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Machine learning-based fault diagnosis for industrial engineering systems, Yang, Rui Zhong, Maiying


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Автор: Yang, Rui Zhong, Maiying   (Руй Ян, Майин Чжун)
Название:  Machine learning-based fault diagnosis for industrial engineering systems
Перевод названия: Руй Ян, Майин Чжун: Диагностика неисправностей на основе машинного обучения для промышленных инженер
ISBN: 9781032147253
Издательство: Taylor&Francis
Классификация:





ISBN-10: 1032147253
Обложка/Формат: Hardback
Страницы: 80
Вес: 0.33 кг.
Дата издания: 15.06.2022
Серия: Advances in intelligent decision-making, systems engineering, and project management
Язык: English
Иллюстрации: 35 tables, black and white; 12 line drawings, black and white; 3 halftones, black and white; 15 illustrations, black and white
Размер: 165 x 243 x 13
Рейтинг:
Поставляется из: Европейский союз
Описание: This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods.Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.
Дополнительное описание: 1. Background and Related Methods. 2. Fault Diagnosis Method Based on Recurrent Convolutional Neural Network. 3. Fault Diagnosis of Rotating Machinery Gear Based on Random Forest Algorithm. 4. Bearing Fault Diagnosis under Different Working Conditions Bas



Artificial intelligence and machine learning applications in civil, mechanical, and industrial engineering

Автор: Gebrail Bekda, Sinan Melih Nigdeli
Название: Artificial intelligence and machine learning applications in civil, mechanical, and industrial engineering
ISBN: 1799803023 ISBN-13(EAN): 9781799803027
Издательство: Mare Nostrum (Eurospan)
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Цена: 29779.00 р.
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Описание: Presents innovative research on the methods and implementation of machine learning and AI in multiple facets of engineering. While highlighting topics including control devices, geotechnology, and artificial neural networks, this book is designed for engineers, academics, researchers, practitioners, and students.

Industrial Applications of Machine Learning

Автор: Pedro Larran?aga; Alberto Ogbechie
Название: Industrial Applications of Machine Learning
ISBN: 0367656876 ISBN-13(EAN): 9780367656874
Издательство: Taylor&Francis
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Цена: 7195.00 р.
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Описание: This book shows how machine learning can be applied to address real-world problems in the fourth industrial revolution and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society

Identification of Multivariable Industrial Processes

Автор: Yucai Zhu; Ton Backx
Название: Identification of Multivariable Industrial Processes
ISBN: 1447120604 ISBN-13(EAN): 9781447120605
Издательство: Springer
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Цена: 13060.00 р.
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Описание: Identification of Multivariable Industrial Processes presents a unified approach to multivariable industrial process identification. It concentrates on industrial processes with reference to model applications. This publication is intended to fill the gap between modern systems and control theory and industrial application.

Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

Автор: Marcin Mrugalski
Название: Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis
ISBN: 331901546X ISBN-13(EAN): 9783319015460
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Introduction.- Designing of dynamic neural networks.- Estimation methods in training of ANNs for robust fault diagnosis.- MLP in robust fault detection of static non-linear systems.- GMDH networks in robust fault detection of dynamic non-linear systems.- State-space GMDH networks for actuator robust FDI.

Fault Diagnosis and Fault-Tolerant Control Based on Adaptive Control Approach

Автор: Qikun Shen; Bin Jiang; Peng Shi
Название: Fault Diagnosis and Fault-Tolerant Control Based on Adaptive Control Approach
ISBN: 3319525298 ISBN-13(EAN): 9783319525297
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems.

Bond Graph Model-based Fault Diagnosis of Hybrid Systems

Автор: Wolfgang Borutzky
Название: Bond Graph Model-based Fault Diagnosis of Hybrid Systems
ISBN: 3319352261 ISBN-13(EAN): 9783319352268
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book presents bond graph model-based fault detection with a focus on hybrid system models. The book addresses model design, simulation, control and model-based fault diagnosis of multidisciplinary engineering systems. The text beings with a brief survey of the state-of-the-art, then focuses on hybrid systems.

Data-Driven Fault Detection for Industrial Processes

Автор: Zhiwen Chen
Название: Data-Driven Fault Detection for Industrial Processes
ISBN: 3658167556 ISBN-13(EAN): 9783658167554
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes.

Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control

Автор: Lan Jianglin, Patton Ronald J.
Название: Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control
ISBN: 3030587622 ISBN-13(EAN): 9783030587628
Издательство: Springer
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Цена: 13974.00 р.
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Описание:

Part I: Introduction.- Introduction.- Robust Integration in Fault Diagnosis and Fault-Tolerant Control.- Part II: Strategies for Robust Integration of Fault Estimation and Fault-Tolerant Control.- Sequential Integration of Fault Estimation and Fault-Tolerant Control.- Iterative Integration of Fault Estimation and Fault-Tolerant Control.- Simultaneous Integration of Fault Estimation and Fault-Tolerant Control.- Robust Decoupling Integration of Fault Estimation and Fault-Tolerant Control.- Adaptive Decoupling Integration of Fault Estimation and Fault-Tolerant Control.- Part III: Extension and Application.- Fault-Tolerant Wind Turbine Pitch Control.- Integration of Fault Estimation and Fault-Tolerant Control for Nonlinear Systems with 3-DOF Helicopter Application.- Integration of Fault Estimation and Fault-Tolerant Control for Large-Scale Interconnected Systems

Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

Автор: Marcin Mrugalski
Название: Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis
ISBN: 3319032860 ISBN-13(EAN): 9783319032863
Издательство: Springer
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Цена: 14365.00 р.
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Описание:

The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems.

A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered.

All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications.

Fault-Diagnosis Applications

Автор: Rolf Isermann
Название: Fault-Diagnosis Applications
ISBN: 3642434762 ISBN-13(EAN): 9783642434761
Издательство: Springer
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Цена: 15672.00 р.
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Описание:

1. Introduction

1.1 Process automation and supervision

1.2 Product life cycle and fault management (asset management)

1.3 Contents

I SUPERVISION, FAULT DETECTION AND DIAGNOSIS

2. Supervision, fault detection and fault diagnosis methods

2.1 Basic tasks of supervision

2.2 Terminology

2.2.1 Faults, failures, malfunctions

2.2.2 Reliability, availability, safety

2.2.3 Fault tolerance and redundancy

2.3 Knowledge based fault detection and diagnosis

2.4 Signal based fault detection methods

2.4.1 Limit checking

2.4.2 Trend checking

2.4.3 Change detection

2.4.4 Adaptive thresholds

2.4.5 Plausibility checks

2.4.6 Signal analysis methods

2.5 Processmodel based fault detection methods

2.5.1 Process models and fault modeling

2.5.2 Fault detection with parameter estimation

2.5.3 Fault detection with state observers and state estimation

2.5.4 Fault detection with parity equations

2.5.5 Direct reconstruction of not measurable variables

2.6 Fault diagnosis methods

2.6.1 Classification methods

2.6.2 Inference methods

2.7 Fault detection in closed loops

2.8 Data flow structure for supervision

II DRIVES AND ACTUATORS

3. Fault diagnosis of electrical drives

3.1 Direct current motor (DC)

3.1.1 Structure and models of the DC motor

3.1.2 Fault detection with parity equations

3.1.3 Fault detection with parameter estimation

3.1.4 Experimental results for fault detection

3.1.5 Experimental results for fault diagnosis with SELECT

3.1.6 Conclusions

3.2 Alternating current motor (AC)

3.2.1 Structure and models of induction motors

3.2.2 Signal based fault detection of power electronics

3.2.3 Model based fault detection of an AC motor

3.2.4 Concusions

4. Fault diagnosis of electrical actuators

4.1 Electromagnetic actuator

4.1.1 Position control

4.1.2 Fault detection with parameter estimation

4.2 Electromagnetic automotive throttle valve actuator

4.2.1 Structure and models of the actuator

4.2.2 Input test cycle for quality control

4.2.3 Fault detection with parameter estimation

4.2.4 Fault detection with parity equations

4.2.5 Fault diagnosis

4.2.6 Fault diagnosis equipment

4.2.7 Conclusions

4.3 Brushless DC motor actuator and aircraft cabin pressure valve

4.3.1 Structure and models

4.3.2 Fault detection with parameter estimation

4.3.3 Fault detection with parity equations

4.3.4 Conclusions

5. Fault diagnosis of fluidic actuators

5.1 Hydraulic servo axis

5.1.1 Hydraulic servo axis structure

5.1.2 Faults of hydraulic servo axes

5.1.3 Models of the spool valve and cylinder

5.1.4 Fault detection and diagnosis of the valve and cylinder

5.1.5 Fault diagnosis

5.1.6 Conclusions

5.2 Pneumatic actuators

5.2.1 Pneumatic flow valve structure and modeling

5.2.2 Fault detection and diagnosis with local linear models

5.2.3 Experimental results

5.2.4 Conclusions

III MACHINES AND PLANTS

6. Fault diagnosis of pumps

6.1 Centrifugal pumps

6.1.1 Status of pump supervision and fault detection

6.1.2 Models of a centrifugal pump and pipe system

6.1.3 Fault detection with parameter estimation

6.1.4 Fault detection with nonlinear parity equations and parameter estimation

6.1.5 Conclusions

6.2 Reciprocating pumps

6.2.1 Structure of a diaphragm pump

6.2.2 Models of a diaphragm pump

6.2.3 Fault detection and diagnosis of the hydraulic part

6.2.4 Fault detection of

Model-Based Fault Diagnosis Techniques

Автор: Steven X. Ding
Название: Model-Based Fault Diagnosis Techniques
ISBN: 1447161114 ISBN-13(EAN): 9781447161110
Издательство: Springer
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Цена: 23508.00 р.
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Описание: This book gives readers a framework of model-based FDI techniques, helping them to become familiar with the basic ideas and schemes in a systematic way. Examples and benchmarks provide a means of practising the ideas and judging the methods described.

Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques

Автор: Silvio Simani; Cesare Fantuzzi; Ron J. Patton
Название: Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques
ISBN: 1849968950 ISBN-13(EAN): 9781849968959
Издательство: Springer
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Цена: 19589.00 р.
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Описание: Safety in industrial process and production plants is a concern of rising importance but because the control devices which are now exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure.


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