Optimal non-periodic inspection for a multivariate degradation model

Barker, CT; Newby, MJ Martin

doi:10.1016/j.ress.2007.03.015

Cited by 131 publications

(66 citation statements)

References 5 publications

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“…The probabilistic description of the state of strain after kload steps (within a given segment of evolution) is given by (Chapman Kolmogorov equation [5]). …”

Section: Determination Of K-step Tpmmentioning

confidence: 99%

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Markov chain modeling of evolution of strains in reinforced concrete flexural beams

Anoop¹,

Rao²,

Lakshmanan³

et al. 2012

Mater. construcc.

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RESUMENA través del análisis de la evolución de la deformación superficial observada experimentalmente en vigas de hormigón armado al entrar en carga, se constata que dicho proceso debe considerarse estocástico. En este trabajo se estudia la utilización de cadenas de Markov para modelizar la evolución estocástica de la deformación de vigas flexotraccionadas. Se propone, para establecer el estado de deformación de estas, un modelo con distribución gaussiana tipo cadena de Markov homogénea de dos niveles (BLHGMC por sus siglas en inglés), cuyo empleo resulta sencillo y práctico. Se comprueba la utilidad del modelo BLHGMC para prever el comportamiento de estos elementos, lo que determina a su vez una mayor racionalidad a la hora de su cálculo y diseño.Palabras clave: cadena de Markov; hormigón reforzado; modelado estocástico; tensión. SUMMARYFrom the analysis of experimentally observed variations in surface strains with loading in reinforced concrete beams, it is noted that there is a need to consider the evolution of strains (with loading) as a stochastic process. Use of Markov Chains for modeling stochastic evolution of strains with loading in reinforced concrete flexural beams is studied in this paper. A simple, yet practically useful, bi-level homogeneous Gaussian Markov Chain (BLHGMC) model is proposed for determining the state of strain in reinforced concrete beams. The BLHGMC model will be useful for predicting behavior/response of reinforced concrete beams leading to more rational design.

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“…The probabilistic description of the state of strain after kload steps (within a given segment of evolution) is given by (Chapman Kolmogorov equation [5]). …”

Section: Determination Of K-step Tpmmentioning

confidence: 99%

“…It is noted that the elements of 1-step TPM [3] and k-step TPM [5] are conditional probabilities [2]. Since a homogeneous Markov Chain is considered in this study, P(P i , P i+1 ) = P(P i-1 , P i ).…”

Section: Determination Of K-step Tpmmentioning

confidence: 99%

Markov chain modeling of evolution of strains in reinforced concrete flexural beams

Anoop¹,

Rao²,

Lakshmanan³

et al. 2012

Mater. construcc.

View full text Add to dashboard Cite

show abstract

“…In the first case, degradations are represented most of the time by stochastic processes (e.g. Wiener's process [4]). The degradation can also be materialised as an accumulative phenomenon (e.g.…”

Section: Problem Statement On Degradation Model For Prognosismentioning

confidence: 99%

Degradation state model-based prognosis for proactively maintaining product performance

et al. 2008

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Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product conditions. It suggests moving from conventional maintenance practices to predictive strategy. Indeed the maintenance action has to be done at the right time according the component Remaining Useful Life (RUL) assessed by a prognosis process. The accuracy of the RUL is mainly depending on the relevance of the component degradation model used for prediction. In that way, this paper aims at discussing an efficient degradation model taking into account the operational conditions, the health monitoring and the maintenance actions. This model is based on discrete states associated with the degradation levels, and on a cumulative function modelling the transition time between successive states. The model is implemented by means of Stochastic Activity Networks (SAN). The feasibility and added value of such degradation models for prognosis is then highlighted through experimentations made on manufacturing TELMA platform.

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“…They analyzed the actual experiment data of the LED tube light system and gave some insights into the failure behavior of the LED lamps system. Barker and Newby [1] used a multivariate Wiener process to describe the degradation of a complex multicomponent system, and then provide an optimal non-periodic inspection policy for it. Son and Savage [13] proposed a design stage method for assessing performance reliability of systems with multiple time-variant responses due to component degradation.…”

Section: Introductionmentioning

confidence: 99%

Lifetime Distribution and Associated Inference of Systems with Multiple Degradation Measurements Based on Gamma Processes

Pan¹,

Feng²,

Sun³

2016

EiN

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Lifetime Distribution anD associateD inference of systems with muLtipLe DegraDation measurements baseD on gamma processes wyznaczanie rozkłaDu czasów życia oraz wnioskowanie DLa systemów wymagających pomiarów współistniejących DegraDacji w oparciu o procesy gamma PAn Z, Feng J, Sun Q. Lifetime distribution and associated inference of systems with multiple degradation measurements based on gamma processes. eksploatacja i niezawodnosc -Maintenance and Reliability 2016; 18 (2): 307-313, http://dx

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Optimal non-periodic inspection for a multivariate degradation model

Cited by 131 publications

References 5 publications

Markov chain modeling of evolution of strains in reinforced concrete flexural beams

Markov chain modeling of evolution of strains in reinforced concrete flexural beams

Degradation state model-based prognosis for proactively maintaining product performance

Lifetime Distribution and Associated Inference of Systems with Multiple Degradation Measurements Based on Gamma Processes

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