Decisions in condition monitoring-an examplar for data fusion architecture

This paper aims to demonstrate the strategy and structures involved in making decisions based on condition data, and to draw parallels with data fusion models. A new df model is demonstrated, and examples are drawn from condition monitoring applications. In particular, the work introduces a new framework for the application of data fusion solutions to the analysis of engineering problems. A review of frameworks used in data fusion applications is presented, along with important factors to consider in the layout of a robust process model, to host a coherent and effective data fusion problem-solving strategy. The main theme of the work focuses on the development of an intelligent multi-sensored engine. The partners involved in this research effort aim to develop a robust methodology for sensing and analysis under harsh environments, stressing its application to the fields of combustion and fault diagnostics analysis. The proposed process model will be used to facilitate the implementation of a common strategy to tackle these problems.