Bivariate statistical analysis through cumulative hazard function method for plant damage incident evaluation

Abstract

Bivariate log-normal distribution analyses coupled with the cumulative hazard function method were conducted on the specific output class of 8 steam turbine units with components such as rotors, moving blades, nozzles, casings and other auxiliary equipment of high-, intermediate- and low-pressure turbines. The damage phenomena were classified into erosion, crack, deformation, corrosion, creep void formation and material degradation with corresponding components. Operation time and start up cycles for damage incidence in respective units were collected and statistically analyzed adding the non-failed data as well as failed data. After applying the bivariate log-normal distribution regression to those data sets, the prescribed failure probability was imposed to construct the equal probability ellipse contours as the quadratic function of operation time and start-up cycles. To determine whether the events were time dependent or cycle dependent, the shape and inclination of the contours were utilized. The order of event incidence was determined by using the lower end values of the major axis of equal probability contours. Although the order of event incidence could show variations according to the prescribed failure probability values, the examples for 90% probability ellipse contours were demonstrated here. The assessment results showed that the statistical analyses were effective for investigating the damage incidental scenario making and maintenance planning for actual plants.