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The present study aimed to display the gamma energy spectrum as a 2D digital image. This process was performed via LabVIEW software. A code was developed for this purpose. It was tested on the gamma energy spectra of Cs-137 and Bi-207 radiation sources. The process of image acquisition of the energy spectrum was performed in two ways; horizontal and vertical. In addition to grayscale image acquisition, the colored image acquisition was also performed using color palettes defined by DICOM standard via Vision Assistant Express. [ABSTRACT FROM AUTHOR]

This paper describes the control system for a dispersion interferometer based on a CO2 laser developed by the Budker Institute of Nuclear Physics (Novosibirsk, Russia) for the Globus-M2 tokamak (Ioffe Institute, St. Petersburg, Russia). The basis of this system is the programmable controller ADAM-5510E/TCP with a set of analog and digital input/output modules and specially developed software that allows monitoring and control of the operation and parameters of interferometer elements. During the year of the dispersion interferometer operation as a standard diagnostic at the Globus-M2 tokamak, the control system showed good levels of reliability and sustainability. [ABSTRACT FROM AUTHOR]

Simple Summary: The backfat thickness of sows reflects their nutrient reserve levels. Controlling the backfat thickness within an appropriate range at different production stages can improve the production performance of sows. However, in large-scale pig farms, due to the cumbersome process of measuring backfat thickness and the large number of sows, it is often not possible to obtain or visually measure the backfat thickness during production. Often, a small difference in feed intake will lead to a large difference in production performance, such that sow production performance cannot be fully optimized. In this study, the relationships between backfat thickness and parameters related to hip area, hip width, hip height, and hip radius are discussed, and a sow backfat thickness estimation model is established. Finally, a sow backfat thickness estimation system is built using the LabVIEW 2023 Q1 (64-bit) software development platform. After inputting the sow buttock image, the system can automatically preprocess the image and extract the parameters required to quickly estimate the backfat thickness of the sow, thereby enhancing the automation of the sow farm. Controlling the backfat thickness of sows within an appropriate range during different production stages helps to increase the number of pigs weaned per sow per year and ultimately enhances the economic benefit to the pig farm. To obtain the backfat thickness of sows automatically, a backfat thickness estimation method based on machine vision is proposed. First, the backfat thickness values and 3D images of the buttocks of 154 Landrace–Yorkshire crossbred sows were obtained using a veterinary ultrasound backfat meter and Azure Kinect DK camera. After preprocessing the 3D images utilizing Python 3.9.16 software, 10 external morphological parameters reflecting the area, width, height, and contour radius of the sow's buttocks were extracted. The relationships between backfat thickness and external morphological parameters were analyzed in a randomly selected group of 100 sows. A significant positive correlation was observed between backfat thickness and buttock morphological parameters, with the Pearson coefficient for the fitted ellipse area achieving values up to 0.90. A backfat thickness estimation model was developed based on selected buttock feature parameters. The model's generalization performance was evaluated using 54 additional sows that were not involved in the model development. The coefficient of determination (R2) between the estimated and actual backfat thicknesses was 0.8923, with a mean absolute error (MAE) of 1.23 mm and a mean absolute percentage error (MAPE) of 5.73%. These metrics indicate that the model can meet production requirements, and the proposed technique offers improved estimation accuracy compared to existing methods. Ultimately, a backfat thickness automatic estimation system was developed using LabVIEW 2023 Q1 (64-bit) software. This research helps to address the cumbersome process of measuring sow backfat thickness and promotes the automation of sow farms. [ABSTRACT FROM AUTHOR]

Milling parts made from glass fiber-reinforced polymer (GFRP) composite materials are recommended to achieve the geometric shapes and dimensional tolerances required for large parts manufactured using the spray lay-up technique. The quality of the surfaces machined by milling is significantly influenced by the temperature generated in the cutting zone. This study aims to develop an Artificial Neural Network (ANN) model to predict the temperature generated when milling GFRP. The ANN model for temperature prediction was created using a virtual instrument developed in the graphical programming language LabVIEW. Predicting temperature is crucial because excessive heat during milling can lead to several issues, such as tool wear and thermal degradation in the polymer matrix. The temperature in the tool–workpiece contact surface during the milling process was measured using a thermography technique with a ThermaCAM SC 640 camera (provided by FLIR Systems AB, Danderyd, Sweden), and the data were analyzed using the ThermaCAM Researcher Professional 2.8 SR-2 software. Experimental research shows that the cutting speed has a much more significant effect on the temperature in the cutting zone compared to axial depth of cut and feed speed. The maximum temperature of 85.19 °C was measured in the tool–workpiece contact zone during machining at a cutting speed of 75.39 m/min, a feed rate of 250 mm/min, and an axial depth of cut of 12 mm. This temperature rise occurred due to the larger contact area and heightened friction resulting from the abrasive characteristics of the reinforcement material. [ABSTRACT FROM AUTHOR]

In this article, power quality disturbances, such as voltage and current unbalances, series and shunt faults, are monitored in three-phase synchronous machines. Because the imbalances affect machine efficiency and service life, it is essential to figure out whether the three-phase voltages/currents are balanced or unbalanced. An integrated detection algorithm is proposed to detect the unbalanced voltages/currents and various abnormal conditions precisely and quickly, which is based on the coherence estimator. Most existing detection methods require more than one cycle time to determine the contingency conditions, while the proposed technique detects these situations in a fast and discrete protection system. The suggested scheme acquires instantaneous measurements of the three-phase voltages and currents taken at the synchronous machine terminals in order to calculate fifteen coherence coefficients that are utilized to detect and assess any unbalance or trouble accurately and swiftly. A new proposal for imbalance and disturbance indicators based on the coherence estimators is developed in this study. Multiple test cases have been conducted to validate the proposed algorithm capabilities using a real power system, which includes a motor-generator set, a three-phase load and measurement transformers. The experimental results have been revealed that the relay reliability and accuracy percentages have been found to be 98.28% and 98.52%, respectively. The quantitative findings of the imbalance and disturbance assessment are recorded. [ABSTRACT FROM AUTHOR]

As the market share of electric vehicles continues to rise, consumer demands for comfort within the vehicle interior have also increased. The noise generated by electric seats during operation has become one of the primary sources of in-cabin noise. However, the offline detection methods for electric seat noise severely limit production capacity. To address this issue, this paper presents an online quality inspection system for automotive electric seats, developed using LabVIEW. This system is capable of simultaneously detecting both the noise and electrical functions of electric seats, thereby resolving problems associated with multiple detection processes and low integration levels that affect production efficiency on the assembly line. The system employs NI boards (9250 + 9182) to collect noise data, while communication between LabVIEW and the Programmable Logic Controller (PLC) allows for programmed control of the seat motor to gather motor current. Additionally, a supervisory computer was developed to process the collected data, which includes generating frequency and time-domain graphs, conducting data analysis and evaluation, and performing database queries. By being co-located with the production line, the system features a highly integrated hardware and software design that facilitates the online synchronous detection of noise performance and electrical functions in automotive electric seats, effectively streamlining the detection process and enhancing overall integration. Practical verification results indicate that the system improves the production line cycle time by 34.84%, enabling rapid and accurate identification of non-conforming items in the seat motor, with a detection time of less than 86 s, thereby meeting the quality inspection needs for automotive electric seats. [ABSTRACT FROM AUTHOR]

Conventional baseband processing techniques for communication must be adapted to the specificities of terahertz channels. Currently, there is limited research on channel coding applicable to terahertz bands, particularly in terms of performing real-time tests that differentiate them from offline processing. This paper presents a test platform for a 300 GHz wireless communication system based on the PXIe platform. The experiment utilizes a high-performance, low-complexity serial scheduling approach with the Minimum Sum-Log Likelihood Ratio Belief Propagation (MS-LLR-BP) soft decision decoding algorithm to test point-to-point real-time line-of-sight communication for low-density parity-check (LDPC) code communication systems. The results indicate that the implementation of LDPC coding in QPSK terahertz wireless transmission systems results in a performance enhancement of approximately 25–55% in bit error rate (BER), demonstrating the excellent performance of LDPC codes against terahertz channel fading. This highlights their potential in future ultra-high-speed communication systems. [ABSTRACT FROM AUTHOR]

Due to the lack of real-time planning for fire escape routes in large buildings, the current route planning methods fail to adequately consider factors related to the fire situation. This study introduces a real-time fire monitoring and dynamic path planning system based on an improved ant colony algorithm, comprising a hierarchical arrangement of upper and lower computing units. The lower unit employs an array of sensors to collect environmental data in real time, which is subsequently transmitted to an upper-level computer equipped with LabVIEW. Following a comprehensive data analysis, pertinent visualizations are presented. Capitalizing on the acquired fire situational awareness, a propagation model for fire spreading is developed. An enhanced ant colony algorithm is then deployed to calculate and plan escape routes by introducing a fire spread model to enhance the accuracy of escape route planning and incorporating the A* algorithm to improve the convergence speed of the ant colony algorithm. In response to potential anomalies in sensor data under elevated temperature conditions, a correction model for data integrity is proposed. The real-time depiction of escape routes is facilitated through the integration of LabVIEW2018 and MATLAB2023a, ensuring the dependability and safety of the path planning process. Empirical results demonstrate the system's capability to perform real-time fire surveillance coupled with efficient escape route planning. When benchmarked against the traditional ant colony algorithm, the refined version exhibits expedited convergence, augmented real-time performance, and effectuates an average reduction of 17.1% in the length of the escape trajectory. Such advancements contribute significantly to enhancing evacuation efficiency and minimizing potential casualties. [ABSTRACT FROM AUTHOR]

This article studies the transformation and assembly process of the Volkswagen (VW) Crafter from conventional to hybrid vehicle of the department of vehicles engineering, University of Debrecen, and uses a computer-aided simulation (CAS) to design the vehicle based on the real measurement data (hardware-in-the-loop, HIL method) obtained from an online CAN bus data measurement platform using MATLAB/Simulink/Simscape and LabVIEW software. The conventional vehicle powered by a 6-speed manual transmission and a 4-stroke, 2.0 Turbocharged Direct Injection Common Rail (TDI CR) Diesel engine and the transformed hybrid electrified powertrain are designed to compare performance. A novel methodology is introduced using Netcan plus 110 devices for the CAN bus analysis of the vehicle's hybrid version. The acquired raw CAN data is analyzed using LabVIEW and decoded with the help of the database (DBC) file into physical values. A classical proportional integral derivative (PID) controller is utilized in the hybrid powertrain system to manage the vehicle consumption and CO2 emissions. However, the intricate nonlinearities and other external environments could make its performance unsatisfactory. This study develops the energy management strategies (EMSs) on the basis of enhanced proportional integral derivative-based genetic algorithm (GA-PID), and compares with proportional integral-based particle swarm optimization (PSO-PI) and fractional order proportional integral derivative (FOPID) controllers, regulating the vehicle speed, allocating optimal torque and speed to the motor and engine and reducing the fuel and energy consumption and the CO2 emissions. The integral time absolute error (ITAE) is proposed as a fitness function for the optimization. The GA-PID demonstrates superior performance, achieving energy efficiency of 90%, extending the battery pack range from 128.75 km to 185.3281 km and reducing the emissions to 74.79 gCO2/km. It outperforms the PSO-PI and FOPID strategies by consuming less battery and motor energy and achieving higher system efficiency. [ABSTRACT FROM AUTHOR]

The magnetoelectric (ME) sensor is a new and promising type of magnetic field sensor with ultrahigh sensitivity. However, there are few reports on the research of real‐time measurement system which can promote its practical application. Herein, a novel real‐time measuring approach for weak AC magnetic fields at relatively low frequency is proposed using Metglas/PZT‐5B ME sensors. The system mainly consists of an oscilloscope, a signal generator, and a program developed with LabVIEW programming. Real‐time measurement of relatively low‐frequency magnetic fields has been achieved by using frequency upconversion methods, simultaneously displaying the frequency and magnitude of the magnetic field. As a result, the real‐time measurement system is able to detect a weak AC magnetic field as low as 0.1 nT@1 Hz, which is promising to push the ME sensor to practical application. [ABSTRACT FROM AUTHOR]

Visible and near-infrared (VIS-NIR) spectral technology is fast, accurate, and non-destructive, which meets the requirements of the separation of coal and gangue. However, the performance of the classification models established by the spectra collected according to the usual single-location collection methods was unsatisfactory. Simulating the production conditions of coal gangue sorting, this paper proposed a multilocation spectral feature fusion identification method for coal and gangue to improve the identification accuracy and developed an identification system. In the multilocation spectral collection method, the spectra of the sample were collected at three locations under the probe, which obtained richer information. In the classification models built based on different feature fusion methods, the one-dimensional convolutional neural network model with feature layer fusion had the strongest classification ability, with an accuracy of 97.61%, an improvement of 8.84% over the best single-location model. The regions of interest for model decision-making were visualized using the Gradient-weighted Class Activation Mapping (Grad-CAM) method to explore the reasons why the multilocation feature fusion method was more advanced. Furthermore, a coal gangue identification system was developed using LabVIEW, which can achieve fast and accurate recognition with an accuracy of 93.15% and an expenditure time of 1.241 s. [ABSTRACT FROM AUTHOR]

A novel detection method, known as RGB‐tracking, was utilized to quantify the relative color changes in reactants/products during the dyeing of a solution of indigo as a model compound. The RGB‐tracking system consists of a digital camera, a light source, a data acquisition device, a LabVIEW program, and its built‐in function (Machine Vision). For the reduction of indigo, two types of reagents were employed: sodium dithionite (Na2S2O4) for the chemical redox process and yeast (Saccharomyces cerevisiae) for the biological fermentation process. As a result, in the case of chemical redox during the reduction of the indigo solution, the progress of the reaction can be described by a color change, that is, the curves of R‐ and G‐pixels, respectively. When the curve for the G‐pixels began to increase, this indicated that leuco‐indigo is being formed. A dramatic increase in the R‐curve indicates that the amount of leuco‐indigo has exceeded than that of indigo itself and that the reaction will gradually reach equilibrium. In contrast to this, additional complex behavior was observed in the case of biological fermentation. When the RGB‐tracking curves for the R‐ and G‐pixels reach their maximum values, this indicates that the concentration of leuco‐indigo was significantly higher than that of indigo itself. The flattening of the RGB‐tracking curves indicates that the reaction has reached equilibrium. [ABSTRACT FROM AUTHOR]

In the present paper, an affordable innovative physical experimental equipment consisting of an upper computer, an ultrasonic sensor module, and an Arduino microcontroller has been designed. The relationship between the position of the slider fixed on two springs and time is measured by using the ultrasonic sensor module. A system for slider motion data and image acquisition is constructed by using the LabVIEW interface of Arduino UNO R3. The purpose of this experiment is to demonstrate and interpret the propagation of waves represented by harmonic motion. The spring oscillator system including a slider and two springs is measured and recorded, and the motion can be realized using curve fitting to the wave equation in Sigmaplot. The vibration periods obtained from experimental measurements and curve fitting of the wave equation are 1.130 s and 1.165 s, respectively. The experimental data are in good agreement with the theoretical model. The experimental measurement results show that the maximum kinetic energy is 0.0792 J, the maximum potential energy is 0.0795 J, and the total energy at the position of half the amplitude is 0.0791 J. The results verify the mechanical energy conservation of spring oscillator system in a short time. This self-made instrument has improved the visualization and the automation level of the corresponding experiments. [ABSTRACT FROM AUTHOR]

In the process of metal wire and additive manufacturing, due to changes in temperature, humidity, current, voltage, and other parameters, as well as the failure of machinery and equipment, a failure may occur in the manufacturing process that seriously affects the current situation of production efficiency and product quality. Based on the demand for monitoring of the key impact parameters of additive manufacturing, this paper develops a parameter monitoring and prediction system for the additive manufacturing feeding process to provide a basis for future fault diagnosis. The fault diagnosis and prediction system for metal wire supply and additive manufacturing utilizes STM 32 as its core, enabling the capture and transmission of temperature, humidity, current, and voltage data. The upper computer system, designed on the LabVIEW 2019 virtual instrument platform, incorporates an LSTM neural network model and facilitates a connection between LabVIEW and MATLAB 2019 to achieve the prediction function. The monitoring and prediction system established in this study is intended to provide basic research assistance in the field of fault diagnosis. [ABSTRACT FROM AUTHOR]

Utilizing an embedded system is crucial for exploring various fields of study, such as ground wave propagation, which interests earth and civil engineering scientists/students. The constructed system includes a data acquisition (DAQ) module and vibration sensors, which can be employed to study wave propagation. It is particularly beneficial for students lacking access to necessary instruments. The sensors utilized are MEMS accelerometers. Developed using LabVIEW programming software, a graphical interface controls the DAQ and visualizes the wave signals. The primary parameter of the DAQ is the sampling frequency, which is adjustable by the user from 1 kHz to 25 kHz. Consequently, when testing with distances ranging from 1 to 10 m between the sensor and the source, a sampling rate exceeding 10 kHz represents ground acceleration reliably. Another aspect addressed in subsequent studies using this system involves analyzing the results to characterize ground wave attributes. [ABSTRACT FROM AUTHOR]

This paper is devoted to the improvement existing models of electronics devices, which are used in powers electronics as switching devices, and investigate a LabVIEW-based automatic test-bench for Silicon carbide (SiC) power devices. In recent years, power electronic devices are required to be capable handle with higher voltage, leads to development of new generation of power electronic devices, such as SiC devices. However, using a simulation platform, such as Spice, to diminish the complexity of power electronic design with these new devices is hindered by the lack of precise models. The proposed test-bench enables not only measuring static characteristics of SiC power devices, but also extracting key parameters required by simulations. These extracted parameters are then employed in the existing device model, and the simulation results which are based on the model with original parameters and models with extracted parameters are compared with measured results. The comparison clearly demonstrates that parameters obtained from the proposed test-bench significantly enhance the Spice model. [ABSTRACT FROM AUTHOR]

This paper describes the design and the development of laser edge isolation (LEI) system for Si solar cells. It consists of a Q-switched 532 nm Nd:YVO4 laser source, an optical set up, a system motorized (X-Y) linear stages, a cell fixing system based on vacuum chuck, a camera to visualize the working zone and a He-Ne laser source for optical alignment. The command and control of the LEI system is ensured by a LabVIEW program and National Instruments (NI) devices. The designed system allows the positioning of the continuous isolation grooves very close to the edges leading to maximize the solar collection area and thus the efficiency. The proposed and developed approach consists to integrate a square shape unity file into the main program with a variable magnification factor, K. In order to demonstrate the operational and functional capabilities of the designed LEI system, series of experiments were conducted, scribing of continuous isolation grooves along four sides of multi crystalline Si solar cells with an area of 100 mm x 100 mm and a thickness of 320 µm to achieve electrical EI. It was shown that the grooves are well continuous and the measured values of continuous grooves lines width and depth are in the range of a typical groove dimensions. The voltage-current characteristics of the solar cells front side EI were analysed using a solar simulator. From our measurements result, we find that the best efficiency equal to 10.4 and the highest fill factor (FF) equal to 67 % ensure a satisfactory edge isolation (EI) of the solar cell. [ABSTRACT FROM AUTHOR]

Within the scope of this study, it was thought that these systems should work faster by investigating the densities in the shipping systems that emerged today and an auditable automation system that could work in real time was tried to be designed. In this context, real-time development of Cartesian robot automation, which can work on the basis of LabVIEW with computer vision, has been provided. In the developed object recognition system, using the OpenCV-based SURF method, products are enabled to detect and recognize barcodes faster. After the quick identification processes, the obtained information was transferred to LabVIEW automation and the product was placed in the mini shelf areas designed in real time with the help of a 3D cartesian robot. At the same time, information from the sensors in the automation system and motor position information were received in real time during the product placement stage and transferred to the LabVIEW graphic interface. By making this information controllable in real time, a traceable system was created on the automation screen. It has been understood that the development of these systems will provide an environment for the formation of industry 4.0 and intelligent systems, and gain from time and workforce. [ABSTRACT FROM AUTHOR]

This work is part of a project that includes methods for studying automation elements' functionality. From this project, I chose to present, in this paper, the hardware and software structure used for the study of angular motion. The generation of movement in the sense of controlling the spinning direction and amplitude is achieved by a DC motor. The Discovery Studio module, a Digilent product, controls the motor through the L298N DC motor driver module. The movement parameters are measured through an experimental incremental transducer through a National Instruments data acquisition module. The software created in LabVIEW allows both the control of the motor and the determination of the spinning direction and amplitude. The user has an interface with movement control elements and visualization of measurement results, for various operating conditions. [ABSTRACT FROM AUTHOR]

In order to quickly detect the validity of the measured data during the experiment, an intelligent sensor test and analysis system integrating data acquisition, processing and analysis functions was designed. Using the YL610 sensor comprehensive training platform, with the help of LabVIEW graphical programming and A/D conversion module, the acquisition and analysis of voltage signal was realized. The experimental results show that the system can efficiently retest, filter and process voltage signals below 5 V, and support users to set and verify the independent variables to be tested on demand. In term of data screening, it can judge and delete the large error data points, and correct the data by previewing the data distribution; the corrected data can be processed by the least square method to generate fitting lines, sensor parameters and data charts, by which the measured data can be compared and analyzed. [ABSTRACT FROM AUTHOR]

This paper uses a dynamic six-degree-of-freedom model that considers torsional and lateral motions to predict the impact of pitting on vibration parameters in a spur gearbox for various operating speeds and torque loads. The study examines the dynamic characteristics of a gearbox with localized pitting damage on a single gear tooth using theoretical and experimental approaches. The research analyzes the forced vibrations of a single-stage spur gear system with pitting damage, which includes variations in mesh stiffness, damping, and gear error excitation, to identify symptoms of default. The equation of motion for the rotary gearbox system is established using the Lagrangian method in tandem with Short-Time Fourier Transform (STFT) and frequency-RPM map fault diagnosis. During real-time vibration monitoring, vibration signals are captured via accelerometers and processed in both the time and frequency domains using the LabVIEW data acquisition signal processing package to extract diagnostic information. The experimental findings demonstrate how vibration analysis combined with time-frequency processing can recognize machine conditions even in harsh operational conditions. Moreover, the experimental results indicate a significant similarity with the theoretical analysis and validate the effectiveness of the RPM frequency technique-based pitting detection method, which can be an asset in gear fault monitoring. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder characterized by abnormal brain activity, resulting in seizures, periods of unusual behavior, and, in severe cases, loss of consciousness. If epilepsy is detected early, it may reduce the patient's health risk significantly. Sometimes people's lives could be saved. There are numerous methods for detecting epileptic activity in brainwaves. One such method is through LabVIEW, a graphical programming software. The peak detection method, implemented in LabVIEW, can be used to detect epileptic activity. Because it reduces erroneous detection, this method is more efficient than manual detection. This research demonstrates epileptic activity by detecting peaks in an EEG database that contains both epileptic and non-epileptic EEG waves from online websites such as the Child Mind Institute and pre-processed EEG datasets. A total of 150 EEG waves were examined, with 25 displaying epileptiform abnormalities and the remaining 125 being completely normal. This method was found to be 97.33% accurate in detecting epileptic activity in the brain. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive system for testing and verifying shunt active power filter control methods. The aim of this experimental platform is to provide tools to a user to objectively compare the individual control methods. The functionality of the system was verified on a hardware platform using least mean squares and recursive least squares algorithms. In the experiments, an average relative suppression of the total harmonic distortion of 22% was achieved. This article describes the principle of the shunt active power filter, the used experimental platform of the controlled current injection source, its control system based on virtual instrumentation and control software and ends with experimental verification. The discussion of the paper outlines the extension of the experimental platform with the cRIO RTOS control system to reduce the latency of reference current generation and further planned research including motivation. [ABSTRACT FROM AUTHOR]

Buckwheat plant height is an important indicator for producers. Due to the decline in agricultural labor, the automatic and real-time acquisition of crop growth information will become a prominent issue for farms in the future. To address this problem, we focused on stereo vision and a regression convolutional neural network (CNN) in order to estimate buckwheat plant height. MobileNet V3 Small, NasNet Mobile, RegNet Y002, EfficientNet V2 B0, MobileNet V3 Large, NasNet Large, RegNet Y008, and EfficientNet V2 L were modified into regression CNNs. Through a five-fold cross-validation of the modeling data, the modified RegNet Y008 was selected as the optimal estimation model. Based on the depth and contour information of buckwheat depth image, the mean absolute error (MAE), root mean square error (RMSE), mean square error (MSE), and mean relative error (MRE) when estimating plant height were 0.56 cm, 0.73 cm, 0.54 cm, and 1.7%, respectively. The coefficient of determination (R2) value between the estimated and measured results was 0.9994. Combined with the LabVIEW software development platform, this method can estimate buckwheat accurately, quickly, and automatically. This work contributes to the automatic management of farms. [ABSTRACT FROM AUTHOR]

Traditional yield monitoring in breeding plots is manually conducted, which is labour-intensive and inefficient. To address this issue, a harvester-borne yield monitoring system that collects yield information during the harvesting in plots was designed. The system consists of a host computer and a slave computer. The slave computer used weight and moisture sensors to collect yield information of crops. The host computer used LabVIEW software to design a data management platform that displays and saves yield information and draws yield distribution maps for data visualization. The host and slave computers communicate data through 4G networks. By designing anti-interference measures, the dynamic experimental results showed that the maximum relative errors between the measured weight and moisture content by the system were 1.330% and 2.800%, which met the accuracy requirements of yield testing in plot breeding. The results indicated that the structure of the system is reasonable and can provide reliable yield monitoring tools for researchers in breeding plots. [ABSTRACT FROM AUTHOR]

A fully automated experimental system was designed for simultaneous measurement of the Seebeck coefficient and electrical resistivity of thermoelectric materials in bulk form. The system incorporates a straightforward and easily fabricated sample holder along with commercially available electronic instrument components. The sample holder showcases a compact design that utilizes two Peltier module heaters to induce sample heating and generate the required temperature gradient. System automation and control are achieved through the implementation of a LabView program. The Seebeck voltage and resistance of the sample (under specified temperature conditions) are determined using I–V measurements. The Seebeck voltage and resistance of the sample correspond to the intercept and slope of the I–V characteristic diagram in the four-point probe method, respectively. To verify the accuracy and reliability of the developed apparatus, a variety of experiments were performed on N-type and P-type bismuth telluride samples. The measurement results closely matched those obtained from commercial systems, with an overall data difference of less than 10% for both the Seebeck coefficient and resistivity measurements. [ABSTRACT FROM AUTHOR]

Ultrasound is widely used in medical and engineering inspections due to its non-destructive and easy-to-use characteristics. However, the complex internal structure of plant stems presents challenges for ultrasound testing. The density and thickness differences in various types of stems can cause different attenuation of ultrasonic signal propagation and the formation of different echo locations. To detect structural changes in plant stems, it is crucial to acquire complete ultrasonic echo RF signals. However, there is currently no dedicated ultrasonic RF detection equipment for plant stems, and some ultrasonic acquisition equipment has limited memory capacity that cannot store a complete echo signal. To address this problem, this paper proposes a double-layer multiple-timing trigger method, which can store multiple trigger sampling memories to meet the sampling needs of different plant stems with different ultrasonic echo locations. The method was tested in experiments and found to be effective in acquiring complete ultrasonic RF echo signals for plant stems. This approach has practical significance for the ultrasonic detection of plant stems. [ABSTRACT FROM AUTHOR]

The simulation of the operation of the wind turbine was performed using two programming media: LabVIEW and MATLAB/Simulink, respectively. MATLAB is a high–level programming environment and language specializing in numerical computing, while LabVIEW is a graphical media and programming language that specializes in interfacing with hardware components. MATLAB/Simulink is predominantly used in simulation because it contains libraries with high–level functions, specialized in fields, which help to quickly develop advanced applications. LabVIEW is mainly used for measurement and data acquisition since it features exceptional compatibility with a large variety of hardware. The goal of this study is to determine which medium is better suited for developing the software component of a wind turbine emulator. The requirement for this task are: complex numerical computing, simplicity and observability, hardware compatibility, data acquisition and storage and the possibility of creating a HMI. These constitute the criteria by which the better suited medium is chosen. [ABSTRACT FROM AUTHOR]

In this article, a hybrid powertrain for the Volkswagen (VW) Crafter is designed using the Model-In-The-Loop (MIL) method. An enhanced Proportional-Integral (PI) control technique based on integral cost functions is developed by carrying out a time-based simulation in MATLAB/Simulink software to realize the optimal fuel economy of the vehicle. Moreover, a comparative study is conducted between the vehicle's hybrid and pure electric versions to assess the optimal battery energy consumption per unit distance traveled. Communication within our vehicles' Electronic Control Units (ECUs) is facilitated by a message-based protocol called a Controller Area Network (CAN). Consequently, this paper presents an online CAN Bus data analysis using the Hardware-In-The-Loop (HIL) method. This method uses a standard frame, J1939 CAN protocol, implemented with Net CAN Plus 110 hardware. A graphical user interface is developed on a host Personal Computer (PC) using LabVIEW for decoding the acquired raw CAN data to physical values. The simulation results reveal that the proposed controller is promising and suitable for realizing optimal performance over the HIL method. [ABSTRACT FROM AUTHOR]

Application of fuzzy control has been observed in various engineering fields due to its ability to handle uncertainties and non-linearities. In this study, the advantages of using fuzzy control in heat pump systems are being investigated. Specifically, the performance of a heat pump system with a conventional proportional-integral-derivative (PID) controller is being compared to that of a heat pump system with a fuzzy logic controller. It has been demonstrated by the results that the fuzzy control-based heat pump system offers better performance in terms of energy efficiency, temperature control, and overall system stability. This study contributes to the understanding of the potential benefits of fuzzy control-based heat pump systems and provides a foundation for further research in this area. [ABSTRACT FROM AUTHOR]

Aiming to precisely characterize the performance of micro-compact circulation pumps, a high-precision closed miniature circulating pump performance test system based on LabVIEW was designed. Firstly, based on the four design criteria of circulating pump test system, the overall framework of closed circulating pump test system was established.Then, virtual technology, sense technology and test technology were combined to complete the hardware construction to collect and transform the parameters, and a data management center was adopted to realize the management of the software. Finally, performance test and cavitation test were designed, and four aspects of test logic, data analysis, flow rate adjustment and application comparison were analyzed and summarized. The results of the work demonstrate that the test system is used for performance test on the micro-circulation pump and for the cavitation test, and that it is a good solution to the problem of the high precision characterization of the performance of the mini circulation pump, and the accuracy of the flow through control is maintained at a steady ±0.5%, which proves out the reliability of the test system. The test system may provide a test method for micro circulation pumps as well as technical support for monitoring the operational status of high precision micro circulation pumps. [ABSTRACT FROM AUTHOR]

With the increasing world population, energy production and distribution has a very important place today. Insulators are one of the elements that play the most active role in the reliability and continuity of electrical transmission and distribution lines. Faults from insulators account for the highest rate of power system failures. Icing and subsequent insulator failures cause flashover on the insulator surface in areas where intense winter conditions occur, leading to power outages and major socioeconomic consequences. Leakage currents are directly related to the surface properties of ice-coated insulators. In this study, the surface of insulators made of different materials were iced in a laboratory environment and leakage currents were studied by applying an alternating voltage with a network frequency to the insulators according to the degree of icing. Data were obtained with the help of LabVIEW program and leakage currents of porcelain, glass and silicon insulators were compared. The relationship between the leakage current was established by measuring the ambient temperature and humidity values of the insulator. [ABSTRACT FROM AUTHOR]

The present research exposes a novel methodology to manufacture fiber optic sensors following the etching process by Hydrofluoric Acid deposition through a real-time monitoring diameter measurement by computer vision. This is based on virtual instrumentation developed with the National Instruments® technology and a conventional digital microscope. Here, the system has been tested proving its feasibility by the SMS structure diameter reduction from its original diameter of 125 μ until approximately 42.5   μ m . The results obtained have allowed us to demonstrate a stable state behavior of the developed system during the etching process through diameter measurement at three different structure sections. Therefore, this proposal will contribute to the etched fiber optic sensor development that requires reaching an enhanced sensitivity. Finally, to demonstrate the previously mentioned SMS without chemical corrosion, and the etched manufactured SMS, both have been applied as glucose concentration sensors. [ABSTRACT FROM AUTHOR]

Eliminating the Gibbs oscillations that occur during the Finite Impulse Response (FIR) digital filter design with the Fourier Series method will ensure correct filtering. For this reason, the development of the window improves the performance of the filter and, therefore, the system. In this study, the cosh window function is designed using Particle Swarm Optimization, which is a preferred optimization method in many areas. Thus, alternatives to the standard results obtained from the existing traditional calculations will be produced, and different windows that perform the same function will be obtained. In addition, exponential and cosh window functions were designed in LabVIEW environment, which is a graphical programming language-based program, and the designed windows were analyzed at different parameter values. LabVIEW provides a fast and easy programming environment, and it provides the opportunity to realize real-time applications with its external hardware. Utilizing this feature, the amplitude spectrum of cosh window designed in LabVIEW is displayed in real time for different window parameter values. As a result, FIR digital filters were designed using cosh window based on optimization and the cosh window designed in LabVIEW, and the distorted EEG signal was filtered using these filters and displayed in real time. [ABSTRACT FROM AUTHOR]

This article is about the design, development and validation of a new monitoring architecture for individual cells and stacks to facilitate the study of proton exchange fuel cells. The system consists of four main elements: input signals, signal processing boards, analogue-to-digital converters (ADCs) and a master terminal unit (MTU). The latter integrates a high-level graphic user interface (GUI) software developed by National Instruments LABVIEW, while the ADCs are based on three digital acquisition units (DAQs). Graphs showing the temperature, currents and voltages in individual cells as well as stacks are integrated for ease of reference. The system validation was carried out both in static and dynamic modes of operation using a Ballard Nexa 1.2 kW fuel cell fed by a hydrogen cylinder, with a Prodigit 32612 electronic load at the output. The system was able to measure the voltage distributions of individual cells, and temperatures at different equidistant points of the stack both with and without an external load, validating its use as an indispensable tool for the study and characterization of these systems. [ABSTRACT FROM AUTHOR]

The spindle system is important in the machine tool. The vibration signal generated by the spindle system in the machine tool has a great influence on the machining accuracy of the product and the abrasion and lifetime of the tool. Therefore, it is necessary to monitor the vibration signal in the machining process of the machine tool spindle in real time. The vibration sensor is used to monitor the vibration signal of the machine tool spindle in this paper. The data collected by the sensors are transmitted to the Bluetooth module by the serial port for wireless communication. The vibration signal and its frequency domain transformation of the spindle are received by LabVIEW software platform, and the original waveform is displayed, the threshold alarm and the storage of data are realized. The experimental results show that the designed system can realize the online monitoring of the vibration state of the machine tool spindle effectively. [ABSTRACT FROM AUTHOR]

The research was to further improve the automation level and packaging accuracy of feed crushing machinery. The study designed an intelligent control and online monitoring platform for feed crushing system based on LabVIEW and PLC. Regarding the structure and process flow of feed crushing machinery, the hardware and software design of control system were completed using PLC as core controller. LabVIEW was an upper computer that achieves centralized control and data monitoring. Propose a control mode that can adapt to system to improve packaging accuracy. The results showed that the intelligent control and online monitoring platform of feed crushing system could operate smoothly, improve the platform's data collection and on-site application capabilities, the control mode that improved packaging accuracy had a significant effect, with an accuracy controlled within 0.5%. The study indicates that the research can provide reference for the design of feed crushing machinery control system. [ABSTRACT FROM AUTHOR]

Gearboxes are one of the most important and widely exposed to different types of faults in machines. Therefore, manufacturers and researchers have made significant efforts to develop different fault detection and diagnostic approaches for gearboxes. However, many research foundations, such as universities, are currently working on developing different gearbox test rigs to understand the failure mechanisms in gearboxes. As a result, in this article, a gearbox testing rig was proposed and fabricated to evaluate gear performance under lowspeed working conditions. It describes the primary mechanical apparatus and the measurement tools used during the experimental analysis of a multistage gearbox transmission system. The data-gathering equipment used to acquire the observed vibration data is also discussed. LabVIEW software was used to build a data acquisition platform using an accelerometer and a NI DAQ device. Then different vibration tests were conducted under different operating conditions, when the gearbox was healthy and then faulty, on this test rig, and the gathered vibration data were analyzed based on time domain signal analysis. The preliminary results are promising and open the horizon for simulating different gearbox test scenarios. [ABSTRACT FROM AUTHOR]

This research presents a web-based lighting laboratory infrastructure that allows students to access and control application tools in lighting technology education through online real-time equipment. Designed for Distance Vocational Training and Education, this system uses the LabVIEW Virtual Instrumentation Program to control lighting levels. In this program, the interface developed allows students to control and monitor applications online using cameras, sensors, and controllers. In the modeled system, the lighting levels of LED lamps are controlled through PID controllers. Furthermore, a web page was designed that provides synchronized (simultaneous) access to application instrumentation for the students. Each user can run applications in a specific period through this website. Students can also monitor the lighting level of the laboratory in real-time with a webcam. Individual storage of the data obtained in the model also supports conducting necessary analyses. Students can strengthen their theoretical knowledge by running lighting technique experiment applications with real equipment in the Distance Vocational Training and Education. In the evaluation part of the research, the answers are given by the students (95%) also stated that they increased the theoretical knowledge of doing remote experiments. In total 98.5% of students believe that the ability to repeat experiments anywhere in this system will accelerate the learning process. [ABSTRACT FROM AUTHOR]

In this study, elastic waves generated from a SKD11 (HV670) steel specimen under various corrosive solutions were investigated. The frequency characteristics of the waves, as well as how hydrogen aggregation and crack propagation affected these characteristics, were studied using time-frequency analysis conducted in LabVIEW. The waves detected were either in a low frequency band, below 40 kHz, or in a high frequency band, above 60 kHz. The low frequency waves below 40 kHz were caused by hydrogen aggregation and corrosion, while the high frequency waves above 60 kHz were caused by crack initiation and propagation due to HAC. Inspection by SEM confirmed that the grains and cracks were caused by HAC via hydrogen embrittlement. [ABSTRACT FROM AUTHOR]

In order to clarify the thermal efficiency of plasma torch under different working parameters, so as to accurately get the real-time energy of plasma jet,and then applying plasma technology to the preparation of aluminum nitride powders and other materials, based on a self-developed plasma torch working with two gas injections, the real-time online thermal efficiency of the proposed plasma torch was monitored by using virtual instrument technology, and the thermal efficiency characteristics was analyzed and discussed. The experimental results show that with a fixed working current, the thermal efficiency increases from 51% to 67% with increasing the main gas injection flow-rate, while it increases first and then decreases with increasing the protective gas injection flow-rate. The thermal efficiency of the proposed plasma torch working with a work current of 70 A is higher about 4% than that at 100 A. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are often to perform autonomous sensing and controlling the real world objects through the sensor nodes across the globe. Since these sensor nodes are operated by the energy of the battery that has been performed a vital role in deploying a sensor network. Hence, the battery power needs to be minimized to prolong network lifetime for healthcare applications. The monitored data transmission is very important to process in building wireless sensor networks. In order to provide efficient data transmission wireless technology standards are followed as IEEE 802.15.4 standards that provide desirable communication between end to end with optimal routes using the proposed Energy Optimization Algorithm. The proposed algorithm has been improved the data packet transmission efficiency up to 25% and also helps to prolong the life time of Wireless Sensor Networks in order to achieve the efficient data transmission for health care monitoring. [ABSTRACT FROM AUTHOR]

With the purpose of improving the voltage quality of a 300 MVA energy storage generator (MG300) for HL-3 device, a new excitation controller (PEC) suitable for pulsed discharging mode is designed, which is based on NI CompactRIO (CRIO) hardware platform and adopts digital proportional integral derivative (PID) algorithm. This controller is based on an embedded real-time system to realize an excitation control algorithm combining feed-forward and PID feedback. According to the reference waveform preset by the central control system (CCS), the output voltage of MG300 is controlled by the PEC in real-time during the plasma discharging and energy release. The new PEC is suitable for the development of advanced excitation control algorithms. With a modular design, it has the advantages of instant reconfiguration and flexible expansion. Based on the basic idea of engineering processing, the excitation feedback control system (EFCS) under the pulse discharge process of MG300 is analyzed. Then, the determination of this hardware architecture and the construction of programs are performed. The simulation model research is carried out to better understand the working mechanism of the EFCS during a discharging process. Subsequently, the engineering commissioning is carried out under the condition that MG300 provides energy for Poloidal Field (PF) Coils. In addition, the MG300 terminal voltage does not vary by more than 3.3% when multiple PF loads are applied. The test results show that PEC meets design requirements and achieves the desired goals. • A novel excitation controller is designed for the motor generator for HL-3. • The controller, suitable for a pulsed mode, integrates the excitation regulator and the triggering unit. • It is validated that the controller is effective under sudden loads and unloads on the generator. [ABSTRACT FROM AUTHOR]

We present a low-cost and wide-applicability method for measuring the zero-crossing temperature (ZCT) of a ultralow expansion (ULE) cavity by using a scanning transfer cavity. As a demonstration of our method, we leverage a low-fineness scanning confocal Fabry-Pérot interferometer (FPI) and a Helium-Neon (He-Ne) laser as a frequency bridge and reference respectively to characterize the frequency of cavity mode. Combined with a LabVIEW based data acquisition (DAQ) card, we can easily and visually quantify the wavelength of ULE-based stabilized laser relative to the reference laser, further quickly and accurately derive ZCT value by monitoring its dependence on temperature. The total measurement uncertainty is analyzed in detail and determined to be 0.27 °C. Our represented method shows a wide range of applicable wavelength by extending the number of FPI with complementary coating ranges and flexibly selecting frequency references. [Display omitted] • The presented method has the merits of low-cost and wide range of applicable wavelength, which are hard to be satisfied simultaneously in traditional methods. • The scanning transfer cavity can linkage the mode of ULE cavity and reference laser, which can be either a stable laser source or any laser locked by any technique. • By extending the number of scanning transfer cavities and flexibly choosing reference lasers, the presented method shows a wide range of applicable wavelength. • Assisted with data acquisition card, the relative wavelength of measured laser is easily and visually recorded, further ZCT can be quickly and accurately derived. [ABSTRACT FROM AUTHOR]

The value of a semiconductor's diode temperature determines the correct operation of this element and its useful lifetime. One of the methods for determining the die temperature of a semiconductor diode is through the use of indirect thermographic measurements. The accuracy of the thermographic temperature measurement of the diode case depends on the prevailing conditions. The temperature of the mold body (the black part of the diode case made of epoxy resin) depends on the place of measurement. The temperature of the place above the die is closer to the die temperature than the temperature of mold body fragments above the base plate. In addition, the difficulty of its thermographic temperature measurement increases when the surface whose temperature is being measured is in motion. Then, the temperature measured by thermography may not apply to the warmest point in the case where the die temperature is determined. Information about the difference between temperatures of the different parts of the mold body and the die may be important. For this reason, it was decided to check how much the temperature measurement error of the die diode changes if the temperature of the diode case is not measured at the point that is above the die. [ABSTRACT FROM AUTHOR]

For newly developed measuring systems, it is easy to estimate type-B uncertainties based on technical data from the measuring modules applied. However, it is difficult to estimate A-type uncertainties due to the unknown type and level of interferences infiltrating the measuring system. This is a particularly important problem for measurements carried out in the presence of typical of power grid disturbances. The aim of the research was to develop a method and a measurement stand for experimental assessment of uncertainties in a measuring system that makes use of data acquisition modules containing analog-to-digital converters (ADCs). The paper describes, in detail, the design of a completed test stand. It presents an original application in the LabVIEW environment, which enables testing the dependence of the uncertainties with the quantity of the measurements averaged in a series, for different kinds and levels of interferences infiltrating the measuring path. The results of tests for several popular measuring modules are presented. An analysis of the determined uncertainties was carried out in relation to the parameters of the tested measurement modules and for various levels of interferences. It is proved that an increase in the number of averaged measurements to approx. 100–200 always results in a decrease in uncertainty for each tested module and under all conditions. However, a further increase in the quantity of measurements, even up to 1000 averaged measurements, proved reasonable only for high-accuracy modules, in particular with a high level of interferences. An excessive increase in the quantity of averaged measurements proved a low effect for modules characterised by a low resolution and with a low level of interferences. The measurement results also proved that when estimated, uncertainties in the interference probability distribution are significant, especially if they deviate from normal distribution. [ABSTRACT FROM AUTHOR]

Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof of design and manufacturing tests are needed. Test sites are designed to carry out two things, i.e., proof of design and manufacturing tests. The team responsible for designing test sites considers several parameters like deployment cost, test time, test coverage, etc. In this study, an automated test site using a supervised machine learning algorithm for testing an ultra-high frequency (UHF) transceiver is presented. The test site is designed in three steps. Firstly, an initial manual test site is designed. Secondly, the manual design is upgraded into a fully automated test site. And finally supervised machine learning is applied to the automated design to further enhance the capability. The manual test site setup is required to streamline the test sequence and validate the control and measurements taken from the test equipment and unit under test (UUT) performance. The manual test results showed a high test time, and some inconsistencies were observed when the test operator was required to change component values to tune the UUT. There was also a sudden increase in the UUT quantities and so, to cater for this, the test site is upgraded to an automated test site while the issue of inconsistencies is resolved through the application of machine learning. The automated test site significantly reduced test time per UUT. To support the test operator in selecting the correct component value the first time, a supervised machine learning algorithm is applied. The results show an overall improvement in terms of reduced test time, increased consistency, and improved quality through automation and machine learning. [ABSTRACT FROM AUTHOR]

A comprehensive test system for proton exchange membrane fuel cells (PEMFCs) is designed and developed for monitoring and controlling the inlet and outlet parameters and safety issues of fuel cells. The data acquisition and output instruction rely on the connection between PLC (programmable logic controller) and OPC (object linking and embedding for process control). Based on Siemens S7-200 series PLC and PID (proportion integration differentiation) technology, the margin of error in relative humidity of inlet air is controlled at less than 0.7%. Furthermore, a hydrogen recycling system and an alarm module are introduced, considering the hydrogen or nitrogen solenoid valve power failure, cooling fan power failure, temperature anomaly, and hydrogen leakage. This developed test system is evaluated by the experimental investigation of PEMFC performance. The results show that the test system has very good test and control performances. At a cell temperature of 40 °C, enhanced performance in the polarization tests is depicted at a high humidification temperature of 60 °C. [ABSTRACT FROM AUTHOR]

This research designed a DC motor control system experiments and developed a platform for on-line implementation of these experiments. This was with a view to contributing to the number of online laboratory experiments while providing a common platform for other on-line users. In this research, three experiments were designed using LabVIEW software. The developed platform is implemented online using the Massachusetts Institute of Technology interactive laboratory architecture. The control system performance was then evaluated by administering questionnaires to users with the aim of eliciting information on the ease of use of the operating system. The successful control of the DC motor and integration of the experiment engines into the iLab Interactive architecture were achieved. In conclusion, the online DC motor control laboratory was deployed and provided ready access to a DC motor control over the Internet with beginner and intermediate-level experiments in the field of control system and engineering [ABSTRACT FROM AUTHOR]