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| Author | : Jun Wang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 155 |
| Release | : 2021-09-13 |
| Genre | : Technology & Engineering |
| ISBN | : 2889712990 |
| Author | : Nam-Ho Kim |
| Publisher | : Springer |
| Total Pages | : 355 |
| Release | : 2016-10-24 |
| Genre | : Technology & Engineering |
| ISBN | : 3319447424 |
This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application.Among the many topics discussed in-depth are:• Prognostics tutorials using least-squares• Bayesian inference and parameter estimation• Physics-based prognostics algorithms including nonlinear least squares, Bayesian method, and particle filter• Data-driven prognostics algorithms including Gaussian process regression and neural network• Comparison of different prognostics algorithms divThe authors also present several applications of prognostics in practical engineering systems, including wear in a revolute joint, fatigue crack growth in a panel, prognostics using accelerated life test data, fatigue damage in bearings, and more. Prognostics tutorials with a Matlab code using simple examples are provided, along with a companion website that presents Matlab programs for different algorithms as well as measurement data. Each chapter contains a comprehensive set of exercise problems, some of which require Matlab programs, making this an ideal book for graduate students in mechanical, civil, aerospace, electrical, and industrial engineering and engineering mechanics, as well as researchers and maintenance engineers in the above fields.
| Author | : Stephen Ekwaro-Osire |
| Publisher | : Springer |
| Total Pages | : 273 |
| Release | : 2017-04-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3319558528 |
This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters.It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.
| Author | : Kadry, Seifedine |
| Publisher | : IGI Global |
| Total Pages | : 461 |
| Release | : 2012-09-30 |
| Genre | : Technology & Engineering |
| ISBN | : 146662096X |
Industrial Prognostics predicts an industrial systems lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to increase the systems performance and reliability. Diagnostics and Prognostics of Engineering Systems: Methods and Techniques provides widespread coverage and discussions on the methods and techniques of diagnosis and prognosis systems. Including practical examples to display the methods effectiveness in real-world applications as well as the latest trends and research, this reference source aims to introduce fundamental theory and practice for system diagnosis and prognosis.
| Author | : Olga Dolinina |
| Publisher | : Springer Nature |
| Total Pages | : 694 |
| Release | : 2023-04-24 |
| Genre | : Technology & Engineering |
| ISBN | : 303122938X |
This book is based on the accepted research papers presented in the International Conference "Artificial Intelligence in Engineering & Science" (AIES-2022). The aim of the AIES Conference is to bring together researchers involved in the theory of computational intelligence, knowledge engineering, fuzzy systems, soft computing, machine learning and related areas and applications in engineering, bioinformatics, industry, medicine, energy, smart city, social spheres and other areas. This book presents new perspective research results: models, methods, algorithms and applications in the field of Artificial Intelligence (AI). Particular emphasis is given to the medical applications - medical images recognition, development of the expert systems which could be interesting for the AI researchers as well for the physicians looking for the new ideas in medicine. The central audience of the book are researchers, industrial practitioners, students specialized in the Artificial Intelligence.
| Author | : Xianping Zhong |
| Publisher | : Frontiers Media SA |
| Total Pages | : 142 |
| Release | : 2022-09-27 |
| Genre | : Technology & Engineering |
| ISBN | : 2889767086 |
| Author | : William Aylward |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2022 |
| Genre | : |
| ISBN | : |
| Author | : Michael G. Pecht |
| Publisher | : John Wiley & Sons |
| Total Pages | : 809 |
| Release | : 2018-08-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1119515300 |
An indispensable guide for engineers and data scientists in design, testing, operation, manufacturing, and maintenance A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to: assess methods for damage estimation of components and systems due to field loading conditions assess the cost and benefits of prognostic implementations develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles and/or timely repair actions; obtain knowledge of load history for future design, qualification, and root cause analysis reduce the occurrence of no fault found (NFF) subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.
| Author | : PHM Society |
| Publisher | : Lulu.com |
| Total Pages | : 127 |
| Release | : 2013-09-24 |
| Genre | : Technology & Engineering |
| ISBN | : 1936263122 |
PHM Society established International Journal of Prognostics and Health Management (IJPHM) in 2009 to facilitate archival publication of peer-reviewed results from research and development in the area of PHM. As a journal solely dedicated to the emerging field of PHM IJPHM is the first of its kind and has been a focal point for dissemination of peer-reviewed PHM knowledge. While for the first few years the journal maintained only an online presence, the printed volumes will now be available and can be obtained upon request.
| Author | : Gennadij V Arkadov |
| Publisher | : Elsevier |
| Total Pages | : 369 |
| Release | : 2012-09-27 |
| Genre | : Technology & Engineering |
| ISBN | : 0857093991 |
Probabilistic safety assessment methods are used to calculate nuclear power plant durability and resource lifetime. Successful calculation of the reliability and ageing of components is critical for forecasting safety and directing preventative maintenance, and Probabilistic safety assessment for optimum nuclear power plant life management provides a comprehensive review of the theory and application of these methods. Part one reviews probabilistic methods for predicting the reliability of equipment. Following an introduction to key terminology, concepts and definitions, formal-statistical and various physico–statistical approaches are discussed. Approaches based on the use of defect-free models are considered, along with those using binomial distribution and models based on the residual defectiveness of structural materials. The practical applications of probabilistic methods for strength reliability are subsequently explored in part two. Probabilistic methods for increasing the reliability and safety of nuclear power plant components are investigated, as are the use of such methods for optimising non-destructive tests, hydraulic tests, technical certification and planned-preventative maintenance. Finally, the book concludes with information on the use of probabilistic methods in ensuring leak tightness of nuclear power plant steam generator heat exchanger pipes. With its distinguished authors, Probabilistic safety assessment for optimum nuclear power plant life management is a valuable reference for all nuclear plant designers, operators, nuclear safety engineers and managers, as well as academics and researchers in this field. Discusses the theory and application of probabilistic safety assessment methods used to calculate nuclear power plant (NPP) durability and lifetime Reviews probabilistic methods in their application to NPP components and ageing pipelines for the forecasting of NPP resource lifetime and safety Addresses the key areas of probabilistic safety analysis, optimization of the operations through in-service inspection (ISI) utilising non-destructive testing, and maintenance, service and repair approaches
