Master Thesis: A Framework for Fault Detection and Identification for Smart Energy Systems in Office Environments

Motivation:

A reliable and robust smart energy system should also have features to isolate and identify faults by observing the behavior of components, actuators and sensors. The fortiss smart energy demonstrator operating in the fortiss office environment is a middleware, which monitors and controls (smart) devices (e.g. light switches, electric plugs etc.).

In the absence of such feature, the presence of a fault is detected only when a component-level or system-level failure occurs, which leads to total disruption of the system. For instance, a potential fault is indicated by the registration of a light-switch signal but the lack of increase in power consumption or the lack of increase in measured brightness. At the same time, a coincidental increase in brightness but a lack of increase in power consumption can be an indication of a defect in the power meter.

Objective:

The goal of this thesis is to extend an existing component that checks the running status of different components in the demonstrator. A framework will be developed to detect and identify the software faults with in the demonstrator using the model-based fault detection and Identification techniques.

Tasks:

  • An in-depth literature survey on model-based Fault Detection and Identification (FDI) techniques.
  • Development of use cases, design and requirement identification within the scope of the demonstrator.
  • Creation of a FDI framework and implementation of the framework into the fortiss smart energy demonstrator.
  • Evaluation of the framework according to the requirements and suitability of the approach w.r.t the Service Oriented Architecture-based distributed systems.

 Prerequisites:

  • Good knowledge of Java
  • Automata and logic theory knowledge
  • Knowledge of matlab/simulink

Contact and Information: Pragya Kirti Gupta, Markus Duchon,  Bernhard Schätz