Vision Builder Research Articles

Smart Grasping of a Soft Robotic Gripper Using NI Vision Builder Automated Inspection Based on LabVIEW Program

Smart Grasping of a Soft Robotic Gripper Using NI Vision Builder Automated Inspection Based on LabVIEW Program

Application of image processing using NI LabVIEW for mold distribution analysis in blue cheese

The NI LabVIEW is a software for real-time data processing and it is widely used for process control in industry. It has a lot of additional libraries and modules which extend its functions and support its applications in many different areas. Vision Builder and Vision Assistant are modules in NI LabVIEW which support image acquisition and processing. These modules are used for the purpose of the current research in order develop an algorithm to analyze mold distribution in blue cheese. Eight trademarks of blue cheese are used for comparative analysis of mold distribution. Every sample is cut with special cheese slicer in order to evaluate its mold distribution. The samples are captured with digital camera and images are processed in NI LabVIEW environment. Coefficient of mold (ratio of pixels with mold to all pixels in cut surface of cheese) is calculated for nine regions of interest on every picture. This coefficient is used for statistical analysis of mold distribution. It is observed that cheese which have low quantity of mold are presented with non-even mold distribution and cheese which have high quantity of mold are presented with almost even mold distribution. The results show that the upgraded experimental setting could be successfully applied for mold distribution analysis of blue cheese and the LabVIEW environment and its software modules Vision Builder and Vision Assistant could be effectively applied for fast and accurate evaluation of mold quantity and distribution in blue cheese.

Study on duck weight estimation by using image processing

The objective of this research was to process digital image to investigate the possibility of ducks weight estimation based on the software LabVIEW with the vision builder. In this study the images were record by the top-view camera. An ellipse fitting algorithm was applied to localize ducks within the stall. Estimating duck weight consists of these steps. First, image acquisition. Second, counts pixel of the samples. Third calculate duck weight by using samples pixel as the output. Results from this study showed that, the estimated ducks weight by using digital photos had 3.27% of the error when compare to the measured weight. The correlation coefficient of the body weight prediction equation from a comparison between measured (absolute) and estimated by camera for all duck is clearly high (R2=0.91). It was found that the system able to estimate duck weight with an acceptable error. So we can develop this research processing or build up the automatic sorting duck in the future. This method operated pretty well in prophecy live weight.

Inspection of the Cogwheel Using Virtual Instrumentation

This paper deals with use of machine vision for the needs of automated inspections based on virtual instrumentation using a visualization tool named Vision Builder for Automated Inspection (VBAI) – National Instruments (NI). An application for camera tests of dimensions, shapes and presence is designed in experimental parts. This work is focused on the control, detection and distribution properties of internal holes.

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.

The use of computer image analysis in determining material flow in the roller press compacting unit during compacting of fine-grained material

Mechanisms of fine-grained material flow in a roller press are a constant subject of research. The proper transfer of feed in the feeder has a significant influence on the correct course of the compaction and consolidation process, product quality, and the intensity of wear of the forming components. A few mathematical models of compaction process have been put forth, but they are focused mainly on loads in the compacting unit and consolidated material properties. During compaction the loose material properties including the Young module, the external and internal friction coefficient, and the side pressure coefficient change continuously. Therefore visualisation tests were carried out to survey the flow of material in a compaction unit equipped with rollers with a flat working surface and gravity feeder. Using the NI Vision Builder program, the recorded video observations were analyzed and the medium speed distribution of the material in the feeder was determined. The results were presented in the form of graphs and compared with one another, specifying the relationship between the material speed distribution and the press operation parameters.

IMAQ Vision Builder Applications in SEM Image Processing of Pharmaceutical Powders

IMAQ Vision includes a set of optimized functions for image processing (filtering and geometric transformations) and analysis of different areas of interest (perimeter, area, orientation, height, length and width). Also with this program, it may determine the edges of objects, distances and angles between the edges, an object can be searched based on its shape. Particle analysis provides the ability to count objects within the pharmaceutical or biological applications. Image calibration is done to give the user instead of the unit pixel measurements, in units such as millimeters, inches, microns. This paper aims to examine the pharmaceutical powder containing ketoprofen in order to determine the quality of the particles and if this are optimal for pharmaceutical applications. It aims to detect surface defects in the deposited layer such as cracks or clusters of particles that cause surface irregularity. IMAQ Vision by processing images, increase productivity, versatility and reproducibility also reducing manufacturing costs.

Leading knowledge management in a secondary school

Leading knowledge management in a secondary school

Using Machine Vision for Flexible Automatic Assembly System

Flexible automatic assembly systems become the useful automation system for high mixed production lines of manufacturing processes. This research was aimed to design the primary prototype of the flexible automatic pick and place assembly system. We integrated the machine vision system with the robotic system to conduct a pick and place process. The product models consisted of a main part and an assembly part. The main parts were transferred to the mechanical system through a conveyor belt. When the main parts were held at the specific location, the images of the main parts were captured. Using the image processing of LabVIEW NI vision software and NI vision builder and image calibration method, we could obtain the shape, and orientation of assemble space in the main part which were used to control selective compliance articulated robot arm (SCARA). The SCARA was used to pick the assembly parts from the storage station and place them into the assembly spaces on the main parts. As the results of the prototyping, we evaluated the coordinate conversion factors from the image calibration and used them to control the movement of the SCARA. We finally obtained the reliable flexible automatic assembly system that could detect and identify the shape, and orientation of the assembly space correctly. The SCARA could also pick the correct assembly parts and place them into the assembly space perfectly.

Object positioning in storages of robotized workcells using LabVIEW Vision

During the manufacturing process, each performed task is previously developed and adapted to the conditions and the possibilities of the manufacturing plant. The production process is supervised by a team of specialists because any downtime causes great loss of time and hence financial loss. Sensors used in industry for tracking and supervision various stages of a production process make it much easier to maintain it continuous. One of groups of sensors used in industrial applications are non-contact sensors. This group includes: light barriers, optical sensors, rangefinders, vision systems, and ultrasonic sensors. Through to the rapid development of electronics the vision systems were widespread as the most flexible type of non-contact sensors. These systems consist of cameras, devices for data acquisition, devices for data analysis and specialized software. Vision systems work well as sensors that control the production process itself as well as the sensors that control the product quality level. The LabVIEW program as well as the LabVIEW Vision and LabVIEW Builder represent the application that enables program the informatics system intended to process and product quality control. The paper presents elaborated application for positioning elements in a robotized workcell. Basing on geometric parameters of manipulated object or on the basis of previously developed graphical pattern it is possible to determine the position of particular manipulated elements. This application could work in an automatic mode and in real time cooperating with the robot control system. It allows making the workcell functioning more autonomous.

Technological process supervising using vision systems cooperating with the LabVIEW vision builder

One of the most important tasks in the production process is to supervise its proper functioning. Lack of required supervision over the production process can lead to incorrect manufacturing of the final element, through the production line downtime and hence to financial losses. The worst result is the damage of the equipment involved in the manufacturing process. Engineers supervise the production flow correctness use the great range of sensors supporting the supervising of a manufacturing element. Vision systems are one of sensors families. In recent years, thanks to the accelerated development of electronics as well as the easier access to electronic products and attractive prices, they become the cheap and universal type of sensors. These sensors detect practically all objects, regardless of their shape or even the state of matter. The only problem is considered with transparent or mirror objects, detected from the wrong angle. Integrating the vision system with the LabVIEW Vision and the LabVIEW Vision Builder it is possible to determine not only at what position is the given element but also to set its reorientation relative to any point in an analyzed space. The paper presents an example of automated inspection. The paper presents an example of automated inspection of the manufacturing process in a production workcell using the vision supervising system. The aim of the work is to elaborate the vision system that could integrate different applications and devices used in different production systems to control the manufacturing process.

단신 : 페달링 시 정량적인 동적 피팅을 위한 실시간 평가 시스템

In this study, a real-time evaluation system for quantitative dynamic fitting during pedaling was developed. The system is consisted of LED markers, a digital camera connected to a computer and a marker detecting program. LED markers are attached to hip, knee, ankle joint and fifth metatarsal in the sagittal plane. Playstation3 eye which is selected as a main digital camera in this paper has many merits for using motion capture, such as high FPS (Frame per second) about 180FPS, <TEX>$320{\times}240$</TEX> resolution, and low-cost with easy to use. The maker detecting program was made by using Labview2010 with Vision builder. The program was made up of three parts, image acquisition & processing, marker detection & joint angle calculation, and output section. The digital camera's image was acquired in 95FPS, and the program was set-up to measure the lower-joint angle in real-time, providing the user as a graph, and allowing to save it as a test file. The system was verified by pedalling at three saddle heights (knee angle: 25, 35, <TEX>$45^{\circ}$</TEX>) and three cadences (30, 60, 90 rpm) at each saddle heights by using Holmes method, a method of measuring lower limbs angle, to determine the saddle height. The result has shown low average error and strong correlation of the system, respectively, <TEX>$1.18{\pm}0.44^{\circ}$</TEX>, <TEX>$0.99{\pm}0.01^{\circ}$</TEX>. There was little error due to the changes in the saddle height but absolute error occurred by cadence. Considering the average error is approximately <TEX>$1^{\circ}$</TEX>, it is a suitable system for quantitative dynamic fitting evaluation. It is necessary to decrease error by using two digital camera with frontal and sagittal plane in future study.

Measurement of void fraction in flow boiling of ZnO–water nanofluids using image processing technique

In recent years, nanofluids have been an active area of research in many engineering applications, especially for nuclear reactor safety systems due to their enhanced thermal properties as a coolant. In this study, experiments were performed in subcooled flow boiling of water and ZnO–water nanofluids with different nanoparticle concentrations (0.001–0.01vol.%) in horizontal annulus at heat fluxes varying from 100 to 550kW/m2 and flow rates from 0.1 to 0.175lps at 1bar inlet pressure and constant subcooling of 20°C to determine the void fraction by image processing technique. Parametric effects of nanoparticle volume fraction, heat flux, flow rate and axial location of heater rod on void fraction were studied. Bubble images during flow boiling were captured with high speed visualization and analyzed by National Instruments IMAQ Vision Builder 6.1 image processing software. Results show that void fraction decreases up to 86% with the use of nanofluid in place of water and it also decreases with increasing nanoparticle concentration and flow rate, whereas increase in heat flux and axial location of heater rod have opposite effect.

Investigation of Bubble Behavior in Subcooled Flow Boiling of Water in a Horizontal Annulus Using High-Speed Flow Visualization

Experiments have been carried out to study bubble behavior in subcooled flow boiling of water in a horizontal annulus at mass fluxes from 400 to 1200 kg/m2-s, heat fluxes from 0.1 to 1 MW/m2, and pressures varying from 1 to 4 bar using high-speed visualization methods. National Instruments Labview IMAQ Vision Builder automated image-processing software was used to analyze the images obtained by high-speed visualization to obtain bubble size and bubble density. The parametric effects of pressure, mass flux, and heat flux on bubble behavior have also been brought out. Experimental results were validated by comparing with the predicted bubble sizes by using the Zeitoun and Shoukri (1996) correlation and were found to be in good agreement. It was found that bubble behavior is significantly affected by mass flux of working fluid and applied heat flux, whereas pressure of working fluid influences the bubble formation process indirectly.

Measurement of dust concentration based on VBAI

There are almost no economic and management solutions in automated measurement of dust concentration of magnesium oxide smelting electric arc furnace mouth. Nearly a thousand degrees of heat and the strong magnetic fields created by high-current Constitutes a serious interference with the sensor. This makes close-contact measurement method becomes almost impossible. To solve the above problem, this paper proposes a measurement scheme based on VBAI (Vision Builder for Automated Inspection, a software developed by National Instruments) to calculate the dust concentration. It uses visual analysis of the means to calculate the number of dust particles per unit volume of. And then it calculates the dust concentration. Though the analysis of the actual photo of the smelting site, the relative dust concentration in the mouth of the furnace is calculate. This method will be applied to the precipitator 70 kW motor inverter control and has a high recognition rate and significant application prospects.

A visualization study of flow boiling heat transfer with nanofluids

In recent years, fluids containing suspension of nanometer-sized particles (nanofluids) have been an active area of research due to their enhanced thermal properties over the base fluids. This makes them very attractive as heat transfer fluids in many applications. Bubble study through visualization during nanofluid flow boiling may provide valuable insight in the mechanisms by which the nanoparticles affect the heat transfer performance. In this study, experiments were performed in subcooled flow boiling of ZnO–water nanofluids with different low particle concentrations (≤0.01 volume %) in horizontal annulus at heat fluxes from 100 to 450 kW/m2 and flow rates from 0.1 to 0.175 lps at 1-bar inlet pressure and constant subcooling of 20 °C to determine bubble behavior by optical method and to study the parametric effect of heat flux, flow rate and particle volume fraction of ZnO on bubble behavior. Bubble images were captured with high-speed video camera using XCAP SV-642 software. Images were analyzed with the purpose of finding bubble characteristics viz. bubble diameter and bubble density using National Instruments IMAQ Vision Builder 6.1 image processing software. The results show that increase in heat flux leads to increase in bubble diameter. Addition of nanoparticles into the base fluid enhances the maximum bubble diameter and decreases the bubble density. Bubble diameter and bubble density decrease in both water and nanofluids with increase of flow rate. The heat transfer coefficient increases with increase in heat flux and particle volume fraction of ZnO.

자동차 부품 카시트 프레임 검사를 위한 머신비전 개발

본 논문에서는 생산 현장에서 작업자가 육안으로 하고 있는 자동차 부품 카시트 프레임의 전수(全數) 검사를 위한 머신 비전 시스템의 개발에 관한 연구를 다룬다. 이러한 제안된 머신비전 검사시스템은 생산 현장에서 날로 증가하는 품질 향상에 대한 요구와 수요를 충족시키기 위해 설계되었다. 이 컴퓨터 기반의 검사시스템은 실시간으로 제품의 다양한 결함들에 대한 품질 검사를 할 수 있도록 설계되었다. 본 연구의 검사방법에 사용된 소프트웨어는 NI-LabVIEW가 사용하였으며, LabVIEW Vision 이미지 함수를 사용하여 검사 프로그램을 개발하였다. 개발된 검사 알고리즘은 생산 부품의 실시간 검사에 적용 될 수 있으며, 검사 영역과 설정 값을 비전 시스템 운용자가 설정할 수있도록 프로그램이 만들어져 검증되었다. 제안된 검사시스템은 카시트 프레임 검사를 성공적으로 수행하였다. This study presents the development of a machine vision inspection system(MVIS) purposely for car seat frames as an alternative for human inspection. The proposed MVIS is designed to meet the demands, features and specifications of car seat frame manufacturing companies in striving for increased throughput of better quality. This computer-based MVIS is designed to perform quality measures by detecting holes, nuts and welding spots on every car seat frame in real time. In this study, the NI Vision Builder software for Automatic Inspection was used as a solution in configuring the aimed quality measurements. The techniques for visual inspection are optimized through qualitative analysis and simulation of human tolerance on inspecting car seat frames. Furthermore, this study exemplifies the incorporation of the optimized vision inspection environment to the pre-inspection and post-inspection subsystems. The system built on this proposed MVIS for car seat frames has successfully found the possible detections.

A Real Time Quality Monitoring System for the Lighting Industry: A Practical and Rapid Approach Using Computer Vision and Image Processing (CVIP) Tools

In China, the manufacturing of lighting products is very labour intensive. The approach used to check quality and control production relies on operators who test using various types of fixtures. In order to increase the competitiveness of the manufacturer and the efficiency of production, the authors propose an integrated system. This system has two major elements: a computer vision system (CVS) and a real-time monitoring system (RTMS). This model focuses not only on the rapid and practical application of modern technology to a traditional industry, but also represents a process innovation in the lighting industry. This paper describes the design and development of the prototyped lighting inspection system based on a practical and fast approach using computer vision and imaging processing (CVIP) tools. LabVIEW with IMAQ Vision Builder is the chosen tool for building the CVS. Experimental results show that this system produces a lower error rate than humans produce in the quality checking process. The whole integrated manufacturing strategy, aimed at achieving a better performance, is most suitable for a China and other labour intensive environments such as India.

Comparison of color techniques to measure the color of parboiled rice

A combination of digital camera, computer and graphic software can provide a less expensive and more versatile technique to determine the surface color of parboiled rice compared to instrumental color measurement. The instrument was used to measure rice powder and whole rice. Pearson correlation coefficients and sample paired t-test on total color difference (Δ E), L and b values were calculated. The value of Δ E of samples from the instrumental technique was 0.69–4.61 (powder), 4.7–10.2 (whole rice) with a coefficient of variance (CV) ranging from 3.5 to 25.3% and from 15.4 to 46.6%. Meanwhile, the digital image technique gave a Δ E value ranging from 4.2 to 13.77 with a CV from 6.3 to 21.2%, respectively. A highly significant correlation ( R 2 = 0.7451, R 2 = 0.8074, R 2 = 0.7518,) was obtained for Δ E between instrumental (powder and whole rice), Vision Builder and instrumental (powder), and instrumental (whole rice) and Vision Builder. The chromatic b value of instrumental for powder had a significant correlation with the Vision Builder data ( R 2 = 0.7741). The results suggest that although the digital image provided the surface color of parboiled rice, it was less accurate than the instrumental for powder. Therefore results from the digital image should be interpreted with caution.

A computer vision method to locate cold spots in foods in microwave sterilization processes

A major challenge in developing advanced thermal processess based on electromagnetic heating is to determine the location of cold spots in foods. A rapid and reliable method was developed in this study with the aim to effectively locate the cold spot in model food sterilized in microwave systems. The developed method involved application of chemical marker M-2 yield to a model food, mashed potatoes, using computer vision system and an image processing software IMAQ Vision Builder to capture and analyze color patterns after thermal processes. A systematic study was conducted to establish relationships among M-2 yields, color values from captured images of cut food samples, and thermal lethality ( F 0 ) . Several factors including consistency of imaging background and positions of lights over the diffuser box were considered to standardize the method. To facilitate the comparative study of heating characteristic for different combinations of power levels and F 0 , a mapping scale using unheated and saturated mashed potato samples was developed by fixing the lowest and upper most gray-scale values. Color values equivalent to gray-level values were positively correlated to F 0 and M-2 yield. The specified cold spot location determined by computer vision method was validated in a 915 MHz single-mode microwave sterilization system. The results showed that the computer vision method can potentially be used as an effective tool in microwave sterilization process development for regulatory acceptance and industrial applications.