34 citations · 80 across the 8 of their papers we have counts for
8 papers
Data-driven Residual Generation for Early Fault Detection with Limited Data
Hamed Khorasgani, Ahmed Farahat, Chetan Gupta
Traditionally, fault detection and isolation community has used system dynamic equations to generate diagnosers and to analyze detectability and isolability of the dynamic systems.…
Deep Time Series Models for Scarce Data
Qiyao Wang, Ahmed Farahat, Chetan Gupta +1
Time series data have grown at an explosive rate in numerous domains and have stimulated a surge of time series modeling research. A comprehensive comparison of different time seri…
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz +5
Deep learning classifiers are assisting humans in making decisions and hence the user's trust in these models is of paramount importance. Trust is often a function of constant beha…
Health Indicator Forecasting for Improving Remaining Useful Life Estimation
Qiyao Wang, Ahmed Farahat, Chetan Gupta +1
Prognostics is concerned with predicting the future health of the equipment and any potential failures. With the advances in the Internet of Things (IoT), data-driven approaches fo…
Generative Adversarial Networks for Failure Prediction
Shuai Zheng, Ahmed Farahat, Chetan Gupta
Prognostics and Health Management (PHM) is an emerging engineering discipline which is concerned with the analysis and prediction of equipment health and performance. One of the ke…
Remaining Useful Life Estimation Using Functional Data Analysis
Qiyao Wang, Shuai Zheng, Ahmed Farahat +2
Remaining Useful Life (RUL) of an equipment or one of its components is defined as the time left until the equipment or component reaches its end of useful life. Accurate RUL estim…