Validation of Reliability Prediction Models
This paper proposes new methods to assess the validity of reliability prediction models through a Bayesian approach. The concept of Bayesian hypothesis testing is extended to system-level problems where full-scale testing is impossible. Component-level validation results are used to derive a system-...
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| Veröffentlicht in: | SAE transactions 2003-01, Vol.112, p.452-458 |
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| container_title | SAE transactions |
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| creator | Rebba, Ramesh Mahadevan, Sankaran Zhang, Ruoxue |
| description | This paper proposes new methods to assess the validity of reliability prediction models through a Bayesian approach. The concept of Bayesian hypothesis testing is extended to system-level problems where full-scale testing is impossible. Component-level validation results are used to derive a system-level validation measure. This derivation depends on the knowledge of interrelationships between component modules. Bayes networks are used for the propagation of validation information from the component-level to system-level. Validation of reliability prediction model for a single degree of freedom oscillator under high-cycle fatigue and fatigue life prediction of a helicopter rotor hub is illustrated for this purpose. |
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The concept of Bayesian hypothesis testing is extended to system-level problems where full-scale testing is impossible. Component-level validation results are used to derive a system-level validation measure. This derivation depends on the knowledge of interrelationships between component modules. Bayes networks are used for the propagation of validation information from the component-level to system-level. Validation of reliability prediction model for a single degree of freedom oscillator under high-cycle fatigue and fatigue life prediction of a helicopter rotor hub is illustrated for this purpose.</description><subject>Bayesian networks</subject><subject>Delamination</subject><subject>Estimate reliability</subject><subject>Modeling</subject><subject>Natural frequencies</subject><subject>Probabilities</subject><subject>Random variables</subject><subject>Statistics</subject><subject>System failures</subject><subject>Test data</subject><issn>0096-736X</issn><issn>2577-1531</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNpjYuA0MjU31zU0NTZkYeA0MLA00zU3NovgYOAqLs4yMDA2NDU34mTQDkvMyUxJLMnMz1PIT1MISs3JTEzKzMksqVQIKEpNyUwGy_jmp6TmFPMwsKYl5hSn8kJpbgZZN9cQZw_drOKS_KL4gqLM3MSiyngTEzNLSzMDE2NC8gDa6y55</recordid><startdate>20030101</startdate><enddate>20030101</enddate><creator>Rebba, Ramesh</creator><creator>Mahadevan, Sankaran</creator><creator>Zhang, Ruoxue</creator><general>Society of Automotive Engineers, Inc</general><scope/></search><sort><creationdate>20030101</creationdate><title>Validation of Reliability Prediction Models</title><author>Rebba, Ramesh ; Mahadevan, Sankaran ; Zhang, Ruoxue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-jstor_primary_446996043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Bayesian networks</topic><topic>Delamination</topic><topic>Estimate reliability</topic><topic>Modeling</topic><topic>Natural frequencies</topic><topic>Probabilities</topic><topic>Random variables</topic><topic>Statistics</topic><topic>System failures</topic><topic>Test data</topic><toplevel>online_resources</toplevel><creatorcontrib>Rebba, Ramesh</creatorcontrib><creatorcontrib>Mahadevan, Sankaran</creatorcontrib><creatorcontrib>Zhang, Ruoxue</creatorcontrib><jtitle>SAE transactions</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rebba, Ramesh</au><au>Mahadevan, Sankaran</au><au>Zhang, Ruoxue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of Reliability Prediction Models</atitle><jtitle>SAE transactions</jtitle><date>2003-01-01</date><risdate>2003</risdate><volume>112</volume><spage>452</spage><epage>458</epage><pages>452-458</pages><issn>0096-736X</issn><eissn>2577-1531</eissn><abstract>This paper proposes new methods to assess the validity of reliability prediction models through a Bayesian approach. The concept of Bayesian hypothesis testing is extended to system-level problems where full-scale testing is impossible. Component-level validation results are used to derive a system-level validation measure. This derivation depends on the knowledge of interrelationships between component modules. Bayes networks are used for the propagation of validation information from the component-level to system-level. Validation of reliability prediction model for a single degree of freedom oscillator under high-cycle fatigue and fatigue life prediction of a helicopter rotor hub is illustrated for this purpose.</abstract><pub>Society of Automotive Engineers, Inc</pub></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0096-736X |
| ispartof | SAE transactions, 2003-01, Vol.112, p.452-458 |
| issn | 0096-736X 2577-1531 |
| language | eng |
| recordid | cdi_jstor_primary_44699604 |
| source | Jstor Complete Legacy |
| subjects | Bayesian networks Delamination Estimate reliability Modeling Natural frequencies Probabilities Random variables Statistics System failures Test data |
| title | Validation of Reliability Prediction Models |
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