CALCE Presents during Special Sessions at AAAI Symposium
Association for the Advance Artificial Intelligence organized a special session on the uses of Artificial Intelligence for Prognostics. CALCE PHM group presented four papers on Electronics Prognostic included a prognostic methodology using symbolic time series analysis to detect anomalies and predict the future health of electronic products, the use of principle component analysis with support vector machines (SVMs) to detect and predict the health of multivariate systems based on training data representative of healthy operating condition, the use of Multivariate State Estimation Techniques as input in estimating the remaining useful life of electronic products and a methodology to consider uncertainty present in system while doing prognostics with a focus on electronic system subjected to random vibration.