Early Detection of Bearing Damage by Means of Decision Trees

Kilundu, Bovic; Letot, Christophe; Dehombreux, Pierre; Chiementin, Xavier

doi:10.3182/20081205-2-cl-4009.00038

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…For the fault diagnosis problem of rotating machinery, researchers have presented solutions including the dimensionless algorithms [4][5][6], neural networks [7][8][9], classification method [10][11][12][13][14], and evidence theory [15][16][17]. Among these, the dimensionless algorithm is insensitive to signal disturbance, amplitude changes, and stable frequency signals.…”

Section: Introductionmentioning

confidence: 99%

Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi‐Information Fusion

Xiao

Zhang

et al. 2019

Shock and Vibration

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Due to the complexity of the structure and process of large-scale petrochemical equipment, different fault characteristics are mixed and present multiple couplings and ambiguities, leading to the difficulty in identifying composite faults in rotating machinery. This paper proposes a composite faults diagnosis method for rotating machinery of the large unit based on evidence theory and multi-information fusion. The evidence theory and multi-information fusion method mainly deal with multisource information and conflict information, synthesize multiple uncertain information, and obtain synthetic information from multiple data sources. To detect faults in rotating machinery, the dimensionless index ranges of composite faults are first used to form a feature set as the reference. Then, a two-sample distribution test is applied to compare the known fault samples with the tested fault samples, and the maximum statistical distance is used. Finally, the multiple maximum statistical distances are fused by evidence theory and identifying fault types based on the fusion result. The proposed method was applied to the large petrochemical unit simulation experiment system, the results of which showed that our proposed method could accurately identify composite faults and provide maintenance guidance for composite fault diagnosis.

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Section: Introductionmentioning

confidence: 99%

Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi‐Information Fusion

Xiao

Zhang

et al. 2019

Shock and Vibration

Self Cite

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“…3(a). There are several methods for envelope detection; however, a new method is introduced in reference [20], which is based on r.m.s. calculation in a moving window and is similar to the short-time r.m.s.…”

Section: Short-time Statistical Methodsmentioning

confidence: 99%

Rolling bearing fault detection by short-time statistical features

Behzad

Bastami

2011

Proceedings of the Institution of Mechanical Engineers, Part E:

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Rolling element bearing fault diagnosis is a very important part of condition-based maintenance. In this article, a new method for detection of rolling element bearing defects is proposed. The method is based on the concept of the cyclostationarity of the vibration signal to find periodicity in statistical features of the vibration signal. Various statistical features are examined to find the best choice. Several case studies including inner race, outer race, and rolling element defects are investigated in this article. Comparison with the envelope analysis showed that the proposed method benefits from clearer defect frequency identification.

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“…The procedure will be carried out until the final nodes in a hierarchical representation are obtained. The DT has been used successfully to detect bearing damage and incipient defects at early stage [115].…”

Section: Decision Tree (Dt)mentioning

confidence: 99%

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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Early Detection of Bearing Damage by Means of Decision Trees

Cited by 8 publications

References 9 publications

Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi‐Information Fusion

Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi‐Information Fusion

Rolling bearing fault detection by short-time statistical features

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

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