildings

Abstract

Buildings are equipped with increasingly complex Heating, Ventilation and Air Conditioning (HVAC) systems whose energy efficiency can degrade over time because of unnoticed faults. Facility managers (FM) often do not have the time and adapted tools to identify and correct issues. Building Automation Systems generate a multitude of measurement data that can be used to identify operational malfunctions at an early stage by applying fault detection and diagnosis (FDD) methods. However, this data itself can be hardly accessible and contain errors for example due to the degradation of the sensor quality over time. These issues limit the application of analytic methods like FDD in existing buildings. In this paper, we present a prototype implementation of a mobile measurement system based on Internet of Things (IoT) technologies that functions together with an automated FDD system to detect operational faults in HVAC systems independently of the existing measurement infrastructure. Additionally, the solution provides a user interface giving a quick overview on found faults and displaying them in spatial relation with the HVAC system through an integrated BIM visualization. Here, we describe the technical details and the required conditions for the use of our prototype and show the results of an exemplary implementation on an air handling unit.