DOCSLIB.ORG

Integrating Data Acquisition and Instrument Control with Your Scilab Scripts

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Integrating Data Acquisition and Instrument Control with Your Scilab Scripts Integrating Data Acquisition and Instrument Control with Your Scilab Scripts Darcy Dement Marketing Director National Instruments France [email protected] Who We Are 800 700 •Leaders in Computer-based Measurement and Automation 600 •Long-term track record of NI HQ growth and profitability 500 •$677M revenue in 2009 400 •More than 5,100 employees; operations in 40+ countries 300 •Fortune’s 100 Best Companies to 200 Work For 11 consecutive years •16% invested in R&D 100 0 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 2 What We Do Low-Cost Modular Productive Software Highly Integrated Hardware for Development Tools Systems Platforms Measurement and Control Used By Engineers and Scientists for Test, Design, and Control 3 The Numerical Mathematics Consortium http://www.nmconsortium.org/ 4 Discussion Topics: Connecting Math with the Physical World • Need for adding interactivity & instrumentation • A software option for interfacing with the physical world: NI LabVIEW • Using Scilab with LabVIEW • Use cases • Demo • Technical information 5 Textual Math Strengths • Scripted math • Sequential order of execution • Vector and matrix operations • Algorithm design for signal processing • Familiarity • User network and community 6 Need for Instrumentation & Interactivity • Acquire real-world data • Perform frequency • Visualize data with with hardware analysis, probability, professional user • Generate real stimuli statistics, math, curve interfaces • Control any of 1000’s of fitting, interpolation, digital • Generate reports instruments with available signal processing, etc. • Publish and control drivers • Create custom algorithms applications on the web • Connect to databases • Efficiently store data in multiple file formats 7 Need for Instrumentation & Interactivity • Acquire real-world data • Perform frequency • Visualize data with with hardware analysis, probability, professional user • Generate real stimuli statistics, math, curve interfaces • Control any of 1000’s of fitting, interpolation, digital • Generate reports instruments with available signal processing, etc. • Publish and control drivers • Create custom algorithms applications on the web • Connect to databases • Efficiently store data in multiple file formats 8 Complementing Your Scripts with Instrumentation and Presentation Mathematical Simulation Measurement and Presentation 9 Complementing Your Scripts with Instrumentation and Presentation Mathematical Simulation Measurement and Presentation 10 What is LabVIEW? Compiled Graphical Development Environment for Engineering & Science • Implement and deploy custom applications . Automated test & measurement . Graphical system design • Easily implement and deploy custom GUIs by applying an open, hybrid (graphical + textual) programming approach • Acquire / generate signals, instrumentation • Apply analysis and signal processing • Present results in an interactive graphical format locally or online 11 Integrate LabVIEW with Scilab Scripts to Add Interactivity to Simulations 12 Integrate LabVIEW with Scilab Scripts to Add Interactive Visualization to Simulations 13 LabVIEW-Scilab Script Integration Simplifies Acquisition and Analysis of Live Signals 14 ni.com/idnet: Your Source for Instrument Drivers with LabVIEW Drivers for 6000+ instruments from over 275 vendors 15 Multiple NI Data Acquisition Options, Same Software Ethernet Wi-Fi PXI USB PCI PXI Express PCI Express 16 DEMO Instrument Your Algorithms 17 How it Works: Using Scilab Scripts within LabVIEW 1. Install Scilab 4.1.1 or later, LabVIEW 8.0 or later, and the freely downloadable gateway 2. Open LabVIEW, create a new LabVIEW VI, and insert a Scilab script node on the VI block diagram 3. Enter your Scilab script in the Scilab script node 4. Right-click the Scilab script node border, select Add Input or Add Output, and enter input / output variable names 5. Connect LabVIEW wires to the new inputs and outputs When you run your application, LabVIEW invokes the Scilab engine to execute your script 19 Downloading the Free Scilab-LabVIEW Gateway scilab.org ni.com/info and enter: infoscilab 20 Conclusion & Call-to-Action • LabVIEW adds instrumentation and interactivity to bring life to your mathematical simulations • Let us know about your applications for the Scilab / LabVIEW link (forums.ni.com, or http://url.ie/6dns) • Try LabVIEW free for 30 days – download at ni.com/labview [email protected] 21.
Load more

Recommended publications
  • IADS Group Uses Multiple MATLAB Licenses
    Can We Migrate Our Analysis Routines to Python? Introduction • Can we migrate our analysis routines to Python? - MATLAB is powerful, but it’s expensive. - Capable open-source alternatives exist and are thriving. • Recent developments in scientific Python libraries have made migration from MATLAB to Python possible and attractive. • The IADS Group uses multiple MATLAB licenses. Dominance of MATLAB • MATLAB is the standard language for engineering analysis. • No need to be a programmer to solve engineering problems. • Used for collaboration and development of analysis routines. • MATLAB is required for study in an engineering curriculum - ECE 309 (CSUN), “Numerical Methods in Electrical Engineering”, is now taught using MATLAB. It was taught using Pascal in the 1980s… Dependence on MATLAB • IADS uses MATLAB to prototype new analysis routines. • IADS uses MATLAB to test and maintain data export and import. We need MATLAB! • IADS uses a set of MATLAB scripts to test Autospectrum and PSD results for Every Release. • IADS is dependent upon MATLAB. Problems with Dependency • Budget constraints mean fewer licenses and toolboxes are available. • MATLAB version changes force retest What happens of data interfaces. if they take MATLAB away • Retest requires an active license. from us? • Test Scripts are unusable without a license. • Having no backup plan in place is risky. Requirements for a Replacement • Should have broad industry acceptance. • Should have scientific libraries that mimic functionality that is commonly used in MATLAB by the flight test community. • Should have similar syntax. • Total MATLAB functionality is not necessary for our purposes, but it would be nice for going forward. • Should be relatively free of periodic licensing hassles.
    [Show full text]
  • A Comparative Evaluation of Matlab, Octave, R, and Julia on Maya 1 Introduction
    A Comparative Evaluation of Matlab, Octave, R, and Julia on Maya Sai K. Popuri and Matthias K. Gobbert* Department of Mathematics and Statistics, University of Maryland, Baltimore County *Corresponding author: [email protected], www.umbc.edu/~gobbert Technical Report HPCF{2017{3, hpcf.umbc.edu > Publications Abstract Matlab is the most popular commercial package for numerical computations in mathematics, statistics, the sciences, engineering, and other fields. Octave is a freely available software used for numerical computing. R is a popular open source freely available software often used for statistical analysis and computing. Julia is a recent open source freely available high-level programming language with a sophisticated com- piler for high-performance numerical and statistical computing. They are all available to download on the Linux, Windows, and Mac OS X operating systems. We investigate whether the three freely available software are viable alternatives to Matlab for uses in research and teaching. We compare the results on part of the equipment of the cluster maya in the UMBC High Performance Computing Facility. The equipment has 72 nodes, each with two Intel E5-2650v2 Ivy Bridge (2.6 GHz, 20 MB cache) proces- sors with 8 cores per CPU, for a total of 16 cores per node. All nodes have 64 GB of main memory and are connected by a quad-data rate InfiniBand interconnect. The tests focused on usability lead us to conclude that Octave is the most compatible with Matlab, since it uses the same syntax and has the native capability of running m-files. R was hampered by somewhat different syntax or function names and some missing functions.
    [Show full text]
  • Julia, My New Friend for Computing and Optimization? Pierre Haessig, Lilian Besson
    Julia, my new friend for computing and optimization? Pierre Haessig, Lilian Besson To cite this version: Pierre Haessig, Lilian Besson. Julia, my new friend for computing and optimization?. Master. France. 2018. cel-01830248 HAL Id: cel-01830248 https://hal.archives-ouvertes.fr/cel-01830248 Submitted on 4 Jul 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. « Julia, my new computing friend? » | 14 June 2018, IETR@Vannes | By: L. Besson & P. Haessig 1 « Julia, my New frieNd for computiNg aNd optimizatioN? » Intro to the Julia programming language, for MATLAB users Date: 14th of June 2018 Who: Lilian Besson & Pierre Haessig (SCEE & AUT team @ IETR / CentraleSupélec campus Rennes) « Julia, my new computing friend? » | 14 June 2018, IETR@Vannes | By: L. Besson & P. Haessig 2 AgeNda for today [30 miN] 1. What is Julia? [5 miN] 2. ComparisoN with MATLAB [5 miN] 3. Two examples of problems solved Julia [5 miN] 4. LoNger ex. oN optimizatioN with JuMP [13miN] 5. LiNks for more iNformatioN ? [2 miN] « Julia, my new computing friend? » | 14 June 2018, IETR@Vannes | By: L. Besson & P. Haessig 3 1. What is Julia ? Open-source and free programming language (MIT license) Developed since 2012 (creators: MIT researchers) Growing popularity worldwide, in research, data science, finance etc… Multi-platform: Windows, Mac OS X, GNU/Linux..
    [Show full text]
  • Delivering a Professional ®
    Delivering a professional ® We stand on the shoulders of giants (2015) Custodians of OpenFOAM® (2016) … www.esi-group.com 1 Copyright © ESICopyright Group, 2017. © ESI All Group, rights reserved.2017. All rights reserved. OpenFOAM – foreword Greetings from, and thanks to the Team • OpenCFD Core Development‣ Karen Kettle and Supporting Teams ‣ Takashi Minabe (Japan) ‣ Andrew Heather ‣ Mohsen Battoei (North America) ‣ Mattijs Janssens ‣ Ravi Ajjampudi (India) ‣ Sergio Ferraris ‣ Bjorn Landmann, Sebastien Vilfayeau (Germany) ‣ Mark Olesen ‣ Matej Forman (Training Coordinator) ‣ Prashant Sonakar ‣ Roger Almenar ‣ Pawan Ghildiyal ‣ Fred Mendonca OpenFOAM Operation www.esi-group.com 2 Copyright © ESI Group, 2017. All rights reserved. OpenCFD – Commitment to OpenFOAM Users Development and Release Schedule • OpenCFD owns the trademark • Releasing OpenFOAM since 2004 • Professional Six-monthly Development and Release cycle, including ‣ New developments ‣ Consolidated bug-fixes ‣ Overhaulled testing procedure for Quality Assurance ‣ Release and Development repositories in GitLab https://develop.openfoam.com ‣ Master branch ‣ Develop branch (includes > Master > Release ‣ Community Repositories > Develop www.esi-group.com 3 Copyright © ESI Group, 2017. All rights reserved. OpenCFD – Commitment to OpenFOAM Users Development and Release Schedule • OpenFOAM.com releases so far • OpenFOAM-v3.0+ on Jan 13th 2016 • OpenFOAM-v1606+ on June 30th 2016 • OpenFOAM-v1612+ on 23rd December 2016 • OpenFOAM-v1706 on 30th June 2017 www.esi-group.com 4 Copyright
    [Show full text]
  • Ordinary Differential Equations (ODE) Using Euler's Technique And
    Mathematical Models and Methods in Modern Science Ordinary Differential Equations (ODE) using Euler’s Technique and SCILAB Programming ZULZAMRI SALLEH Applied Sciences and Advance Technology Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology Bandar Teknologi Maritim Jalan Pantai Remis 32200 Lumut, Perak MALAYSIA [email protected] http://www.mimet.edu.my Abstract: - Mathematics is very important for the engineering and scientist but to make understand the mathematics is very difficult if without proper tools and suitable measurement. A numerical method is one of the algorithms which involved with computer programming. In this paper, Scilab is used to carter the problems related the mathematical models such as Matrices, operation with ODE’s and solving the Integration. It remains true that solutions of the vast majority of first order initial value problems cannot be found by analytical means. Therefore, it is important to be able to approach the problem in other ways. Today there are numerous methods that produce numerical approximations to solutions of differential equations. Here, we introduce the oldest and simplest such method, originated by Euler about 1768. It is called the tangent line method or the Euler method. It uses a fixed step size h and generates the approximate solution. The purpose of this paper is to show the details of implementing of Euler’s method and made comparison between modify Euler’s and exact value by integration solution, as well as solve the ODE’s use built-in functions available in Scilab programming. Key-Words: - Numerical Methods, Scilab programming, Euler methods, Ordinary Differential Equation. 1 Introduction availability of digital computers has led to a Numerical methods are techniques by which veritable explosion in the use and development of mathematical problems are formulated so that they numerical methods [1].
    [Show full text]
  • Key Benefits Key Features
    With the MapleSim LabVIEW®/VeriStand™ Connector, you can • Includes a set of Maple language commands, which extend your LabVIEW and VeriStand applications by integrating provides programmatic access to all functionality as an MapleSim’s high-performance, multi-domain environment alternative to the interactive interface and supports into your existing toolchain. The MapleSim LabVIEW/ custom application development. VeriStand Connector accelerates any project that requires • Supports both the External Model Interface (EMI) and high-fidelity engineering models for hardware-in-the-loop the Simulation Interface Toolkit (SIT). applications, such as component testing and electronic • Allows generated block code to be viewed and modified. controller development and integration. • Automatically generates an HTML help page for each block for easy lookup of definitions and parameter Key Benefits defaults. • Complex engineering system models can be developed and optimized rapidly in the intuitive visual modeling environment of MapleSim. • The high-performance, high-fidelity MapleSim models are automatically converted to user-code blocks for easy inclusion in your LabVIEW VIs and VeriStand Applications. • The model code is fully optimized for high-speed real- time simulation, allowing you to get the performance you need for hardware-in-the-loop (HIL) testing without sacrificing fidelity. Key Features • Exports MapleSim models to LabVIEW and VeriStand, including rotational, translational, and multibody mechanical systems, thermal models, and electric circuits. • Creates ANSI C code blocks for fast execution within LabVIEW, VeriStand, and the corresponding real-time platforms. • Code blocks are created from the symbolically simplified system equations produced by MapleSim, resulting in compact, highly efficient models. • The resulting code is further optimized using the powerful optimization tools in Maple, ensuring fast execution.
    [Show full text]
  • Running Sagemath (With Or Without Installation)
    Running SageMath (with or without installation) http://www.sagemath.org/ Éric Gourgoulhon Running SageMath 9 Feb. 2017 1 / 5 Various ways to install/access SageMath 7.5.1 Install on your computer: 2 options: install a compiled binary version for Linux, MacOS X or Windows1 from http://www.sagemath.org/download.html compile from source (Linux, MacOS X): check the prerequisites (see here for Ubuntu) and run git clone git://github.com/sagemath/sage.git cd sage MAKE=’make -j8’ make Run on your computer without installation: Sage Debian Live http://sagedebianlive.metelu.net/ Bootable USB flash drive with SageMath (boosted with octave, scilab), Geogebra, LaTeX, gimp, vlc, LibreOffice,... Open a (free) account on SageMathCloud https://cloud.sagemath.com/ Run in SageMathCell Single cell mode: http://sagecell.sagemath.org/ 1requires VirtualBox; alternatively, a full Windows installer is in pre-release stage at https://github.com/embray/sage-windows/releases Éric Gourgoulhon Running SageMath 9 Feb. 2017 2 / 5 Example 1: installing on Ubuntu 16.04 1 Download the archive sage-7.5.1-Ubuntu_16.04-x86_64.tar.bz2 from one the mirrors listed at http://www.sagemath.org/download-linux.html 2 Run the following commands in a terminal: bunzip2 sage-7.5.1-Ubuntu_16.04-x86_64.tar.bz2 tar xvf sage-7.5.1-Ubuntu_16.04-x86_64.tar cd SageMath ./sage -n jupyter A Jupyter home page should then open in your browser. Click on New and select SageMath 7.5.1 to open a Jupyter notebook with a SageMath kernel. Éric Gourgoulhon Running SageMath 9 Feb. 2017 3 / 5 Example 2: using the SageMathCloud 1 Open a free account on https://cloud.sagemath.com/ 2 Create a new project 3 In the second top menu, click on New to create a new file 4 Select Jupyter Notebook for the file type 5 In the Jupyter menu, click on Kernel, then Change kernel and choose SageMath 7.5 Éric Gourgoulhon Running SageMath 9 Feb.
    [Show full text]
  • Towards a Fully Automated Extraction and Interpretation of Tabular Data Using Machine Learning
    UPTEC F 19050 Examensarbete 30 hp August 2019 Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Per Hedbrant Master Thesis in Engineering Physics Department of Engineering Sciences Uppsala University Sweden Abstract Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Teknisk- naturvetenskaplig fakultet UTH-enheten Motivation A challenge for researchers at CBCS is the ability to efficiently manage the Besöksadress: different data formats that frequently are changed. Significant amount of time is Ångströmlaboratoriet Lägerhyddsvägen 1 spent on manual pre-processing, converting from one format to another. There are Hus 4, Plan 0 currently no solutions that uses pattern recognition to locate and automatically recognise data structures in a spreadsheet. Postadress: Box 536 751 21 Uppsala Problem Definition The desired solution is to build a self-learning Software as-a-Service (SaaS) for Telefon: automated recognition and loading of data stored in arbitrary formats. The aim of 018 – 471 30 03 this study is three-folded: A) Investigate if unsupervised machine learning Telefax: methods can be used to label different types of cells in spreadsheets. B) 018 – 471 30 00 Investigate if a hypothesis-generating algorithm can be used to label different types of cells in spreadsheets. C) Advise on choices of architecture and Hemsida: technologies for the SaaS solution. http://www.teknat.uu.se/student Method A pre-processing framework is built that can read and pre-process any type of spreadsheet into a feature matrix. Different datasets are read and clustered. An investigation on the usefulness of reducing the dimensionality is also done.
    [Show full text]
  • Introduction to Scilab
    www.scilab.org INTRODUCTION TO SCILAB Consortium sCilab Domaine de Voluceau - Rocquencourt - B.P. 105 - 78153 Le Chesnay Cedex France This document has been written by Michaël Baudin from the Scilab Consortium. © November 2010 The Scilab Consortium - Digiteo. All rights reserved. November 2010 Abstract In this document, we make an overview of Scilab features so that we can get familiar with this environment. The goal is to present the core of skills necessary to start with Scilab. In the first part, we present how to get and install this software on our computer. We also present how to get some help with the provided in-line documentation and also thanks to web resources and forums. In the remaining sections, we present the Scilab language, especially its structured programming features. We present an important feature of Scilab, that is the management of real matrices and overview the linear algebra library. The definition of functions and the elementary management of input and output variables is presented. We present Scilab's graphical features and show how to create a 2D plot, how to configure the title and the legend and how to export that plot into a vectorial or bitmap format. Contents 1 Overview5 1.1 Introduction................................5 1.2 Overview of Scilab............................5 1.3 How to get and install Scilab.......................6 1.3.1 Installing Scilab under Windows.................7 1.3.2 Installing Scilab under Linux..................7 1.3.3 Installing Scilab under Mac OS.................8 1.4 How to get help..............................8 1.5 Mailing lists, wiki and bug reports....................9 1.6 Getting help from Scilab demonstrations and macros........
    [Show full text]
  • Scilab for Very Beginners
    Scilab for very beginners Scilab Enterprises S.A.S - 143 bis rue Yves Le Coz - 78000 Versailles (France) - www.scilab-enterprises.com This document has been co-written by Scilab Enterprises and Christine Gomez, mathematics teacher at Lycée Descartes (Descartes HiGh School) in Antony, Hauts-de-Seine (France). © 2013 Scilab Enterprises. All riGhts reserved. Scilab for very beGinners - 2/33 Table of content Introduction About this document 4 Install Scilab 4 MailinG list 4 Complementary resources 4 Chapter 1 – Become familiar with Scilab The General environment and the console 5 Simple numerical calculations 6 The menu bar 7 The editor 8 The Graphics window 9 Windows manaGement and workspace customization 11 Chapter 2 - Programming Variables, assignment and display 12 Loops 16 Tests 17 2 and 3D plots 18 Supplements on matrices and vectors 23 Calculation accuracy 29 SolvinG differential equations 30 Chapter 3 – Useful Scilab functions In analysis 32 In probability and statistics 32 To display and plot 33 Utilities 33 Scilab for very beGinners - 3/33 Introduction About this document The purpose of this document is to Guide you step by step in explorinG the various basic features of Scilab for a user who has never used numerical computation software. This presentation is voluntarily limited to the essential to allow easier handling of Scilab. Computations, Graphs and illustrations are made with Scilab 5.4.0. You can reproduce all those commands from this version. Install Scilab Scilab is numerical computation software that anybody can freely download. Available under Windows, Linux and Mac OS X, Scilab can be downloaded at the followinG address: http://www.scilab.orG/ You can be notified of new releases of Scilab software by subscribinG to our channel notification at the following address: http://lists.scilab.orG/mailman/listinfo/release Mailing list To facilitate the exchanGe between Scilab users, dedicated mailinG lists exist (list in French, list for the education world, international list in English).
    [Show full text]
  • Some Effective Methods for Teaching Mathematics Courses in Technological Universities
    International Journal of Education and Information Studies. ISSN 2277-3169 Volume 6, Number 1 (2016), pp. 11-18 © Research India Publications http://www.ripublication.com Some Effective Methods for Teaching Mathematics Courses in Technological Universities Dr. D. S. Sankar Professor, School of Applied Sciences and Mathematics, Universiti Teknologi Brunei, Jalan Tungku Link, BE1410, Brunei Darussalam E-mail: [email protected] Dr. Rama Rao Karri Principal Lecturer, Petroleum and Chemical Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei, Jalan Tungku Link, Gadong BE1410, Brunei Darussalam E-mail: [email protected] Abstract This article discusses some effective and useful methods for teaching various mathematics topics to the students of undergraduate and post-graduate degree programmes in technological universities. These teaching methods not only equip the students to acquire knowledge and skills for solving real world problems efficiently, but also these methods enhance the teacher’s ability to demonstrate the mathematical concepts effectively along with suitable physical examples. The exposure to mathematical softwares like MATLAB, SCILAB, MATHEMATICA, etc not only increases the students confidential level to solve variety of typical problems which they come across in their respective disciplines of study, but also it enables them to visualize the surfaces of the functions of several variable. Peer learning, seminar based learning and project based learning are other methods of learning environment to the students which makes the students to learn mathematics by themselves. These are higher level learning methods which enhances the students understanding on the mathematical concepts and it enables them to take up research projects. It is noted that the teaching and learning of mathematics with the support of mathematical softwares is believed to be more effective when compared to the effects of other methods of teaching and learning of mathematics.
    [Show full text]
  • Compiling Maplesim C Code for Simulation in Vissim
    Compiling MapleSim C Code for Simulation in VisSim 1 Introduction MapleSim generates ANSI C code from any model. The code contains the differential equations that describe the model dynamics, and a solver. Moreover, the code is royalty-free, and can be used in any simulation tool (or development project) that accepts external code. VisSim is a signal-flow simulation tool with strength in embedded systems programming, real-time data acquisition and OPC. This document will describe the steps required to • Generate C code from a MapleSim model of a DC Motor. The C code will contain a solver. • Implement the C code in a simulation DLL for VisSim. VisSim provides a DLL Wizard that sets up a Visual Studio C project for a simulation DLL. MapleSim code will be copied into this project. After a few modifications, the project will be compiled to a DLL. The DLL can then be used as a block in a VisSim simulation. The techniques demonstrated in this document can used to implement MapleSim code in any other environment. MapleSim’s royalty -free C code can be implemented in other modeling environment s, such as VisSim MapleSim’s C code can also be used in Mathcad 2 API for the Maplesim Code The C code generated by MapleSim contains four significant functions. • SolverSetup(t0, *ic, *u, *p, *y, h, *S) • SolverStep(*u, *S) where SolverStep is EulerStep, RK2Step, RK3Step or RK4Step • SolverUpdate(*u, *p, first, internal, *S) • SolverOutputs(*y, *S) u are the inputs, p are subsystem parameters (i.e. variables defined in a subsystem mask), ic are the initial conditions, y are the outputs, t0 is the initial time, and h is the time step.
    [Show full text]