Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Interdisciplinary Treatment to Arc Welding Power Sources

E-BookPDF1 - PDF WatermarkE-Book
229 Seiten
Englisch
Springer Nature Singaporeerschienen am30.06.20181st ed. 2019
This book presents the fundamentals of arc phenomena, various arc welding power sources, their control strategies, welding data acquisition, and welding optimization. In addition, it discusses a broad range of electrical concepts in welding, including power source characteristics, associated parameters, arc welding power source classification, control strategies, data acquisitions techniques, as well as optimization methods. It also offers advice on how to minimize the flaws and improve the efficacy and performance of welds, as well as insights into the mechanical behavior expressed in terms of electromagnetic phenomena, which is rarely addressed. The book provides a comprehensive review of interdisciplinary concepts, offering researchers a wide selection of strategies, parameters, and sequences of operations to choose from.



Dr. S. Arungalai Vendan is an associate professor at the Industrial Automation and Instrumentation Division, VIT University, Vellore, India. He has been working on advanced welding processes since 2006. He received his Ph.D. degree from the National Institute of Technology (Institute of national importance), Tiruchirappalli, India in 2010. He has received several fellowships and awards for his technical contributions by various government agencies. He has successfully completed government funded research projects and industrial consultancy projects, and has published more than 70 research papers in international journal and conference proceedings.  He has associations with top manufacturing industries and Research and Development centers under various capacities. His research interests mainly focus on the interdisciplinary science which has confluence of terminologies from electrical/mechanical/metallurgical/ materials and magnetic technologies.

Prof. Liang Gao received his Ph.D. degree in Mechatronic Engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is currently a professor at the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and the vice director of the State Key Lab of Digital Manufacturing Equipment & Technology. His chief research interests include optimization in design and manufacturing, and he has published more than 150 academic papers,. He is currently an associate editor for Swarm and Evolutionary Computation and the Journal of Industrial and Production Engineering, and an editorial board member of the European Journal of Industrial Engineering and Operations Research Perspectives.
Dr. Akhil Garg is an associate professor at the Ministry of Education's Intelligent Manufacturing Key Laboratory, Shantou University, China. He has been working on sustainable manufacturing processes and optimization methods since 2011. He received his doctoral degree from Nanyang Technological University (NTU), Singapore in 2014. He has published over 50 SCI-indexed articles in the areas of manufacturing and optimization.
Dr. P. Kavitha is an associate professor at the School of Electrical Engineering, VIT University, Vellore, India. Her research interests include control systems, analog and digital circuits, advanced control theory, process automation and process control.

Dr. G. Dhivyasri is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. Dr. Dhivyasri's research interests include, control system, MEMS, sensors and signal conditioning, as well as analog & digital communication systems.

Dr. Rahul SG is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. His research interests include control systems, industrial instrumentation, analytical instrumentation, programmable logic controller (PLC), and digital electronics.



mehr
Verfügbare Formate
BuchGebunden
EUR106,99
BuchKartoniert, Paperback
EUR106,99
E-BookPDF1 - PDF WatermarkE-Book
EUR96,29

Produkt

KlappentextThis book presents the fundamentals of arc phenomena, various arc welding power sources, their control strategies, welding data acquisition, and welding optimization. In addition, it discusses a broad range of electrical concepts in welding, including power source characteristics, associated parameters, arc welding power source classification, control strategies, data acquisitions techniques, as well as optimization methods. It also offers advice on how to minimize the flaws and improve the efficacy and performance of welds, as well as insights into the mechanical behavior expressed in terms of electromagnetic phenomena, which is rarely addressed. The book provides a comprehensive review of interdisciplinary concepts, offering researchers a wide selection of strategies, parameters, and sequences of operations to choose from.



Dr. S. Arungalai Vendan is an associate professor at the Industrial Automation and Instrumentation Division, VIT University, Vellore, India. He has been working on advanced welding processes since 2006. He received his Ph.D. degree from the National Institute of Technology (Institute of national importance), Tiruchirappalli, India in 2010. He has received several fellowships and awards for his technical contributions by various government agencies. He has successfully completed government funded research projects and industrial consultancy projects, and has published more than 70 research papers in international journal and conference proceedings.  He has associations with top manufacturing industries and Research and Development centers under various capacities. His research interests mainly focus on the interdisciplinary science which has confluence of terminologies from electrical/mechanical/metallurgical/ materials and magnetic technologies.

Prof. Liang Gao received his Ph.D. degree in Mechatronic Engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is currently a professor at the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and the vice director of the State Key Lab of Digital Manufacturing Equipment & Technology. His chief research interests include optimization in design and manufacturing, and he has published more than 150 academic papers,. He is currently an associate editor for Swarm and Evolutionary Computation and the Journal of Industrial and Production Engineering, and an editorial board member of the European Journal of Industrial Engineering and Operations Research Perspectives.
Dr. Akhil Garg is an associate professor at the Ministry of Education's Intelligent Manufacturing Key Laboratory, Shantou University, China. He has been working on sustainable manufacturing processes and optimization methods since 2011. He received his doctoral degree from Nanyang Technological University (NTU), Singapore in 2014. He has published over 50 SCI-indexed articles in the areas of manufacturing and optimization.
Dr. P. Kavitha is an associate professor at the School of Electrical Engineering, VIT University, Vellore, India. Her research interests include control systems, analog and digital circuits, advanced control theory, process automation and process control.

Dr. G. Dhivyasri is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. Dr. Dhivyasri's research interests include, control system, MEMS, sensors and signal conditioning, as well as analog & digital communication systems.

Dr. Rahul SG is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. His research interests include control systems, industrial instrumentation, analytical instrumentation, programmable logic controller (PLC), and digital electronics.



Details
Weitere ISBN/GTIN9789811308062
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis1 - PDF Watermark
FormatE107
Erscheinungsjahr2018
Erscheinungsdatum30.06.2018
Auflage1st ed. 2019
Seiten229 Seiten
SpracheEnglisch
IllustrationenX, 229 p. 139 illus., 101 illus. in color.
Artikel-Nr.3460637
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
1;Contents;5
2;1 Welding an Overview;11
2.1;1.1 Basics of Arc Welding;12
2.1.1;1.1.1 Electric Charge;13
2.1.2;1.1.2 Electric Current;13
2.1.3;1.1.3 Voltage;13
2.1.4;1.1.4 Electrical Resistance;14
2.1.5;1.1.5 Heat Input;14
2.1.6;1.1.6 Power;15
2.2;1.2 Equivalent Electrical Analogous Representation of Arc Welding;15
2.3;1.3 Arc Welding as a Confluence of Several Disciplines;16
2.4;1.4 Applications of Arc Welding;16
2.5;References;24
3;2 Insight into Arc Welding Power Source Terminologies;25
3.1;2.1 Critical Arc Power Source Terminologies for Welding;25
3.1.1;2.1.1 Arc Plasma;25
3.1.2;2.1.2 Arc Efficiency;26
3.1.3;2.1.3 Arc Stability;26
3.1.4;2.1.4 Arc Blow;27
3.1.5;2.1.5 Pinch Effect;27
3.1.6;2.1.6 Arc Shielding;27
3.2;2.2 Influence of Power Source Parameters on Weldment;28
3.2.1;2.2.1 Open-Circuit Voltage (OCV);28
3.2.2;2.2.2 Arc Voltage;29
3.2.3;2.2.3 Welding Current;30
3.2.4;2.2.4 Electrode Polarity;31
3.2.5;2.2.5 Power Factor;31
3.2.6;2.2.6 Duty Cycle and Current Rating;32
3.2.7;2.2.7 Class of Insulation;32
3.3;2.3 Impact of Power Source Characteristics on Weldments;33
3.3.1;2.3.1 Static Characteristics;33
3.3.2;2.3.2 Dynamic Characteristics;35
3.4;2.4 Classification of Arc Welding Power Sources;35
3.4.1;2.4.1 Static Types;35
3.4.2;2.4.2 Rotating Types;39
3.5;2.5 Power Sources Components Briefing;41
3.5.1;2.5.1 Diode;41
3.5.2;2.5.2 BJT;42
3.5.3;2.5.3 MOSFET;44
3.5.4;2.5.4 Insulated Gate Bipolar Transistor (IGBT);46
3.5.5;2.5.5 Silicon-Controlled Rectifier (SCR);46
3.5.6;2.5.6 Pulse Width Modulators (PWM);48
3.5.7;2.5.7 Microprocessor;49
3.5.8;2.5.8 Microcontroller;49
3.5.9;2.5.9 Field-Programmable Gate Arrays (FPGAs);49
3.6;2.6 Evolution of Arc Welding Power Sources;50
3.7;2.7 Switch-Based Techniques Adopted for Welding Power Sources;53
3.8;2.8 Literature Addressing Power Source Parameters;71
3.9;References;77
4;3 Control Terminologies and Schemes for Arc Welding Processes;81
4.1;3.1 Control System Terminologies;81
4.1.1;3.1.1 Process;81
4.1.2;3.1.2 System;82
4.1.3;3.1.3 Control System;82
4.1.4;3.1.4 Parameters/Variables;82
4.1.5;3.1.5 Control;83
4.1.6;3.1.6 Disturbances;83
4.1.7;3.1.7 Setpoint;83
4.1.8;3.1.8 Feedback;83
4.1.9;3.1.9 Error;84
4.1.10;3.1.10 Transfer Function;84
4.1.11;3.1.11 Open Loop System;84
4.1.12;3.1.12 Closed-Loop System;85
4.2;3.2 Control System Analysis;86
4.2.1;3.2.1 Order of the System;86
4.2.2;3.2.2 Zeroth Order System;86
4.2.3;3.2.3 First-Order System;87
4.2.4;3.2.4 Second-Order System;87
4.2.5;3.2.5 Linearity;88
4.2.6;3.2.6 Sensitivity;88
4.3;3.3 Introduction to Fundamental Controllers;88
4.4;3.4 Stability Analysis;89
4.5;3.5 Significance of Control System;90
4.6;3.6 Control System for Arc Welding;90
4.6.1;3.6.1 Sensing System;91
4.6.2;3.6.2 Control Strategy and Algorithms;91
4.6.3;3.6.3 Desired Gating Signals;92
4.7;3.7 Controller Schemes Adopted for Welding Power Sources;92
4.8;3.8 Process Parametric Influences on Weld Quality;94
4.9;3.9 Real-Time Sample Reports on Formulating Adaptive Control Scheme for Cold Metal Transfer for JoiningAA6061;129
4.9.1;3.9.1 Objective;129
4.9.2;3.9.2 Implementation;129
4.9.3;3.9.3 Controller Results;131
4.9.4;3.9.4 MRAC Controller Response;132
4.10;References;135
5;4 Power Sources and Challenges for Different Arc Welding Processes;137
5.1;4.1 Power Sources in Manual Metal Arc Welding (MMA);137
5.2;4.2 Power Sources in Shielded Metal Arc Welding (SMAC);137
5.3;4.3 Power Sources in Gas Tungsten Arc Welding (GTAW)/Tungsten Inert Gas Arc Welding (TIG);138
5.4;4.4 Power Sources in Gas Metal Arc Welding/Metal Inert Gas Welding (GMAW/MIG);139
5.5;4.5 Power Sources in Submerged Arc Welding (SAW);140
5.6;4.6 Major Challenges in Power Sources;140
5.6.1;4.6.1 Harmonics;140
5.6.2;4.6.2 Effects of Magnetic Field in Arc Welding;142
5.6.3;4.6.3 Protection of Power Sources;144
5.6.4;4.6.4 Cooling System;144
5.7;References;147
6;5 Sensors for Welding Data Acquisition;149
6.1;5.1 Data Acquisition System;149
6.1.1;5.1.1 What Are Sensors and Transducers?;150
6.1.2;5.1.2 Signals;151
6.1.3;5.1.3 What Is a DAQ Hardware?;154
6.2;5.2 Physical Principles of Sensing;154
6.2.1;5.2.1 Characteristics of Different Sensor Types;155
6.2.2;5.2.2 Basic Terminologies;156
6.2.3;5.2.3 Choosing a Sensor;156
6.3;5.3 Key Measurement Components of a DAQ Device;157
6.3.1;5.3.1 Signal Conditioning;157
6.3.2;5.3.2 Analog-to-Digital Converter (ADC);158
6.3.3;5.3.3 Computer Bus;158
6.4;5.4 Role of Computer in a DAQ System;158
6.4.1;5.4.1 Application Software;158
6.4.2;5.4.2 Driver Software;161
6.5;5.5 Data Acquisition in Arc Welding Processes;161
6.5.1;5.5.1 Measuring Current and Voltage;161
6.5.2;5.5.2 Wire Feed Speed;163
6.5.3;5.5.3 Shielding Gas Flow;165
6.5.4;5.5.4 Temperature;165
6.5.5;5.5.5 Sensors for Geometrical Parameters;167
6.5.6;5.5.6 Arc Sensors;170
6.5.7;5.5.7 Typical Sensors and Their Outputs;171
6.6;5.6 Parameters of Arc Welding Sensors for Various Applications;171
6.7;5.7 Data Acquisition Using LabVIEW;171
6.7.1;5.7.1 Physical Input/Output Signals;173
6.7.2;5.7.2 DAQ Device/Hardware;173
6.7.3;5.7.3 Driver Software;173
6.7.4;5.7.4 Application Software;174
6.7.5;5.7.5 Measurement and Automation Explorer;174
6.7.6;5.7.6 DAQ Assistant;175
6.8;5.8 Case Study 1: Measurement of Temperature During Joining of 316L Stainless Steel by CMT Process;176
6.8.1;5.8.1 Process Details;176
6.8.2;5.8.2 Description of DAQ Unit;177
6.8.3;5.8.3 Experimental Data;178
6.8.4;5.8.4 Temperature Plots;178
6.9;5.9 Case Study 2: Characterization of Gas Metal Arc Welding System Using DAQ;179
6.9.1;5.9.1 Description;179
6.9.2;5.9.2 Welding Procedure;180
6.10;5.10 Results;182
6.11;References;189
7;6 Optimization in Arc Welding Process;190
7.1;6.1 Introduction to Optimization;190
7.1.1;6.1.1 Constructing a Model;190
7.1.2;6.1.2 System Identification in Arc Welding;191
7.2;6.2 Significance of Optimization in Welding;191
7.3;6.3 ANN-Based Optimization Techniques to Arc Welding Processes;192
7.3.1;6.3.1 Introduction to ANN;192
7.3.2;6.3.2 Backpropagation Neural Network (BP-NN);195
7.4;6.4 Development of PSO-Based Backpropagation Neural Network;197
7.4.1;6.4.1 Particle Swarm Optimization;197
7.4.2;6.4.2 Development of BP-NN Using PSO Algorithm;198
7.5;6.5 Development of Levenberg-Marquardt (LM) Algorithm-Based Backpropagation Neural Network;201
7.5.1;6.5.1 Introduction to LM Algorithm;201
7.5.2;6.5.2 Computing the Jacobian Matrix;201
7.5.3;6.5.3 Steps in Levenberg-Marquardt Algorithm;202
7.6;6.6 Genetic Algorithm for Tuning the Neural Network;203
7.7;6.7 Case Study 1: Optimization of Flux Cored Arc Welding Parameters Using GA;205
7.7.1;6.7.1 Objective;205
7.7.2;6.7.2 Experimentation;205
7.7.3;6.7.3 Optimization;207
7.8;6.8 Case Study 2: Optimization and Prediction of Hardness and Shear Strength Using PSO Based ANN in FSW of AA6061 Alloys;209
7.8.1;6.8.1 Objective;209
7.8.2;6.8.2 Experimentation;209
7.8.3;6.8.3 Implementation;210
7.9;6.9 Case Study 3: LM Algorithm-Based ANN Model to Predict Strength and Joint Resistance of Al-Cu Alloys Joined by Ultrasonic Welding Process;212
7.9.1;6.9.1 Objective;212
7.9.2;6.9.2 Experimentation;213
7.9.3;6.9.3 Implementation;213
7.10;References;216
8;7 Codes and Safety Standards During Welding;217
8.1;7.1 Risk Management Process;217
8.1.1;7.1.1 Identifying the Potential Hazards;217
8.1.2;7.1.2 Assessment of Risk;218
8.1.3;7.1.3 Risk Control;218
8.2;7.2 Specific Hazards and Control Measures;219
8.2.1;7.2.1 Airborne Contaminants;219
8.2.2;7.2.2 Radiation;220
8.2.3;7.2.3 Electrical Risks;221
8.2.4;7.2.4 Risks Due to Electromagnetic Fields;223
8.2.5;7.2.5 Exposure to Heat and Burns;223
8.2.6;7.2.6 Compressed and Liquefied Gases;224
8.2.7;7.2.7 Personal Protective Equipment (PPE);224
8.2.8;7.2.8 Health Monitoring;224
8.3;7.3 Standard Operating Procedures During Arc Welding;228
8.3.1;7.3.1 Engine Power Equipment;228
8.3.2;7.3.2 In Presence of Electric and Magnetic Fields;229
8.3.3;7.3.3 During Handling Cylinders;230
8.3.4;7.3.4 While Handling Shielding Gases;230
8.4;7.4 Welding Codes: American Welding Society (AWS);230
8.5;7.5 Quality Assurance and Quality Management;232
8.5.1;7.5.1 En ISO 15609;232
8.5.2;7.5.2 En ISO 15614-1;232
8.5.3;7.5.3 EN ISO 15614-2;234
8.5.4;7.5.4 EN ISO 15610;234
8.5.5;7.5.5 EN ISO 5817 and ISO 10042;235
8.6;References;237mehr

Autor

Dr. S. Arungalai Vendan is an associate professor at the Industrial Automation and Instrumentation Division, VIT University, Vellore, India. He has been working on advanced welding processes since 2006. He received his Ph.D. degree from the National Institute of Technology (Institute of national importance), Tiruchirappalli, India in 2010. He has received several fellowships and awards for his technical contributions by various government agencies. He has successfully completed government funded research projects and industrial consultancy projects, and has published more than 70 research papers in international journal and conference proceedings. He has associations with top manufacturing industries and Research and Development centers under various capacities. His research interests mainly focus on the interdisciplinary science which has confluence of terminologies from electrical/mechanical/metallurgical/ materials and magnetic technologies.

Prof. Liang Gao received his Ph.D. degree in Mechatronic Engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is currently a professor at the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and the vice director of the State Key Lab of Digital Manufacturing Equipment & Technology. His chief research interests include optimization in design and manufacturing, and he has published more than 150 academic papers,. He is currently an associate editor for Swarm and Evolutionary Computation and the Journal of Industrial and Production Engineering, and an editorial board member of the European Journal of Industrial Engineering and Operations Research Perspectives.
Dr. Akhil Garg is an associate professor at the Ministry of Education's Intelligent Manufacturing Key Laboratory, Shantou University, China. He has been working on sustainable manufacturing processes and optimization methods since 2011. He received his doctoral degree from Nanyang Technological University (NTU), Singapore in 2014. He has published over 50 SCI-indexed articles in the areas of manufacturing and optimization.
Dr. P. Kavitha is an associate professor at the School of Electrical Engineering, VIT University, Vellore, India. Her research interests include control systems, analog and digital circuits, advanced control theory, process automation and process control.

Dr. G. Dhivyasri is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. Dr. Dhivyasri's research interests include, control system, MEMS, sensors and signal conditioning, as well as analog & digital communication systems.

Dr. Rahul SG is an assistant professor at the School of Electrical Engineering, VIT University, Vellore, India. His research interests include control systems, industrial instrumentation, analytical instrumentation, programmable logic controller (PLC), and digital electronics.