Multiscale Statistical Modeling Approach To Monitoring Mechanical Systems PDF Download
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| Author | : Kenneth C. Chou |
| Publisher | : |
| Total Pages | : 11 |
| Release | : 1996 |
| Genre | : |
| ISBN | : |
Download Multiscale Statistical Modeling Approach to Monitoring Mechanical Systems Book in PDF, ePub and Kindle
Signal processing for condition based maintenance and equipment monitoring has focused in recent years on non-stationary signal analysis using time-frequency representations of the signal. These representations are used to identify non-stationary events in the signal that indicate some change in the state of a structure or a machine. It is important to be able to reliably detect such changes in real time to do necessary preventive maintenance and also to minimize unnecessary maintenance. While transformations such as the Wigner-Ville, Gabor, and wavelet transforms are useful in highlighting time-frequency features of the signal, the application of such transforms to the monitoring problem requires additional for making decisions concerning the condition of the object being monitored. In particular, the interpretation of the transform coefficients in terms of physical events is essential to making such decisions. We develop a methodology for identifying the physical state of the object based on statistical models of the signals, which could comprise, for example, multiple outputs from devices such as accelerometers, strain sensors and acoustic emission sensors. Classification of machine states based on monitoring signals is performed by comparing likelihood scores for each machine state. We present examples of applying our system to various data, including damped sinusoids and noisy chirps, as a way of illustrating system performance for the case of transient monitoring signals. We compare our system to one which is trained using a DFT-based (non-time-frequency-based) representation (in particular, LPC coefficients) and show that our system exhibits both superior performance as well as greater robustness to noise in the signals.
| Author | : |
| Publisher | : |
| Total Pages | : 624 |
| Release | : 1996 |
| Genre | : Shock (Mechanics) |
| ISBN | : |
Download The Shock and Vibration Digest Book in PDF, ePub and Kindle
| Author | : Ugo Galvanetto |
| Publisher | : Imperial College Press |
| Total Pages | : 349 |
| Release | : 2010 |
| Genre | : Science |
| ISBN | : 1848163088 |
Download Multiscale Modeling in Solid Mechanics Book in PDF, ePub and Kindle
This unique volume presents the state of the art in the field of multiscale modeling in solid mechanics, with particular emphasis on computational approaches. For the first time, contributions from both leading experts in the field and younger promising researchers are combined to give a comprehensive description of the recently proposed techniques and the engineering problems tackled using these techniques. The book begins with a detailed introduction to the theories on which different multiscale approaches are based, with regards to linear Homogenisation as well as various nonlinear approaches. It then presents advanced applications of multiscale approaches applied to nonlinear mechanical problems. Finally, the novel topic of materials with self-similar structure is discussed. Sample Chapter(s). Chapter 1: Computational Homogenisation for Non-Linear Heterogeneous Solids (808 KB). Contents: Computational Homogenisation for Non-Linear Heterogeneous Solids (V G Kouznetsova et al.); Two-Scale Asymptotic Homogenisation-Based Finite Element Analysis of Composite Materials (Q-Z Xiao & B L Karihaloo); Multi-Scale Boundary Element Modelling of Material Degradation and Fracture (G K Sfantos & M H Aliabadi); Non-Uniform Transformation Field Analysis: A Reduced Model for Multiscale Non-Linear Problems in Solid Mechanics (J-C Michel & P Suquet); Multiscale Approach for the Thermomechanical Analysis of Hierarchical Structures (M J Lefik et al.); Recent Advances in Masonry Modelling: Micro-Modelling and Homogenisation (P B Louren o); Mechanics of Materials with Self-Similar Hierarchical Microstructure (R C Picu & M A Soare). Readership: Researchers and academics in the field of heterogeneous materials and mechanical engineering; professionals in aeronautical engineering and materials science.
| Author | : Fouzi Harrou |
| Publisher | : Elsevier |
| Total Pages | : 330 |
| Release | : 2020-07-03 |
| Genre | : Technology & Engineering |
| ISBN | : 0128193662 |
Download Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches Book in PDF, ePub and Kindle
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods
| Author | : Weinan E |
| Publisher | : Cambridge University Press |
| Total Pages | : 485 |
| Release | : 2011-07-07 |
| Genre | : Mathematics |
| ISBN | : 1107096545 |
Download Principles of Multiscale Modeling Book in PDF, ePub and Kindle
A systematic discussion of the fundamental principles, written by a leading contributor to the field.
| Author | : Manolis Papadrakakis |
| Publisher | : Springer |
| Total Pages | : 303 |
| Release | : 2014-07-02 |
| Genre | : Science |
| ISBN | : 3319063316 |
Download Multiscale Modeling and Uncertainty Quantification of Materials and Structures Book in PDF, ePub and Kindle
This book contains the proceedings of the IUTAM Symposium on Multiscale Modeling and Uncertainty Quantification of Materials and Structures that was held at Santorini, Greece, September 9 – 11, 2013. It consists of 20 chapters which are divided in five thematic topics: Damage and fracture, homogenization, inverse problems–identification, multiscale stochastic mechanics and stochastic dynamics. Over the last few years, the intense research activity at micro scale and nano scale reflected the need to account for disparate levels of uncertainty from various sources and across scales. As even over-refined deterministic approaches are not able to account for this issue, an efficient blending of stochastic and multiscale methodologies is required to provide a rational framework for the analysis and design of materials and structures. The purpose of this IUTAM Symposium was to promote achievements in uncertainty quantification combined with multiscale modeling and to encourage research and development in this growing field with the aim of improving the safety and reliability of engineered materials and structures. Special emphasis was placed on multiscale material modeling and simulation as well as on the multiscale analysis and uncertainty quantification of fracture mechanics of heterogeneous media. The homogenization of two-phase random media was also thoroughly examined in several presentations. Various topics of multiscale stochastic mechanics, such as identification of material models, scale coupling, modeling of random microstructures, analysis of CNT-reinforced composites and stochastic finite elements, have been analyzed and discussed. A large number of papers were finally devoted to innovative methods in stochastic dynamics.
| Author | : Bingyan Chen |
| Publisher | : Springer Nature |
| Total Pages | : 640 |
| Release | : |
| Genre | : |
| ISBN | : 3031702352 |
Download Proceedings of the TEPEN International Workshop on Fault Diagnostic and Prognostic Book in PDF, ePub and Kindle
| Author | : Pascal Granger |
| Publisher | : MDPI |
| Total Pages | : 214 |
| Release | : 2019-07-11 |
| Genre | : Technology & Engineering |
| ISBN | : 303921179X |
Download Multiscale and Innovative Kinetic Approaches in Heterogeneous Catalysis Book in PDF, ePub and Kindle
Kinetics and reactor modeling for heterogeneous catalytic reactions are prominent tools for investigating and understanding catalyst functionalities at nanoscale and the related rates of complex reaction networks. This book illustrates some examples related to the transformation of simple to more complex feedstocks, including different types of reactor designs, i.e., steady-state, transient plug flow reactors, and TAP reactors for which there is sometimes a strong gap in the operating conditions from ultra-high-vacuum to high-pressure conditions. In conjunction, new methodologies have emerged, giving rise to more robust microkinetics models. As exemplified, they include the kinetics and the dynamics of the reactors and span a large range of length and time scales. The objective of this Special Issue is to provide contributions that can illustrate recent advances and novel methodologies for elucidating the kinetics of heterogeneous reactions and the necessary multiscale approach for optimizing the reactor design. This book is dedicated to postgraduate and scientific researchers, and experts in heterogeneous catalysis. It may also serve as a source of original information for the elaboration of lessons on catalysis for Master students.
| Author | : Cher Ming Tan |
| Publisher | : Springer |
| Total Pages | : 294 |
| Release | : 2017-01-20 |
| Genre | : Technology & Engineering |
| ISBN | : 9811032904 |
Download Theory and Practice of Quality and Reliability Engineering in Asia Industry Book in PDF, ePub and Kindle
This book discusses the application of quality and reliability engineering in Asian industries, and offers information for multinational companies (MNC) looking to transfer some of their operation and manufacturing capabilities to Asia and at the same time maintain high levels of reliability and quality. It is also provides small and medium enterprises (SME) in Asia with insights into producing high-quality and reliable products. It mainly comprises peer-reviewed papers that were presented at the Asian Network for Quality (ANQ) Congress 2014 held in Singapore (August, 2014), which provides a platform for companies, especially those within Asia where rapid changes and growth in manufacturing are taking place, to present their quality and reliability practices. The book presents practical demonstrations of how quality and reliability methodologies can be modified for the unique Asian market, and as such is a valuable resource for students, academics, professionals and practitioners in the field of quality and reliability.
| Author | : Charles R. Farrar |
| Publisher | : John Wiley & Sons |
| Total Pages | : 735 |
| Release | : 2012-11-19 |
| Genre | : Technology & Engineering |
| ISBN | : 1118443217 |
Download Structural Health Monitoring Book in PDF, ePub and Kindle
Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. This paradigm provides a comprehensive framework for developing SHM solutions. Structural Health Monitoring: A Machine Learning Perspective makes extensive use of the authors’ detailed surveys of the technical literature, the experience they have gained from teaching numerous courses on this subject, and the results of performing numerous analytical and experimental structural health monitoring studies. Considers structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm Emphasises an integrated approach to the development of structural health monitoring solutions by coupling the measurement hardware portion of the problem directly with the data interrogation algorithms Benefits from extensive use of the authors’ detailed surveys of 800 papers in the technical literature and the experience they have gained from teaching numerous short courses on this subject.
