Diagnosis and Failure Prognosis of Intermittent Faults: A Bond Graph Approach

Abstract

Diagnosis of incipient parametric faults has been widely addressed and various model-based as well as data-based methods have been reported in the literature. In contrast to incipient faults, it is unknown if, when and for how long intermittent faults will reappear which makes their diagnosis and prognosis difficult. This paper addresses intermittent faults with a magnitude that increases over time. Such a sequence of intermittent faults may reach a failure alarm threshold and may eventually lead to a component or even a system failure. The proposed approach uses a diagnostic Bond Graph (DBG) model for an online detection, isolation and estimation of intermittent faults. Pulses of increasing height and varying width not equally spaced on the time evolution of residuals of Analytical Redundancy Relations (ARRs) obtained from an offline developed DBG indicate a degradation trend of a parameter or a variable. Certain values of this trend are concurrently extrapolated in a repeated failure prognosis resulting in a sequence of Remaining Useful Life (RUL) estimates. The proposed BG-based approach to a failure prognosis in the presence of intermittent faults can be combined with a previously presented BG-approach to incipient fault prognosis and is applicable to mode switching models. For illustration, it is applied in a case study to a small electronic circuit in an offline simulation. The case study also considers intermittent faults of constant magnitude.