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Author: National Aeronautics and Space Administration (NASA) Publisher: Createspace Independent Publishing Platform ISBN: 9781721152452 Category : Languages : en Pages : 154
Book Description
The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory. Saleeb, Atef F. and Ponnaluru, Gopi Krishna Glenn Research Center NCC3-808; WBS 846-02-07-03
Author: National Aeronautics and Space Administration (NASA) Publisher: Createspace Independent Publishing Platform ISBN: 9781721152452 Category : Languages : en Pages : 154
Book Description
The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory. Saleeb, Atef F. and Ponnaluru, Gopi Krishna Glenn Research Center NCC3-808; WBS 846-02-07-03
Author: M. Arif Wani Publisher: Springer ISBN: 9789811567582 Category : Technology & Engineering Languages : en Pages : 300
Book Description
This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
Author: Joseph Mathew Publisher: Springer Science & Business Media ISBN: 1846288142 Category : Technology & Engineering Languages : en Pages : 1261
Book Description
It is with great pleasure that we welcome you to the inaugural World Congress on Engineering Asset Management (WCEAM) being held at the Conrad Jupiters Hotel on the Gold Coast from July 11 to 14, 2006. More than 170 authors from 28 countries have contributed over 160 papers to be presented over the first three days of the conference. Day four will be host to a series of workshops devoted to the practice of various aspects of Engineering Asset Management. WCEAM is a new annual global forum on the various multidisciplinary aspects of Engineering Asset Management. It deals with the presentation and publication of outputs of research and development activities as well as the application of knowledge in the practical aspects of: strategic asset management risk management in asset management design and life-cycle integrity of physical assets asset performance and level of service models financial analysis methods for physical assets reliability modelling and prognostics information systems and knowledge management asset data management, warehousing and mining condition monitoring and intelligent maintenance intelligent sensors and devices regulations and standards in asset management human dimensions in integrated asset management education and training in asset management and performance management in asset management. We have attracted academics, practitioners and scientists from around the world to share their knowledge in this important emerging transdiscipline that impacts on almost every aspect of daily life.
Author: Hae Young Noh Publisher: Springer Nature ISBN: 3031054490 Category : Technology & Engineering Languages : en Pages : 111
Book Description
Dynamics of Civil Structures, Volume 2: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the second volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of the Dynamics of Civil Structures, including papers on: Structural Vibration Humans & Structures Innovative Measurement for Structural Applications Smart Structures and Automation Modal Identification of Structural Systems Bridges and Novel Vibration Analysis Sensors and Control
Author: Gupta, Brij B. Publisher: IGI Global ISBN: Category : Computers Languages : en Pages : 530
Book Description
The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.
Author: Chunwei Zhang Publisher: CRC Press ISBN: 1040150063 Category : Technology & Engineering Languages : en Pages : 245
Book Description
Structural health monitoring is a powerful tool across civil, mechanical, automotive, and aerospace engineering, allowing the assessment and measurement of physical parameters in real time. Processing changes in the vibration signals of a dynamic system can detect, locate, and quantify any damage existing in the system. This book presents a comprehensive state‐of‐the‐art review of the applications in time, frequency, and time‐frequency domains of signal‐processing techniques for damage perception, localization, and quantification in various structural systems. Experimental investigations are illustrated, including the development of a set of damage indices based on the signal features extracted through various signal‐processing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the Hilbert–Huang transform based on three decomposition methods such as empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. Also, the chapters assess the performance and sensitivity of different approaches, including multiple signal classification and empirical wavelet transform techniques in damage detection and quantification. Artificial neural networks for automated damage identification are introduced. This book suits students, engineers, and researchers who are investigating structural health monitoring, signal processing, and damage identification of structures.
Author: Li Hu Publisher: Springer Nature ISBN: 9811391130 Category : Medical Languages : en Pages : 435
Book Description
This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.
Author: Qianlei Jia Publisher: Infinite Study ISBN: Category : Mathematics Languages : en Pages : 20
Book Description
Fault detection, with the characteristics of strong uncertainty and randomness, has always been one of the research hotspots in the field of aerospace. Considering that devices will inevitably encounter various unknown interference in the process of use, which greatly limits the performance of many traditional fault detection methods. Therefore, the main aim of this paper is to address this problem from the perspective of uncertainty and randomness of measurement signal. In information engineering, interval-valued neutrosophic sets (IVNSs), belief rule base (BRB), and Dempster-Shafer (D-S) evidence reasoning are always characterized by the strong ability in revealing uncertainty, but each has its drawbacks. As a result, the three theories are firstly combined in this paper to form a powerful fault detection algorithm. Besides, a series of innovations are proposed to improve the method, including a new score function based on p-norm for IVNSs and a new approach of calculating the similarity between IVNSs, which are both proved by authoritative prerequisites. To illustrate the effectiveness of the proposed method, flush air data sensing (FADS), a technologically advanced airborne sensor, is adopted in this paper. The aerodynamic model of FADS is analyzed in detail using knowledge of aerodynamics under subsonic and supersonic conditions, meanwhile, the high-precision model is established based on the aerodynamic database obtained from CFD software.
Author: Daniel Balageas Publisher: John Wiley & Sons ISBN: 0470394404 Category : Technology & Engineering Languages : en Pages : 496
Book Description
This book is organized around the various sensing techniques used to achieve structural health monitoring. Its main focus is on sensors, signal and data reduction methods and inverse techniques, which enable the identification of the physical parameters, affected by the presence of the damage, on which a diagnostic is established. Structural Health Monitoring is not oriented by the type of applications or linked to special classes of problems, but rather presents broader families of techniques: vibration and modal analysis; optical fibre sensing; acousto-ultrasonics, using piezoelectric transducers; and electric and electromagnetic techniques. Each chapter has been written by specialists in the subject area who possess a broad range of practical experience. The book will be accessible to students and those new to the field, but the exhaustive overview of present research and development, as well as the numerous references provided, also make it required reading for experienced researchers and engineers.
Author: National Aeronautics and Space Administration (NASA)
Author: National Aeronautics and Space Administration (NASA)
Author: M. Arif Wani
Author: Joseph Mathew
Author: Hae Young Noh
Author: 
Author: Gupta, Brij B.
Author: Chunwei Zhang
Author: Li Hu
Author: Qianlei Jia
Author: Daniel Balageas