TY - JOUR A2 - Li, Gang AU - Pous, Nicolas AU - Gingras, Denis AU - Gruyer, Dominique PY - 2017 DA - 2017/01/16 TI - Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations SP - 1763934 VL - 2017 AB - This work proposes a fault detection architecture for vehicle embedded sensors, allowing to deal with both system nonlinearity and environmental disturbances and degradations. The proposed method uses analytical redundancy and a nonlinear transformation to generate the residual value allowing the fault detection. A strategy dedicated to the optimization of the detection parameters choice is also developed. SN - 1687-5249 UR - https://doi.org/10.1155/2017/1763934 DO - 10.1155/2017/1763934 JF - Journal of Control Science and Engineering PB - Hindawi KW - ER -