Research on Fault Diagnosis of a Marine Fuel System Based on the SaDE-ELM Algorithm

Wei, Yi; Yue, Yaokun

doi:10.3390/a11060082

Cited by 7 publications

(5 citation statements)

References 26 publications

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“…By decreasing the isentropic efficiency of the air cooler (by 5%, 10%, or 15%) and increasing the intake and output pressure fluctuation, failure is simulated. 59–63…”

Section: Resultsmentioning

confidence: 99%

A literature review and future research agenda on fault detection and diagnosis studies in marine machinery systems

Orhan

Celik

2023

Proceedings of the Institution of Mechanical Engineers, Part M:

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Fault detection and diagnostics (FDD) have great potential to enable safety, efficiency, and reliability measures of critical machinery systems. However, it is clear that there is a lack of systematic literature review to identify and classify the FDD studies conducted within the scope of marine engineering. This paper offers a systematic review of FDD models particular to marine machinery and systems. The numbers of 72 core articles were highlighted through a comprehensive literature review conducted in the 2002–2022 period. The studies are classified based on the mostly utilized methods such as data-driven, model-based, knowledge-based, and new generation-hybrid. In addition, new generation and hybrid methods are discussed in detail. The experimental environment (i.e. shipboard, labs, simulator) and technical details of the conducted studies are extensively discussed. While 56.94% of the examined studies are related to the main engine, 43.06% of them are related to auxiliary engines. In addition, the main and auxiliary engine studies are also divided into subject headings and examined in detail. Given the recent developments in green and smart maritime concepts, a future research agenda of the FDD studies on marine machinery systems is then pinpointed. Consequently, the study stimulates scholars interested in FDD while it enables innovative ideas for marine engineers, technology providers, ship operators, and maritime entrepreneurs.

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“…By decreasing the isentropic efficiency of the air cooler (by 5%, 10%, or 15%) and increasing the intake and output pressure fluctuation, failure is simulated. 59–63…”

Section: Resultsmentioning

confidence: 99%

A literature review and future research agenda on fault detection and diagnosis studies in marine machinery systems

Orhan

Celik

2023

Proceedings of the Institution of Mechanical Engineers, Part M:

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“…Dimension reduction can not only reduce data dimensions, but also extract effective information and discard useless information. Some well-known methods used for dimension reduction of a feature space are the principal component analysis (PCA) [20] and the linear discriminant analysis (LDA) [21]. In this study, LDA is used for data dimension reduction.…”

Section: Dimension Reduction Based On Linear Discriminant Analysismentioning

confidence: 99%

Facial Expression Recognition Based on Discrete Separable Shearlet Transform and Feature Selection

2018

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In this paper, a novel approach to facial expression recognition based on the discrete separable shearlet transform (DSST) and normalized mutual information feature selection is proposed. The approach can be divided into five steps. First, all test and training images are preprocessed. Second, DSST is applied to the preprocessed facial expression images, and all the transformation coefficients are obtained as the original feature set. Third, an improved normalized mutual information feature selection is proposed to find the optimal feature subset of the original feature set, thus we can retain the key classification information of the original data. Fourth, the feature extraction and selection of the feature space is reduced by employing linear discriminant analysis. Finally, a support vector machine is used to recognize the expressions. In this study, experimental verification was carried out on four open facial expression databases. The results show that this method can not only improve the recognition rate of facial expressions, but also significantly reduce the computational complexity and improve the system efficiency.

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“…where 0 < ρ < 1, and ρ is the weight adjustment factor. In Equation (11), the flexible combination of the radial basis kernel function and polynomial kernel function is obtained by adjusting the value of ρ [38]. When ρ > 0.5, the polynomial kernel function is dominant and the mixed function shows strong generalization ability and when ρ < 0.5, the radial basis kernel function is dominant, and the mixed kernel function shows strong learning ability.…”

Section: Construction Of Mixed Kernel Functionmentioning

confidence: 99%

A Forecast Model of the Number of Containers for Containership Voyage

2018

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Container ships must pass through multiple ports of call during a voyage. Therefore, forecasting container volume information at the port of origin followed by sending such information to subsequent ports is crucial for container terminal management and container stowage personnel. Numerous factors influence container allocation to container ships for a voyage, and the degree of influence varies, engendering a complex nonlinearity. Therefore, this paper proposes a model based on gray relational analysis (GRA) and mixed kernel support vector machine (SVM) for predicting container allocation to a container ship for a voyage. First, in this model, the weights of influencing factors are determined through GRA. Then, the weighted factors serve as the input of the SVM model, and SVM model parameters are optimized through a genetic algorithm. Numerical simulations revealed that the proposed model could effectively predict the number of containers for container ship voyage and that it exhibited strong generalization ability and high accuracy. Accordingly, this model provides a new method for predicting container volume for a voyage.

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Research on Fault Diagnosis of a Marine Fuel System Based on the SaDE-ELM Algorithm

Cited by 7 publications

References 26 publications

A literature review and future research agenda on fault detection and diagnosis studies in marine machinery systems

A literature review and future research agenda on fault detection and diagnosis studies in marine machinery systems

Facial Expression Recognition Based on Discrete Separable Shearlet Transform and Feature Selection

A Forecast Model of the Number of Containers for Containership Voyage

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