Real time plasma disruptions detection in JET implemented with the ITMS platform using FPGA based IDAQ

The use of FPGAs in data acquisition cards for processing purposes allows an efficient real time pattern recognition algorithm implementation. Using 13 JETs database waveforms an algorithm for detecting incoming plasma disruptions has been implemented. This algorithm is written in MATLAB using floating point representation. In this work we show the methodology used to implement the real time version of the algorithm using Intelligent Data Acquisition Cards (IDAQ), DAQ devices with field programmable gate array (FPGA) for local processing. This methodology is based on the translation of the MATLAB code to LabVIEW and the final coding of specific pieces of code in LabVIEW for FPGA in fixed point format. The whole system for evaluating the real time disruption detection (RTDD) has been implemented using the Intelligent Test and Measurement System (ITMS) platform. ITMS offers distributed data acquisition, distribution and real time processing capabilities with advanced, but easy to use, software tools that simplify application development and system setup. The RTDD implementation uses a standard PXI/PXIe architecture. Two 8 channel analog output cards play JETs database signals, two 8 channel DAQ with FPGA acquire signals and computes a feature vector based in FFT analysis. Finally the vector acquired is used by the system CPU to execute a pattern recognition algorithm to estimate an incoming disruption

Expert system decision support for low-cost launch vehicle operations

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation

Database Performance Tuning Methods for Manufacturing Execution System

In manufacturing industry where data are produced and shared every day, data volumes could be large enough for the database performance to become an issue. Manufacturing Execution System (MES) is such a system that cannot tolerate with poor database performance as the system relies heavily on real-time reporting that requires instance query responses. Manufacturing products’ quality and production targets can be affected as the result of delayed queries. Therefore, the need to maintain the acceptable level of database performance in this domain is crucial. One task in maintaining database performance is identification and diagnosis of the root causes that may cause delayed queries. Poor query design has been identified as one major cause of delayed queries that affect real-time reporting. Nevertheless, as various methods available to deal with poor query design, it is important for a database administrator to decide the method or combination of methods that work best. In this paper, we present a case study on the methods used by a real manufacturing industry company called as Silterra and the methods proposed in the literature that deal with poor query design. For each method, we elicit its strength and weaknesses and analyse the practical implementation of it

A real-time distributed analysis automation for hurricane surface wind observations

From 1993 until 1999, the Hurricane Research Division of the National Oceanic and Atmospheric Administration (NOAA) produced real-time analyses of surface wind observations to help determine a storm\u27s wind intensity and extent. Limitations of the real-time analysis system included platform and filesystem dependency, lacking data integrity and feasibility for Internet deployment. In 2000, a new system was developed, built upon a Java prototype of a quality control graphical client interface for wind observations and an object-relational database. The objective was to integrate them in a distributed object approach with the legacy code responsible for the actual real-time wind analysis and image product generation. Common Object Request Broker Architecture (CORBA) was evaluated, but Java Remote Method Invocation (AMI) offered important advantages in terms of reuse and deployment. Even more substantial, though, were the efforts towards object-oriented redesign, implementation and testing of the quality control interface and its database performance interaction. As a result, a full-featured application can now be launched from the Web, potentially accessible by tropical cyclone forecast and warning centers worldwide

NEAR REAL-TIME EXERCISE MACHINE POWER STATISTICS REPORTING

Cal Poly’s Recreation Center expansion project provides an opportunity to implement Energy Harvesting From Exercise Machines (EHFEM). Part of this implementation is a system that reports the exercise machines’ energy production. Although products capable of reporting exercise machine energy harvesting statistics exist, they have limited capabilities. This thesis project defends a system capable of reporting exercise machine power statistics in near real-time. The system consists of display, database, and power measurement modules. The display module presents statistics in an interactive, graphical, and widely-accessible way. The database module provides an efficient way of organizing and accessing stored statistics. Multiple power measurement module types gather power and energy generation measurements from multiple exercise machine types and transmit those measurements to the database module over the computer network

The Power of Point of Sale Improving Growth, Profit, and Customer Service in a Retail Business

For many small businesses, creating a captivating retail experience is the key to success, and finding the right technologies to enable that experience is crucial for sustaining a competitive advantage. This project is a case study designed to evaluate and select a Point of Sale (POS) system and Inventory Management (IM) system for a small business based upon its specific industry needs. The project creates a three step framework leading up to the real world implementation of these systems and uses the Rhode Island based company - Wildwood Inc. - as the subject of the study. Wildwood Inc. is a garden center and nursery that uses manual processes for both its checkout and inventory management practices, but due to its growth is experiencing difficulties in serving its customers effectively. The project looks at specific challenges facing Wildwood and creates a roadmap for POS and IM implementation that can be generalized for businesses looking to upgrade their systems. The framework for the implementation includes (1) initial research and current process analysis, (2) new system evaluation and process comparison, and (3) a final recommendation for management. The project explores the necessary capabilities of POS and IM systems within the retail agriculture industry; creates a comparison matrix of potential product offerings based upon hardware components, software features, technical support, and price points; and develops a final recommendation for Wildwood considering its specific needs. Upon completion, Wildwood will have the information necessary to purchase a computerized system that can: (1) Maintain a database of all inventory, including plant characteristics, units in stock, price, supplier, and SKU number, (2) facilitate a more efficient checkout method that eliminates handwritten receipts of purchases and digitally records all sales within the system, expedites the checkout process for both customers and employees, and 4 communicates with the IM system to allow for real-time inventory updates upon completion of POS transactions, and (3) runs a variety of reports on the collected data so that management has greater accuracy and success when making business decisions

A Probabilistic Approach to the Drag-Based Model

The forecast of the time of arrival of a coronal mass ejection (CME) to Earth is of critical importance for our high-technology society and for any future manned exploration of the Solar System. As critical as the forecast accuracy is the knowledge of its precision, i.e. the error associated to the estimate. We propose a statistical approach for the computation of the time of arrival using the drag-based model by introducing the probability distributions, rather than exact values, as input parameters, thus allowing the evaluation of the uncertainty on the forecast. We test this approach using a set of CMEs whose transit times are known, and obtain extremely promising results: the average value of the absolute differences between measure and forecast is 9.1h, and half of these residuals are within the estimated errors. These results suggest that this approach deserves further investigation. We are working to realize a real-time implementation which ingests the outputs of automated CME tracking algorithms as inputs to create a database of events useful for a further validation of the approach.Comment: 18 pages, 4 figure

Development of Inventory Management System in a Total Productive Maintenance Environment

Implementation of Total Productive Maintenance (TPM) is increasingly being seen as a suitable initiative or technique for effectively involving the workforce in manufacturing based organizations to increase productivity with the support of both effective and efficient maintenance works as well as inventory management system. The aim of this research is concerned with the development of a computerize inventory management system using Microsoft Visual Basic 6.0. This improvement is to replace present manual paperwork procedure towards the implementation of TPM and IS014000. The proposed system attempts to achieve this by providing a database for parts information storage with search function, ability to record each inventory transactions in real time, calculating material requirement planning (MRP), create Bill Of Materials (BOM) and making purchase order (PO). This research also includes the evaluation of the system on real data from the company. The data shows that this system produced correct result and reduce the time spend on data searching by 80.4% or increase the manpower efficiency by 510%. These results show that this system can lead to increase the controllability and monitoring of inventory, and increase manpower efficiency