Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Instrumentation: Theory and Practice, Part 1
This book emphasizes simple and concise coverage of the fundamental aspects of measuring systems. It is designed to provide the reader with essential knowledge regarding signals, signal analysis, signal conditioning circuits, and data acquisition systems. The prerequisites are a basic knowledge of multivariable calculus, introductory physics, and a familiarity with basic electrical circuits and components. Delivers topics and techniques that are fundamental to the understanding of the measurement process. These include standards, dynamic characteristics of measuring devices, statistical analysis of data, uncertainty analysis, signal conditioning devices, transistors,and logic circuits, analog to digital converters. To aid in the understanding of the subject matter and related applications, the book chapters are complemented with examples and problems. Careful attention was paid to the details of figures and illustration to help enforce the learning objectives of this book.
Instrumentation
The use of sensors and instrumentation for measuring and control is growing at a very rapid rate in all facets of life in today's world. This Part II of Instrumentation: Theory and Practice is designed to provide the reader with essential knowledge regarding a broad spectrum of sensors and transducers and their applications. This textbook is intended for use as an introductory one-semester course at the junior level of an undergraduate program. It is also very relevant for technicians, engineers, and researchers who had no formal training in instrumentation and wish to engage in experimental measurements. The prerequisites are: a basic knowledge of multivariable calculus, introductory physic...
Intelligent Manufacturing and Mechatronics
This book presents the proceedings of SympoSIMM 2020, the 3rd edition of the Symposium on Intelligent Manufacturing and Mechatronics. Focusing on “Strengthening Innovations Towards Industry 4.0”, the book presents studies on the details of Industry 4.0’s current trends. Divided into five parts covering various areas of manufacturing engineering and mechatronics stream, namely, artificial intelligence, instrumentation and controls, intelligent manufacturing, modelling and simulation, and robotics, the book will be a valuable resource for readers wishing to embrace the new era of Industry 4.0.
Advances in Additive Manufacturing Technologies
We are delighted to present the proceedings of the 5th International Conference on Advances in Additive Manufacturing Technologies (ICAAMT 2023). This conference serves as a premier forum for researchers, practitioners, and industry experts to share their latest findings, innovations, and insights in the field of additive manufacturing. The rapid advancements and the increasing adoption of these technologies across various sectors underscore the importance of this gathering. The conference was held from November 27-29, 2023, in Chennai, India and organized by the Department of Mechanical Engineering, Chennai Institute of Technology, Chennai, India.
Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science. The book Discusses basic as well as advance research in the field of prognostics. Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume. Covers prognostics and health management (PHM) of engineering systems. Discusses latest approaches in the field of prognostics based on machine learning. The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.
