Title :
Statistical Classifiers for Structural Health Monitoring
Author :
Tschöpe, Constanze ; Wolff, Matthias
Author_Institution :
Fraunhofer-Inst. fur Zerstorungsfreie Prufverfahren, Dresden, Germany
Abstract :
Multisensor problems are important tasks in the field of structural health monitoring. By means of signals originating from different sensors, we have to make a decision about the test object. We describe a universal, largely problem independent method, which applies statistical classifiers in order to identify objects or assess their state. This work presents the results of a series of studies, which systematically investigated such approaches for a great variety of technical and biological signals. We give an overview on the theoretical background and describe two selected application examples.
Keywords :
acoustic signal detection; condition monitoring; hidden Markov models; pattern classification; structural engineering computing; acoustic signal detection; hidden Markov models; multisensor problems; pattern classification; statistical classifiers; structural health monitoring; Aircraft; Computerized monitoring; Hidden Markov models; Information analysis; Nondestructive testing; Signal analysis; Signal detection; Signal processing; Support vector machine classification; Support vector machines; Acoustic signal detection; aircraft testing; hidden Markov models (HMM); multisensor systems; nondestructive testing; pattern classification; support vector machines (SVM);
Journal_Title :
Sensors Journal, IEEE
DOI :
10.1109/JSEN.2009.2019330