bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Scale Brain Tumor Segmentation Method based on U-Net Network
Authors: Zhang Fuchun , Wu Liang , Wang Yuwen , Yang Yue , Li Meng , Li Jitao , Xu Yike
Published: June 2022

Brain tumor is a serious threat to human health. Because the size and shape of brain tumors can be uneven, irregular and unstructured. Automatic segmentation of tumors from magnetic resonance imaging (MRI) is a challenging task. Brain tumor segmentation using computer-aided diagnosis has important clinical significance for the prognosis and treatment of patients. The traditional U-Net network can not take full advantage of context information, which is easy to cause the loss of effective information of image. Therefore, we propose a multi-scale segmentation method for brain tumors based on U-Net network, in which a multi-scale module for feature extraction is added between down-sampling and up-sampling. The brain tumor public dataset BraTS2020 is used for testing. Dice coefficient was used as the evaluation index, and our experimental method made the average dice of the whole tumor area, core tumor area and enhanced tumor area reach 87.57%, 86.20% and 84.24%, respectively. The experimental results show that the proposed method has comparable precision with typical brain tumor segmentation methods.
Research on fault diagnosis of drive motor based on MATLAB / Simulink simulation
Authors: Xia Faying , Fang Yi
Published: June 2022

Drive motor, as the “heart” of electric vehicles, is the only power source of the vehicle. Its healthy state directly affects the driver’s driving experience and even threatens personal safety. In this paper, the fault diagnosis of drive motor is studied, including the introduction of fault diagnosis and drive motor, and the fault classification and simulation analysis of drive motor. Taking the permanent magnet synchronous motor as an example, the model of the drive motor is built based on MATLAB / Simulink simulation software, and the current and speed changes of the drive motor under normal and fault conditions are compared and analyzed. Finally, the future development trend of drive motor in electric vehicles and the development of fault diagnosis technology are prospected.
GBAS flight test integrity simulation evaluation
Authors: Liu Ruihua , Liu Chang
Published: June 2022

In order to improve the navigation performance of the conventional ground-based augmentation system (GBAS) Category I precision approach phase, the performance ver ification of the integrity technology of the GBAS based on BeiDou satellite navigation system is studied. The integrity and system pseudo-range error models of the CAT I precision approach based on BeiDou are investigated, combined with the provisions in relevant standards and the calculation method of integrity. The experimental results show that the integrity data calculated by the system meets the CAT I precision approach integrity requirements of the Radio Technical Commission for Aeronautics specification and provides a timely warning when anomalies occur in the pseudo-rang error model through changes in the protection level.
Power distribution abnormal data identification and processing system based on correlation classification
Authors: Bin Dongmei , Yu Tong , Ling Ying , Chen Wendi , Lu Liyu , Chen Haiguang
Published: June 2022

when the conventional system classifies the power distribution data, the data category is not fine enough, resulting in low accuracy of abnormal data identification, high false detection rate and large correction error. A power distribution abnormal data identification and processing system based on correlation classification is proposed. In terms of hardware, multi-layer framework is adopted, and the overall hardware structure of the system is composed of communication modules, so as to optimize the power distribution data and signal acquisition circuit and suppress signal noise; In terms of software, set the data classification convergence conditions, iteratively increase the number of distribution data clustering centers until the convergence conditions are met, realize the fine correlation classification of data, draw the classified data curve, obtain the normal data feasible region, judge that there are abnormalities in the data beyond the feasible region, and use the vertical comparison method for correction. The results show that the designed system improves the accuracy of abnormal data identification, reduces the false detection rate and correction error, and the accuracy of abnormal data identification and processing is better than that of the conventional system.
Research on online monitoring and early warning technology of tripping and closing circuit of intelligent substation
Authors: Zhang Yunlin , Ma Yan , Li Zhifei , Wu Hang , Zhuoyan Jiang
Published: June 2022

In view of the lack of effective on-line monitoring means for the tripping and closing circuit and the problem that the tripping and closing circuit mistakenly opens and closes the primary equipment due to excessive leakage current, an on-line monitoring and early warning scheme for the tripping and closing circuit is proposed, and an online monitoring and early warning system for current data and switch state data of the tripping and closing circuit is designed. Hall current sensors are installed at many places of the tripping and closing circuit to collect the leakage current in real time. Relying on the sampling unit and management unit of intelligent wave recorder, the online monitoring and early warning system digitally collect, analyse and process the information of tripping and closing circuit, realize the fault early warning and positioning of tripping and closing circuit, and improve the ability of circuit anomaly monitoring and early warning. Through the field application in substation, the feasibility of the system is verified.
Power Dispatching Voice Backtracking System Based on Knowledge Base
Authors: Guo Meng , Xu Sheng , Chen Jinlong , Du Jiang , Chen Long , Bai Hongyu
Published: June 2022

With the rapid development of the scale and structure of the power grid, the power dispatching center has built a complete dispatching exchange communication network, which can meet the daily dispatching communication needs, but various problems are also emerging in the dispatching process. Aiming at the problem of high integration of physical power grid and information system, this paper proposes a voice backtracking system for power dispatching based on knowledge base, which includes knowledge base establishment, knowledge storage, knowledge question answering sorting and knowledge base front-end question answering. Firstly, the basic model of power dispatching knowledge processing is trained, and then the knowledge is extracted from the domain corpus, and finally, the knowledge question answering is realized by using the ranking model. Through the experimental comparison, it is proved that the accuracy of the method in this paper is higher than that of the method in the postprocessing by adding the MRC model in the pre-processing of knowledge extraction, and it is better than other methods in the comparative test. It provides technical support for power system voice dispatching management and provides a reference for other areas of voice management.
Analysis of the optimal parameters for serpentine laying of high-voltage cables considering the influence of various factors
Authors: Xuan Shengxiexian , Teng Zupeng , Jiang Ying , Xiong Junlin , Ma Xuchu , Wu Qi , Ma Xikui
Published: June 2022

High-voltage power cables can be subjected to thermomechanical forces during operation due to the rising cable temperature or drastic ambient temperature changes, which threaten the operational safety of the cables. In this paper, first of all, the thermal expansion, serpentine arc displacement and serpentine arc axial force of the cable in the limit operation state are analyzed theoretically. The serpentine arc displacement and serpentine arc axial force under different serpentine laying parameters are compared and the optimal laying method is derived. Then the theoretical optimal solution is simulated using finite element analysis method to prove the correctness of the theoretical results. Finally, the recommended laying parameters of the serpentine laying method are given.
Research on bearing surface defect detection system based on machine vision
Authors: Wang Jinmian , Qiao Jiping , Guo Meicen
Published: June 2022

Aiming at the shortcomings of manual detection methods for surface defects of bearing outer rings, a surface defect detection method based on machine vision is proposed. The common defects on the bearing surface are scratches, cracks, and peeling. The defect images are analyzed by the LabVIEW image processing module. Make fast and accurate inspections. In this paper, a CMOS industrial camera is used to obtain the bearing image, and the gray histogram of the image is analyzed to determine whether it is a defective bearing. In order to solve the problem of uneven illumination in image segmentation, it is proposed to first use morphological processing for background. Then, the difference map containing defect information is obtained, and then the Otsu method is used for image segmentation; an edge detection method is designed based on morphology, which can achieve complete edge extraction and good denoising effect. Experiments show that the method has strong practicability and self-adaptability, and can accurately detect bearing surface defects.
An intelligent monitoring system based on computer vision
Authors: Cui Dejing , Ren Weilong , He Wenjin
Published: June 2022

Aiming at the customs supervision area of the comprehensive bonded area, this paper proposes an intelligent monitoring system based on computer vision through the research of computer vision, photoelectric sensors, digital image processing, data transmission network, automatic control and intelligent video analysis. We have realized the comprehensive supervision of people, vehicles, and things in the park, uploading all collected information to the centralized storage server, realizing uninterrupted data tracking, analysis, alarming, centralized management, unified scheduling, and command of front-end equipment. We have comprehensively improved the level of supervision of the comprehensive bonded area, provided the most intuitive information for emergency response, and performed the best response to emergencies according to the emergency plan to build a more intelligent comprehensive bonded area.
A Hybrid Control Strategy for Half-bridge Three-level LLC Resonant Converter
Authors: Chen Yuqiang , Wang Fusheng
Published: June 2022

The half-bridge three-level LLC resonant converter uses the resonant process of the inductance and the capacitance to transfer energy. It has the advantages of low voltage stress on the switch and high efficiency, but there are problems such as narrow voltage gain range. To widen the voltage gain range of the converter, a hybrid control strategy for a half-bridge three-level LLC resonant converter is proposed in this paper. The voltage gain of the converter is divided into three gain intervals: low, medium and high. Burst control is used in the low gain interval, phase shift control is adopted in the middle gain interval, and frequency modulation control is adopted in the high gain interval. The experiment results show that the proposed control strategy can realize a wide range of output voltage gain of the converter.
UWB-based Real-Time 3D High Precision Localization System
Authors: Liu M H , Zhang Sheng , Pan Yi
Published: June 2022

Ultra-Wideband (UWB) positioning technique featuring high accuracy and low cost has been drawing increasing interest. Angel of arrival (AOA), time difference of arrival (TDOA) and time of arrival (TOA) are common methods for positioning. With DecaWave1000 ranging systems, which applies TOA method, sub-meter accuracy can be achieved easily. However, the traditional DW1000 UWB localization system is unscalable and the ranging stability remains improving. In this paper, a brand new Scalable Multi-Base Multi-Tag (SMBMT) scheme based on traditional DW1000 UWB localization system is proposed to improve the system’s efficiency and scalability. Then an effective data processing algorithm Data Kalman Filter is offered using ranging information only, to diminish the ranging error in the system. By changing the system equation, Data KF is also able to optimize the dynamic trajectory. Finally, the proposed system is tested and the algorithm is analysed. The result shows that not only does applying SMBMT scheme improves the scalability and ranging efficiency of UWB localization system but also increases the accuracy and stability in positioning.
Algorithm Design of Mirror Tracking System
Authors: ZHAO Yameng , JIANG Jian
Published: June 2022

In the current national defense background, the requirements for the performance of weapons are increasing day by day, the speed of the flying target and the flight state provide important parameters for the improvement of the characteristics of weapons, ballistics and ammunition. In the shooting range test, the high-speed flying target is tracked and photographed to obtain important indicators such as the flight status of the flying target in high-speed flight. This paper studies a ballistic tracking camera system based on a rotating mirror. It is composed of a system, which can track the flight trajectory of the flying target in the air in real time, and obtain important information of the flying target in flight through high-speed camera shooting. Design the mirror tracking system to capture the flight status of the flying target, analyze the flight trajectory parameters of the target through MATLAB, and optimize the accuracy and response speed of the motor control algorithm. The motor turns the mirror to reflect the flying target to the high-speed camera. The feasibility of the system is ver ifi ed. Th e tot al sc ann ing range of the system for tracking flying targets is 90°, and the scanning accuracy is ±0.5°.
Application Research of Face Recognition Algorithm based on MATLAB
Authors: Gong F , Zhang YM , Jiang X Z
Published: June 2022

Face recognition is a biometric recognition technology based on human facial features. Its application is generally to collect relevant face images through the camera, extract the video stream containing the face, or monitor the face in real time. This paper will take matlab simulation software as the research platform to study the effect of different face recognition algorithms in practical application. The main research method is to establish the corresponding face recognition application simulation interface on MATLAB, carry out simulation verification through different face recognition algorithms, compare and analyze the simulation results, and summarize the advantages and disadvantages of face recognition in the process of practical application,it provides a certain reference for the follow-up application of face recognition in real life.
The Research and implementation of high-speed Master-slave CAN-FD composite system based on Cortex-M7
Authors: Chen Zerui , Zhang Guoguang , Na Jiesi
Published: June 2022

All CAN bus is widely used in communication and control between electronic control units of automobiles. At present, the rapid development of intelligent network system has put forward higher requirements on the speed, capacity, reliability and stability of real-time data exchange.In this paper, the microcontroller based on Cortex-M7 architecture and the third-generation high-speed CAN transceiver are selected to build the interface module. According to the high-level CAN communication protocol, the control command is sent and the fault diagnosis and status monitoring is carried out in real time. At the same time, the industrial data from the signal processing module is received and stored. The test results show that the interface system is configured with several groups of filters of different interception modes based on the dual-channel CAN-FD communication, realizing higher transmission rate, longer data frames and multiple frame sending and receiving and is downward compatible with BxCAN. It has the characteristics of strong comprehensive performance, high reliability, portability and versatility. It also provides theoretical verification and data support for the optimization design and application of CAN bus in domestic industrial products.
Research on Common Mode Voltage Suppression Algorithm Based on Three Levels
Authors: Liu Heng , Wang Fusheng , Xie Yuanchao
Published: June 2022

The high frequency common mode voltage generated by the traditional two-level inverter and multilevel inverter modulation scheme is higher. In order to solve the problem of common-mode voltage in three-level inverter, a method to suppress the common-mode voltage in three-level inverter is proposed in this paper. Research comparing sinusoidal pulse width modulation (SPWM) and zero common mode voltage modulation methods. Through the application of the new modulation method to the three-level inverter, the effectiveness of the method is proved by simulation.
Direction of arrival and target scale estimation based on split beamforming algorithm
Authors: Leng Kaijing , Deng Leilei
Published: June 2022

Based on the theory of split beamforming algorithm and the experimental data collected by circular array, this paper analyzes the characteristics of DOA and target size estimation. In this paper, the signal receiving model of planar circular array and the split beamforming algorithm are studied. Then, based on the data collected from the lake experiment, the DOA estimation results of conventional beamforming algorithm, multiple signal classification algorithm and split beamforming algorithm are analyzed, and the target scale estimation results of split beamforming algorithm is analyzed. The experimental data analysis shows that the split beamforming algorithm has good direction finding stability, and the target scale estimation error based on the split beamforming algorithm is small.
Analysis of the differences in the messages broadcast by different GEOs of WAAS
Authors: Liu Ruihua , Tian Yanting
Published: June 2022

The Wide Area Augmentation System(WAAS) is the most mature satellite-based augmentation system currently available to provide higher performance navigation and positioning services for civil aviation users. WAAS broadcasts a wide range of differential correction data and integrity information to users via Geostationary Orbit(GEO) satellites to achieve enhanced navigation performance of GNSS. This paper selects the enhanced messages broadcast by different GEO satellites from February 1st to February 7th, 2022, decodes and compares the data of the messages MT2-5 and MT25, and analyzes the differences of the messages broadcast by different GEOs.
Research on on-line monitoring system of CVT metering anomaly
Authors: Liu Yongping , Wang Shouzhi , Xia Xin , He Chuanliang , Li Jinlong
Published: June 2022

The stability of capacitive voltage transformer (CVT) is low due to the influence of multiple factors in the operation process. The measurement error occurs from time to time, and there is a great measurement risk. However, the existing inspection methods for CVT periodic power failure are inefficient and cannot meet the requirements of intelligent substation for automatic monitoring of key equipment status. In view of the above problems, an online monitoring system for CVT measurement abnormality is designed to realize the real-time evaluation of the operation error of CVT measurement abnormality without power failure, guide the verification, operation and maintenance of CVT directional power failure according to the error evaluation results, timely find out the out of tolerance transformer, realize power recovery, and provide an effective scheme to replace the traditional periodic power failure detection method. The system has passed the test of the third-party inspection and testing organization, and the system has good functionality, compatibility, reliability and portability.
Numerical simulation and optimization of heat dissipation structure for high power insulated gate bipolar transistor (IGBT)
Authors: Hu Waikit , Cui Wei
Published: June 2022

With the increasing integration level of IGBT components, heat dissipation capacity determines whether its working state is stable. The third-generation semiconductor chips are expected to be made of SiC or GaN materials, with lower power loss and higher thermostability. Currently, the widely used backplane heat dissipation schemes cannot meet the heat dissipation requirements of high-power IGBT modules. In this study, an aluminium alloy shell with an AlN column is proposed to replace the traditional plastic shell to further improve the heat dissipation of IGBT devices. 180°C is set as the expected maximum temperature of the module, and finite element modelling and analysis of the heat dissipation structure of the IGBT device is carried out. Four types of design schemes are compared and the heat dissipation structure is optimized. AlN heat-transfer blocks and Ag sintering are introduced to realise the novel design. The results show that traditional single-side heat dissipation can not meet the requirements. The improved double-side dissipation scheme meets the requirement when the heat sink fin height is more than 15mm. And the optimized heat sink shall have 14 fins of 20mm in height. The results of this study can provide a reference for the thermal management and design of high-power third-generation semiconductor devices.
Technology Strategy for Meticulous Governance of Smart Cities: Memory Bus Width Aware Pruning for Efficient Image Super-Resolution Implementation in FPGA
Authors: Zhang Chuo
Published: June 2022

The mega-city governance is based on the aggregation, collation, development and application of multi-scene data, and efficient access to scene data is a key link to promote the meticulous governance of smart cities. Super-resolution technique is the process of upscaling and improving the details within an image. In this paper, we implement a 16-layer residual neural network (ResNet) for the efficient image super-resolution in FPGA. We discover that the memory access is the major performance bottleneck of this implementation. To reduce the memory access overhead, we design a pruning algorithm with the consideration of the memory bus width. Since the memory used in our design generates 256 bits for each access, the proposed pruning algorithm drops the kernel by aligning this bit width. That is, all kernels in one layer are ranked by its L1-norm and we drop the kernels out of the 256 bits. The experimental results show that the proposed method reduces the number of weights by 50% compared with the baseline. As a result, the inference speed can be enhanced by 3 times.
Key Technologies of Media Big Data in-Depth Analysis System Based on 5G Platform
Authors: Lin Qiang , Zhang Xilin
Published: June 2022

To meet the needs of large-scale users for personalized streaming media services with high speed, low delay, and high quality in a 5G mobile network environment, this paper studies the resource allocation mechanism of streaming media based on a 5G network from the perspective of user demand prediction, which can alleviate the pressure of mobile network, improve the utilization rate of streaming media resources and the quality of user service experience. The augmented reality visualization of large-scale social media data must rely on the computing power of distributed clusters. This paper constructs a distributed parallel processing framework in a high-performance cluster environment, which adopts a loosely coupled organizational structure. Each module can be combined, called, and expanded arbitrarily under the condition of following a unified interface. In this paper, the algebraic method of parallel computing algorithm is innovatively proposed to describe parallel processing tasks and organize and call large-scale data-parallel processing operators, which effectively supports the business requirements of large-scale parallel processing of large-scale spatial social media data and solves the bottleneck of large-scale spatial social media data-parallel processing.
Research on Monitoring Data Security Sharing Method for Hydropower Station Operation and Maintenance
Authors: Ma Yuanjiang , Hong Liang , Qin Taisong , Hao Xia , Tan Taiquan
Published: June 2022

The computer monitoring system centrally and uniformly manages the hydropower stations in the basin, which has high operation efficiency. The current data security sharing methods can not solve the multi-party trust problems such as data ownership and data security. In this regard, a monitoring data security sharing method for hydropower station operation and maintenance is proposed. The monitoring data of hydropower station comes from multiple independent operation systems developed by different suppliers according to different application requirements. The multi-source data are integrated and processed to meet the interactive needs of users. User permission has the characteristics of dynamic change, which can identify the permission attributes. Create a trusted container based on the user ID, locate the monitoring data, and trace the source in data sharing and storage. The access policy is formulated by the data user and bound with the private key, while the data is given an attribute set during encryption. Each data user has a corresponding access policy and a private key corresponding to the access policy, so as to realize the security sharing of monitoring data. The test results show that the design method in this paper can effectively reduce the communication overhead and storage overhead, and has good computing performance.
SOLOv2-based multi-view contactless bovine body size measurement
Authors: Ai Biao , Li Qi
Published: June 2022

To address the problems that traditional bovine body measurement methods require a lot of manual assistance and lead to stress reactions in cattle, this paper achieves contactless measurement of bovine body length, withers height, chest breath, belly breath and chest depth by using a deep learning approach. This paper use SOLOv2 instance segmentation to identify cattle and extract cattle contours from the top and side views, combines cattle image dataset and OpenCV image processing function to extract cattle feature parts, and use discrete curvature calculation method to extract cattle body size to calculate feature points, and calculate cattle body size parameters by Euclidean distance calculation method. Experiments were conducted using custom model cattle to which bovine body size measurements were taken, after comparing with the manual measurement results, the average relative errors of body length, body height, chest depth, chest breath and belly breath of the model cattle were 1.36%, 0.44%, 2.05%, 2.80% and 1.47%, respectively. The experiment proved that this measurement method performed well in the non-contact measurement of bovine body size and had good accuracy, which provided a new way and method for the measurement of the non-stress response of cattle.
Python-based film review data acquisition and visualization design
Authors: Yang Yong , Xin Liu Ying , Zhang Yu Xi , Zhang Na
Published: June 2022

With the rapid development of the Internet and artificial intelligence era, how to obtain effective information is particularly important in the complex network world. In order to obtain a real movie viewing experience and provide some reference for other users, this article is based on the Python language, taking the popular movie “Shuimen bridge of Changjin Lake” as an example on Douban website, and using web crawler technology to comment and rate users, etc. Relevant data is crawled, the crawled data is the object of analysis, and data visualization processing is carried out to more intuitively show the true feelings of moviegoers. The results show that the film meets the expectations of the public and is worthy of recommendation.
An approach to error label discrimination based on joint clustering
Authors: Tan Z M , Liu J Y , Li Q , Wang D Y , Wang C Y
Published: June 2022

Inaccurate multi-label learning aims at dealing with multi-label data with wrong labels. Error labels in data sets usually result in cognitive bias for objects. To discriminate and correct wrong labels is a significant issue in multi-label learning. In this paper, a joint discrimination model based on fuzzy C-means (FCM) and possible C-means (PCM) is proposed to find wrong labels in data sets. In this model, the connection between samples and their labels is analyzed based on the assumption of consistence between samples and their labels. Samples and labels are clustered by considering this connection in the joint FCM-PCM clustering model. An inconsistence measure between a sample and its label is established to recognize wrong labels. A series of simulated experiments are comparatively implemented on several real multi-label data sets and experimental results show superior performance of the proposed model in comparison with two state of the art methods of mislabeling correction.
Testing homogeneity of high-dimensional covariance matrices under non-normality
Authors: Shen Jieqiong
Published: June 2022

In this paper, we test the homogeneity of multiple covariance matrices when the dimension may exceed the sample sizes. A test statistic is proposed which does not depend on the normality assumption. Furthermore, the asymptotic distribution of the test statistic is derived. Numerical simulations indicate that the proposed test has accurate significance level, and has a greater improvement in power than some existing tests.
The research of begin the Apache Giraph
Authors: Shen Haowei
Published: June 2022

Apache Giraph is an open-source image processing framework built from Apache Hadoop. Apache Giraph is based on bulk synchronous parallel and Google’s Pregel. It is suitable for running large-scale logical calculations, such as page ranking, shared links, personalized ranking, etc. Giraph focuses on social graph computing and is at the core of Facebook’s open graph tool, handling trillions of connections between users and their behaviors in a few minutes. But because the time is limited, the work just has been done with Hadoop. This paper will be mainly talked about Hadoop and how the difficulty to be solved.
Empirical Analysis of Factors Affecting Air Quality in China-Based on the Skew-Normal Spatial Dynamic Panel Data Models
Authors: Yang Yan , Ju Yuanyuan , Wu Liucang , Dai Lin
Published: June 2022

To explore the influence factors of air quality, the air quality data of 31 provincial capitals in China from 2014 to 2019 is studied by introducing skew-normal spatial dynamic panel data models in this paper. A Markov Chain Monte Carlo algorithm is developed to estimate the unknown parameters in the model. The main conclusions of the research are followed. (1) The variation of air quality in China could be well reflected by the skew-normal space dynamic panel data model. (2) PM10 had the most significant influence on air quality among the five air quality indexes, such as SO2, CO, NO2, PM10 and O3. (3) There are significant temporal and spatial correlations on air quality among provincial capitals. (4) In China, the air quality in southern and southwestern is excellent, while the air quality in northern is slightly polluted. These conclusions provide theoretical guidance for improving air quality in China and a scientific basis for making decisions of relevant departments.
Extraction and Analysis of Crowd Activity Vergence Model in Space-Time Vector Field
Authors: Liu Haiyan , Li Jing , Guo Qiang , Zhang Youwei , Lu Chuanwei , Hu Fang , Wu Hongjian
Published: June 2022

The vergence model of crowd activity is one of the core contents of human mobility research. Traditional methods do not consider the mobility of crowd activities in terms of extracting vergence models. In this paper, the model extraction problem is transformed into a time series clustering problem, and the mobility of crowd activities is dynamically modeled by introducing vector field theory. Then, the vergence of the crowd is calculated by the divergence. Finally, a time series composed of the crowd vergence is constructed to obtain the main vergence model of crowd activity through clustering. The method proposed in this paper is experimentally verified on the Didi Chuxing data in Haikou City, and four main vergence models of the crowd activity are extracted, which proves that the method proposed in this paper is effective and provides research ideas and method support for exploring human mobility.
Research on the Variable Weight Combined Prediction Based on the Optimization Weighting Method
Authors: Wang Xiaoli
Published: June 2022

This paper improves fixed weight combined prediction model, which is established on the predicted value of the ARIMA model and the predicted value of the BP neural network model. Based on the minimum sum of error squares, the time varying optimal weight of the combined prediction model is determined, variable weight combined prediction model is constructed. Based on the analysis of the change rule of Shaanxi province’s GDP over the years, the combined model is used to fit Shaanxi province GDP from 2018 to 2021.The result shows that the fitting errors are 0.11%, 0.01, 0.01% and 0.11%, respectively. The variable weight combined model is used to predict Shaanxi province GDP from 2022 to 2023, which is 29502 billion and 31301 billion respectively. Compared with the ARIMA and BP models, variable weight combined model improves the prediction effect.
Dynamic Optimization Method of High-speed Solenoid Valve Parameters
Authors: Feng Yulong , Xu Tao , Dai Yang
Published: June 2022

The high-speed solenoid valve is the core component of the cotton foreign fiber machine, and its dynamic response characteristics of high-speed air flow at the inlet and outlet are the key to determine the accuracy of foreign fiber strike. In order to improve the dynamic response performance of high-speed solenoid valve under variable working conditions, based on the electromagnetic action mechanism of solenoid valve, the parameter analysis model of high-speed solenoid valve for outlet pressure optimization is established in COMSOL. Taking the inlet pressure and driving voltage of solenoid valve as the system optimization variables, the high-speed response law of outlet pressure rise lag time and outlet pressure change is obtained. The simulation result shows that when the driving voltage of solenoid valve changes from 21V to 27V, the lag time of outlet pressure rise decreases by 57.8%. When the inlet pressure increases from 2 bar to 7 bar, the lag time of outlet pressure rise decreases by 48.14% and the change rate of inlet and outlet differential pressure decreases by 8.4%. The dynamic optimization test system of high-speed solenoid valve parameters is built to verify the simulation results, and the change trend consistent with the simulation results is obtained.
Research on fault diagnosis method of radar antenna transmission gear based on motor current characteristics
Authors: Song Yawei , Hua Liangfa , Yan Kai , Han Wei , Zhu Pei , Ye Zehao
Published: June 2022

In order to complete the monitoring and early warning of radar antenna transmission device with more and more frequent faults, a gear fault judgment method suitable for radar equipment is proposed in this paper. According to the fault characteristics of radar antenna transmission gear, the motor current frequency difference of transmission mechanism under normal and fault conditions is compared, and the simulation experiment is completed. The simulation results verify the feasibility and correctness of this method.
Structure Optimization and Numerical Simulation of Micro Gas Turbine Regenerator
Authors: Wang Chongyang , Jiang Weiting , Pan Weiguo , He Tingni
Published: June 2022

In this paper, we mainly study the flow and heat transfer performance of a 300kW micro gas turbine plate regenerator. We built three-dimensional structural models of high-temperature single-channel, low-temperature single-channel, and heat exchange units. In the meantime, large-scale commercial CFD software is used for numerical simulation analysis. We have optimized the channel structure in the low-temperature side guide zone. The results show that: the pressure loss of the low-temperature side channel is reduced by 18.7%, and the efficiency of the regenerator is increased by 0.02%.
Reliability Relation Extraction Technology of Power Distribution Equipment Based on Machine Learning
Authors: Dai Zikuo , Xu Yan , Shi Kejian , You Yang , Li Bingxin
Published: June 2022

As the key link of power transmission in the power distribution system, the distribution transformer is the core of the entire power distribution system and is responsible for the electrical connection between the medium voltage side and the low voltage side, and based on this to further ensure the stable operation of the power distribution system. Data types, sources, selection principles and data processing methods relate to the operating state of distribution transformers; then expound the meaning of operating state indicators, and build a distribution transformer operating state index model; finally, an improved weight method is used to determine the distribution transformers of the weight coefficient of the running status indicator. Therefore, it is appropriate to verify the membership function and membership matrix selected in this paper. It is suitable for the fuzzy comprehensive evaluation calculation of the reliability of distribution transformers, which verifies the accuracy of the reliability evaluation results. The maintenance strategy of distribution transformers based on reliability assessment can be optimized according to the operation status of the equipment so as to improve the operation reliability of distribution transformers and ensure the safe, reliable and economical operation of the equipment. The maintenance strategy of distribution transformers based on reliability assessment can be optimized according to the operation status of the equipment, which is to improve the operation reliability of distribution transformers and ensure the safe, reliable and economical operation of the equipment.
Integrated control method for electromagnetic compatibility of lift facility control system for naval craft
Authors: Yan Xuefan
Published: June 2022

Lifting facilities electromechanical servo system has a compact structure, high specific power, high control accuracy, low vibration and noise, high reliability. In recent years, small and medium power electromechanical servo systems have been widely used in the aerospace field, and the application of distributed high-power electromechanical servo systems in the naval field to replace the traditional valve-controlled centralized ship-wide hydraulic servo system has a broad application prospect, becoming one of the important links to achieve a new generation of "all-electric" ships. But along with the power level, electromechanical servo system electromagnetic compatibility problems are increasingly prominent, and must be considered from the system design in a comprehensive manner. This paper takes a ship electromechanical servo system as an example, starts from the system functional unit, combines the ship and servo system electromagnetic environment characteristics, sorts out the key links of each unit electromagnetic compatibility control, and takes targeted measures in the electromagnetic compatibility design, the product finally passed the electromagnetic compatibility test, which can provide reference for electromechanical servo system electromagnetic compatibility design.
PI parameter optimization of Asynchronous motor vector control based on MIGA
Authors: Jing Bowen , Guo Zhijun , Wu Jingbo
Published: June 2022

In motor control, the stable control of motor speed and the stability in the face of sudden torque are two important indicators to evaluate the quality of the control system. This paper proposes a multi-island genetic algorithm (MIGA) and fuzzy PI vector control algorithm. Combined with the asynchronous motor control method, the simulation test and bench test are carried out. Taking the Integral Time Multiplied by the Absolute Value of Error (ITAE) minimum as the optimization goal, the MIGA optimization algorithm is used to obtain the optimal solution for the quantization factors ke0, kec0
, proportional factors kup, kui
of the fuzzy PI controller. The optimal parameters are imported into the asynchronous motor control model for simulation verification and bench test verification. The simulation test shows that the fuzzy PI control method optimized by MIGA can effectively reduce the speed rise time, overshoot and steady-state error. When the load is suddenly applied, the speed drop is 5.16 r/min, and the adjustment time is 0.015s. The bench test shows that: under the changing load, the change trend of the speed curve of the simulation and the test is basically the same, which proves the correctness and effectiveness of the algorithm proposed in this paper.
Study on influencing factors of trailing edge flow characteristics of transonic micro turbine rotor
Authors: Sun Xiang-Lin , Xia Chen , Chen Jin-Wen
Published: June 2022

In order to meet the needs of the development of high-performance micro-engine, the micro-turbine is faced with the technical challenge of high-load and transonic flow. At present, the flow characteristics and loss mechanism of high-load micro-impeller are not clear. In this paper, the flow characteristics of high-load micro-turbine rotor are studied. The results show that the loss in rotor trailing edge is the main factor that affect the operation of the micro transonic turbine, and the key to reduce the loss is to reduce the wake diffusion range and the Mach number in front of the extended shock wave. By adjusting the local curvature of the front in front of the incident point of the back-extension wave in the throat of the suction surface, the convergent-divergent ratio is in the range of 1.04 ~ 1.08. Meanwhile, the Mach number of wave front can be reduced by 3.4% and the reflection of trailing edge inward extension can be effectively suppressed, and the total rotor pressure loss coefficient can be reduced by 14.1% at most. The thickness has an important effect on the wave strength and wake loss in the trailing edge. When the relative thickness of the trailing edge decreases by 50%, the maximum Mach number on the suction surface decreases by 7.8%, the turbine stage efficiency increases by 1.92%, and the relative thickness of trailing edge is 0.124~0.185, the studied micro-transonic turbine performs better.
Research on Acoustic Characteristics of Low-noise Modular Hydraulic Power Unit
Authors: Wang Nei , Qian Yuan , Xiang Chao , Liu Yiou , Mao Xuyao
Published: June 2022

As the power source of a hydraulic system, hydraulic power unit also act as the main vibration and noise source. In this paper, systematic noise source characteristic and vibration performance of the low-noise modular hydraulic power unit are analysed, and specific measures to reduce vibration noise in the design process are studied. Firstly, through dry and wet mode analysis of the system, it is proved that the optimization of the pipeline and the oil tank separator plates should be emphasized in the system design. Based on that, by identifying the exciting forces of the motor and applying them to the analysis model, the vertical acceleration vibration response of 16 measuring points could be calculated. The results show that the attenuation of shaft frequency vibration noise should be focused in the acoustic design of the system. Above all, this paper provides a way in low-noise modular hydraulic power unit design.
Hybrids acceptance tools for the CMS Phase-2 Tracker Upgrade
Authors: Hollos A. , Blanchot G. , Kovacs M. , Loutit M. , Makarenko I. , Mateos I. , Otarid Y. , Seif El Nasr S. , Zografos A.
Published: June 2022

Up to fifty thousand front-end and service hybrids are required for the CMS Outer Tracker Phase-2 Upgrade. These hybrids, which are built on carbon fibre stiffened circuits and contain several flip-chip ASICs, will be glued in module structures, making repairs almost impossible. Due to their complexity, testing within production is a very important aspect. A multiplexed testing infrastructure, based on custom crates and test cards, is presented. This testing hardware is supported by software tools to enable the exhaustive verification of hybrids at the manufacturing sites and for their acceptance within the collaboration.
The development of the alarm system for HLS-II
Authors: Xu S. , Liu G.F. , Gan Y.F. , Qin T. , Xuan K. , Li C. , Li W.M. , Sun X.K.
Published: June 2022

Hefei Light Source II (HLS-II) is a vacuum ultraviolet synchrotron light source. The control system of HLS-II is a distributed system based on the experimental physics and industrial control system (EPICS). The alarm system of HLS-II is responsible for monitoring the alarm state of the facility and distributing the alarm message in time. It facilitates the operator to troubleshoot problem efficiently, so as to improve the availability of HLS-II. Phoebus/Alarms (Alarms) is the latest alarm software released in EPICS community. Based on Alarms, the alarm system of HLS-II is designed, developed and deployed. The alarm distribution strategy is designed from the perspective of the HLS-II operation mode, alarm severity and alarm representative to overcome alarm floods. The 3 ways to distribute the alarm message are added to the HLS-II alarm system, which include WeChat, SMS and web-based GUI. In order to configure alarm options efficiently and conveniently, an alarm configuration management tool is developed based on the MySQL database and Browser/Server architecture. The alarm system of HLS-II has been deployed since November 2021. The result indicates that the alarm system is effective and convenient to operate.
Asymmetric restart in a stochastic climate model: A theoretical perspective to prevent the abnormal precipitation accumulation caused by global warming
Authors: Ali Syed Yunus , Choudhury Nabadip , Mondal Debasish
Published: June 2022

The continuous heating of the Earth’s surface and aerosphere causes global warming. Recent developments predict that at the end of the twenty-first century, with 3 °C on average global warming will yield a regional augmentation in the probability of the abnormally large precipitation accumulation in a single downpour event. We examine this issue using a stochastic climate model and provide a theoretical scheme to the increased possibility of cloudburst in a single rainfall event. We find that implementing a permanent upper cut-off in column integrated water vapour or an asymmetric stochastic resetting can reduce the abnormally high accumulation probability of such rainstorms. We report that an optimum upper limit of column integrated water vapour in the atmosphere ascertain the decrease in the heavy precipitation-accumulation. The presence of such a perpetual upper ceiling in the moisture content is energy exorbitant and can significantly affect the mean downpour. A careful choice of the system parameters ensures the decrease in mean accumulation size within a ten per cent tolerance limit. We introduce an asymmetric stochastic resetting to the amount of column integrated water vapour at its upper threshold to recompense the energy cost. We perceive that an adaptive restart rate is efficient enough to reduce the probability of targeted precipitation accumulation to the desired extent.