Principles of data-fusion in multi-sensor systems for non-destructive testing

Chioclea, Shmuel; Dickstein, Phineas
May 2000
AIP Conference Proceedings;2000, Vol. 509 Issue 1, p805
Academic Journal
In recent years, there has been progress in the application of measurement and control systems that engage multi-sensor arrays. Several algorithms and techniques have been developed for the integration of the information obtained from the sensors. The fusion of the data may be complicated due to the fact that each sensor has its own performance characteristics, and because different sensors may detect different physical phenomena. As a result, data fusion turns out to be a multidisciplinary field, which applies principles adopted from other fields such as signal processing, artificial intelligence, statistics, and The Theory of Information. The data fusion machine tries to imitate the human brain, in combining data from numerous sensors and making optimal inferences about the environment. The present paper provides a critical review of data fusion algorithms and techniques and a trenchant summary of the experience gained to date from the several preliminary NDT studies which have been applying multi-sensor data fusion systems. Consequently, this paper provides a list of rules and criteria to be followed in future applications of data fusion to nondestructive testing. © 2000 American Institute of Physics.


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