Download or read book Monitoring Multimode Continuous Processes written by Marcos Quiñones-Grueiro and published by Springer Nature. This book was released on 2020-08-04 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.
Download or read book An Investigation of Strategies for Multivariate Monitoring of Continuous Processes written by Teri Reed Rhoads and published by . This book was released on 1999 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adapting Experimental and Monitoring Methods for Continuous Processes Under Feedback Control written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis written by Xiangyu Kong and published by Springer Nature. This book was released on with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovative Techniques and Applications of Modelling Identification and Control written by Quanmin Zhu and published by Springer. This book was released on 2018-04-20 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems. The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.
Download or read book Secure and Trusted Cyber Physical Systems written by Shantanu Pal and published by Springer Nature. This book was released on 2022-09-02 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the latest design and development of security issues and various defences to construct safe, secure and trusted Cyber-Physical Systems (CPS). In addition, the book presents a detailed analysis of the recent approaches to security solutions and future research directions for large-scale CPS, including its various challenges and significant security requirements. Furthermore, the book provides practical guidance on delivering robust, privacy, and trust-aware CPS at scale. Finally, the book presents a holistic insight into IoT technologies, particularly its latest development in strategic applications in mission-critical systems, including large-scale Industrial IoT, Industry 4.0, and Industrial Control Systems. As such, the book offers an essential reference guide about the latest design and development in CPS for students, engineers, designers, and professional developers.
Download or read book Multivariate Statistical Process Control written by Zhiqiang Ge and published by Springer Science & Business Media. This book was released on 2012-11-28 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
- Author : Ankur Kumar
- Publisher : MLforPSE
- Release : 2024-01-12
- ISBN :
- Pages : 365 pages
Machine Learning in Python for Process and Equipment Condition Monitoring and Predictive Maintenance
Download or read book Machine Learning in Python for Process and Equipment Condition Monitoring and Predictive Maintenance written by Ankur Kumar and published by MLforPSE. This book was released on 2024-01-12 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to help readers quickly gain a working knowledge of machine learning-based techniques that are widely employed for building equipment condition monitoring, plantwide monitoring , and predictive maintenance solutions in process industry . The book covers a broad spectrum of techniques ranging from univariate control charts to deep learning-based prediction of remaining useful life. Consequently, the readers can leverage the concepts learned to build advanced solutions for fault detection, fault diagnosis, and fault prognosis. The application focused approach of the book is reader friendly and easily digestible to the practicing and aspiring process engineers and data scientists. Upon completion, readers will be able to confidently navigate the Prognostics and Health Management literature and make judicious selection of modeling approaches suitable for their problems. This book has been divided into seven parts. Part 1 lays down the basic foundations of ML-assisted process and equipment condition monitoring, and predictive maintenance. Part 2 provides in-detail presentation of classical ML techniques for univariate signal monitoring. Different types of control charts and time-series pattern matching methodologies are discussed. Part 3 is focused on the widely popular multivariate statistical process monitoring (MSPM) techniques. Emphasis is paid to both the fault detection and fault isolation/diagnosis aspects. Part 4 covers the process monitoring applications of classical machine learning techniques such as k-NN, isolation forests, support vector machines, etc. These techniques come in handy for processes that cannot be satisfactorily handled via MSPM techniques. Part 5 navigates the world of artificial neural networks (ANN) and studies the different ANN structures that are commonly employed for fault detection and diagnosis in process industry. Part 6 focusses on vibration-based monitoring of rotating machinery and Part 7 deals with prognostic techniques for predictive maintenance applications. Broadly, the book covers the following: Exploratory analysis of process data Best practices for process monitoring and predictive maintenance solutions Univariate monitoring via control charts and time series data mining Multivariate statistical process monitoring techniques (PCA, PLS, FDA, etc.) Machine learning and deep learning techniques to handle dynamic, nonlinear, and multimodal processes Fault detection and diagnosis of rotating machinery using vibration data Remaining useful life predictions for predictive maintenance
Download or read book Quantum Continuous Variables written by Alessio Serafini and published by CRC Press. This book was released on 2017-07-20 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum Continuous Variables introduces the theory of continuous variable quantum systems, from its foundations based on the framework of Gaussian states to modern developments, including its applications to quantum information and forthcoming quantum technologies. This new book addresses the theory of Gaussian states, operations, and dynamics in great depth and breadth, through a novel approach that embraces both the Hilbert space and phase descriptions. The volume includes coverage of entanglement theory and quantum information protocols, and their connection with relevant experimental set-ups. General techniques for non-Gaussian manipulations also emerge as the treatment unfolds, and are demonstrated with specific case studies. This book will be of interest to graduate students looking to familiarise themselves with the field, in addition to experienced researchers eager to enhance their understanding of its theoretical methods. It will also appeal to experimentalists searching for a rigorous but accessible treatment of the theory in the area.
Download or read book Neural Information Processing written by Derong Liu and published by Springer. This book was released on 2017-11-07 with total page 951 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Download or read book 13th International Symposium on Process SystemsEngineering PSE 2018 July 1 5 2018 written by Mario R. Eden and published by Elsevier. This book was released on 2018-07-19 with total page 2602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Process Systems Engineering brings together the international community of researchers and engineers interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 13th International Symposium on Process Systems Engineering PSE 2018 event held San Diego, CA, July 1-5 2018. The book contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE. Highlights how the Process Systems Engineering community contributes to the sustainability of modern society Establishes the core products of Process Systems Engineering Defines the future challenges of Process Systems Engineering
Download or read book Process Control System Fault Diagnosis written by Ruben Gonzalez and published by John Wiley & Sons. This book was released on 2016-07-21 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc., Canada Biao Huang, University of Alberta, Canada Data-driven Inferential Solutions for Control System Fault Diagnosis A typical modern process system consists of hundreds or even thousands of control loops, which are overwhelming for plant personnel to monitor. The main objectives of this book are to establish a new framework for control system fault diagnosis, to synthesize observations of different monitors with a prior knowledge, and to pinpoint possible abnormal sources on the basis of Bayesian theory. Process Control System Fault Diagnosis: A Bayesian Approach consolidates results developed by the authors, along with the fundamentals, and presents them in a systematic way. The book provides a comprehensive coverage of various Bayesian methods for control system fault diagnosis, along with a detailed tutorial. The book is useful for graduate students and researchers as a monograph and as a reference for state-of-the-art techniques in control system performance monitoring and fault diagnosis. Since several self-contained practical examples are included in the book, it also provides a place for practicing engineers to look for solutions to their daily monitoring and diagnosis problems. Key features: • A comprehensive coverage of Bayesian Inference for control system fault diagnosis. • Theory and applications are self-contained. • Provides detailed algorithms and sample Matlab codes. • Theory is illustrated through benchmark simulation examples, pilot-scale experiments and industrial application. Process Control System Fault Diagnosis: A Bayesian Approach is a comprehensive guide for graduate students, practicing engineers, and researchers who are interests in applying theory to practice.
Download or read book Emerging Technologies for In Situ Processing written by D.J. Ehrlich and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the NATO Advanced Research Workshop, Cargèse, France, May 4-8, 1987
Download or read book The Dynamics of Disability written by National Research Council and published by National Academies Press. This book was released on 2002-09-16 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Society Security disability program faces urgent challenges: more people receiving benefits than ever before, the prospect of even more claimants as baby boomers age, changing attitudes culminating in the Americans With Disabilities Act. Disability is now understood as a dynamic process, and Social Security must comprehend that process to plan adequately for the times ahead. The Dynamics of Disability provides expert analysis and recommendations in key areas: Understanding the current social, economic, and physical environmental factors in determining eligibility for disability benefits. Developing and implementing a monitoring system to measure and track trends in work disability. Improving the process for making decisions on disability claims. Building Social Security's capacity for conducting needed research. This book provides a wealth of detail on the workings of the Social Security disability program, recent and emerging disability trends, issues and previous experience in researching disability, and more. It will be of primary interest to federal policy makers, the Congress, and researchersâ€"and it will be useful to state disability officials, medical and rehabilitation professionals, and the disability community.
Download or read book Continuos time Markov modulated Chains In Operations Research written by Alexander M Andronov and published by World Scientific. This book was released on 2024-04-22 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are widely used for description and an analysis of various processes in system reliability, risk, queuing, data communication, logistic and storage systems. The book contains various applications of the theory of continuous-time Markov-modulated processes in operation research. All analytical results are illustrated by numerical computations. Used algorithms allow overcoming computation difficulties successfully. For example, a calculation of transient probabilities of states for a continuous-time finite Markov chain uses eigenvalues and eigenvectors of the corresponding matrix (generator). In a more complex case of differential or integral equations, such a simple explicit form of a solution is missing. The explicit form of solution is presented by means of infinity sums of functions. For example, often we have to deal with the so-called renewal equation. Its solution is presented as an infinite sum of the renewal function. In this case, an approximation of functions of interest and iterative computation procedures are used.
Download or read book The Principles of Integrated Technology in Avionics Systems written by Guoqing Wang and published by Academic Press. This book was released on 2020-01-17 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Principles of Integrated Technology in Avionics Systems describes how integration can improve flight operations, enhance system processing efficiency and equip resource integration. The title provides systematic coverage of avionics system architecture and ground system integration. Looking beyond hardware resource sharing alone, it guides the reader through the benefits and scope of a modern integrated avionics system. Integrated technology enhances the performance of organizations by improving system capacity and boosting efficiency. Avionics systems are the functional center of aircraft systems. System integration technology plays a vital role in the complex world of avionics and an integrated avionics system will fully-address systems, information and processes. Introduces integration technology in complex avionics systems Guides the reader through the scope and benefits of avionic system integration Gives practical guidance on using integration to optimize an avionics system Describes the basis of avionics system architecture and ground system integration Presents modern avionics as a system that is becoming increasingly integrated