Performing Diagnosis in Building with Partially Valid Heterogeneous Tests

Year: 2019 Volume: 13 Issue: 10 654 - 659 Pages

• Authors:
• Houda Najeh
• Mahendra Pratap Singh
• Stéphane Ploix
• Antoine Caucheteux
• Karim Chabir
• Mohamed Naceur Abdelkrim

Abstract: Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

• Keywords:
• Heterogeneous tests
• validity
• building system
• sensor grids
• sensor fault
• diagnosis
• fault detection and isolation.

Automatic Thresholding for Data Gap Detection for a Set of Sensors in Instrumented Buildings

Year: 2019 Volume: 13 Issue: 1 1 - 5 Pages

• Authors:
• Houda Najeh
• Stéphane Ploix
• Mahendra Pratap Singh
• Karim Chabir
• Mohamed Naceur Abdelkrim

Abstract: Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

• Keywords:
• Building system
• time series
• diagnosis
• outliers
• delay
• data gap.