Artificial neural network models for predicting degradation trends in system components and sensors

A prediction model based-on artificial neural network technology was developed for trend forecasting of a given degradation process in a system component. The model utilizes the engineering analysis of the degradation process under study with the analysis of process field data and information to pre...

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Bibliographic Details
Published inProceedings AUTOTESTCON 2003. IEEE Systems Readiness Technology Conference pp. 647 - 651
Main Authors Naghedolfeizi, M., Arora, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Artificial neural networks
Biological neural networks
Biological system modeling
Degradation
Information analysis
Inspection
Intelligent networks
Mathematics
Predictive models
Sensor systems
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Summary:A prediction model based-on artificial neural network technology was developed for trend forecasting of a given degradation process in a system component. The model utilizes the engineering analysis of the degradation process under study with the analysis of process field data and information to predict future trend in the degradation. The neural network prediction models were applied to simulated degradation data of a typical system component. The prediction results showed that the neural network models were capable of recognizing the correct future degradation trends in data even with a limited amount of input data. In addition, the models were able to capture the dynamics and nonlinearities associated with the degradation process data.
ISBN:0780378377
9780780378377
ISSN:1080-7725
DOI:10.1109/AUTEST.2003.1243645