Uncertainty Quantification in System-level Prognostics: Application to Tennessee Eastman Process

Abstract

This paper addresses the problem of uncertainty quantification in system-level prognostics. To this purpose, a three-step methodology, based on the inoperability input-output model, is presented. The first step concerns the estimation of the system inoperability, using a new adapted particle filtering method, while considering the interactions between its components. The second step focuses on the long-term prediction of the system inoperability in order to determine its evolution. Finally, in the third step, a method for calculating the remaining useful life of the system, based on the system configuration, is formulated. The proposed methodology is applied on data obtained from the Tennessee Eastman Process simulations to predict the shutdown due to violation of process constraints.

System-level failure prognostics: Literature review and main challenges

“…In (88), and based on the new paradigms proposed in (130; 131), a probabilistic SRUL calculation is proposed for series and parallel configuration. Many systems are made up of these types of configurations or with more complex compositions from these simple ones, e.g., parallel-series or series-parallel.…”

“…However, some prognostic works are beginning to address large-scale systems. For instance, in (23), the risks of "loss of separation" (two In (88), in a large-scale industrial system composed of several interconnected systems, a failure is considered as the interruption of the operational continuity resulting from the violation of the variables shutdown limits. In (63), the authors proposed a method based on multi-agent computing to update information on the health status of several components/systems.…”

“…For instance, in Daigle et al, 23 the risks of ''loss of separation'' (two aircraft becoming very close) and dry breakdowns are considered as reversible progressive degradation, and the aim is to determine, by Monte Carlo simulation algorithms, the time before these risks exceed a certain probability. In Tamssaouet et al, 88 in a large-scale industrial system composed of several interconnected systems, a failure is considered as the interruption of the operational continuity resulting from the violation of the variables shutdown limits. In Benaggoune et al, 63 the authors proposed a method based on multi-agent computing to update information on the health status of several components/systems.…”

Challenges and Opportunities of System-Level Prognostics

“…Parallel Monte Carlo simulation and recursive Bayesian method are integrated for the purpose of failure prognostics under dependency While the list of papers for this approach is given in Table 3, some of them are explained in detail as follows. Tamssaouet et al [97][98][99][100][101][102] proposed a methodology based on the inoperability input-output model to evaluate the system-level RUL in the situation where multiple interactions between components and the influence of the environment exist. Liu et al [103] introduced dynamic reliability assessment and RUL prediction of a system that consists of a pump and valve.…”

“…Tennessee Eastman Process Inoperability input-output model [97][98][99][100][101][102] Interaction between components Influence of the environment…”