A combination of two texts authored by Patrick Dunn, this set covers sensor technology as well as basic measurement and data analysis subjects, a combination not covered together in other references. Written for junior-level mechanical and aerospace engineering students, the topic coverage allows for flexible approaches to using the combination book in courses. MATLAB® applications are included in all sections of the combination, and concise, applied coverage of sensor technology is offered. Numerous chapter examples and problems are included, with complete solutions available.

Fundamentals of Sensors for Engineering and Science is a practical analysis of sensors and measurement, designed to help readers make informed decisions when selecting an appropriate sensor for a given application. Spurred by a growing demand for information on the evolution of modern sensors, this book evaluates current applications to illustrate

The third edition of Measurement and Data Analysis for Engineering and Science provides an up-to-date approach to presenting the methods of experimentation in science and engineering. Widely adopted by colleges and universities within the U.S. and abroad, this edition has been developed as a modular work to make it more adaptable to different approaches from various schools. This text details current methods and highlights the six fundamental tools required for implementation: planning an experiment, identifying measurement system components, assessing measurement system component performance, setting signal sampling conditions, analyzing experimental results, and reporting experimental results. What’s New in the Third Edition: This latest edition includes a new chapter order that presents a logical sequence of topics in experimentation, from the planning of an experiment to the reporting of the experimental results. It adds a new chapter on sensors and transducers that describes approximately 50 different sensors commonly used in engineering, presents uncertainty analysis in two separate chapters, and provides a problem topic summary in each chapter. New topics include smart measurement systems, focusing on the Arduino® microcontroller and its use in the wireless transmission of data, and MATLAB® and Simulink® programming for microcontrollers. Further topic additions are on the rejection of data outliers, light radiation, calibrations of sensors, comparison of first-order sensor responses, the voltage divider, determining an appropriate sample period, and planning a successful experiment. Measurement and Data Analysis for Engineering and Science also contains more than 100 solved example problems, over 400 homework problems, and provides over 75 MATLAB® Sidebars with accompanying MATLAB M-files, Arduino codes, and data files available for download.

Fundamentals of Sensors for Engineering and Science is a practical analysis of sensors and measurement, designed to help readers make informed decisions when selecting an appropriate sensor for a given application. Spurred by a growing demand for information on the evolution of modern sensors, this book evaluates current applications to illustrate their wide range of uses, as well as the many ways they can be classified. Emphasizing the underlying physics involved, author Patrick Dunn reviews the sensors commonly used in engineering and science. He also covers the sensors of the human body, as well as biomimetic sensors used to simulate human functions. The book organizes and describes contemporary examples of manmade sensors based on their core physical principles. Fundamentals—including scaling considerations involved in micro- and nano-sensor development and uncertainty—are introduced at the beginning of the text. A companion to the popular Measurement and Data Analysis for Engineering and Science, Second Edition, this book will benefit instructors, industry professionals, and anyone else with an interest in this burgeoning field. Clarifying the primary role and key characteristics of sensors in engineering and science, this text includes a wealth of examples and chapter problems, and it also provides online links to updated ancillary materials.

This book covers sensors and multiple sensor systems, including sensor networks and multi-sensor data fusion. It presents the physics and principles of operation and discusses sensor selection, ratings and performance specifications, necessary hardware and software for integration into an engineering system and signal processing and data analysis. Additionally, it discusses parameter estimation, decision making and practical applications. Even though the book has all the features of a course textbook, it also contains a wealth of practical information on the subject.

This book presents the principles, methods and techniques to characterize materials and technical systems. The book is organized with concise text-graphics compilations in three parts: The first part describes the fundamentals of measurement, testing and sensor technology, including a survey of sensor types for dimensional metrology, kinematics, dynamics, and temperature. It describes also microsensors and embedded sensors. The second part gives an overview of materials and explains the application of measurement, testing and sensor technology to characterize composition, microstructure, properties and performance of materials as well as deterioration mechanisms and reliability. The third part introduces the general systems theory for the characterization of technical systems, exemplified by mechatronic and tribological systems. It describes technical diagnostics for structural health monitoring and performance control.

The third edition of Measurement and Data Analysis for Engineering and Science provides an up-to-date approach to presenting the methods of experimentation in science and engineering. Widely adopted by colleges and universities within the U.S. and abroad, this edition has been developed as a modular work to make it more adaptable to different approaches from various schools. This text details current methods and highlights the six fundamental tools required for implementation: planning an experiment, identifying measurement system components, assessing measurement system component performance, setting signal sampling conditions, analyzing experimental results, and reporting experimental results. What’s New in the Third Edition: This latest edition includes a new chapter order that presents a logical sequence of topics in experimentation, from the planning of an experiment to the reporting of the experimental results. It adds a new chapter on sensors and transducers that describes approximately 50 different sensors commonly used in engineering, presents uncertainty analysis in two separate chapters, and provides a problem topic summary in each chapter. New topics include smart measurement systems, focusing on the Arduino® microcontroller and its use in the wireless transmission of data, and MATLAB® and Simulink® programming for microcontrollers. Further topic additions are on the rejection of data outliers, light radiation, calibrations of sensors, comparison of first-order sensor responses, the voltage divider, determining an appropriate sample period, and planning a successful experiment. Measurement and Data Analysis for Engineering and Science also contains more than 100 solved example problems, over 400 homework problems, and provides over 75 MATLAB® Sidebars with accompanying MATLAB M-files, Arduino codes, and data files available for download.