Author: Florian KönigPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Fault Detection for Sliding Bearings Using Acoustic Emission Signals and Machine Learning Methods
Author: Florian KönigProceedings of ITS-IFToMM 2024
Author: Enrico CiulliPublisher: Springer Nature
ISBN: 3031626168
Category :
Languages : en
Pages : 492
Book Description
Proceedings of the 15th International Conference on Vibration Problems
Author: Publisher: Springer Nature
ISBN: 9819959225
Category : Vibration
Languages : en
Pages : 492
Book Description
This book presents the Proceedings of the 15th International Conference on Vibration Problems (ICoVP 2023) and covers vibration problems of engineering both in theoretical and applied fields. Various topics covered in this volume are Vibration in Oil and Gas, Structural Dynamics, Structural Health Monitoring, Rotor Dynamics, Measurement Diagnostics in Vibration, Computational methods in Vibration and Wave Mechanics, Dynamics of Coupled Systems, Dynamics of Micro and Macro Systems, Multi-body dynamics, Nonlinear dynamics Reliability of dynamic systems, Vibrations due to solid/liquid phase interaction, Vibrations of transport systems, Seismic Isolation, Soil dynamics, Geotechnical earthquake engineering Dynamics of concrete structures, Underwater shock waves (Tsunami), Vibration control, uncertainty quantification and reliability analysis of dynamic structures, Vibration problems associated with nuclear power reactors, Earthquake engineering, impact and wind loading and vibration in composite structures and fracture mechanics. This book will be useful for both professionals and researchers working on vibrations problems in multidisciplinary areas.
Tribo-Informatics
Author: Zhinan ZhangPublisher: CRC Press
ISBN: 1040013791
Category : Technology & Engineering
Languages : en
Pages : 231
Book Description
This book details how artificial intelligence and other informatic methods can be applied to the field of tribology. Using problems often found within tribological condition monitoring, behaviour prediction, system optimization and mechanism analysis, the book covers methods used such as Artificial Neural Networks (ANN). Including case studies throughout, the book offers an accessible introduction to tribological research, beginning with background on the theory behind tribo-informatics, and updates in the latest technology. It describes how to establish a tribo-informatics database, methods through which to express tribo-systems such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF), and its applications. It can be used in state monitoring, behaviour prediction and system optimization. Through case studies, practical examples of how tribo-informatics can be implemented are shown throughout various industries. This book will be of interest to students and researchers in the field of tribology, friction, wear and artificial intelligence.
Study of a Machine Learning Based Methodology Applied to Fault Detection and Identification in an Electromechanical System
Author: Davide PalmisanoPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
This work addresses the application of two di erent methods in order to detect faults in bearings operating within an electromechanical system, based on the measurement of vibrations and stator currents. The electromechanical system considered is a shaft connected to an electric induction motor. Two bearings are mounted on the shaft; these bearings can be metallic or ceramic. The bearings can be found in three di erent conditions: healthy or with a inner race hole of 1 mm or 2 mm. First of all the analisys of theorical fault frequencies was explored. The goal of this method is to identify theorical fault frequencies, depending on features of the bearing, in order to verify the presence of peaks in the frequency signals obtained from laboratory measurements. The accuracy of the theoretical frequency calculation was demonstrated by the actual presence of these peaks in the frequency signals, however it was expected to be found a proportion between the peak heights, and the severity of the fault, but this didn't happened. That led to the development of the second method, based on the building of a neural network able to classify the bearings with respect to their conditions, starting from 15 di erent statistical time domain features as input. Two reduction technicques, LDA and PCA, were implemented in order to reduce the number of input to the two most signi cant features; after that the neural network was built. The results obtained with this second method are very satisfactory as they allow to classify with a good performance both considering the di erent scenarios of bearing material and measured signal taken individually, but also considering all four di erent scenarios at the same time.
Fault Detection in Rotating Machinery Using Acoustic Emission
Author: Juan Luis Ferrando ChaconPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Fault Detection
Author: Léa M. SimonPublisher: Nova Science Pub Incorporated
ISBN: 9781617282911
Category : Technology & Engineering
Languages : en
Pages : 302
Book Description
Fault detection is a subfield of control engineering which concerns itself with monitoring a system, identifying when a fault has occurred and pinpointing the type of fault and its location. Two approaches can be distinguished: a direct pattern recognition of sensor readings that indicate a fault and an analysis of the discrepancy between the sensor readings and expected values. This book reviews research in the field of fault detection including the introduction of an automatic, effective but simpler-to-use system for fault diagnosis in bearings; the monitoring and diagnosis of discrete event systems using time petri nets; fault detection and diagnosis using statistical and soft computing methods.
Proceedings of IncoME-VI and TEPEN 2021
Author: Hao ZhangPublisher: Springer Nature
ISBN: 3030990753
Category : Technology & Engineering
Languages : en
Pages : 1074
Book Description
This volume gathers the latest advances, innovations and applications in the field of condition monitoring, plant maintenance and reliability, as presented by leading international researchers and engineers at the 6th International Conference on Maintenance Engineering and the 2021 conference of the Efficiency and Performance Engineering Network (IncoME-VI TEPEN 2021), held in Tianjin, China on October 20-23, 2021. Topics include vibro-acoustics monitoring, condition-based maintenance, sensing and instrumentation, machine health monitoring, maintenance auditing and organization, non-destructive testing, reliability, asset management, condition monitoring, life-cycle cost optimisation, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics. The contributions, which were selected through a rigorous international peer-review process, share exciting ideas that will spur novel research directions and foster new multidisciplinary collaborations.
Structural Health Monitoring Damage Detection Systems for Aerospace
Author: Markus G. R. SausePublisher: Springer Nature
ISBN: 3030721922
Category : Aerospace engineering
Languages : en
Pages : 292
Book Description
This open access book presents established methods of structural health monitoring (SHM) and discusses their technological merit in the current aerospace environment. While the aerospace industry aims for weight reduction to improve fuel efficiency, reduce environmental impact, and to decrease maintenance time and operating costs, aircraft structures are often designed and built heavier than required in order to accommodate unpredictable failure. A way to overcome this approach is the use of SHM systems to detect the presence of defects. This book covers all major contemporary aerospace-relevant SHM methods, from the basics of each method to the various defect types that SHM is required to detect to discussion of signal processing developments alongside considerations of aerospace safety requirements. It will be of interest to professionals in industry and academic researchers alike, as well as engineering students. This article/publication is based upon work from COST Action CA18203 (ODIN - http://odin-cost.com/), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation.
Author: Hamdan Mohd. Isa