Create more robust, more flexible LabVIEW applications--through software design principles! Writing LabVIEW software to perform a complex task is never easy--especially when those last-minute feature requests cause a complexity explosion in your system, forcing you to rework much of your code! Jon Conway and Steve Watts offer a better solution: LCOD-LabVIEW Component Oriented Design--which, for the first time, applies the theories and principles of software design to LabVIEW programming. The material is presented in a lighthearted, engaging manner that makes learning enjoyable, even if you're not a computer scientist. LCOD software engineering techniques make your software more robust and better able to handle complexity--by making it simpler! Even large, industrial-grade applications become manageable. Design to embrace flexibility first, making changes and bug fixes much less painful Pragmatic discussion of the authors' tried and tested techniques, written by--and for--working programmers Covers design principles; LCOD overview, implementation, and complementary techniques; engineering essentials; style issues; and more Complete with practical advice on requirements gathering, prototyping, user interface design, and rich with examples Work through an example LCOD project (all code included on companion Web site) to tie the lessons together This book is intended for test engineers, system integrators, electronics engineers, software engineers, and other intermediate to advanced LabVIEW programmers. None of the methods discussed are complex, so users can benefit as soon as they are proficient with the syntax of LabVIEW.Go to the companion Web site located at http: //author.phptr.com/watts/ for full source code and book updates.
Dieses Handbuch gibt eine geschlossene Darstellung in die Programmierung mit LabVIEW, beginnend mit einer grundlegenden Einführung bis hin zur Behandlung von Software-Konzepten, die auch die Realisierung umfangreicherer Software-Projekte ermöglichen. Es behandelt drei Themenbereiche. I Grundlagen der Software-Entwicklung II ausführliche Einführung in die Entwicklungsumgebung LabVIEW und die Programmerstellung. III Strukturen und Datentypen. Programmierkenntnisse bzw. Vorkenntnisse sind nicht erforderlich.
LabVIEWTM has become one of the preeminent platforms for the development of data acquisition and data analysis programs. LabVIEWTM: A Developer’s Guide to Real World Integration explains how to integrate LabVIEW into real-life applications. Written by experienced LabVIEW developers and engineers, the book describes how LabVIEW has been pivotal in solving real-world challenges. Each chapter is self-contained and demonstrates the power and simplicity of LabVIEW in various applications, from image processing to solar tracking systems. Many of the chapters explore how exciting new technologies can be implemented in LabVIEW to enable novel solutions to new or existing problems. The text also presents novel tricks and tips for integrating LabVIEW with third-party hardware and software. Ideal for LabVIEW users who develop stand-alone applications, this down-to-earth guide shows how LabVIEW provides solutions to a variety of application problems. It includes projects and virtual instrumentation for most of the programs and utilities described. Many of the authors’ own software contributions are available on the accompanying CD-ROM.
This book brings together everything you need to achieve superior results with PC-based image processing and analysis. Thomas Klinger combines a highly accessible overview of the field's key concepts, tools, and techniques; the first expert introduction to NI's breakthrough IMAQ Vision software; and several start-to-finish application case studies. You also get an extensive library of code and image samples, as well as a complete trial version of IMAQ Vision for Windows.
This book provides a practical and accessible understanding of the fundamental principles of virtual instrumentation. It explains how to acquire, analyze and present data using LabVIEW (Laboratory Virtual Instrument Engineering Workbench) as the application development environment. The book introduces the students to the graphical system design model and its different phases of functionality such as design, prototyping and deployment. It explains the basic concepts of graphical programming and highlights the features and techniques used in LabVIEW to create Virtual Instruments (VIs). Using the technique of modular programming, the book teaches how to make a VI as a subVI. Arrays, clusters, structures and strings in LabVIEW are covered in detail. The book also includes coverage of emerging graphical system design technologies for real-world applications. In addition, extensive discussions on data acquisition, image acquisition, motion control and LabVIEW tools are presented. This book is designed for undergraduate and postgraduate students of instrumentation and control engineering, electronics and instrumentation engineering, electrical and electronics engineering, electronics and communication engineering, and computer science and engineering. It will be also useful to engineering students of other disciplines where courses in virtual instrumentation are offered. Key Features : Builds the concept of virtual instrumentation by using clear-cut programming elements. Includes a summary that outlines important learning points and skills taught in the chapter. Offers a number of solved problems to help students gain hands-on experience of problem solving. Provides several chapter-end questions and problems to assist students in reinforcing their knowledge.
For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.
Arduino boards have impressed both hackers and professional engineers. Whether you're a hobbyist or a professional, it isn't just a breadboard and a hazy idea that keeps you going. It's essential to institute a proper design, device instrumentation and, indeed, test your project thoroughly before committing to a particular prototype. Practical Arduino Engineering begins by outlining the engineering process, from the basic requirements and preliminary design to prototyping and testing. Each and every chapter exemplifies this process and demonstrates how you can profit from the implementation solid engineering principles—regardless of whether you just play in your basement or you want to publicize and sell your devices. Arduino is a brilliant prototyping platform that allows users to test and iterate design ideas. Imitation by other Arduino makers, hackers and engineers often proves your design's popularity. Practical Arduino Engineering will teach you to follow the engineering process carefully; over time, you will be able to review and improve this process, and even extend its scope. Practical Arduino Engineering is not purely theoretical. In addition, you'll learn the process of hardware engineering as applicable to Arduino projects, and the importance of the process in each and every project presented in this book. To set the stage, Practical Arduino Engineering begins by reviewing the Arduino software landscape, then shows how to set up an Arduino project for testing. Even if you already know your compiler toolchain and the basics of Arduino programming, this refresher course can help fill in the gaps and explain why your compiler may spit out certain error messages. Practical Arduino Engineering then gradually builds up the engineering process, from single devices like LCDs, potentiometers and GPS modules, to the integration of several modules into larger projects, such as a wireless temperature measurement system, and ultimately an entire robot. The engineering projects become progressively more challenging throughout the first 4 engineering chapters. Next, you'll proceed with simple steps towards the first intelligent part of a robot: the object detector. You'll find yourself teaching your robot how to avoid very hot objects or insurmountable obstacles. The basic design requirements for a complete robot and, indeed, the detailed design and prototyping for robots can be extremely tricky, which is why engineering discipline is invaluable. Practical Arduino Engineering then enters the world of domestic engineering by introducing home alarm systems—not quite as simple as they seem. A solid, robust system can only be built by following the engineering process detailed in previous chapters, and this section reinforces that process. You'll then take a step further in your Arduino engineering process: instrumentation and control, and some error messaging using GSM. Control is introduced via the Xbox controller, a very powerful piece of technology able to play a considerable role in robotics projects. Having already learned to control motion and to sense and avoid objects, you'll learn how to debug your Arduino projects of varying complexities via the hardware instrumentation software LabVIEW. To complete the journey into Practical Arduino Engineering, you'll discover how to use a special Arduino board to rely on Bluetooth Mate Silver for control of domestic and mobile Arduino projects. Using Bluetooth Mate Silver, you'll learn to implement basic engineering design with almost any Arduino project, and be able to justify, build, debug, and extend Arduino-based designs using a solid engineering approach. Please note: the print version of this title is black & white; the eBook is full color.
Transform physical phenomena into computer-acceptable data using a truly object-oriented language About This Book Create your own data acquisition system independently using LabVIEW and build interactive dashboards Collect data using National Instrument's and third-party, open source, affordable hardware Step-by-step real-world examples using various tools that illustrate the fundamentals of data acquisition Who This Book Is For If you are an engineer, scientist, experienced hobbyist, or student, you will highly benefit from the content and examples illustrated in this book. A working knowledge of precision testing, measurement instruments, and electronics, as well as a background in computer fundamentals and programming is expected. What You Will Learn Create a virtual instrument which highlights common functionality of LabVIEW Get familiarized with common buses such as Serial, GPIB, and SCPI commands Staircase signal acquisition using NI-DAQmx Discover how to measure light intensity and distance Master LabVIEW debugging techniques Build a data acquisition application complete with an installer and required drivers Utilize open source microcontroller Arduino and a 32-bit Arduino compatible Uno32 using LabVIEW programming environment In Detail NI LabVIEW's intuitive graphical interface eliminates the steep learning curve associated with text-based languages such as C or C++. LabVIEW is a proven and powerful integrated development environment to interact with measurement and control hardware, analyze data, publish results, and distribute systems. This hands-on tutorial guide helps you harness the power of LabVIEW for data acquisition. This book begins with a quick introduction to LabVIEW, running through the fundamentals of communication and data collection. Then get to grips with the auto-code generation feature of LabVIEW using its GUI interface. You will learn how to use NI-DAQmax Data acquisition VIs, showing how LabVIEW can be used to appropriate a true physical phenomenon (such as temperature, light, and so on) and convert it to an appropriate data type that can be manipulated and analyzed with a computer. You will also learn how to create Distribution Kit for LabVIEW, acquainting yourself with various debugging techniques offered by LabVIEW to help you in situations where bugs are not letting you run your programs as intended. By the end of the book, you will have a clear idea how to build your own data acquisition system independently and much more. Style and approach A hands-on practical guide that starts by laying down the software and hardware foundations necessary for subsequent data acquisition-intensive chapters. The book is packed full of specific examples with software screenshots and schematic diagrams to guide you through the creation of each virtual instrument.
The 35 papers in this volume were presented at the Industrial and Environmental Monitors and Biosensors Symposium, January 1999. They are divided into nine sessions addressing subjects such as: sensors for energy industry; sensors for engine industry; and sensors for materials evaluation.
21-22 June, 2004, Glasgow, Scotland, United Kingdom
Author: Hilton Lewis,Gianni Raffi
Publisher: Society of Photo Optical
Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
This guide describes how to implement modern GUI (Graphic'ser Interface) methodologies within the LabVIEW application. The book provides interface design strategies and basic graphic design principles, and includes over 100 step-by-step LabVIEW GUI Code examples.
Digital Signal Processing System Design combines textual and graphical programming to form a hybrid programming approach, enabling a more effective means of building and analyzing DSP systems. The hybrid programming approach allows the use of previously developed textual programming solutions to be integrated into LabVIEW’s highly interactive and visual environment, providing an easier and quicker method for building DSP systems. This book is an ideal introduction for engineers and students seeking to develop DSP systems in quick time. Features: The only DSP laboratory book that combines textual and graphical programming 12 lab experiments that incorporate C/MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature Lab experiments covering basic DSP implementation topics including sampling, digital filtering, fixed-point data representation, frequency domain processing Interesting applications using the hybrid programming approach, such as a software-defined radio system, a 4-QAM Modem, and a cochlear implant simulator The only DSP project book that combines textual and graphical programming 12 Lab projects that incorporate MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature Interesting applications such as the design of a cochlear implant simulator and a software-defined radio system
Sloshing causes liquid to fluctuate, making accurate level readings difficult to obtain in dynamic environments. The measurement system described uses a single-tube capacitive sensor to obtain an instantaneous level reading of the fluid surface, thereby accurately determining the fluid quantity in the presence of slosh. A neural network based classification technique has been applied to predict the actual quantity of the fluid contained in a tank under sloshing conditions. In A neural network approach to fluid quantity measurement in dynamic environments, effects of temperature variations and contamination on the capacitive sensor are discussed, and the authors propose that these effects can also be eliminated with the proposed neural network based classification system. To examine the performance of the classification system, many field trials were carried out on a running vehicle at various tank volume levels that range from 5 L to 50 L. The effectiveness of signal enhancement on the neural network based signal classification system is also investigated. Results obtained from the investigation are compared with traditionally used statistical averaging methods, and proves that the neural network based measurement system can produce highly accurate fluid quantity measurements in a dynamic environment. Although in this case a capacitive sensor was used to demonstrate measurement system this methodology is valid for all types of electronic sensors. The approach demonstrated in A neural network approach to fluid quantity measurement in dynamic environments can be applied to a wide range of fluid quantity measurement applications in the automotive, naval and aviation industries to produce accurate fluid level readings. Students, lecturers, and experts will find the description of current research about accurate fluid level measurement in dynamic environments using neural network approach useful.