Solenoid operated valves (SOVs) are critical components in many industrial applications. There has been a continuing interest in the industry to have robust condition monitoring, prognostics and health management tools to support the condition based maintenance and predictive maintenance program for such valves. For critical assets like SOVs, it is of paramount interest to understand why a component might be declared as defective. In such a situation, a first principle-model based approach will always be preferred to a purely data-driven approach, because of its inherent interpretability. Furthermore, first principle-models typically have less free parameters than their data driven counterparts and will require less data to identify their parameters. In this paper, we present the improvement of a first-principle model of alternating current (AC) powered SOVs taking into account two important degradation effects. Using this model, we show that the state of degradation can be estimated from current and input voltage measurement signals on the solenoids. Our method is validated using data from an accelerated life test campaign on 48 identical AC-powered SOVs.
Keywords: AC solenoid operated valves; Accelerated life test; Condition monitoring; Magneto-mechanical modelling; Shading ring; Wear.
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