LabVIEW Platform Research Articles

Digital Platform for Distance and On-site Engineering Learning

This paper considers the experience of elaborating and implementing an on-site and distance practical study of electronics and circuit Engineering in the educational process. Authors provide possibilities of using both distance and on-site laboratory practical works. The paper includes recommendations for choosing hardware-based solutions. It also shows the implemented version of remote user access to individual data of laboratory research, which provides individualization of obtaining experiment data, when using FTP means of data transfer. Data from a remote experiment, in this case, is completely closed from access by third parties, while the teacher is given access to data from experimental studies of all students. The solution was implemented in the LabVIEW platform, as well as the general solution for implementing software access to a remote bench. The paper describes the main elements of the hardware and software system, shows its structure and presents the work examples. It also notes the integration of the LabVIEW software and the Multisim circuit and system simulating platform, which serves to improve the quality of specialists training during distance and on-site practical works. The authors consider several options for conducting distance and on-site laboratory practical works when preparing laboratory layouts for use. The work of students, both distance and on-site, as well as teacher-student interaction, is organized using the MOODLE platform.

Developing a wireless real-time automated home approach utilizing NI MyRIO microcontroller board and LabVIEW platform

<p>In this paper, a design process and a hardware implementation for a wireless real-time home automation system approach based on NI MyRIO microcontroller board and LabVIEW platform has been developed. The proposed automated system has two hardware elements: the first one is a personal computer as a system main server hosting the designed LabVIEW platform and the second element is a NI MyRIO microcontroller board for managing the operating between the appliances and the sensors. The appliances can be automatically monitored, controlled, and accessed in response to the signals from the related sensors or manually by the system end-user through smart phone based on Wi-Fi and cloud computing technology. To approve the reliability of the proposed automated system, a hardware realization for three appliances: temperature management, light energy saving, and biometric security system of face recognition with fingerprint check has been introduced. The proposed system has a simple structure, economically cost effective and flexible scaling up for a proper automated home future.</p>

Experimental Study on Flow Characteristics of Hydraulic Multi-Way Valve Based on CAN Communication

This paper develops a CAN communication multi-way valve measurement and control system. This paper elaborates on the introduction of hydraulic circuit, the construction of measurement and control system. In the LabVIEW platform, the author designs the application program through the CAN communication card, writes the signal generator to control the multi-way valve, and then draws the flow characteristic curves of the multi-way valve.

A Real-Time Synchrophasor-Based Zone-3 Supervision of Distance Relays Under Load Encroachment Condition

This paper deals with the implementation of a real-time supervisory protection algorithm to avert the mal-operation of third zone element of distance relays during load encroachment. The proposed supervisory algorithm controls the operation of the backup zone (Zone-3) of distance relays by analyzing the synchrophasor data obtained from the phasor measurement units (PMUs) located throughout the power system network. The combination of the inherently higher delay time of Zone-3 element and the latency associated with PMUs to communicate information to the central control center makes the algorithm suitable for transmission line protection. The superiority of the proposed method is verified by conducting extensive real-time experiments on a laboratory model for a 400-km extra high voltage transmission line and implementing the protection algorithm on the LabVIEW platform at the System Protection and Control Centre. PMUs have been realized using National Instruments (NI) Compact Reconfigurable Input–Output embedded controllers, and the synchrophasor estimation algorithm is deployed using LabVIEW field-programmable gate array software. The results obtained from the experimental setup validate the viability of the proposed algorithm for the real-time implementation.

Spectroscopy of an intrinsic fluorophore in animal and plant milk for potential identification of their quality

Riboflavin (RF), commonly known as vitamin B2, is an essential ingredient in any milk variety of animal origin. The photophysics of the molecule RF, including its interaction with biological macromolecules, are well studied. Here, we have investigated the possibility of the molecule as a potential biomarker of milk quality. We also found omnipresence of this molecule in milk of plant origin (soy milk). Spectroscopic studies on various animal and plant milks of different commercial origins confirmed the potential of RF for use in identifying the quality of the milk varieties. Our developed strategy involved identification or spectroscopic signature of RF by measuring optical density at 365 nm (quality factor 1) and fluorescence intensity around 520 nm (excitation at 365 nm; quality factor 2) on a very small amount of whole milk (10 µL). We also developed a prototype device called Mil-Q-Way to be used in the real field. The required interfacing software in the LabView platform was also developed. A 2-parameter plot (quality factor 1 on the x-axis and quality factor 2 on the y-axis) called the Mil-Q-Way plot clearly differentiates the quality of milks of different commercial origins. The low-cost device based on simple spectroscopy was shown to screen for the presence of harmful adulterants in drinkable milk.

A Novel Method And Implementation Of Digital Algorithm For First Order Non Linear Spherical Tank Level Control Process With An Integral Windup

The primary goal of the process control is to control, monitor and to maintain different kinds of process stations at the desired stable conditions for improving the productivity and product quality. In industries most of the process are non - linear, controlling such type of system is difficult. So, spherical tanks are one among the non-linear systems which can be used to store maximum quantity of product in minimum area. These types of non-linear systems violate the superposition principle and are very difficult to control and monitor. Generally, conventional PID Controller is used for controlling a process in a plant. In Level control process, there exists the sudden change in final control element which leads to maximum overshoot and larger settling time, this stated phenomenon requires tuning of gain values to control the process variable to the set point. In order to overcome the above-mentioned problem, Anti reset windup concept is preferred. The mathematical modelling of a given process is obtained using black box system identification methodology. The accuracy in controlling the process variable is complicated due to its dynamic behaviour and characteristics. So in order to maintain the proper characteristics of non-linear system the mathematical modelling has been obtained by conducting the open loop test. In ancient stage the Ziegler Nicholas method is implemented to tune the PID parameters such as Kp, τi and τd which takes larger settling time, maximum Integral Square error and maximum peak overshoot. After tuning the PID gain values with the help of anti reset windup, the overshoot and settling time will be reduced. In this proposed work, Deadbeat and Dahlin’s Algorithms are used to convert the transfer function of the level process from ‘S’ domain to ‘Z’ domain (digital controller). The transfer function is used in MATLAB (Matrix Laboratory) to analyse the output of level process and the simulations are taken for the plant with above mentioned two different algorithms. For real time interface the LabVIEW platform is used and the results are discussed. This proposed digital controller with anti reset windup provides lower steady state error, minimum peak overshoot and minimum error criteria indices.

DESIGN AND IMPLEMENTATION OF LOW COST DATA ACQUISITION SYSTEM FOR ECG SIGNAL AND EDR USING LABVIEW AND ARDUINO

usage of electrocardiogram (ECG) signals not only limited to the medical services, but also used for studying, learning, processing and analysing. However, the devices such as BIOPAC Systems that used for this purpose are extremely expensive and often not existed, particularly in the third world. The aim of this paper is to design and implement low cost data acquisition system to capture ECG signals and generating ECG-Derived Respiration (EDR) using the LabVIEW platform and Arduino with help of AD8232 chip. The system is designed to monitor the heart signals over the time and calculates the heart rate accurately. It also constructs the breathing signal indirectly by detecting R peaks in ECG signals and interpolating them. Furthermore, this system introduces a unique feature through giving ability to save both the heart and breathing signals as the Matlab file to be used for further analysis. The outcomes show that the ECG signals are in the standard range, as well as constructing breathing signal was successfully done, and the obtained low cost system can be useful for biomedical studies.

Model Predictive Control for rotary inverted pendulum using LabVIEW

Inverted pendulum is a popular nonlinear system, extensively used in the study and analysis of various control techniques. Inverted pendulum has got variety of applications in robotics, aerospace, Segway etc. The paper deals with mathematical modelling, parameter estimation, disturbance rejection and tracking control of QNET 2.0 Rotary Inverted Pendulum Board for NI ELVIS in LabVIEW platform. A Model Predictive Controller is designed to maintain the pendulum in upright position and to handle disturbances. The tracking control problem for arm angle is also considered. A comparison between the disturbance rejections using MPC with standard LQR is carried out. Finally experimental results are described and compared based on the two control techniques designed for the stabilization of rotary inverted pendulum.

SMT Component Inspection in PCBA’s using Image Processing Techniques

In the present evolving technology, an Automated Optical Inspection is a solution for identifying the various types of defects occurring in assembled PCB with SMT components. As these high-end machines are expensive, moreover the small scale industries can’t afford such a huge investment, in this paper a low cost image processing technique where a good known reference image is compared with the acquired image is being tried. This work provides an automated approach for identifying few of the defects related to the SMT components found in the assembled PCB, using three different techniques namely Contour Analysis, Optical Character Recognition and Pixel Subtraction for identifying shifted components, value of the components and missing components respectively in LabVIEW platform. The time taken for identifying the various defects through different techniques are calculated and tabulated. Using these techniques the number of errors can be decreased in turn the end performance can also be enhanced with the increased production yield.

A Versatile Load Leveling Method for Fuel cell-based Electric Drive for Vehicular Application

This paper presents a flexible power control strategy of a fuel cell (FC)- battery combined hybrid power source fed DC motor drive suitable to be used in electric vehicles which can be capable of working efficiently with an straightforward control method, operating the drive precisely in FC and hybrid modes during the entire drive operation. Although Fuel Cells are very widely accepted by the electric vehicle manufacturing industries, still the power control criterion can be improved to increase overall efficiency. The most appropriate Master Slave Control technique has been implemented to control the modes based on load power requirement and transient operations. The controller with the algorithm guarantees that total load is shared exactly between the two sources all through intense load and transients conditions. Such method inevitably facilitates the fuel cell to work in normal load region throughout transient and steady state by equally sharing the load current between the master and slave converters. The efficacy of the proposed scheme is verified through simulation which is carried out using MATLAB/Simulink software. Investigational tests are carried out using LabVIEW platform with PCI 6251 DAQ I/O interfacing card for viability of the system. FC can be considered as most vital electric power and component of an electric vehicle.

Arc Image Processing Based on LabVIEW

The breaking capacity of the vacuum switch is closely related to the morphological changes of the vacuum arc. The arc arcing image is the direct basis for the change of the arc shape. How to accurately process the arc drawing image is of great significance for analyzing the arc shape change. In this paper, an arc image processing method based on virtual instrument development platform LabVIEW is designed. The NI Vision Builder AI image processing module of LabVIEW is used to accurately extract the arc shape. The key information of arc shape can be accurately extracted by the processing of arc image such as grayscale, filtering and edge extraction, and so on. The experimental results show that this method can effectively process the arc image. The experimental results can provide theoretical basis for the analysis of arc morphological changes.

MPC-Based Distributed Control for Intelligent Energy Management of AC Microgrids

Power scheduling of distributed storage devices and renewable energy resources in microgrids is crucial for their reliable and optimal operation. Conventionally, the power scheduling problem is solved with a centralized energy management control, which has access to all the information from the overall system. This type of control has limitations related to computational burden, communication latencies, and missing information. Therefore, the primary objective of this paper is to propose a distributed energy management strategy, to reduce the operational cost of microgrids, and to enhance the computation time. The strategy is formulated based on the model predictive control method since it allows the control action in the current time-step to be optimized while taking into account the future time-steps. Outputs of the energy management system are the optimal power references generated for all energy resources based on the system’s demand, constraints, and objective functions. To illustrate the effectiveness of the distributed model predictive control, the proposed algorithm is validated through simulation, on a microgrid candidate via MATLAB/Simulink, and controller hardware-in-the-loop experiment on a LabVIEW platform using National Instruments control devices (myRIO). The results will show the computation time in the distributed IEM method is improved compared to centralized IEM. Additionally, the results will show the robustness of the distributed IEM in the plug and play scenario.

Reactor de microondas de flujo continuo automatizado para la producción de biodiesel

Microwaves for organic synthesis are widely used due to the fact that reaction times are reduced with product conversion and selectivity improved. In this work, transesterification was carried out continuously to obtain biodiesel. A control system adapted to a home microwave oven was developed, by automating the process for continuous flow and with the less operator intervention. An embedded system and virtual instrumentation created in LabVIEW platform, for activation/deactivation orders and monitoring data supported by a PIC 18F4550 microcontroller was developed. The operative part is a power interface of transistors and activators formed by relays. The temperature sensor and power stage of the operative part of the process were linked through a PC interface by using an algorithm for data acquisition. Communication and control of the system was made through the LabVIEW platform in order to monitor, in real time, the parameters required to obtain the product. Results of automation and performance are presented.

Sistema Embebido de Análisis y Control por Medio de Visión Artificial y Mediciones Ultrasónicas, Basado en LabVIEW y Hardware roboRIO

In maintenance is vital to know the physical state of a equipment or process in real time effectively, fast and reliable way, since it would avoid short, medium or long term failures, caused by the bad operation or wear of parts that make up the process or equipment. One of the tools in which he allows this is known as; "Predictive maintenance", where the use of new processing and analysis technologies is indispensable. The implementation of a monitoring system by artificial vision in maintenance will eliminate the need to diagnose in person parts of a team or process. For this reason, an embedded system of artificial vision and ultrasonic measurements was designed and implemented, using the LabVIEW platform and RoboRIO hardware, capable to; analyze, monitor, classify, record and process the visible electromagnetic spectrum of a number N of objects with dimensions (X, Y, Z) in a production process. Which achieves an effectiveness of 87% against an ideal system, in which there is no error. Being this is the first of 3 phases of a more complex artificial vision monitoring system for the diagnosis of maintenance equipment and processes.

Dual‐mode control of multi‐functional converter in solar PV system for small off‐grid applications

Solar PV system for off-grid applications is growing at a faster rate because of its compatibility and ease of implementation. The modern smart building consists of hybrid AC and DC loads. The solar PV system generates DC power and can also supply the DC loads. To supply the AC loads, the DC power need conversion to AC using a DC–AC converter. A general solar PV system consists of two stages, one is to extract the maximum power and the other one is to convert it into a suitable DC or AC. Here, a single-stage multi-functional converter (MFC) is employed, which extracts maximum power and supplies to both AC and DC loads. To overcome the intermittency of solar PV output, battery energy storage is interfaced through a non-isolated buck–boost converter. The MFC operates in two modes, i.e. hybrid power flow mode and inverter mode, depending upon the availability of solar PV output. The proposed system is simulated using the PSCAD/EMTDC software. An experimental test setup using solar array simulator and a multifunctional power electronics converter has been developed for demonstration of the results. The control algorithms are implemented using NI PXI-7842R series FPGA controller through LabVIEW platform.

Development of HL-2M data integration and acquisition system for magnetic diagnostics

Magnetic measurement and diagnostics are critical for the operation of magnetic confinement experimental facilities and plasma analysis, while differential signals are mostly detected by a detector. For this, we have developed and designed a stable and reliable data integration system for HL-2M magnetic measurement and magnetic diagnostics. The system will be used for real-time control of HL-2M after the construction of HL-2M is completed. The system is built based on the PXI platform, and the software system is based on the LABVIEW platform. Key technologies realized by the system primarily include drift compensation, pulse data acquisition technology, multi-threading processing technology and transmission control communication protocol. Trials of the system were successfully carried out on HL-2A, and the results showed that the system could fully meet the construction needs of HL-2M.

Process-integrated steel ladle monitoring, based on infrared imaging – a robust approach to avoid ladle breakout

ABSTRACT Ladle breakout is a risky affair which is always present in steel making. The ladle breakout involves equipment damage and loss of production and sometimes loss of life. The present article describes the method of automatic detection of hotspot on the cold side of a ladle shell with the help of a group of infrared camera and subsequent processing of the infrared images in the LabVIEW platform. The system layout as implemented in the steel plant along with various pitfalls likely to be encountered during operation is discussed. Finally, the result of the trial run in the steel plant is presented. The system is found to be very effective as a preventive maintenance program to stop or minimise the ladle breakout.

Design and performance of an automated single column sequential extraction chromatographic system

An automated extraction chromatographic system and its virtual instrument system based on LabVIEW platform have been developed and characterized to perform single column-based sequential radiochemical procedures. The developed system was characterized by its dead volume and memory effect pertinent to fluidic tubing, and the linearity of feeding pump speed. An automated sequential procedure was developed for the rapid and reproducible separation of strontium from calcium, barium and yttrium with strontium selective resin.

Multi-purpose machine vision platform for different microfluidics applications.

Image processing is widely growing as a useful tool in biosensing applications. It can be used to convert any camera/microscope into an optical sensor with wide range of capabilities such as monitoring completion of colorimetric reactions, differentiating and counting cells, and tracking motile cells/organisms. However, implementation of image processing in Lab-on-Chip devices is still challenging for researchers with little expertise in this field. Here, we present a multi-purpose real-time machine vision platform for tracking and analyzing objects inside lab-on-chip devices and for automating many microfluidic applications. Our LabVIEW-based machine vision platform, which is freely available on our webpage ( http://www.assiutmicrofluidics.com/research ), enables non-experts in image processing and machine vision to easily assemble their image processing pipeline based on the intended application. The program was designed for plug and play interfacing with a wide range of imaging devices including USB microscopes, high-speed cameras, and smartphone cameras. Moreover, to achieve portability, the program can be loaded on myRIO, a portable pocket size fully functional LabVIEW platform, to perform all program capabilities outside the lab without the need for a PC. To prove functionality of our program, we used it in real-time closed loop control of hydrodynamic focusing and control of flow velocity of cells inside a microchannel. We also demonstrated the program abilities in different lab-on-chip applications such as tracking, differentiation, and counting of blood cells.

Dynamic Modeling of McKibben Muscle Using Empirical Model and Particle Swarm Optimization Method

This paper explores empirical modeling of McKibben muscle in characterizing its hysteresis behavior and nonlinearities during quasi-static, quasi-rate, and historic dependencies. The unconventional materials-based actuating system called McKibben muscle has excellent properties of power-to-weight ratio, which could be used in rehabilitation orthosis application for condition monitoring, physical enhancement, and rehabilitation therapy. McKibben muscle is known to exhibit hysteresis behavior and it is rate-dependent (the level of hysteresis depends closely on rate of input excitation frequency). This behavior is undesirable and it must be considered in realizing high precision control application. In this paper, the nonlinearities of McKibben muscle is characterized using empirical modeling with multiple correction functions such as shape irregularity and slenderness. A particle swarm optimization (PSO) method is used to determine the best parametric values of the proposed empirical with modified dynamic friction model. The LabVIEW and MATLAB platforms are used for data analysis, modeling and simulation. The results confirm that this model able to significantly characterize the nonlinearities of McKibben muscle while considering all dependencies.