Author
Nicole Kessissoglou
Other affiliations: James Cook University, University of Lyon
Bio: Nicole Kessissoglou is an academic researcher from University of New South Wales. The author has contributed to research in topics: Hull & Noise. The author has an hindex of 23, co-authored 153 publications receiving 2011 citations. Previous affiliations of Nicole Kessissoglou include James Cook University & University of Lyon.
Topics: Hull, Noise, Sound power, Sound pressure, Finite element method
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the correlation of vibration analysis and wear debris analysis was investigated in an experimental test rig consisting of a worm gearbox driven by an electric motor, and the results from this paper have given more understanding on the dependent and independent roles of vibration and wear deformation analyses in machine condition monitoring and fault diagnosis.
138 citations
TL;DR: In this paper, the free vibrational characteristics of isotropic coupled conical-cylindrical shells are analyzed using two different methods: a wave solution and a power series solution.
126 citations
TL;DR: In this article, the correlation between vibration analysis and wear debris analysis was investigated by investigating different operating conditions of an experimental rig, consisting of a worm gearbox driven by an electric motor.
121 citations
TL;DR: In this article, the structural and acoustic responses of a submarine under harmonic force excitation were analyzed by solving the cylindrical shell equations of motion using a wave approach and the conical shell equations with a power series solution.
119 citations
TL;DR: In this article, the effectiveness of combining both vibration analysis and wear debris analysis in an integrated machine condition monitoring maintenance program was investigated, and a series of studies was conducted on a spur gearbox test rig.
105 citations
Cited by
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TL;DR: A state-of-the-art review of past and recent developments in the SFEM area and indicating future directions as well as some open issues to be examined by the computational mechanics community in the future are provided.
851 citations
Journal Article•
TL;DR: The updated version of ICSD-2 was characterized by the significant improvements of its logicality and clinical practicability, and was more consistent with the International Classification of Disease.
Abstract: Since the introduction of the first edition of International Classification of Sleep Disorders: Diagnostic and Coding Manual(ICSD-1)in 1990,national and international meetings were held to openly discuss the ongoing developments of sleep disorders and a new International Classification of Sleep Disorders: Diagnostic and Coding Manual(ICSD-2)was published in 2005.Compared with ICSD-1,the classification of ICSD-2 was developed in a manner compatible with new International Classification of Diseases(ICD-9 and ICD-10)and formed a coordinated system of International Classification of Diseases.The updated version was characterized by the significant improvements of its logicality and clinical practicability,and was more consistent with the International Classification of Disease.The contents of ICSD-2 were introduced in this article.
596 citations
TL;DR: In this article, the authors have presented the various signal processing methods applied to the fault diagnosis of rolling element bearings with the objective of giving an opportunity to the examiners to decide and select the best possible signal analysis method as well as the excellent defect representative features for future application in the prognostic approaches.
453 citations
TL;DR: In this article, the authors provide a critical review of the predictive health monitoring methods of the entire defect evolution process i.e. wear evolution over the whole lifetime and suggest enhancements for rolling element bearing monitoring.
346 citations
TL;DR: In this article, the authors present a state-of-the-art review of vibration monitoring methods and signal processing techniques for structural health monitoring in manufacturing operations, which can be used as a tool to acquire, visualize and analyse the sampled data collected in any machining operation which can then be used for decision making about maintenance strategies.
Abstract: Machines without vibrations in the working environment are something non-existent. During machining operations, these vibrations are directly linked to problems in systems having rotating or reciprocating parts, such as bearings, engines, gear boxes, shafts, turbines and motors. Vibration analysis has proved to be a measure for any cause of inaccuracy in manufacturing processes and components or any maintenance decisions related to the machine. The non-contact measurement of vibration signal is very important for reliable structural health monitoring for quality assurance, optimizing profitability of products and services, to enhance manufacturing productivity and to reduce regular periodic inspections. This paper presents a state-of-the-art review of recent vibration monitoring methods and signal processing techniques for structural health monitoring in manufacturing operations. These methods and techniques are used as a tool to acquire, visualize and analyse the sampled data collected in any machining operation which can then be used for decision making about maintenance strategies.
271 citations