A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

作者：Zufiria Pedro J^*

来源：Applied Mathematics and Computation, 2012, 218(23): 11391-11403.

DOI：10.1016/j.amc.2012.05.024

• Fault diagnosis
• Continuous-time dynamical systems
• Quickest detection
• Ornstein-Uhlenbeck stochastic process

In this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein-Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.

• 出版日期2012-8-1