bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of TiO2 photocatalyst towards methylene blue degradation using simple dip coating
Authors: Utami Fisca Dian , Surtiyeni Neni , Amalia Nadya , Sustini Euis , Abdullah Mikrajuddin
Published: June 2022

The purpose of a recent study is to evaluate the performances of TiO2 in destroying organic effluent. TiO2 photocatalyst presented a high performance in eliminating methylene blue (MB). Technical anatase of titania was employed. Dip coating was employed to immobilize titania onto the transparent plastic, followed by putting the additional polymer (alteco glue). From the photocatalytic testing, 100 mL of 25 mg L-1 MB was clearly eliminated after 12 hours of irradiation under solar exposure. Variation of TiO2 concentration and the additional polymer was carried out to study the performance of the catalyst.
Size effect at discharging process of coconut oil as latent thermal energy storage
Authors: ‘Ulhaq S D , Yusuf A , Wonorahardjo S , Sutjahja I M
Published: June 2022

Coconut oil is one of the organic PCM materials with high thermal energy storage capability in the form of sensible and latent heat. Ideally, the latent heat storage occurs at a relatively constant temperature associated with phase change transition. Due to relatively low thermal conductivity, the size effect is important to optimize material performance, particularly at the discharging process related to latent heat release. This study will show the simulation results of the size effect in the solidification process of coconut oil by using ANSYS FLUENT. Three plastic balls with radii 2 cm, 3 cm, and 6 cm filled with coconut oil solidified from 308 K to 293 K, and several temperature detectors were placed in the ball to study the heat exchange process. The input parameters of density, heat capacity, thermal conductivity, and viscosity were taken from previous experimental studies. We reported the time evolution of temperature and liquid fraction until the molten coconut oil solidified from different detector positions in each ball.
Effect of Tetrabutylammonium on Methylene Blue Adsorption
Authors: Ledyastuti M , Sofyan O P , Zulfikar M A
Published: June 2022

Artificial dyes such as methylene blue are commonly detected in textile industry wastewater. Clay is commonly used as an economical and effective adsorbent for methylene blue in textile waste treatment. The addition of surfactants into the system is usually done to increase the adsorption capacity of the clay. In this study, we used a molecular dynamics simulation method to study the effect of tetrabutylammonium organic surfactant on the adsorption process of methylene blue on the clay surface. The modelled clays are pyrophyllite and montmorillonite which are hydrophobic and negatively charged, respectively. The simulation results show that the addition of tetrabutylammonium surfactant causes a 12 % and 40% decrease in the binding of methylene blue to the surfaces of pyrophyllite and montmorillonite, respectively. This is due to the occurrence of competitive adsorption in both systems. Therefore, the addition of tetrabutylammonium surfactant was considered ineffective in increasing the adsorption capacity of pyrophyllite and montmorillonite.
Qualitative Modelling the Dancing Volvox with Two-Body System: Comparing Simple Mechanics with Observation Video
Authors: Nurafni Sevi , Taufik Intan
Published: June 2022

Volvox cells normally construct a spherical colony of hundred of cells and moving together to perform their basic needs. More than moving a single colony, two attached volvox colonies can ‘dance’ and move together. This system can be modeled as a two-body system, where its center of mass (COM) is performing simple translational (TRAN) motion, while the two colonies center is rotating around the COM with roll (ROLL) or spin (SPIN) motions. From the available observation video, about 10 s or 325 frames can be isolatedfor Sobel edge detection to get a clear picture of the dancing motion of two volvox colonies. It has been observed that the dancing volvox has a superposition motion of the other motion (TRAN, ROLL, SPIN), which has been compared qualitatively with the simple mechanics model of the two-body system. From the model, the translational velocityis about 1.25 m/s, and its roll and spin angular velocity are about 0.785 and 3.063 rad/s, respectively. The results of the study concluded that the mode of motion of the two Volvox colonies was a combination of spin and translational motion.
Electric field-induced modification of Dzyaloshinskii-Moriya interaction in Fe/Mg0(001) with heavy metal insertions
Authors: Pradipto Abdul-Muizz , Nakamura Kohji
Published: June 2022

The effect of external electric field on the Dzyaloshinskii-Moriya interaction (DMI) in Fe/M/MgO(001) (M=Os, Ir, Pt, Au) is investigated by means of first principles full-potential linearized augmented plane wave (FLAPW)-based Density Functional Theory method. We find that, apart from the Au layer insertion, the sign of the DMI is altered by the introduction of the heavy metal, such that the magnetic chirality in Fe/M/MgO(001) is inverted from that of Fe/MgO(001). The magnitudes of DMI in the Fe/Os/MgO and Fe/Ir/MgO are enhanced by 5 - 7 times compared to that without the heavy metal insertion. The increase of the DMI can be attributed to the strength of spin-orbit coupling of the heavy metal layer, implied by the asymmetry of the orbital moments of the heavy metals within the spin spiral structures. When an external electric field is applied, no significant modification to the DMI can be observed. Our work suggests that additional heavy metal layer might be necessary for a fine control of DMI, and hence of the overall magnetic domain-related properties, by external gate voltages.
Some Possible Schemes in Higher Dimensional Stationary Skyrme Blackhole Formulation
Authors: Fadhilla E S , Gunara B E , Atmaja A N
Published: June 2022

In this article we present some possible ways on how to formulate a stationary blackhole in higher dimensional generalized Skyrme model with minimal gravitational coupling. We consider a generalized Skyrme action which includes all possibble higher order kinetic terms as the representations of all strain tensor invariants. Some possible spacetime ansatzs are mentioned, such as Myers-Perry metric and general higher dimensional axisymmetric metric with one rotation plane. Here, we find that there exist some Skyrme field ansatzs, obeying the same symmetries of the spacetime manifold, which lead to a diagonal strain tensor.
The Relative Entropy of One Graviton Creation in Early Universe
Authors: Trenggana A , Zen F P
Published: June 2022

The detection of nonclassicality of primordial gravitational waves (PGWs) is one way to prove the quantum theory of gravity. The nonclassical feature can be seen as a non-gaussianity, that could happen if there is a graviton creation in a squeezed state of Bunch-Davies vacuum. This condition would also produce an entanglement state. In this paper, we study that non-gaussianity by using relative entropy as a measurement. We find that, when the value of α (the entanglement constant) is near to one, the non-gaussianity would get its highest value. For the presence of matter field, the non-gaussianity still has the same characteristic for different values of α. But, in this case, the relative entropy value is constant for every value of the squeezed parameter.
Preparation of Platina Nanoparticles with the Presence of Cellulose Nano Crystals
Authors: Wibowo Arie , Santoso Rachmad , Judawisastra Hermawan , Budhi Yogi Wibisono
Published: June 2022

Platina play a crucial role in catalytic converter device as one of catalyst that convert toxic gases in the exhaust gas emission to less toxic gas pollutant. The performance of this device can be significantly elevated by implementing platina nanoparticles (Pt NPs) because catalytic performance can be increased by decreasing its particles size. However, nanoparticles are not stable and tend to agglomerate, thus prohibit formation of nano particles. In this context, utilization of cellulose nano crystals (CNCs) in fabrication of Pt NPs are attractive due to their ability to encourage nucleation and prevent agglomeration of nanoparticles. In this study, Pt NPs was prepared by reduction of H2PtCl6 solution at various temperature (25, 33 and 40 °C) with the presence of CNCs. Based on visual observation, darker precipitate was observed by increasing temperature. Further characterization using UV-Vis spectroscopy showed that about 90% of Pt4+ in solution were successfully convert to dark particles at 40 °C. Transmission electron microscopy (TEM) and selected area electron diffraction (SAED) revealed that the dark particles in sample is Pt NPs with particles size 16.5 ± 3.2 nm.
Modification of screen-printed carbon electrode (SPCE) by the Nafion functionalized silicon nanoparticles (SiNP/Naf) materials in non-enzymatic electrochemical sensor for uric acid (UA) detection
Authors: Huda N , Sambegoro P L , Septiani N L W , Iqbal M , Sholehah A , Yuliarto B
Published: June 2022

A non-enzymatic electrochemical sensor has been successfully developed to detect uric acid (UA) based on a modified screen-printed carbon electrode (SPCE) using Nafion functionalized silicon nanoparticles. Silicon nanoparticles (SiNPs) material is used because of their advantages, including its abundant availability, good biocompatibility, and adjustable porosity and surface area according to the synthesis method used. Nafion is a sulfonated tetrafluoroethylene-based fluoropolymer-copolymer that has been widely used for electrochemical sensors and is functioned as a stabilizer of the sensor. In this study, SiNPs material was successfully synthesized through the non-thermal chemical vapor deposition method. XRD diffractogram and SEM image confirmed its structure and morphology. The crystallinity of the produced SiNPs is 69.85%. SEM-EDS characterization was also carried out to confirm the success of the SPCE modification by SiNPs and SiNPs/Naf materials. The changes in the morphology of SPCE and the EDS spectrum that were measured indicated the success of the SPCE modification process for each stage. Cyclic voltammetry, electrochemical impedance spectroscopy, and differential pulse voltammetry study were used to analyze the electrochemical characteristics and performance of non-enzymatic electrochemical sensors based on SPCE/SiNPs/Naf structures against uric acid analytes. Based on the results of electrochemical analysis, the sensitivity, detection limit, and quantification limit of the sensor are 0.01 μA.mM-1. cm-2, 0.21 μM, and 0.69 μM respectively in the linear measurement range of uric acid concentration of 10 – 1000 μM. Then, a sensor stability study was also carried out which resulted in an RSD value of 4.83%.
Review of Learning Result of The Physics Base on SSCS (Search, Solve, Create, and Share) Model in Terms of Critical Thinking Skills
Authors: Putri Q S , Suharno  , Budiawanti S
Published: June 2022

Since 2020, the whole world has been affected by Covid 19. The impact of the Covid 19 pandemic is not only on the social sector but also on the education sector. So that education must continue to be carried out using distance learning or online. However, changes in the learning process also affect the teaching and learning conditions of students and teachers. Therefore, it is necessary to apply an appropriate learning model. One of them uses the SSCS learning model. SSCS is a learning model that can improve critical thinking skills. The SSCS model has four stages: search, problem-solving (solve), create, and share. At the search stage, students are taught to understand the problem. Next, students make a plan to solve the problem. In the next step, students build a solution from the problem-solving strategy that has been arranged in the previous stage. Finally, the solutions that have been constructed are disseminated and evaluated for continuous improvement. The purpose of this paper is to provide a comprehensive description of the development of the SSCS model, especially in physics learning that has been carried out to improve critical thinking skills. It was concluded that distance and direct knowledge using the SSCS learning model experienced an increase in abilities and scores of around 40% - 50%.
Photovoltaic Performance of TiO2 Mesoporous Films with Different Working Areas for Dye-sensitized Solar Cells
Authors: Nasikhudin  , Astarini Nadiya Ayu , Rahman Muhamad Fadhil , Diantoro Markus , Aripriharta  , Osman Zurina
Published: June 2022

The photovoltaic performance of Dye-sensitized Solar Cells (DSSC) could be optimized by playing the working area of the mesoporous TiO2 photoanode. A small working area will enhance the photovoltage and power conversion efficiency. In comparison, a large working area will improve the recombination rate and reduce the photon particle transport rate at the photoanode. The TiO2 based photoanode layer consists of a blocking layer and mesoporous paste deposited using spin coating and screen printing technique, respectively with various working areas of 0.25, 0.30, and 0.56 cm2. The cells were characterized using XRD, SEM-EDX, UV-Vis spectroscopy, and solar simulator. XRD confirmed that the TiO2 was in the anatase phase. SEM image represented a high surface area of mesoporous TiO2 indicated by porosity level up to 70%. The elemental analysis of TiO2 using EDX observed the presence of Ti and O peaks. The TiO2 mesoporous-based photoanode immersed in 0.07 mM of N719 solution possessed an absorbance range in the ultraviolet to the visible light. The working area of 0.25 cm2 exhibited a promising power conversion efficiency of 2.02% with a circuit current density of 10.8 mA/cm2 under an illumination light of 100 mW/cm2.
SiamAVOT: A High-performance Siamese Network Tracker for Aerial Visual Object Tracking
Authors: Deng Pingyu , Qiu Xuyi , Yao Ziyu , Li Lei
Published: June 2022

Aerial vision object tracking technology plays an increasingly critical part in intelligent perception and task cognition when aircraft perform various reconnaissance missions. However, the particularity in object types and visual angles in aerial vision imagery render the tracking process more prone to deformation, scale variation, motion blur and occlusion, making this technique very challenging. A high-performance Siamese network tracker for aerial visual object tracking, SiamAVOT, is proposed to deal with this problem in this paper. First, we utilize the SiamCAR infrastructure to introduce the Bottleneck Attention Module (BAM) attention mechanism after its backbone network for fusion of low and high level features to improve recognition for deformation object features. Then, we change to Distance-IoU (DIoU) loss for the bounding box regression during the training process to improve the network’s ability to predict scale variation. Finally, a Kalman filter online learning module that integrates time and space trajectory information is designed to solve the object motion blur and occlusion disappearance problem in the inference process. The proposed SiamAVOT achieves leading performance on the UAV123 and AVOT40 aerial datasets and can run in real-time at 72 FPS.
Crack Detection based on Convnext and Normalization
Authors: Zhang Hongfei , Liu Chun , Ho James , Zhang Zhiwei
Published: June 2022

Cracks, mostly caused by irregular expansion and contraction, indicating potential damage to a building, are of great significance to building quality assessment and predicting potential disasters like earthquakes. In this paper, after a comparison of the conventional methods using image processing techniques to detect the cracks and the newly-proposed CNN method, ConvNeXt is involved, which shows more sufficiency and stability. At the stage of the experiment, due to the specialization of the datasets and the methodology, a serial of image processing is engaged as the preprocessing before the data are used to train the CNN model. By using two crack-specialized datasets, namely, Concrete Crack Images for Classification and the SDNET2018, over 60,000 images are selected as the training samples. After adequate training and the AdamW involved as the optimizer, an accuracy of 99.0% on the dataset is reached and the expected results of accuracy of 99.0% are obtained.
Single Image Super-Resolution Algorithm based on Fixed-Point Multi-Model Gaussian Process Regression
Authors: Lu Ziwei , Yu Hongfei
Published: June 2022

To solve the problem of large amount of computation in matrix inversion of Gaussian process regression model, a super-resolution algorithm based on local Gaussian process regression of fixed point multi-model is proposed. Firstly, the training samples are classified by Gaussian mixture model, and image patches are randomly selected as fixed points in each type of training samples, and its K nearest neighbor patch are searched. Secondly, local Gaussian process regression model by using its low-mid-frequency components and the corresponding high frequency components. Again, low resolution test image patch is classified, only the K nearest neighbor test image patch is searched during reconstruction. And then, find the nearest fixed point in each kind of image patch, and use the local Gaussian process regression model based on the fixed point to predict its corresponding high-frequency component. Finally, corresponding high frequency information is predicted by using this trained model, which improves the reconstruction efficiency. Experimental results have demonstrated that the proposed algorithm is superior in both quantitative and qualitative aspects against other algorithms.
Scene Classification of Remote Sensing Images Using EfficientNetV2 with Coordinate Attention
Authors: Wang Zengkun , Cao Yang , Yu Hongfei , Sun Caihua , Chen Xuejian , Jin Zhanggen , Kong Weili
Published: June 2022

The high intra class diversity of remote sensing image scene often leads to the problem of difficult classification of remote sensing image scenes. Therefore, this paper proposes the CA-EfficientNetV2 model, embedding the coordinate attention into the head of the EfficientNetV2 network to enhance the classification effect. The coordinate attention is used to generate the position relationship between image spaces and channels so as to learn features efficiently. We trained three improved models CA-EfficientNetV2-S, CA-EfficientNetV2-M and CA-EfficientNetV2-L on UC Merced remote sensing dataset respectively. The classification accuracy reached 99.55%, 97.49% and 97.09% respectively. Among them, CA-EfficientNetV2-S had the best effect, which was improved by 0.8% compared with the original network.
Research on Skin Disease Health Detection of College Students based on Deep Learning
Authors: Zheng Guiyue , Li Meng , Zhang Fuchun , Wang Baiyang , Ji Yuelong
Published: June 2022

Skin disease is a common diseases. Although it is very common, the manifestations of skin diseases are various, and the diagnosis process is relatively difficult, and the requirements for dermatologists are also very high. And the recognition efficiency of detection also needs to be improved. To this end, this paper mainly investigates the potential of classifying skin diseases in deep learning convolutional neural networks to enhance the recognition accuracy. The VGG16 neural network was trained using the training data of the ISIC 2019 challenge, and the training data was augmented to increase the accuracy of the model, and accurately classify 3 skin diseases with 97% accuracy. This method can help doctors to make auxiliary diagnosis and provide technical support for skin disease diagnosis.
Analysis and Design of Two-Stage Cascaded LED Load Wireless Power Transfer System
Authors: Zhang Bin , Hei Guoyu , Li Huirong
Published: June 2022

This paper proposes a two-stage cascaded wireless power transfer (WPT) system aimed at increasing the transfer radius and supplying power to multiple low-power loads. The proposed WPT scheme is regarded as a cascading of two WPT systems. The system realizes constant current power supply for two-stage LED load and put emphasis on solving the problems of limited power supply radius and power supply of multiple constant current/voltage loads in WPT system. Four basic power supply types of transmission network are discussed in this paper, and the compensation network structures and parameters suiting for these types are determined by analyzing every stage’s input and output characteristic using two-port network T matrix. The result of research validates that constant current is achieved in general. Moreover, the two stage’s maximum efficiency is 68.04% when the LED total number changes from 6 to 13, which proves the feasibility of the proposed scheme.
Single-phase disconnection fault location of active distribution network based on negative-sequence differential impedance
Authors: Ma Tianxiang , Duan Xin , Zhang Zhiyuan , Shen Hongliang , Xu Yan , Zou Nan
Published: June 2022

Accidents such as overvoltage, personal injury and motor damage caused by singlephase disconnection faults occur frequently in active distribution networks. In response to this problem, firstly, the negative-sequence differential impedance is defined and a protection method based on negative-sequence differential impedance is proposed, the method uses the amplitude of negative-sequence differential impedance as an action quantity and uses its phase to construct an adaptive braking threshold. Secondly, in case of protection failure under overload, the zero-sequence voltage amplitude difference is proposed as an auxiliary criterion, and the influence of different types of distributed generators on the zero-sequence voltage difference on both sides of the fault fracture is analyzed. Finally, it is verified by simulation that the method can be positioned reliably and is not affected by the neutral point grounding method, transition resistance, load and distributed generators.
Multi-terminal Detection and Localization of Partial Discharge in Transformer
Authors: Li Yang , Tang Zhiguo
Published: June 2022

The transformer is the key equipment in the power system, and partial discharge is the main reason for the deterioration of the insulation of the transformer. The existing partial discharge detection method cannot determine whether the discharge comes from the transformer body or the peripheral equipment of the transformer when the discharge signal is detected. In order to study the difference between the internal and external partial discharges of the transformer received signals at the detection end and form an effective positioning method, this paper injects high frequency small signals into the external leads, inside the windings and surrounding screens of the 110kV three-phase double-winding transformer to simulate the external discharge of the transformer, the discharge inside and outside of the windings. The research shows that the first wave polarity of the external discharge and the internal non-winding discharge of the transformer is the same at each detection terminal, and the first wave polarity of the winding discharge signal at each detection terminal is different. The polarity information can be used to judge whether the winding discharges; the external discharge is the same as the transformer internal discharge. Non-winding discharge has different proportions of high-frequency and low-frequency components in each detection terminal signal. The signal energy of each detection terminal of external discharge is concentrated in low frequency, and the signal energy of each detection terminal of non-winding discharge inside the transformer is concentrated in high frequency, which can be judged by frequency domain information. The external discharge and the internal non-winding discharge of the transformer provide a reference for the research on the multi-terminal detection and positioning of the transformer.
Research on Improvement of Substation Monitoring Capability Based on AI Algorithm
Authors: Zheng Runlan , Niu Ben , She Chuyun , Gao Demin
Published: June 2022

The limitations of video surveillance in traditional substations have a serious impact on the intelligent monitoring of substations. In order to improve the level of monitoring intelligence, this paper conducts research on the improvement of substation monitoring capabilities based on AI algorithms. First, it analyzes the low pixels of video surveillance and the problems existing in the monitoring system, and then provides hardware support through ARM-based CPU and deep learning algorithms. Improve the recognition ability of pictures, and then solve the problem of low pixels and reduce the pressure of data processing. Finally, the effectiveness of the method in this paper is verified by the actual operation field test.
Design And Implementation Of Real-time Vehicle Speed Monitoring Device For Front And Rear Vehicles
Authors: Wei Conghao , Lin Ni
Published: June 2022

A real-time vehicle speed monitoring system is designed based on the millimeterwave radar sensor.This paper details the system design scheme, hardware composition and core algorithm.On this basis, the physical monitoring system is set up.After testing, the scheme design of the system is reasonable and feasible.Compared with the traditional car itself speed detection system, the system has the characteristics of simple structure, novel and easy to realize, and can be widely used in the future intelligent vehicle field.
Analysis of Combined Resistive Superconducting Current Limiter
Authors: Wu Boxiang , Zhang Baoge , Hou Bodun , Sun Rui , Ping Shanyan , Jiao Yuemin
Published: June 2022

Based on a brief analysis of the discovered quench mechanism and basic model of the resistive superconducting current limiter, in order to alleviate the defects of the conventional resistive superconducting current limiter, a Combination of fault current limiting operating modes of the current transformer. A custom model of resistive superconducting current limiter was built on the PSCAD/EMTDC simulation platform, and based on a 200kV DC transmission system, the influence of the combined operating mode resistive superconducting current limiter on the circuit was studied, and it was shown that the Define the correctness and necessity of the model. The simulation results show that the resistive superconducting current limiter in the combined operation mode can effectively suppress the short-circuit fault current, reduce the system’s requirements for the breaking capacity of the DC circuit breaker, and improve the safety of the system operation.
Research on integrated test technology of relay protection device based on cloud-edge collaboration
Authors: Wang Junkang , Wang Jiayi , Wu Jishun , Wang Weidong , Liu Yejie , Ba Quanke
Published: June 2022

The relay protection debugging of smart substation is limited to single unit test. For the intelligent equipment across bays, it can only be tested in batches and one by one, and there is no means to test the integrated system of bus and main transformer with multiple bays. This paper proposes an integrated test technology of intelligent substation based on cloud-edge collaboration. Build an integrated test system based on cloud edge collaboration, which is cross bays, multi intelligent devices and remote vertical connection. Open up the test island of single equipment. Establish equipment signal acquisition and output, multi-protocol access of edge equipment, unified cloud management and process monitoring system. It can realize the value integration of high-quality resources such as substation managers, testers and test expert database. This method improves the testing comprehensiveness, pertinence and timeliness.
Research on automatic scanning method of network vulnerabilities in power system
Authors: Sun Meng , Wang Qi , He Jue , Huang Huailin , Huang Yu , Shen Xiaojie , Xiao Yaohui , Fan Suchun
Published: June 2022

Power system network is an important guarantee for the smooth operation of power enterprises. Considering the current automatic network vulnerability scanning method of power system, the detection rate of network vulnerability scanning is low due to its poor scheduling ability. Therefore, this paper designs a new automatic scanning method for network vulnerabilities in power system. According to the infrastructure of power system network vulnerability scanner, the power system web page interaction behavior recognition model is constructed to complete the power system web page interaction behavior recognition. On this basis, the power system network scanning scheduling algorithm is designed. Combined with genetic algorithm, the variation process of power system network vulnerabilities is determined, the power system network security situation is determined, the power system network scanning scheduling and vulnerability mining are realized, and the design of power system network leakage automatic scanning method is completed. The experimental link is constructed to verify this method. The verification shows that this method can effectively improve the detection rate of network vulnerability scanning and the efficiency of vulnerability scanning to a certain extent.
FPGA-based multi-channel thermocouple temperature measurement system
Authors: Liang Xiyin , Cai Miao , Ma Muqi , Lu Xiao , Fu Peng , Li Ke
Published: June 2022

Aiming at the high and low temperature test requirements of spacecraft before being sent into space, this paper designs and implements a multi-channel thermocouple temperature measurement system based on FPGA.The system adopts thermocouple as temperature sensor, and ADT7310 is used as thermocouple cold junction temperature compensation, which solves the problem of thermocouple cold junction compensation better.The front end adopts AD7193, a 24-bit analog-to-digital converter with low noise, multi-channel and low power consumption, to amplify and A/D convert the signal at measuring junction of thermocouple.The control core is a field programmable logic gate array FPGA, which can better solve the problem of parallel processing of multi-channel temperature signals. At the same time, it uses the transposition method of the thermocouple standard graduation table, the interpolation look-up table algorithm and the cold junction compensation reverse look-up table algorithm, which is effective The temperature measurement accuracy of each channel is improved.The experimental results show that the system can be connected to 24 K-type or T-type thermocouple sensors, the measurement range can reach -200°C∼220°C (73.15K∼493.15K), and the relative error is less than ±0.3%F.S.
Design of a precise current source with adjustable frequency for AC-FSM
Authors: Duan Rujiao , Yang Xuyun , Qi Yonggang , Liu Zhe
Published: June 2022

AC-FSM is a new technology of external monitoring the internal corrosion for oil and gas pipelines. The current source stability of the FSM equipment is one of the important factors affecting the monitoring accuracy. According to the equipment requirements, a precision current source with adjustable frequency is designed. With C8051MCU as the control core, DAC conversion and differential amplifier are used to control the frequency and the current amount. The experiment shows that the output of excitation power supply has good consistency, the changing range was less than 0.3 %. When the temperature changes, under the condition of low frequency 5Hz, the change of current is less than 0.5 %, under the condition of high frequency 102Hz, the change of current is less than 0.4 %, which avoids the influence of temperature drift. This equipment is suitable for the long period operation of oil and gas pipelines in the field.
Design and Implementation of Single-phase Power Quality Monitor Based on IM1281B
Authors: Liu Zhenmin , Mei Erzhao , Fan Jingfeng , Zhang Yifei
Published: June 2022

In order to better analyze the influence of electrical equipment on power grid fluctuations, a detection system is designed for power quality monitoring. The system uses 51 single-chip microcomputer as the control core, combined with IM1281B single-phase mutual inductance energy metering module, to collect real-time voltage RMS, current RMS, power factor, apparent power, active power and other electrical parameters of electrical equipment connected to the grid. The standard Modbus-RTU is used for communication between IM1281B and the single-chip microcomputer, which realizes the real-time acquisition and processing of multiple electrical parameters of the electrical equipment connected to the power grid. The experimental results show that, the single-phase power quality monitor designed based on IM1281B is simple in structure, and relatively complete in collecting electrical parameters, which can meet the needs of power quality analysis.
Simulation and Fault Diagnosis of Electric Vehicle DC/DC Converter Based on BP Neural Network
Authors: Liu Yaning , Li Xiaopeng , Duan Xiuzhen
Published: June 2022

In recent years, Power electronic systems (such as DC/DC converters) have become more complex due to their needs. Under a series of harsh operating environments such as high temperatures, they are likely to fail, seriously endangering people’s property safety.This paper focuses on the research on the structure principle and fault diagnosis of the DC/DC converter system of electric vehicles, and introduces the structure principle of the electric vehicle DC/DC converter and the development of power electronic fault diagnosis.And the fault diagnosis method of DC/DC converter system is proposed. Finally, the research on fault diagnosis of DC/DC converters is summarized and prospected, hoping to provide new ideas and perspectives for the research and development of fault diagnosis of DC/DC converters for electric vehicles.
Design and Research of the H-bridge inverter system Based on IGBT
Authors: Qi Liang , Zhang Haiyan , Chen Jianghong
Published: June 2022

The paper mainly proposes the design and evaluation method of H-bridge inverter from two aspects of the electrical and thermal performance for the development of the H-bridge inverter system. Firstly, a design method is proposed and used for the H-bridge circuit, which is based on the surge voltage of the the insulated gate bipolar transistor(IGBT) in the condition of turning-off; Otherwise, the thermal resistance equivalent circuit of H-bridge inverter system is analysed, and a method is utilized to calculate the energy loss and temperature rise of the system; Finally, the availability and feasibility of the proposed method and the designed system is verified by the experiments.
A Carrier-free Miniaturized Ka-band T/R Module Design for Easy Automatic Assembly
Authors: Li Jiangjiang , Bai Fengjuan , Xv Yifei
Published: June 2022

A Ka-band four-channel T/R module for electronic scanning array radar is proposed in this paper, which is small in size, lightweight, easy to produce, and has good channel consistency. Adopting the open cavity design on both sides, the microwave signal and the power signal are completely isolated in space with good electromagnetic compatibility characteristics. Moreover, a “carrier-free” assembly scheme is proposed in this design, which removes the thermal matching carriers at the bottom of the MMIC chips used in traditional modules, simplifying the assembly process and achieving a high automation rate. The reliability of the scheme is verified by rigorous temperature shock and random vibration tests. The overall size of the module is 50 mm*84 mm*9.2 mm, and the weight of a single channel is only 17.5 g. The transmit saturated output power is greater than 21.5 dBm, and flatness is less than 0.8 dB. The receiving increase is greater than 7.5 dB, and flatness is less than 1 dB. The noise figure is better than 5.5 dB. The design ideas proposed in this paper have good generalization in the design of low-power T/R module.
A Novel Channel Coding Scheme by Concatenating LDPC with BCH for NAND Flash Memory
Authors: Li Hongyuan , Jiang Xiaobo , Yu Zhenghong , Zheng Wanjun
Published: June 2022

Insuring data reliability on NAND Flash Memory is an important research issue. As adopting a very powerful error-correcting code gradually becomes a strategic demand for the endurance of nowadays NAND Flash memory, Low Density Parity Check (LDPC) codes are recently proposed due to their outstanding error correcting capability. In this paper, a novel Channel Coding Scheme concatenated LDPC with BCH NAND Flash Memory is proposed. Firstly a particular LDPC code with low error floor is constructed and BCH codes are used to generate soft information for LDPC codes. Simulation showed that the proposed Channel Coding Scheme obtains the benefit of both overcoming difficulties of soft information generation and the compatiblity with existing BCH code. With the low error floor of constructed LDPC codes, the proposed Channel Coding Scheme can increase P/E cycles of NAND flash memory more significantly comparing the BCH code.
Optimal control strategy of global return power based on soft switching under triple phase-shift control
Authors: Cheng Weizheng , Wang Fusheng , Li Rui
Published: June 2022

Return power and soft switching are important performance indicators for dual active bridge DC-DC converters (DAB). Aiming at the problem that the DAB converter has a large return power under the traditional control strategy, a control strategy that optimizes the return power in the full power range is proposed, and on this basis, the soft switching range of the switching device is increased. The control strategy not only ensures the minimum return power in the entire power range, but also increases the soft switching range, reduces the switching loss, and further improves the efficiency. Finally, an experimental platform is built for verification, and the experimental results verify the validity of the theoretical analysis.
Radar Target Detection Based on Waveform Design under Atmospheric Attenuation
Authors: Hu Haofei , Fan Chongyi , Huang Xiaotao
Published: June 2022

Under the condition of atmospheric attenuation, the mismatch of radar echo signals leads to the decrease of signal-to-noise ratio (SNR) and detection probability. A joint optimization algorithm for transmitting signal and receiving filter of MIMO radar with atmospheric system response is presented in this paper. Considering the energy constraint, similarity constraint and spectral coexistence constraint of the transmitting signal, and introducing the atmospheric channel response matrix, the echo model under the atmospheric response condition is constructed. By optimizing the transmitting signal and the receiving filter, the echo signal SNR and radar detection probability can be improved. On this basis, the ARMA stochastic model is used to simulate the atmospheric system response. Solve non-convex problems by matrix optimization, positive semi-definite relaxation, Charnes-Cooper transformation, and loop optimization methods. Finally, the rank-one matrix decomposition method is used to extract the optimal signal from the signal autocorrelation matrix. And we analyze the convergence of the algorithm, the degree of SNR improvement and the detection probability. Through numerical experiments, it is proved that after the atmospheric channel response is introduced and matched correctly, the SNR of the echo signal can be improved and the radar detection probability can be greatly increased.
Research on The Accuracy Improvement Method of Angle Encoder based on Kalman Filter
Authors: Guo Yihe , Liu Dongdong , Wu Ning , Chen Saifeng
Published: June 2022

In order to improve the accuracy of the magnetic encoder, this paper analyzes the noise characteristics in output signal of magnetic Angle encoder in the real environment, a magnetic encoder based on Kalman Filter (KF) is proposed to solve the problem of random noise which affects the precision of magnetic encoder. The state equation based on the circular motion model is established, and the real-time voltage values of the two output signals are obtained under constant speed rotation of the motor, the angle errors calculated by the voltage signals before and after KF are compared and analyzed. The results show that the scheme can effectively reduce the random noise and improve the Angle accuracy by more than 50% at constant rotation speed. It is proved that the scheme is feasible in industry.
Research on dual antenna design of RFID sensor
Authors: Zhu Li , Yang Fan , Hu Xingyu , Wu Yiming , Yang Zikang , Li Xiaohan , Li Jiansheng
Published: June 2022

With the popularization and application of RFID sensors, the energy supply of internal circuits is a key problem. When multiple monitoring quantities are involved, the traditional energy extraction method of RFID sensors often leads to insufficient energy. Therefore, this paper designs an RFID sensor integrating acceleration and temperature sensing parameters, and proposes a cross placed dual antenna scheme. In order to increase the concentration of antenna radiation energy, a metal reflective aluminum plate is added. Through experimental tests, it is proved that the scheme can well optimize the radiation direction and performance of the antenna.
Design of Small Platform Sonar Data Acquisition and Storage System Based on NI-CRIO
Authors: Hao Yunbo , Kang Zhenwei , Zhao Honglin
Published: June 2022

The signal acquisition system is an important part of the sonar system. This paper presents a stable multi-channel underwater acoustic signal acquisition system based on NI-CompactRIO, aiming at the compact feature of the small platform sonar system. It realizes the simultaneous acquisition of multi-channel analog signals and the function of storing mass original data. The acquisition system basically comprises of sampling using the self-made acquisition module and storing using U disk. The software is programmed by LabVIEW. Finally, the stability of the system is verified by the experiment on the lake.
A high-precision harmonic distortion measurement algorithm and its system design based on time-domain matrix operations
Authors: Shao Kunming , Zhao Mingjian , Zheng Jiachun , Zeng Guangsen , Li Bin , Ma Biyun , Wu Zhaohui
Published: June 2022

In this paper, a harmonic distortion measurement algorithm and its system design based on time-domain matrix operations are proposed, which can quickly calculate the harmonic amplitudes, phases and total harmonic distortion of a signal. To realize the calculation of harmonic signal parameters in the time domain, we proposed a method to convert the nonlinear function representing the signal into a linear function, constructed a matrix equation, and solved the equation by the row transformation method, which significantly reduced the complexity of the algorithm. Finally, based on the proposed algorithm, a system design was implemented by the digital signal processing theory, and the measurements showed that the system achieves an amplitude error of nearly 1% and a THD error of less than 0.3% when measuring the generated 10 kHz fundamental with 5-order harmonics. The system can be used to measure and calculate the amplitudes and THD of harmonic distortion signals with high precision.
Data anomaly detection based on improved kernel density estimation
Authors: Wu Qiuyuan , Qiao Jiping , Wang Jinmian
Published: June 2022

With the advent of the era of big data, while machines process data instead of humans, timely detection of abnormal conditions in data through algorithms has become the focus of research, and the importance of data detection accuracy has also increased. Therefore, based on the traditional kernel density estimation theory, this paper adds adaptive diffusion equation theory to improve it, selects the best window width value to achieve a high degree of data distribution fitting, and further formulates detection rules. Finally, compared with other traditional detection methods, the results show that the method proposed in this paper can improve the accuracy and stability of abnormal data detection.
A nonfunctional data transformation approach via kurtosis adjustment and its application to SVM classification
Authors: Liu Yu
Published: June 2022

Many statistical methods are very sensitive to data containing outliers and heavy tails, and simply eliminating these data often does not achieve the desired results. We usually need to do some data transformation to make it approximately follow a normal distribution. But not all data can be transformed into a normal distribution, and then we can only adjust the shape of its data distribution to make its shape close to a normal distribution. The kurtosis of the distribution can better reflect the peakedness or flatness of the distribution. So in this paper, I propose a nonfunctional data transformation approach to improve the efficiency of statistical methods by continuously adjusting the kurtosis of the data while maintaining the distribution of the data. I apply the transformed data to SVM classification, and the numerical results show that the transformed data by my method performs significantly better than the untransformed data, as well as better than other comparable methods.
Rainfall study based on ARIMA-RBF combined model
Authors: Zhao Jialu , Chen Ruyun , Xin Haiyuan
Published: June 2022

The traditional differential integrated moving average autoregressive model (ARIMA) has some deviations in the prediction accuracy of monthly rainfall. In this paper, we propose to combine the ARIMA model with the radial basis function neural network (RBF) neural network model to predict the monthly rainfall in Nanchang, Jiangxi Province, using the ARIMA-RBF model. Firstly, the ARIMA model is used to predict the monthly rainfall and calculate its residuals, and then the RBF neural network model is used to approximate and compensate the prediction results of the ARIMA model to correct the final prediction results. The results show that the prediction results of the combined model are better than those of the single ARIMA model and the single RBF neural network model with good accuracy.
Finite element Modeling of Magnetic levitation Planar motor Halbach permanent magnet array
Authors: Xu Wenru , Zhang Shengguo , Yang Jiawei , Hou Hao
Published: June 2022

Maglev plane motor (MLPM) is a new type of plane motor. It’s main electromagnetic structure is composed of permanent magnet array and coil array. The physical hardware basis of magnetic levitation plane motor (MLPM) is permanent magnet array. The key problem in the design of magnetic levitation plane motor (MLPM) is how to obtain high driving efficiency, reduce harmonic interference, and form a planar permanent magnet array with good expansion and technology. Through research, it is found that Halbach permanent magnet array has this advantage. In this paper, physical simulation software COMSOL is used for finite element modeling of Halbach permanent magnet array, which provides a basis for subsequent parameter optimization.
Determining the curve with the quickest descent under gravitational force alone
Authors: sha Shuo
Published: June 2022

Various curvatures can be drawn between two different points. However, what curve will yield the fastest descent for an object to travel from the higher point to the lower point under the force of gravity alone? This essay utilizes theoretical methods such as calculus, optimization, and parametric equations and experimental approaches to show that a curve - shaped like a cycloid - will yield the fastest descent. This conclusion has practical applications for the design of roller coaster trajectories along with other entertainment facilities.