Embedded Fault Class Detection Methodology For Condition Based Machine Monitoring And Predictive Maintenance
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| Author | : Amiya Ranjan Mohanty |
| Publisher | : CRC Press |
| Total Pages | : 282 |
| Release | : 2014-12-22 |
| Genre | : Science |
| ISBN | : 1466593059 |
Find the Fault in the Machines Drawing on the author’s more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, and rotating machines in particular. A Single-Source Solution for Practice Machinery Conditioning Monitoring Since vibration is one of the most widely used fault detection techniques, the book offers an assessment of vibration analysis and rotor-dynamics. It also covers the techniques of wear and debris analysis, and motor current signature analysis to detect faults in rotating mechanical systems as well as thermography, the nondestructive test NDT techniques (ultrasonics and radiography), and additional methods. The author includes relevant case studies from his own experience spanning over the past 20 years, and detailing practical fault diagnosis exercises involving various industries ranging from steel and cement plants to gas turbine driven frigates. While mathematics is kept to a minimum, he also provides worked examples and MATLAB® codes. This book contains 15 chapters and provides topical information that includes: A brief overview of the maintenance techniques Fundamentals of machinery vibration and rotor dynamics Basics of signal processing and instrumentation, which are essential for monitoring the health of machines Requirements of vibration monitoring and noise monitoring Electrical machinery faults Thermography for condition monitoring Techniques of wear debris analysis and some of the nondestructive test (NDT) techniques for condition monitoring like ultrasonics and radiography Machine tool condition monitoring Engineering failure analysis Several case studies, mostly on failure analysis, from the author’s consulting experience Machinery Condition Monitoring: Principles and Practices presents the latest techniques in fault diagnosis and prognosis, provides many real-life practical examples, and empowers you to diagnose the faults in machines all on your own.
| Author | : Siba K. Udgata |
| Publisher | : Springer Nature |
| Total Pages | : 575 |
| Release | : 2021-04-19 |
| Genre | : Technology & Engineering |
| ISBN | : 981336081X |
This book features best selected research papers presented at the International Conference on Machine Learning, Internet of Things and Big Data (ICMIB 2020) held at Indira Gandhi Institute of Technology, Sarang, India, during September 2020. It comprises high-quality research work by academicians and industrial experts in the field of machine learning, mobile computing, natural language processing, fuzzy computing, green computing, human–computer interaction, information retrieval, intelligent control, data mining and knowledge discovery, evolutionary computing, IoT and applications in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence, internet security, pattern recognition, predictive analytics applications in healthcare, sensor networks and social sensing and statistical analysis of search techniques.
| Author | : Joao Gama |
| Publisher | : Springer Nature |
| Total Pages | : 317 |
| Release | : 2021-01-09 |
| Genre | : Computers |
| ISBN | : 3030667707 |
This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.
| Author | : Edwin Lughofer |
| Publisher | : Springer |
| Total Pages | : 564 |
| Release | : 2019-02-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3030056457 |
This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.
| Author | : R. Keith Mobley |
| Publisher | : Elsevier |
| Total Pages | : 451 |
| Release | : 2002-10-24 |
| Genre | : Technology & Engineering |
| ISBN | : 0080478697 |
This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. - A comprehensive introduction to a system of monitoring critical industrial equipment - Optimize the availability of process machinery and greatly reduce the cost of maintenance - Provides the means to improve product quality, productivity and profitability of manufacturing and production plants
| Author | : Marco Antonio Aceves-Fernandez |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 466 |
| Release | : 2018-06-27 |
| Genre | : Computers |
| ISBN | : 178923364X |
Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.
| Author | : Dewayne Hopper |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2016-06 |
| Genre | : Technology & Engineering |
| ISBN | : 9781682850510 |
The innovations and advancements in the field of science and technology have brought a tremendous shift in the field of engineering. Electrical, electronic and control engineering are some of the major engineering disciplines that have developed at a rapid pace. This book explores all the important aspects of these disciplines in the present day scenario with respect to topics such as power and electrical engineering, information and communication technologies, mechatronics, control engineering, design of new devices, etc. Those in search of information to further their knowledge will be greatly assisted by this comprehensive book.
| Author | : Hamid A. Toliyat |
| Publisher | : CRC Press |
| Total Pages | : 272 |
| Release | : 2017-12-19 |
| Genre | : Technology & Engineering |
| ISBN | : 1420006282 |
With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condition monitoring scheme—thus improving safety and reliability in electric motor operation. It also supplies a solid foundation in the fundamentals of fault cause and effect. Combines Theoretical Analysis and Practical Application Written by experts in electrical engineering, the book approaches the fault diagnosis of electrical motors through the process of theoretical analysis and practical application. It begins by explaining how to analyze the fundamentals of machine failure using the winding functions method, the magnetic equivalent circuit method, and finite element analysis. It then examines how to implement fault diagnosis using techniques such as the motor current signature analysis (MCSA) method, frequency domain method, model-based techniques, and a pattern recognition scheme. Emphasizing the MCSA implementation method, the authors discuss robust signal processing techniques and the implementation of reference-frame-theory-based fault diagnosis for hybrid vehicles. Fault Modeling, Diagnosis, and Implementation in One Volume Based on years of research and development at the Electrical Machines & Power Electronics (EMPE) Laboratory at Texas A&M University, this book describes practical analysis and implementation strategies that readers can use in their work. It brings together, in one volume, the fundamentals of motor fault conditions, advanced fault modeling theory, fault diagnosis techniques, and low-cost DSP-based fault diagnosis implementation strategies.
| Author | : |
| Publisher | : |
| Total Pages | : 906 |
| Release | : 1991 |
| Genre | : Marine engineering |
| ISBN | : |
| Author | : Barney L. Capehart |
| Publisher | : CRC Press |
| Total Pages | : 582 |
| Release | : 2020-12-22 |
| Genre | : Computers |
| ISBN | : 8770222983 |
This book promotes the benefits of the development and application of energy information and control systems. This wave of information technology (IT) and web-based energy information and control systems (web based EIS/ECS) continues to roll on with increasing speed and intensity. This handbook presents recent technological advancements in the field, as well as a compilation of the best information from three previous books in this area. The combined thrust of this information is that the highest level functions of the building and facility automation system are delivered by a web based EIS/ECS system that provides energy management, facility management, overall facility operational management and ties in with the enterprise resource management system for the entire facility or the group of facilities being managed.
