Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Liu, Liansheng; Zhi, Zhuo; Zhang, Hanxing; Guo, Qing; Yu, Peng; Liu, Datong

doi:10.3390/e21111061

Cited by 18 publications

(15 citation statements)

References 165 publications

(294 reference statements)

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“…For example, a new entropy aging indicator has been proposed, and software aging has been estimated on the basis of multidimensional multiscale entropy [60,61]. Recently, information entropy is used in the fault diagnosis of rotating machinery [67][68][69], such as rolling bearings [67].…”

Section: Research Progress On Defect Diagnosismentioning

confidence: 99%

Entropy Generation Methodology for Defect Analysis of Electronic and Mechanical Components—A Review

Cai

Cui

Qin

et al. 2020

Entropy

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Understanding the defect characterization of electronic and mechanical components is a crucial step in diagnosing component lifetime. Technologies for determining reliability, such as thermal modeling, cohesion modeling, statistical distribution, and entropy generation analysis, have been developed widely. Defect analysis based on the irreversibility entropy generation methodology is favorable for electronic and mechanical components because the second law of thermodynamics plays a unique role in the analysis of various damage assessment problems encountered in the engineering field. In recent years, numerical and theoretical studies involving entropy generation methodologies have been carried out to predict and diagnose the lifetime of electronic and mechanical components. This work aimed to review previous defect analysis studies that used entropy generation methodologies for electronic and mechanical components. The methodologies are classified into two categories, namely, damage analysis for electronic devices and defect diagnosis for mechanical components. Entropy generation formulations are also divided into two detailed derivations and are summarized and discussed by combining their applications. This work is expected to clarify the relationship among entropy generation methodologies, and benefit the research and development of reliable engineering components.

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Section: Research Progress On Defect Diagnosismentioning

confidence: 99%

Entropy Generation Methodology for Defect Analysis of Electronic and Mechanical Components—A Review

Cai

Cui

Qin

et al. 2020

Entropy

View full text Add to dashboard Cite

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“…, and F are the matrices with The maximum-likelihood of v and s 2 in equation (17) may result in the over-fitting. To avoid this problem, Bayesian perspective is adopted, as given by…”

Section: Rvmmentioning

confidence: 99%

“…The application of entropy theories on bearing fault diagnosis has been investigated comprehensively. 17 The problem of recognizing the early fault in bearing and gear has been considered in Wang et al 18 To improve the fault diagnosis of bearing, the novel convolutional neural network can be utilized by enhancing the related features. 19,20 To identify the different kinds of fault, the method based on smoothness index-based Bayesian inference is adopted.…”

Section: Introductionmentioning

confidence: 99%

In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data

Liu

Guo

Wang³

et al. 2020

Advances in Mechanical Engineering

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The in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate results. To solve this problem, we propose one kind of quantitative analysis of its on-wing sensing data to implement remaining useful life prediction of auxiliary power unit. Except the most important performance parameter exhaust gas temperature, the other potential parameters are utilized based on mutual information, which can be used as the quantitative metric. In this way, the quantitative threshold of mutual information for enhancing remaining useful life prediction result can be determined. The implemented cross-validation experiments verify the effectiveness of the proposed method. The real on-wing sensing data of auxiliary power unit for experiment are from China Southern Airlines Company Limited Shenyang Maintenance Base, which spends over $6.5 million on auxiliary power unit maintenance and repair each year for the fleet of over 500 aircrafts. Although the relative improvement is not too large, it is helpful to reduce the maintenance and repair cost.

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“…12–17 The importance of CM and FD engineering processes comes from the serious need for continuous monitoring of the health of the industrial components and systems through their life. 18–23 Moreover, the main goals are to improve the reliability, 24–26 safety, 27–29 availability, 30,31 efficiency, 32,33 and to reduce the maintenance costs 34,35 as well as to avoid a breakdown or sudden failures. 36,37 In modern industrial applications, 38,39 rotating machinery (RM) 40–42 becomes the most important equipment.…”

Section: Introductionmentioning

confidence: 99%

Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study

AlShorman

Alkahatni

Masadeh

et al. 2021

Advances in Mechanical Engineering

125

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Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating machinery (RM) has a vital role in the modern industrial world. However, the remaining useful life (RUL) of machinery is crucial for continuous monitoring and timely maintenance. Moreover, reduced maintenance costs, enhanced safety, efficiency, reliability, and availability are the main important industrial issues to maintain valuable and high-cost machinery. Undoubtedly, induction motor (IM) is considered to be a pivotal component in industrial machines. Recently, acoustic emission (AE) becomes a very accurate and efficient method for fault, leaks and fatigue detection and monitoring techniques. Moreover, CM and FD based on the AE of IM have been growing over recent years. The proposed research study aims to review condition monitoring (CM) and fault diagnosis (FD) studies based on sound and AE for four types of faults: bearings, rotor, stator, and compound. The study also points out the advantages and limitations of using sound and AE analysis in CM and FD. Existing public datasets for AE based analysis for CM and FD of IM are also mentioned. Finally, challenges facing AE based CM and FD for RM, especially for IM, and possible future works are addressed in this study.

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Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Cited by 18 publications

References 165 publications

Entropy Generation Methodology for Defect Analysis of Electronic and Mechanical Components—A Review

Entropy Generation Methodology for Defect Analysis of Electronic and Mechanical Components—A Review

In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data

Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study

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