Thematische Bibliographien / Condition monitoring of a bearing / Dissertationen
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Dissertationen zum Thema „Condition monitoring of a bearing“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 29. Juli 2025

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1

Moussa, Wael. "Thermography-Assisted Bearing Condition Monitoring." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31379.

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Abstract Despite the large amount of research work in condition based maintenance and condition monitoring methods, there is still a need for more reliable and accurate methods. The clear evidence of that need is the continued dependence on time based maintenance, especially for critical applications such as turbomachinery and airplane engines. The lack of accurate condition monitoring systems could lead to not only the unexpected failures as well as the resulting hazards and repair costs, but also a huge waste of material and time because of unnecessary replacement due to false alarms and unn
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2

Chen, Ping. "Bearing condition monitoring and fault diagnosis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/mq64993.pdf.

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3

Gouws, Rupert. "Condition monitoring of active magnetic bearing systems / R. Gouws." Thesis, North-West University, 2007. http://hdl.handle.net/10394/1305.

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4

Johnston, Andrew Beaton. "Condition monitoring of reciprocating compressors and rolling element bearings." Thesis, University of Aberdeen, 1985. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU365562.

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The prefailure detection of faults in operating plant can effect major rewards in both safety and economy. A successful on-condition maintenance philosophy would pay great dividends particularly in the offshore oil industry where -until recently, only token methods have been employed. Many techniques are available for monitoring mechanical plant and several of these are considered in general terms. Industrial methods are subsequently evaluated on reciprocating compressor and rolling element bearing faults. Bearing fault analysis is considered in two stages. Initially, a series of vibration bas
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5

Feng, Yanhui. "Novel acoustic emission signal processing methods for bearing condition monitoring." Thesis, University of Leicester, 2008. http://hdl.handle.net/2381/8613.

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Rolling Element Bearing is one of the most common mechanical components to be found in critical industrial rotating machinery. Since the failure of bearings will cause the machine to malfunction and may quickly lead to catastrophic failure of the machinery, it is very important to detect any bearing deterioration at an early stage. In this thesis, novel signal processing methods based on Acoustic Emission measurement are developed for bearing condition monitoring. The effectiveness of the proposed methods is experimentally demonstrated to detect and diagnose localised defects and incipient fau
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Gómez, Adrián (Gomez ́Velázquez) 1977. "Condition monitoring of bearing damage : test implementation and data acquisition." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/89288.

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7

Chen, Su Liang. "Development of automated bearing condition monitoring using artificial intelligence techniques." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/195557/.

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A recent series of tapered roller bearing tests have been conducted at the University of Southampton to evaluate the effectiveness of using multiple sensing technologies to detect incipient faults. The test rig was instrumented with on-line sensors including vibration, temperature and electrostatic wear and oil-line debris sensors. Off-line techniques were also used such as debris analysis and bearing surface examination. The electrostatic sensors, in particular, have the potential to detect early decay of tribological contacts within rolling element bearings. These sensors have the unique abi
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8

Billington, Scott Alexander. "Sensor and machine condition effects in roller bearing diagnostics." Thesis, Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/17796.

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9

Soltani, Bozchalooi Iman. "Bearing vibration and oil debris signal enhancement for machinery condition monitoring." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27486.

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Vibration signal and lubricant oil condition are two major sources of information for machine health condition monitoring. Though vibration signal is an indirect indicator of machine conditions, it contains very rich information. On the other hand, the lubricating oil analysis provides a direct indicator of machine health conditions. The joint use of the two sources of information would compensate for their limitations and thus better maintenance actions can be expected. However, this alone is not sufficient since the two sources are often severely contaminated by background and machine interf
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10

Kaewkongka, Tonphong. "Bearing condition monitoring using acoustic emission and vibration : the systems approach." Thesis, Brunel University, 2002. http://bura.brunel.ac.uk/handle/2438/7862.

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This thesis proposes a bearing condition monitoring system using acceleration and acoustic emission (AE) signals. Bearings are perhaps the most omnipresent machine elements and their condition is often critical to the success of an operation or process. Consequently, there is a great need for a timely knowledge of the health status of bearings. Generally, bearing monitoring is the prediction of the component's health or status based on signal detection, processing and classification in order to identify the causes of the problem. As the monitoring system uses both acceleration and acoustic emi
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11

Nembhard, Adrian. "On-bearing vibration response integration for condition monitoring of rotating machinery." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/onbearing-vibration-response-integration-for-condition-monitoring-of-rotating-machinery(f713f156-11f3-4e10-846e-0b9b709f0ff9).html.

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Vibration-based fault diagnosis (FD) with a simple spectrum can be complex, especially when considering FD of rotating machinery with multiple bearings like a multi-stage turbine. Various studies have sought to better interpret fault spectra, but the process remains equivocal. Consequently, it has been accepted that the simple spectra requires support from additional techniques, such as orbit analysis. But even orbit analysis can be inconclusive. Though promising, attempts at developing viable methods that rival the failure coverage of spectrum analysis without gaining computational complexity
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12

Cease, Barry T. "Multi-feature signature analysis for bearing condition monitoring using neural network methodology." Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/19328.

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13

Faghidi, Hamid. "Non-parametric and Non-filtering Methods for Rolling Element Bearing Condition Monitoring." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30689.

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Rolling element bearings are one of the most significant elements and frequently-used components in mechanical systems. Bearing fault detection and diagnosis is important for preventing productivity loss and averting catastrophic failures of mechanical systems. In industrial applications, bearing life is often difficult to predict due to different application conditions, load and speed variations, as well as maintenance practices. Therefore, reliable fault detection is necessary to ensure productive and safe operations. Vibration analysis is the most widely used method for detection and diagn
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14

Aini, Reza. "Vibration monitoring and modelling of shaft/bearing assemblies under concentrated elastohydrodynamic condition." Thesis, Kingston University, 1990. http://eprints.kingston.ac.uk/20759/.

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A five degrees of freedom analysis of a perfect precision grinding spindle supported by a pair of back to back angular contact ball bearings is performed. The ball to race contacts are simulated by a non-linear contact spring, representing the elastic deformation of the mating rolling members. Major frequencies associated with various degrees of freedom are observed and a number of design curves, suggesting the best zones of operation for the simulated spindle under radial/ axial loading are also presented. The gyroscopic contribution of an ideal precision spindle was found to be insignificant
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Sandström, Tobias. "Condition Monitoring of Ceramic Ball Bearings in an Engine Testing Dynamometer." Thesis, KTH, Maskinkonstruktion (Inst.), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183126.

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The choice of the topic addressed in this thesis aims to improve the service and maintenance on ceramic ball bearings in a specific test dynamometer and through an engineering approach develop tools for condition monitoring. The company connected to this thesis, AVL, is the world's largest privately owned company for development, simulation and testing technology of powertrains for passenger cars, trucks and large engines. Engine testing is a critical part of the business at AVL Sweden and unexpected bearing failure can result in long repair times and great economic losses due to loss of the t
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Mirhadizadeh, S. A. "Monitoring hydrodynamic bearings with acoustic emission and vibration analysis." Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/7888.

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Acoustic emission (AE) is one of many available technologies for condition health monitoring and diagnosis of rotating machines such as bearings. In recent years there have been many developments in the use of Acoustic Emission technology (AET) and its analysis for monitoring the condition of rotating machinery whilst in operation, particularly on high speed machinery. Unlike conventional technologies such as oil analysis, motor current signature analysis (MCSA) and vibration analysis, AET has been introduced due to its increased sensitivity in detecting the earliest stages of loss of mechanic
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Hemmati, Farzad. "Rolling element bearing condition monitoring using acoustic emission technique and advanced signal processing." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43190.

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Acoustic emission (AE) signals generated from defects in rolling element bearings are investigated using simulated defects and experimental measurements in this thesis. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, fault diagnostics, defect size calculation, and prognostics. In
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Rzeszucinski, Pawel. "Development of reliable vibration-based condition indicators and their data fusion for the robust health diagnosis of gearboxes." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/development-of-reliable-vibrationbased-condition-indicators-and-their-data-fusion-for-the-robust-health-diagnosis-of-gearboxes(fa25db2f-89a5-420f-ba56-68ef7da874f9).html.

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Performing condition monitoring related tasks on any machinery is an essential element of their rational maintenance. Endeavours to detect an incipient fault within a system serve multiple purposes from increasing the safety of people responsible for operating the machines through decreasing the running and operational costs, allowing time to plan for the inevitable repairs and making sure that the downtime of the machine is kept to an absolute minimum. All these tasks gain extra importance in a case when machines are operated in dangerous conditions putting people's lives in potential jeopard
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19

Johnson, Jason Eric. "Identifying Common Ultrasonic Predictive Failure Signatures in Bearing Elements for the Development of an Automated Condition Based Ultrasonic Monitoring Controller." Digital Commons @ East Tennessee State University, 2005. https://dc.etsu.edu/etd/1097.

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This thesis presents a new method for Condition Based Ultrasonic Monitoring to be applied in conjunction with a lubrication distribution controller. As part of this thesis, algorithms were developed using ultrasonic sensors to control the application of lubrication to machinery. The controller sensors detect an ultrasonic signal from rolling or sliding machine elements. This signal then alerts the controller to dispense the proper amount of lubrication when needed, as opposed to a time schedule based on average performance or history. The work from this thesis will be used to help reduce equip
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20

Aliwan, Mustafa. "Exploration of a condition monitoring system for rolling bearing based on a wireless sensor network." Thesis, University of Huddersfield, 2016. http://eprints.hud.ac.uk/id/eprint/29080/.

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In recent years, wireless sensor networks (WSN) have attracted attention in machine condition monitoring (CM) fields for a more efficient system based on the inherent advantages of WSN, including ease of installation and relocation, lower maintenance cost and the ability to be installed in places not easily accessible. As critical components of rotating machines, bearings account for more than 40% of the various types of failures, causing considerable unpredicted breakdowns of a plant. Thus, this thesis intends to develop a cost-effective and reliable wireless measurement system for rolling be
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21

Alshimmeri, Fiasael. "Diagnosis of low-speed bearing degradation using acoustic emission techniques." Thesis, Cranfield University, 2017. http://dspace.lib.cranfield.ac.uk/handle/1826/12324.

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It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm
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22

Shahriar, Md Rifat. "Electrical signature analysis-based condition monitoring of wind turbine drivetrain." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/107650/1/Md%20Rifat_Shahriar_Thesis.pdf.

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This thesis focuses on improvements of Electrical Signature Analysis, in order to enable the implementation of this extremely cost-effective technique to a wide range of wind turbine diagnostic applications. Previous limitations have been quantified in detail and novel solutions have been proposed and validated using a specifically designed QUT test-rig and an innovative full-scale wind turbine simulation model. Major contributions include a novel technique for demodulation of low frequency carriers, the quantification of converter and wind-induced speed fluctuations and their effect on diagno
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23

Lindsay, Tara Reeves. "Applying Adaptive Prognostics to Rolling Element Bearings." Thesis, Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7568.

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Rolling element bearing failure can cause problems for industries ranging from mild inconveniences such as simple replacement to catastrophic damage such as large production-line equipment failure. Rolling element bearing failure has plagued industries for many years. Bearings are currently monitored to determine whether or not there is a defect in the bearing, but the remaining lifetime of the bearing remains unknown. This research estimates the bearings remaining lifetime through digital signal processing in conjunction with a modified version of Pariss equationa fatigue-failure equation
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24

Shrestha, Dilesh Raj. "Bearing condition monitoring : An investigation on the possibility of monitoring aging of the lubricating grease by means of acoustic emission and temperature." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-87220.

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Grease is among the most widely used lubricants in rolling element bearings. Proper understanding of the effect of lubrication due to grease aging can provide a significant increase in the life of the engineering systems. However, at present, there is no sufficient understanding of the grease aging effect in rolling elements bearing. This restricts the optimal usage of the bearing and timely monitoring of the grease. The current research work tries to address this issue with an experimental investigation. This project studies the behavior of 4 types of greases in rolling elements bearings for
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25

SHI, Juanjuan. "Morphology-based Fault Feature Extraction and Resampling-free Fault Identification Techniques for Rolling Element Bearing Condition Monitoring." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33422.

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As the failure of a bearing could cause cascading breakdowns of the mechanical system and then lead to costly repairs and production delays, bearing condition monitoring has received much attention for decades. One of the primary methods for this purpose is based on the analysis of vibration signal measured by accelerometers because such data are information-rich. The vibration signal collected from a defective bearing is, however, a mixture of several signal components including the fault-generated impulses, interferences from other machine components, and background noise, where fault-induce
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26

Craig, Mark. "Advanced condition monitoring to predict rolling element bearing wear using multiple in-line and off-line sensing." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/185079/.

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27

Purarjomandlangrudi, Afrooz. "Application of machine learning technique in wind turbine fault diagnosis." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/70624/2/Afrooz_Purarjomandlangrudi_Thesis.pdf.

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In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intellig
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28

Kan, Man Shan. "Multi-sensor condition monitoring of bearings using support vector machines." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110621/1/Man%20Shan_Kan_Thesis.pdf.

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This thesis presents a study on bearing condition monitoring under variable operating conditions using Support Vector Machines. Data collected from multiple sensors including accelerometers, acoustic emission sensors and tachometers are used for the studies presented in this thesis. This work has successfully demonstrated acoustic emission's superiority in bearing incipient fault detection; and the prognostic study has developed an effective prognostic approach to capture the system's dynamics with speed variations and make accurate predictions.
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Moodie, Craig Alexander Simpson. "An investigation into the condition monitoring of large slow speed slew bearings." Access electronically, 2009. http://ro.uow.edu.au/theses/3035.

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30

Van, der Merwe Nicolaas Theodor. "The application of signal processing and artificial intelligence techniques in the condition monitoring of rotating machinery / Nicolaas Theodor van der Merwe." Thesis, North-West University, 2003. http://hdl.handle.net/10394/68.

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Condition monitoring of critical machinery has many economic benefits. The primary objective is to detect faults, for example on rolling element bearings, at an early stage to take corrective action prior to the catastrophic failure of a component. In this context, it is important to be able to discriminate between stable and deteriorating fault conditions. A number of conventional vibration analysis techniques exist by which certain faults in rotating machinery may be identified. However, under circumstances involving multiple fault conditions conventional condition monitoring techniques may
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31

Williams, Tracy Denise. "Remote condition monitoring of rolling element bearings with natural crack development." Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/17243.

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32

Yang, Da-Ming. "Development of novel intelligent condition monitoring procedures for rolling element bearings." Thesis, University of Aberdeen, 2001. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU151909.

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The primary aim of this thesis is to develop a novel procedure for an intelligent automatic diagnostic condition monitoring system for rolling element bearings. The applicability of this procedure is demonstrated by its implementation in a particular electric motor drive system. The novel bearing condition diagnostic procedure developed involves three stages combining the merits of advanced signal processing techniques, feature extraction methods and artificial neural networks. This procedure is the effective combination of these techniques and methods in a holistic approach to the rolling ele
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33

Kannan, Vigneshwar. "Intelligent Approaches for the Improved Condition Monitoring of Rolling Element Bearings." Thesis, Griffith University, 2022. http://hdl.handle.net/10072/419770.

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Rotational machinery is used for various applications and is commonplace in industry and aviation sectors. Rolling Element Bearings (REBs) play a vital part in the optimal functioning of rotational machinery. They can naturally develop faults through standard operation of machinery over time or at an accelerated rate due to external factors. Undetected faults in REBs that have not been addressed with the appropriate maintenance actions can cause severe damage to the machine. Maintenance and repairs once damage reaches this stage will be relatively more expensive. This will lead to unexpected m
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34

Preuss, Jason Lee. "Design and analysis of a composite flywheel preload loss test rig." Thesis, Texas A&M University, 2004. http://hdl.handle.net/1969.1/100.

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Flywheel energy storage units have become a viable alternative to electrochemical batteries in applications such as satellites, uninterrupted power supplies, and hybrid vehicles. However, this performance is contingent upon safe operation since these flywheels can release their stored energy almost instantaneously upon failure. The research presented here investigates a health monitoring technology that may give an early indication of degraded material properties in a concentric ring composite flywheel. The existence of degraded material properties is manifested as a change in mass eccentri
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Ayandokun, O. K. "The incremental motion encoder : a sensor for the integrated condition monitoring of rotating machinery." Thesis, Nottingham Trent University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245075.

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36

Khan, A. F. "Condition monitoring of rolling element bearings : a comparative study of vibration-based techniques." Thesis, University of Nottingham, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292225.

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37

Salvan, Sebastien M. E. "A cost-effective approach to the condition monitoring of multiple rolling-element bearings." Thesis, Loughborough University, 2004. https://dspace.lboro.ac.uk/2134/34754.

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This thesis describes a methodology to monitor the condition of rolling-element bearings rotating inside an industrial machine. More precisely, the machine looked at is a mail processing machine which has to sort mail for Royal Mail continuously over many hours every day (twenty-two hours per day on average). For such utilisation, machine availability is critical hence the necessity to monitor the condition of every rolling-element bearing during the production time. This would enable maintenance action to be taken on a rolling-element bearing detected as damaged before its critical failure wh
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38

Zhou, Wei. "Incipient Bearing Fault Detection for Electric Machines Using Stator Current Noise Cancellation." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19706.

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The objective of this research is to develop a bearing fault detection scheme for electric machines via stator current. A new method, called the stator current noise cancellation method, is proposed to separate bearing fault-related components in the stator current. This method is based on the concept of viewing all bearing-unrelated components as noise and defining the bearing detection problem as a low signal-to-noise ratio (SNR) problem. In this method, a noise cancellation algorithm based on Wiener filtering is employed to solve the problem. Furthermore, a statistical method is proposed to
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Hassin, Osama A. A. "Condition monitoring of journal bearings for predictive maintenance management based on high frequency vibration analysis." Thesis, University of Huddersfield, 2017. http://eprints.hud.ac.uk/id/eprint/34161/.

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Journal bearings are widely used as rotor supports in many machinery systems such as engines, motors, turbines and huge pumps. The journal bearing is simply designed, highly efficient, has a long life, low cost and doesn’t fail easily. Based on preventive maintenance strategies, many monitoring techniques are developed for monitoring journal bearings such as lubricant analysis, vibration analysis, noise and acoustic emission analysis. Vibration monitoring techniques have been developed and it can be implemented online or offline without interrupting the machine operations. The vibration phenom
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Darshana, Welihena Gamage Sameera. "Diagnosis and prognosis of rolling element bearings using audio signals and deep learning." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2021. https://ro.ecu.edu.au/theses/2447.

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Condition monitoring and fault diagnosis of industrial equipment have become increasingly important in the wake of the Fourth Industrial Revolution. Unexpected failures of common industrial equipment components, such as rolling-element bearings, can cause production downtime and the resulting financial losses can be significant for large industries including mining. Proactive maintenance strategies can help mitigate unexpected shutdown events. Real-time condition monitoring of industrial equipment plays a critical role in proactive maintenance. This study presents an intelligent diagnostic sys
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41

Popara, Nikola. "Využití umělé inteligence k monitorování stavu obráběcího stroje." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-444960.

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This thesis is focus on monitoring state of machine parts that are under the most stress. Type of artificial intelligence used in this work is recurrent neural network and its modifications. Chosen type of neural network was used because of the sequential character of used data. This thesis is solving three problems. In first problem algorithm is trying to determine state of mill tool wear using recurrent neural network. Used method for monitoring state is indirect. Second Problem was focused on detecting fault of a bearing and classifying it to specific category. In third problem RNN is used
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Leggat, Brad. "The development of a rule based expert system to automate the digital analysis of condition monitoring parameters captured on rolling element bearings subjected to simulated failure." Master's thesis, University of Cape Town, 1991. http://hdl.handle.net/11427/22497.

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This synopsis provides a brief summary of the development of a rule based expert system to diagnose bearing failure. Firstly it covers the proposal of a generic, expert system based industrial condition monitoring system. It then discusses in more detail the development of a specific aspect ofthe system, viz. the analysis of rolling element bearing condition. The bearing test rig and data capture system are described, followed by primary research to define the bearing analysis solution space. This includes the use of vibration parameters, measured and derived operating conditions and the beari
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43

Bruand, Guillaume. "Surveillance préventive des roulements par analyse multi-capteurs." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT113.

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La surveillance préventive est une approche courante permettant de réduire les coûts associés à la maintenance en milieu industriel. En effet, un diagnostic précoce peut prévenir des dommages critiques sur une machine donnée, et permet à l'utilisateur de planifier la maintenance afin de minimiser le temps d'immobilisation du moyen de production. Dans cette thèse il est montré que les capteurs d'angle sont particulièrement adaptés au diagnostic des machines tournantes, et plus spécifiquement à la détection des défauts de roulement. Ils sont combinés de manière avantageuse afin d'étudier l'orbit
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44

CAVALAGLIO, CAMARGO MOLANO JACOPO. "Sviluppo di una struttura di manutenzione basata sul monitoraggio delle condizioni per Sistemi a Carrelli Indipendenti." Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2020. http://hdl.handle.net/11380/1200061.

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L’obiettivo di questo lavoro è la diagnostica di Sistemi a Carrelli Indipendenti con particolare attenzione ai cuscinetti. Il Sistema a Carrelli Indipendenti è una tecnologia innovativa e promettente nell’ambito delle macchine automatiche, che in alcuni casi può sostiture i tipici sistemi di trasporto basati su catene e cinghie guidate da motori rotativi. Il Sistema a Carrelli Indipendenti combina i vantaggi dei servomotori rotativi con quelli dei motori lineari. Esso consiste in una serie di motori lineari modulari di forma curva o rettilinea, che, combinati insieme, realizzano un circuito ch
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KEHLENBACH, JOSUA. "Fault diagnosis of axlebox roller bearings of high speed rail vehicles based on empirical mode decomposition and machine learning." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299774.

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Axlebox bearings are one of the most critical components of a rail vehicle with regard to safety. An axlebox bearing that breaks during operation can be dangerous for the passengers and expensive for the operator. In-service failure of axlebox bearings has been the cause of many catastrophic accidents. Thus, it is of utmost importance to predict bearing failures as early as possible. This will increase reliability and safety of the vehicle as well as reduce the vehicle maintenance cost. Monitoring of roller bearings is an active research eld, and many methods have been proposed by other resear
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Samouhos, Stephen V. (Stephen Vincent) 1982. "Building condition monitoring." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61611.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 201-206).<br>The building sector of the United States currently consumes over 40% of the United States primary energy supply. Estimates suggest that between 5 and 30% of any building's annual energy consumption is unknowingly wasted due to pathologically malfunctioning lighting and comfort conditioning systems. This thesis is focused on developing analytical methods embodied within useful software tools to quickly ide
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Danielson, Hugo, and Schmuck Benjamin von. "Robot Condition Monitoring : A first step in Condition Monitoring for robotic applications." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-66011.

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The industrial world is in constant demand for faster, cheaper and higher quality manufacturing. Robot utilisation and automation has evolved to become a necessary asset to master in order to stay competitive in the global market. With the growing dependency on robots, unexpected downtime and brakedowns can cause devastating loss of revenue. Consequently, this has lead to an increased importance for an accurate condition based way of performing robotic maintenance. As of writing, robots are predominantly maintained through time dependent maintenance. Part replacement is based on statistical mo
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Blakeley, Bruce. "Audio plant condition monitoring." Thesis, Swansea University, 2001. https://cronfa.swan.ac.uk/Record/cronfa42239.

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Accelerometers are widely used in plant condition monitoring (PCM) to diagnose faults in rotating machinery. This can be expensive, and is typically only used to monitor the condition of critical machines. The objective of this project is to develop a system, using microphones, that could screen less critical machines for faults. Microphones are non-contact sensors that can be placed away from the machines, to avoid damage. If the data gathered by the microphone is reduced to a single parameter, that increases with wear, then analysis would be greatly simplified. This system could be used to p
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Shen, Chia-Hsuan. "Acoustic Based Condition Monitoring." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1341797408.

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Li, Yawei. "Dynamic prognostics of rolling element bearing condition." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/15847.

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