Machine learning-based wear fault diagnosis for marine diesel engine by fusing multiple data-driven models

Zhao, Zhuangzhuang; Xu, Xiaobin; Yang, Jian‐Bo; Chang, Leilei; Yan, Xinping; Wang, Guodong

doi:10.1016/j.knosys.2019.105324

Cited by 88 publications

(38 citation statements)

References 19 publications

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“…Anand et al [16] Zakaulla et al [92] Borjali et al [93] Xu et al [94] Gouarir et al [97] Tran et al [85] Slavkovic et al [99] Suresh et al [102] Optimization of friction parameters by using a force ANN. Predicted coefficient of friction and wear rate of polycarbonate-based composite by using ANN.…”

Section: Machine Learning Methodsmentioning

confidence: 99%

“…Borjali et al [93] employed different machine learning algorithms, such as gradient boosting, M5m CART, and linear regression, to predict the wear rate of polyethylene quantitively from pin-on-disc experiments [93]. Xu et al [94] developed three data-driven models, which are ANN, belief rule base (BRB) and evidential reasoning (ER) from the dataset that was generated from a wear-related problems in a diesel engine. The results showed that the system was enhanced by improving fault tolerant ability [94].…”

Section: Machine Learningmentioning

confidence: 99%

“…Xu et al [94] developed three data-driven models, which are ANN, belief rule base (BRB) and evidential reasoning (ER) from the dataset that was generated from a wear-related problems in a diesel engine. The results showed that the system was enhanced by improving fault tolerant ability [94]. Wang et al [95] improved the funnel sliding mode control for servo devices after replacing the scaling factor that results from tracking errors estimated from NNs [96].…”

Section: Machine Learningmentioning

confidence: 99%

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Practice of Simulation and Life Cycle Assessment in Tribology—A Review

Kurdi

Alhazmi

et al. 2020

Materials

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To simulate today’s complex tribo-contact scenarios, a methodological breakdown of a complex design problem into simpler sub-problems is essential to achieve acceptable simulation outcomes. This also helps to manage iterative, hierarchical systems within given computational power. In this paper, the authors reviewed recent trends of simulation practices in tribology to model tribo-contact scenario and life cycle assessment (LCA) with the help of simulation. With the advancement of modern computers and computing power, increasing effort has been given towards simulation, which not only saves time and resources but also provides meaningful results. Having said that, like every other technique, simulation has some inherent limitations which need to be considered during practice. Keeping this in mind, the pros and cons of both physical experiments and simulation approaches are reviewed together with their interdependency and how one approach can benefit the other. Various simulation techniques are outlined with a focus on machine learning which will dominate simulation approaches in the future. In addition, simulation of tribo-contacts across different length scales and lubrication conditions is discussed in detail. An extension of the simulation approach, together with experimental data, can lead towards LCA of components which will provide us with a better understanding of the efficient usage of limited resources and conservation of both energy and resources.

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Section: Machine Learning Methodsmentioning

confidence: 99%

Section: Machine Learningmentioning

confidence: 99%

Section: Machine Learningmentioning

confidence: 99%

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Practice of Simulation and Life Cycle Assessment in Tribology—A Review

Kurdi

Alhazmi

et al. 2020

Materials

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“…ILBP operator reduces the multiplication times of encoding due to changing of the coding mode of LBP, and the feature extraction efficiency is higher than other types of LBP operators. [3,24], we can see that number of sampling points has a large impact on the time required for LBP feature extraction. In practical application of LBP operator, appropriate circle radius and number of sampling points should be selected according to the application object, so as to take into account the effect of feature extraction and computational efficiency.…”

Section: Feature Extraction Calculation Efficiency Comparisonmentioning

confidence: 96%

“…Vibration signal of diesel engine is a typical nonstationary time-varying signal, which contains abundant characteristic information and can be used to directly, quickly, and accurately reflect the running state of diesel engine. So, how to extract and analyse the characteristic information of vibration signals is always the hotspot of diesel engine fault diagnosis [3,4].…”

Section: Introductionmentioning

confidence: 99%

A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine

Cai

et al. 2020

Shock and Vibration

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Aiming at the feature extraction difficulty of vibration signals, an improved local binary pattern-(ILBP-) based diesel engine fault diagnosis approach is proposed. To effectively make use of the component spatial information in time-frequency images, local binary pattern (LBP) algorithm is applied. Also, in view of the problems that traditional LBP coding is easily interfered by singular pixel points and the relative spatial information is not prominent, an improved coding rule of the LBP operator is put forward in this paper. Compared with some typical LBP algorithms, computational complexity of the proposed ILBP algorithm is greatly reduced, and the coding sparsity is greatly improved. e ILBP operator is applied to fault diagnosis of BF4L1011F diesel engine with eight different valve conditions. For comparison, six kinds of time-frequency distribution are used to convert raw vibration signals into time-frequency images, and then circular LBP, rotation-invariant LBP, uniform LBP, and ILBP operator are applied for texture coding. Finally, nearest neighbor classifier (NNC) and support vector machine (SVM) are used for fault identification.e classification results show that the ILBP operator proposed in this paper can better describe the texture feature information in vibration time-frequency images of the diesel engine, and a good diagnostic effect can be achieved by combining wavelet packet (WP) distribution and ILBP.Hindawi Shock and Vibration Volume 2020, Article ID 9830162, 15 pages https://doi.

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