Damage Informatics for Steam Turbine Components

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Kazunari Fujiyama
Kazunari Fujiyama
α Meijo University Meijo University

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Damage Informatics for Steam Turbine Components

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Abstract

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 equiprobability 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.

References

8 Cites in Article
  1. Kazunari Fujiyama (2011). Risk based engineering for design, material selection and maintenance of power plants.
  2. K Fujiyama,T Kubo,Y Akikuni,T Fujieara,H Kodama,M,T Kawabata (2007). An Integrated Approach of Risk Based maintenance for Steam Turbine Components.
  3. K Fujiyama,T Fujiwara,Y Nakatani,K Daito,A Sakuma,Y Akikuni,S Hayashi,S Matsumoto (2008). Design, Material Selection and Life Assessment of High Temperature Components Using the Unified Statistical Master Curves of Material Properties.
  4. K Fujiyama,H Suzuki,T Tsuboi (2010). Risk-Based Maintenance Procedures for Compound Damage Modes of High Temperature Components.
  5. K Fujiyama,H Ueno,H Hirano,H Kimachi (2013). Risk-based design and maintenance measures for high temperature components under creep-fayigue conditions using Bayesian approach.
  6. J Pearl (2000). Causality: Models, Reasoning and Inference.
  7. G Wadsworth,J Bryan (1974). Applications of Probability and Random Variables, Second Edition.
  8. T Bedford,R Cooks (2009). Probabilistic Risk Analysis: Foundations and Methods.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Kazunari Fujiyama. 2014. \u201cDamage Informatics for Steam Turbine Components\u201d. Global Journal of Research in Engineering - A : Mechanical & Mechanics GJRE-A Volume 14 (GJRE Volume 14 Issue A6): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Version of record

v1.2

Issue date

August 20, 2014

Language
en
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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 equiprobability 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.

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Damage Informatics for Steam Turbine Components

Kazunari Fujiyama
Kazunari Fujiyama Meijo University

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