Semi-Markov Model for the Oxidation Degradation Mechanism in Gas Turbine Nozzles

Abstract

This paper presents the statistical characterization of the oxidation degradation mechanism affecting the nozzles of turbines operated in Oil and Gas utilities. The degradation mechanism is modeled as a four-state, continuous-time semi-Markov process with Weibull distributed transition times. Maximum likelihood estimation is used to infer the parameters of the model from an available set of field data, whereas a numerical approach to estimate the Fisher information matrix is used to characterize the uncertainty in the estimates. The estimates obtained are, then, utilized to compute the probabilities of occupying the four degradation states over time and the corresponding uncertainties. A case study is shown, dealing with real field data

The future of risk assessment

“…Models capable of considering the sequential dynamics of such activities should be used for the emergency phase, e.g., the event sequence diagram [222]. The recovery process also involves the dynamics of maintenance actions, which can be effectively described in terms of the process of transitions between system states, e.g., by semi-Markovian models [52].…”

“…Additional information potentially useful for the estimation of the risk indexes may come from condition-monitoring data. In practice, accident initiating events and safety barriers failures usually occur as a result of degradation mechanisms, e.g., wear [218], corrosion [217], fatigue [83], crack growth [28], oxidation [52], etc. The degradation processes can be monitored in real time and failures can be predicted and anticipated with reference to specific thresholds of the monitored variables.…”

Genetic algorithms for condition-based maintenance optimization under uncertainty

“…The general methodology to estimate these quantities can be found in [13]. In particular, to test the potential of the proposed GA advancements in treating uncertain fitnesses, we consider two numerical settings, with different amount of uncertainty affecting the estimates (Table 1).…”

An unsupervised clustering method for assessing the degradation state of cutting tools used in the packaging industry

“…Multi-state modelling frameworks have been developed for membranes of pumps operating in Nuclear Power Plants (Baraldi et al, 2011), turbine nozzles for the Oil&Gas industry (Compare et al 2016), liners of marine diesel engine cylinders (Giorgio et al, 2011), piping of nuclear power plants (Veeramany et al, 2011) (Cannarile et al, 2017).…”