Online probabilistic operational safety assessment of multi-mode engineering systems using Bayesian methods

Lin, Yufei; Chen, Maoyin; Zhou, Donghua

doi:10.1016/j.ress.2013.05.018

Cited by 23 publications

(13 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Eqs. (7)- (10) indexes are omitted intentionally, as they are in FlexMix algorithm. The REBMIX algorithm is presented in detail in [18,19].…”

Section: Parameter Estimation Of the Weibull-normal Mixture Distributmentioning

confidence: 99%

“…For example, Bučar [6,7] estimated the unknown parameters of the finite Weibull mixture distribution using the expectation-maximization (EM) algorithm, the REBMIX algorithm, the Minimax algorithm and Multivariate regression. Lin et al [10] used the EM algorithm to estimate the unknown parameters of the normal mixture distribution, which was then used to evaluate the operational safety of multi-mode engineering systems. Balakrishnan [11] used the EM algorithm to estimate the unknown parameters of a Gamma distribution.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probability density function of the equivalent stress amplitude using statistical transformation

Nagode¹

2015

Reliability Engineering & System Safety

View full text Add to dashboard Cite

“…In Eqs. (7)- (10) indexes are omitted intentionally, as they are in FlexMix algorithm. The REBMIX algorithm is presented in detail in [18,19].…”

Section: Parameter Estimation Of the Weibull-normal Mixture Distributmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probability density function of the equivalent stress amplitude using statistical transformation

Nagode¹

2015

Reliability Engineering & System Safety

View full text Add to dashboard Cite

“…14 Univariate approaches need to establish a onedimensional (1D) synthesized health index (SHI) using linear regression, 15 principal component analysis (PCA), 2,16 and Mahalanobis distance. 17,18 The thresholds for identifying different health states of the devices or systems during their life cycles must be predefined. However, constructing effective SHIs and defining accurate thresholds are difficult because of time-varying operating condition, environment, noisy measurements, and high-level uncertainties in real applications.…”

Section: Introductionmentioning

confidence: 99%

A telemetry data based diagnostic health monitoring strategy for in-orbit spacecrafts with component degradation

Wang

Cheng

et al. 2019

Advances in Mechanical Engineering

View full text Add to dashboard Cite

Diagnostic health monitoring without prior knowledge is still a hard problem in the prognostic and health management field. A multivariate diagnostic health monitoring strategy is proposed based on telemetry data for in-orbit spacecrafts with component degradation. Compared with the existing univariate or direct diagnostic health monitoring methods, multivariate diagnostic health monitoring methods can avoid constructing one-dimensional synthesized health index and setting empirical thresholds for different health states. In our developed strategy, a deep forest algorithm combined with an effective feature extraction approach and fuzzy C-means clustering algorithm is proposed to achieve more accurate assessment of the current health state. First, a partitioning window is utilized to deal with the raw telemetry data and then features which have high monotonicity and trends are extracted for diagnostic health monitoring. Then, a fuzzy Cmeans algorithm is used to handle unlabeled telemetry data and determine states of degrading component. Finally, a deep forest classifier is adopted to obtain the prognostic model for online probabilistic diagnostic health monitoring. Verification results on a simulated spacecraft attitude control system can demonstrate the effectiveness and feasibility of the proposed multivariate diagnostic health monitoring strategy.

show abstract

“…This is presented by the use of the traditional method of failure tree into BNs to incorporate the effect of the organizational and human factor. Zhou and coworkers used the Bayesian method to calculate the posterior probabilities belonging to each operation mode depending on the sample. The suggested evaluation strategy is applied in two examples; the first is the aircraft gas turbine while the second is an industrial dryer.…”

Section: Introductionmentioning

confidence: 99%

Bayesian network and bow tie to analyze the risk of fire and explosion of pipelines

Zerouali

Kara

Hamaidi

2016

Process Safety Progress

View full text Add to dashboard Cite

As accidents were and still one of the main reasons standing behind the increasing rates of casualties such as death, injuries, and evacuations, the constant improvement of safety measures especially in the field of hydrocarbons remains a major concern. Therefore, in the work in hand, we attempt to shed the light on the ways of developing a method for the evaluation of risks of fire and explosions of pipelines. The causes of the latter and consequences are, in one hand, analyzed by means of fault tree and bow tie methods. On the other hand, a quantitative analysis implementing the Bayesian networks is used to estimate the probability of occurrence of the adverse event. Moreover, 72 basic events were found to be of the primary causes provoking the occurrence of undesirable events. However, some experts often find it difficult to precisely determine the probabilities of occurrence of basic events of the tree. For the purpose of evaluating the occurrence of each basic event, we used the fuzzy logic. Hence, at the end of the study, we were able to develop a model that could help us evaluate the risks accompanied the fires and pipelines explosion as well as the consequences.

show abstract

Online probabilistic operational safety assessment of multi-mode engineering systems using Bayesian methods

Cited by 23 publications

References 23 publications

Probability density function of the equivalent stress amplitude using statistical transformation

Probability density function of the equivalent stress amplitude using statistical transformation

A telemetry data based diagnostic health monitoring strategy for in-orbit spacecrafts with component degradation

Bayesian network and bow tie to analyze the risk of fire and explosion of pipelines

Contact Info

Product

Resources

About