Integrated system health management-based condition assessment for manned spacecraft avionics

Xu, Jiuping; Xu, Lei

doi:10.1177/0954410011431395

Cited by 22 publications

(26 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has been successfully applied in the handling of complex but vague decision making problems in health management areas [67]. Therefore, the FAHP method, the details of which can be seen Xu and Xu [68], was used to amend the weight. λ j was assumed to be the weight computed using the FAHP method.…”

Section: Fahp Methodsmentioning

confidence: 99%

See 1 more Smart Citation

An Integrated Approach to Modelling the Economy-Society-Ecology System in Urbanization Process

Liu

Luo

2014

Sustainability

Self Cite

View full text Add to dashboard Cite

Urbanization has become a key part of social and economic progress in the 21st Century, but achieving healthy and safe urban development has a long way to go for many developed and developing countries. Urbanization has been recognized as a complex ecosystem which is affected by economic, social, and ecological factors. With this in mind, this paper looks at many factors to first evaluate based on the matter-element (ME) method and then model an Economy-Society-Ecology (ESE) subsystem using a hybrid method by a fuzzy analytical hierarchy process (FAHP), and then by using the entropy method (EM) to determine the relevant index weights. To avoid subjectivity when defining the model's boundaries, the technique for order preference by similarity to an ideal solution (TOPSIS) is introduced. Then, a coupling coordination degree model focusing on the degree of coordination in the ESE subsystem is established. Panel data collected from 2003 to 2012 for Chengdu, China, is then simulated to analyze the development process. The results show that: (1) The quality of urbanization continues to improve and the phasic features are presented; (2) The sensitivity analysis of subsystem weight shown that it had less effect on the coupling coordinated system; (3) The coordination in the ESE subsystem has also improved. However, the development rate of the economic subsystem is greater than that of the societal and ecological subsystem. The approach used here therefore, is shown to provide a promising basis for policy-making to support healthy urban development.

show abstract

Section: Fahp Methodsmentioning

confidence: 99%

“…On the fourth level, there are fuzzy scalars which are used in the evaluation of the sub-criteria condition weights. As in the algorithm in Xu and Xu [68], the index weights were calculated and are shown in Table 3.…”

Section: Study Areamentioning

confidence: 99%

An Integrated Approach to Modelling the Economy-Society-Ecology System in Urbanization Process

Liu

Luo

2014

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…1 that data acquisition and preprocessing is the first and most important module in the ISHM. Data acquisition is the collection of the necessary information for data manipulation in the ISHM [15]. In general, data which are used for condition assessment, diagnostics, prognostics, and decision reasoning always need to be preprocessed.…”

Section: B Fusion Model In Data Preprocessedmentioning

confidence: 99%

“…(10)(11)(12)(13)(14)(15)] and the highdimension matrix computation, to handle the centralized fusion, there will be high demands on communication bandwidth and the excessive ability of computation at the central processor. Therefore, on account of the existing decentralized sensor structures and the limited communication bandwidth, the distributed fusion, which can guarantee optimality in the sense of being equivalent to the optimal centralized estimation fusion based on all original information, becomes a natural alternative.…”

Section: A Centralized Fusion Parameter Extractionmentioning

confidence: 99%

“…To achieve as a good performance as the CKF in the correlated process noises case, Eqs. (10)(11)(12)(13)(14)(15) have to be paid good attention when designing a distributed fusion algorithm. At time instant k, besides θ kjk and P kjk , the one-step prediction θ kjk−1 and its error covariance P kjk−1 are given using all raw sensor measurements.…”

Section: B Optimal Distributed Kalman Filtering Fusionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Fusion Parameters Extraction for Integrated System Health Management to Space Avionics

Fan

2013

Journal of Aerospace Information Systems

Self Cite

View full text Add to dashboard Cite

This paper addresses a parameter extraction problem for space avionics integrated system health management. A distributed fusion-based parameter extraction scheme is developed by fusing the preprocessed results of the space avionics multi-sensor module. Because of the complex environment in space avionics, the feature parameters of electronic circuit in avionics systems are often corrupted by temporally correlated noise. For these correlated noise parameter systems, a distributed fusion parameters extraction algorithm is presented, in which the traditional method of dealing with correlated noise by augmenting the systems state vector is avoided. The proposed distributed fusion parameters extraction algorithm guarantees optimality in the sense of being equivalent to the optimal centralized estimated fusion. Numerical examples are provided to demonstrate the performance of the new algorithm.Nomenclaturefilter gain at time k K i k = Kalman filter gain of ith sensor at time k L k = measurement prediction error covariance matrix at time k L i k = measurement prediction error covariance matrix of ith sensor at time k N k;τ = correlations of prediction error of θ k and θ k-τ using measurements up to k-τ − 1 N i k;τ = added recursive terms at ith sensor p, q = orders of autoregressive moving average model P kjk = estimation error covariance matrix of θ kjk P kjk−1 = prediction error covariance matrix of θ kjk−1 P i kjk = estimation error covariance matrix of θ i kjk P i kjk−1 = prediction error covariance matrix of ith sensor at time k q = correlated step of noises R k = correlation matrix of w k R i k = correlation matrix of measurement noise w i k S k-τ= added terms for expression clarity T k;τ = covariances of prediction error of θ k using measurements up to k-τ T i k;τ = added recursive terms at ith sensor V j;t = correlation matrix between v j and v t V t = covariance matrix of noises v t v k = process noise at time k W k = stacked measurement noises in fusion center at time k w i k = measurement noise of ith sensor at time k yt = system output y k = stacked measurements received from all sensors at time k y i k = measurement of ith sensor at time k Δy k = prediction error of measurement at time k δ t−j = Dirac delta function θ k = extracted parameter at time k θ kjk = optimal estimate at time k using all measurements up to time k θ kjk−1 = one-step prediction of extracted parameter θ t = extracted parameters θ i kjk = optimal estimate of ith sensor at time k θ i kjk−1 = one-step prediction of ith sensor at time k Φ k = state transformation matrix at time k

show abstract

Integrated System Health Management-based Fuzzy On-board Condition Prediction for Manned Spacecraft Avionics

Meng

2014

Qual. Reliab. Engng. Int.

Self Cite

View full text Add to dashboard Cite

The purpose of this study is to develop a prediction methodology for a condition assessment of on-board integrated health management systems in manned spacecraft avionics. The framework of this study is based on two main premises. The first is the need to examine the problems in the on-board prediction tools in space avionics integrated system health management, an area that has been rarely focused on. The second is the need to consider the failure correlation coefficients to enable accurate health predictions. To deal with the uncertainty in the prediction process, a fuzzy theory-gray model-support vector machine approach, which uses fuzzy theory combined with a gray model and a support vector machine, is used to make the prediction. An example is given to demonstrate the accuracy and reliability of the model.

show abstract

Integrated system health management-based condition assessment for manned spacecraft avionics

Cited by 22 publications

References 30 publications

An Integrated Approach to Modelling the Economy-Society-Ecology System in Urbanization Process

An Integrated Approach to Modelling the Economy-Society-Ecology System in Urbanization Process

Distributed Fusion Parameters Extraction for Integrated System Health Management to Space Avionics

Integrated System Health Management-based Fuzzy On-board Condition Prediction for Manned Spacecraft Avionics

Contact Info

Product

Resources

About