Discovery of diagnostic knowledge from multisensor data

Wojciech A. Moczulski; Jan M. Zytkow

doi:10.1117/12.421064

27 March 2001 Discovery of diagnostic knowledge from multisensor data

Wojciech A. Moczulski, Jan M. Zytkow

Proceedings Volume 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III; (2001) https://doi.org/10.1117/12.421064
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

The paper deals with discovering qualitative and functional dependencies among attributes that describe a complex technical object. The database contains data which are values of control parameters applied in the experiment and multiple features of vibration signals. These signals can be acquired by a multi-sensor measuring system. Information carried by signals acquired from different sensors is in some sense complementary. However, since correlation between signals observed by some sensors is likely, some redundancy in the data may be achieved. Since redundancy may yield reliability and better quality of predictions, it is reasonable to take it into consideration in the model. The attempt depends on selection of the right combination of attributes and then on recursive application of the Equation Finder in order to find functional equations containing control and dependent attributes. Further on, the equations may be inverted providing the opportunity to obtain predictions of values of control attributes, that is the task of the diagnostics of the object. Such knowledge may then be applied in a diagnostic expert system.

Citation Download Citation

Wojciech A. Moczulski and Jan M. Zytkow "Discovery of diagnostic knowledge from multisensor data", Proc. SPIE 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, (27 March 2001); https://doi.org/10.1117/12.421064

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