LabVIEW Based Real-time Color Measurement System

Colorimetry is of paramount importance to the agricultural industry. Colorimetry refers to the processing of agricultural products for consumer needs from a marketing point of view, and therefore the agricultural industry spends a lot of money and time classifying each product. In the past, agricultural professionals had to use program codes that are difficult to learn, and even the most basic image analysis for agricultural product classification required mastering different program libraries. Today, the LabVIEW platform offers a flexible, fast, easy-to-learn, and complete image analysis infrastructure with various useful modules. For this reason, in this study, a method analysis for color perception with a simple USB webcam and software developed for real-time color analysis on the LabVIEW platform is presented and its success in the basic color analysis is tried to be revealed. The basic application developed for this purpose in LabVIEW v2019 using NI Vision Development Module v19 and NI IMAQ v19 modules. The basic fact that is the LabVIEW application is the idea that LabVIEW can only be analyzed with expensive IEEE 1394, but it should be known that these analyzes can be done with USB webcams. For this purpose, the application includes a USB webcam driver that can be stacked seamlessly. USB Webcam and colorimeter measurement-based results of ƔR factors for each of RGB color channels are 1.161232, 0.506287, 0.432229; ƔG factors for each of RGB color channels are 0.519619, 1.025383, 1.201444; at last ƔB factors for each of RGB color channels are 0.600362, 0.714016, 1.413406, respectively.

Intelligent Collection of Detection Data and Automatic Generation of Report Based on LabVIEW in ABS Adhesion Coefficient Utilization Test

The automobile anti-lock braking system (ABS) is a hot spot in the current research and development of automobiles. The country also has corresponding standards for its performance requirements and test methods. Among them, the utilization rate of the adhesion coefficient is one of its important performance evaluation indicators. In the adhesion coefficient utilization test, the post-processing workload of the data is large, and the authenticity of the data is crucial to the test results. In order to overcome the shortcomings of manual reporting, which takes a long time and is prone to human errors. Based on the LabVIEW platform, this paper constructs a method for automatic generation of test reports, and designs a comprehensive program for automatic report generation. Experimental shows that the use of integrated automation software to issue an adhesion coefficient utilization test report can reduce data post-processing work and greatly improve the efficiency and accuracy of the report.

Development of Real-Time Fuzzy Synchronization of Chaos Based System for Image Encryption

The concept of chaos, which has entered the literature since the 19th century, has been used for the protection of information with the development of information technologies in recent years. Chaos circuits are frequently used in secure communication systems because of its unpredictability and ease of modeling. In this paper, real-time fuzzy control method was used for master-slave synchronization of Rucklidge chaotic circuit. Also, sinusoidal signal and image encryption were used for application of secure communication process in LabVIEW platform. Data acquisition system was used to implement real time application. Fuzzy control performed synchronization at the end of the specified period and image encryption and decryption were successfully obtained in the developed system.

DESIGN AND APPLICATION OF MULTIFUNCTIONAL PERFORMANCE TEST PLATFORM FOR SOIL-ENGAGING TILLAGE COMPONENTS

Parts that come into contact with the soil are ones of the important energy consuming parts in tillage operations. In order to improve the research and development efficiency of tillage components, it is necessary to develop a performance test platform for tillage components with high interchangeability, convenience and comprehensive data collection. Therefore, a performance test platform for combined powered and passive tillage components was designed. Strength analysis and structural design optimization of key components was based on ANSYS. A real-time measurement and control software was developed based on LabVIEW platform. The related tests results show that the test platform can be used to simulate the actual condition and meet the test requirements.

An Intelligent Tire Pressure Monitoring System

Pressure of tire is measured using Tire Pressure Monitoring System (TPMS) model. By measuring the tire pressure, the fuel can be saved and the vehicle can be controlled in better way. The real of tire pressure can be monitored in real time and if the pressure of the tire goes out of the threshold this system gives alarm and alert the driver to ensure the driver safety, hence the life of the driver can be safeguard and pre-warn the driver and passengers. TPMS consists of an electronic unit that sense the tire pressure displays it to user in a LABVIEW platform. This unit includes a pressure sensor and Data Acquisition System. The output of the pressure sensor is given to the Data Acquisition System. Then the DAQ is interfaced with PC to display the tire pressure in the dashboard using the LABVIEW platform. If the tire pressure crosses safe pressure level a warning is generated

Fully Automated Measurement Setup for Photovoltaic Panel Performance Evaluation and Testing under LabVIEW Platform

Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was characterized by high performance standard with accuracy, precision, and resolution that is good enough to practically test any PV panel of the 12 V and 24 V ratings. In this paper, several simulations run and manually performed testing for PV panels were done to verify the automatically obtained results and those were found to be of good conformity (-3% difference with simulation results, 0.01% with manually taken results).

Potato Classification by using Ultrasonic Sensor with LabVIEW

Background: Agricultural product classification is an essential and widely working issue in the agriculture industry. There is a lot of work to be done in this area and the agriculture industry is looking for new applications. The reason is that the software and hardware Technologies are always developing, and the latest technologies giving better results parallel to these developments. Also, the costs of the new technologies are decreasing with the help of low-cost sensor and device technologies. New technique and technology usage also directly related to classification efficiency. The primary data on agriculture are agricultural products, so these technologies and techniques use for agricultural production. Methods: The primary data on agriculture are agricultural products, because of this reason, this research aimed to make ultrasonic sensor measurements with the help of a software which is developed in LabVIEW platform for potato classifications and showing the efficiency of the method for the potato classification, which has different sizes. Result: According to the regression coefficient results, the regression between caliper length measurement (CL) and static ultrasonic sensor length measurement (SUL) found as 95.5%, the regression between caliper length measurement (CL) and dynamic ultrasonic sensor length measurement (DUL) found as 86.9%, the regression between static ultrasonic sensor length measurement (SUL) and dynamic ultrasonic sensor length measurement (DUL) found as 87.9% for potato classification.

Experimental Recognition System for Dirty Eggshell by Using Image Analysis Technique

The present study was focused on the design and implementation of an experimental recognition system for dirty chicken eggshell by using an image analysis technique. Image analysis based observation and evaluation techniques can be used efficiently and effectively for agricultural product quality control. Dirt stains on eggs are the result of mainly by feces (black to light brown stains), uric acid (white stains), yolk, and blood. The experimental system was used to obtain dark level images of dirty stains of chicken eggs owing to feces. For this aim, the dirty chicken eggs which have dirty parts were put under a webcam, and dirtiness degree was evaluated by using developed image analysis software at the LabVIEW platform. For the experiment, 100 clean and 100 dirty eggs were used to accurate the determination of dark stains. The results of the research showed that the designed experimental system pointed an accuracy of 99.8% at painted grade eggs. On the other hand, the accuracy of the differentiation of the dirt stains by feces was 98.5%. The developed system can be upgraded for developing egg sorting machines by presence-absence of dirty stains in eggshell.