Data Driven Process Monitoring And Diagnosis With Support Vector Data Description

Author : Fouzi Harrou,Ying Sun,Amanda S. Hering,Muddu Madakyaru,abdelkader Dairi
Publisher : Elsevier
Page : 330 pages
File Size : 44,7 Mb
Release : 2020-07-03
Category : Technology & Engineering
ISBN : 9780128193662

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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches by Fouzi Harrou,Ying Sun,Amanda S. Hering,Muddu Madakyaru,abdelkader Dairi Pdf

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 : Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa
Publisher : Springer
Page : 716 pages
File Size : 53,5 Mb
Release : 2018-12-03
Category : Computers
ISBN : 9783030042127

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Neural Information Processing by Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa Pdf

The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 4th volume, LNCS 11304, is organized in topical sections on feature selection, clustering, classification, and detection.

Author : Zhidong Deng
Publisher : Springer
Page : 747 pages
File Size : 42,5 Mb
Release : 2019-09-07
Category : Technology & Engineering
ISBN : 9789813290501

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Proceedings of 2019 Chinese Intelligent Automation Conference by Zhidong Deng Pdf

The proceedings present selected research papers from the CIAC2019, held in Jiangsu, China on September 20-22, 2019. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.

Author : Jing Wang,Jinglin Zhou,Xiaolu Chen
Publisher : Springer Nature
Page : 277 pages
File Size : 51,6 Mb
Release : 2022-01-03
Category : Technology & Engineering
ISBN : 9789811680441

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Data-Driven Fault Detection and Reasoning for Industrial Monitoring by Jing Wang,Jinglin Zhou,Xiaolu Chen Pdf

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Author : Chris Aldrich,Lidia Auret
Publisher : Springer Science & Business Media
Page : 374 pages
File Size : 47,9 Mb
Release : 2013-06-15
Category : Computers
ISBN : 9781447151852

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Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods by Chris Aldrich,Lidia Auret Pdf

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.

Author : Marcos Quiñones-Grueiro,Orestes Llanes-Santiago,Antônio José Silva Neto
Publisher : Springer Nature
Page : 153 pages
File Size : 51,5 Mb
Release : 2020-08-04
Category : Technology & Engineering
ISBN : 9783030547387

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Monitoring Multimode Continuous Processes by Marcos Quiñones-Grueiro,Orestes Llanes-Santiago,Antônio José Silva Neto Pdf

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.

Author : Derong Liu,Shengli Xie,Yuanqing Li,Dongbin Zhao,El-Sayed M. El-Alfy
Publisher : Springer
Page : 951 pages
File Size : 54,6 Mb
Release : 2017-11-07
Category : Computers
ISBN : 9783319700878

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Neural Information Processing by Derong Liu,Shengli Xie,Yuanqing Li,Dongbin Zhao,El-Sayed M. El-Alfy Pdf

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.

Author : Stefan Radl,Jiří Jaromír Klemeš,Petar Sabev Varbanov,Thomas Wallek
Publisher : Elsevier
Page : 1766 pages
File Size : 48,9 Mb
Release : 2018-06-26
Category : Technology & Engineering
ISBN : 9780444642363

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28th European Symposium on Computer Aided Process Engineering by Stefan Radl,Jiří Jaromír Klemeš,Petar Sabev Varbanov,Thomas Wallek Pdf

28th European Symposium on Computer Aided Process Engineering, Volume 43 contains the papers presented at the 28th European Society of Computer-Aided Process Engineering (ESCAPE) event held in Graz, Austria June 10-13 , 2018. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 28th European Society of Computer-Aided Process Engineering (ESCAPE) event

Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong
Publisher : Elsevier
Page : 542 pages
File Size : 49,5 Mb
Release : 2021-06-05
Category : Technology & Engineering
ISBN : 9780128217436

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Applications of Artificial Intelligence in Process Systems Engineering by Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong Pdf

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

Author : Qiuye Sun,Jianfang Xiao,Yonghao Gui,Dazhong Ma,Lei Xi
Publisher : Frontiers Media SA
Page : 195 pages
File Size : 47,8 Mb
Release : 2022-05-11
Category : Technology & Engineering
ISBN : 9782889761838

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Applications of Advanced Control and Artificial Intelligence in Smart Grids by Qiuye Sun,Jianfang Xiao,Yonghao Gui,Dazhong Ma,Lei Xi Pdf

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 532 pages
File Size : 48,9 Mb
Release : 2015-12-31
Category : Technology & Engineering
ISBN : 9783319283975

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Proceedings of ELM-2015 Volume 1 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

Author : Chao Shang
Publisher : Springer
Page : 143 pages
File Size : 43,6 Mb
Release : 2018-02-22
Category : Technology & Engineering
ISBN : 9789811066771

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Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research by Chao Shang Pdf

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.

Author : Shiquan Zhou,Aragona Patty,Shiming Chen
Publisher : CRC Press
Page : 1379 pages
File Size : 40,8 Mb
Release : 2017-09-19
Category : Science
ISBN : 9781351648424

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Advances in Energy Science and Equipment Engineering II Volume 2 by Shiquan Zhou,Aragona Patty,Shiming Chen Pdf

The 2016 2nd International Conference on Energy Equipment Science and Engineering (ICEESE 2016) was held on November 12-14, 2016 in Guangzhou, China. ICEESE 2016 brought together innovative academics and industrial experts in the field of energy equipment science and engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in energy equipment science and engineering and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in energy equipment science and engineering and related areas. This second volume of the two-volume set of proceedings covers the field of Structural and Materials Sciences, and Computer Simulation & Computer and Electrical Engineering.

Author : Zhiwen Chen
Publisher : Springer
Page : 112 pages
File Size : 41,5 Mb
Release : 2017-01-02
Category : Technology & Engineering
ISBN : 9783658167561

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Data-Driven Fault Detection for Industrial Processes by Zhiwen Chen Pdf

Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.

Author : Jian Tang,Wen Yu
Publisher : Cambridge Scholars Publishing
Page : 511 pages
File Size : 43,6 Mb
Release : 2020-08-28
Category : Business & Economics
ISBN : 9781527558953

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Industrial Process Modelling with Mechanical Frequency Spectrum Data by Jian Tang,Wen Yu Pdf

Different industries use data analytics and the process modelling technique successfully in a variety of ways. These popular intelligent approaches improve the quality and quantity of production. This book focuses on the technique of soft-sensing based on spectral data with multi-source high-dimensional mechanical frequency in order to assess difficult-to-measure process parameters. The book will be of interest to researchers and professors working in data analytics, engineers and technicians who need a modelling method based on small sample data, and PhD students who need to solve modelling and control challenges in a practical way.