An Fmi-based Toolchain for the Adoption of Model-based Fdd

نویسندگان

  • Marco Bonvini
  • Michael Wetter
  • Michael D. Sohn
چکیده

This work presents a toolchain based on the Functional Mockup Interface (FMI) standard for accelarating the adoption of model-based Fault Detection and Diagnostics (FDD) algorithms. The presented toolchain uses nonlinear state estimation techniques to detect multiple simultaneous faults in presence of noisy sensor measurements. The toolchain enables the use of a dynamic model that emulates correct and faulty equipment, while keeping the computing effort low. The FDD toolchain allows importing dynamic models through an interface that complies with the FMI standard, an application programming interface for the exchange of models which is supported by many simulation tools. This functionality reduces the modeling effort required to setup a model-based FDD algorithm because it allows taking advantage of models available in open-source libraries for building components and HVAC systems that can model various fault scenarios.

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تاریخ انتشار 2014