Statistical data analyses were conducted on the variety of damage modes occurred in steam turbine major components such as high pressure turbine blades/nozzles, casings and low pressure turbine rotors and blades. The data were fitted using log-normal distribution function of operation time and number of starts. Two dimensional distribution functions were constituted by combining the marginal distribution functions of operation time and number of starts. Time-cycle mapping for various events indicated that apparent order of event occurrence and the equi-probability loci representing the time or cycle dependency and data distribution range. The best fit line for mean values of time and cycles of each event was adopted to evaluate the probability function of operation time and used to calculate resultant risk function along the line. The rational results were obtained to determine optimum maintenance periods from the risk functions established for respective turbine sections. The entire procedure including time-cycle mapping expression has been proved to be a quite useful tool for damage assessment, causality assessment and resultant risk assessment to improve the maintenance technology and can be categorized in the brand-new “Damage Informatics†concept.

How to Cite
FUJIYAMA, Kazunari. Damage Informatics for Steam Turbine Components. Global Journal of Research In Engineering, [S.l.], aug. 2014. ISSN 2249-4596. Available at: <https://engineeringresearch.org/index.php/GJRE/article/view/1048>. Date accessed: 12 june 2021.