bluuebunny/crossref_metadata_2025_split huggingface dataset:
Backstepping sliding mode control of electric linear load simulator
Authors: Zhang Jianwei , Fan Yuanxun , Cao Dawei , Lu Pengcheng , Zhang Jiacheng 
Published: February 2021

Abstract
In order to solve the excess force problem in the electric linear load simulator (ELLS), a backstepping sliding mode controller based on the backstepping control idea is proposed. According to the function, the state of the system is divided into load torque subsystem and PMSM mechanical subsystem. First, the virtual control of the load torque subsystem is designed, and then the controller is designed for the PMSM mechanical subsystem, and the Lyapunov stability is proved. Finally, the simulation test is compared. The simulation results show that, compared with the traditional PID control, the controller based on the backstepping sliding mode design can effectively suppress the excess force and improve the loading accuracy of the system.
Design of UAV yaw Angle controller based on variable domain fuzzy PID
Authors: Ning Wang , Zhe Li , Xiaolong Liang , Jiaqiang Zhang 
Published: February 2021

Abstract
Four-rotor UAV is widely used in reconnaissance missions, UAV usually needs to adjust the yaw angle before reconnaissance aerial photography. To improve the speed of the four-rotor uav at the adjustment of yaw angle, this paper presents a variable-domain fuzzy PID controller. First, we established the nonlinear dynamic model of four-rotor UAV. Then, we fuzzed the corresponding variables in the governing equation, formulated fuzzy rules and introduced variable theory to adjust domain of discourse. Finally, we used simulink software to carry out experiments. The experiment result shows that variable-domain fuzzy PID controller has some undoubtedly advantages in performance evaluation compared to traditional PID controller, which including dynamic property and steady state error, and can be used to improve the quality of the adjustment of yaw angle.
Fluid-solid-thermal coupling analysis of an underwater valve
Authors: Han Jiazhen , Xie Yudong , Wang Yong , Pan Zihan 
Published: February 2021

Abstract
An underwater valve at 3000 meters underwater was chosen as the research object, aiming at obtaining the force characteristics of the underwater valve under high pressure and large temperature difference in the deep sea. The principle of fluid-solid-thermal three-field coupling was analyzed by using Fluent and ANSYS Workbench. Through numerical simulation, the fluid temperature distribution, the stress and deformation of the valve were obtained, and the valve was loaded. The influence of pressure and temperature on the performance of underwater valve was discussed. The results show that the fluid medium inside and outside the valve exchanged heat due to the large temperature difference, and vortexes were generated at the bottom of the valve seat, and the fluid pressure energy was converted into heat energy. The force of thermal stress generated by heat exchange on the valve body was greater than the equivalent stress generated by thermal-mechanical load.
Research on Electrical Control and Programmable Controller Based on Laser Tracking Measurement
Authors: Xing GuanSheng , Meng WeiChuan 
Published: February 2021

Abstract
Different production technology and process have different requirements for control circuit. However, no matter what kind of control circuit, it is composed of some basic control links. Programmable controller is a common electronic data control program, which not only plays a lot of advantages in industrial control system, but also is more and more widely used in people's daily life. It is an essential basic equipment in industrial automation system at present. As a kind of high-precision three-coordinate measuring equipment, laser dynamic tracker can be used to measure the spatial position of various single parts and complete sets of equipment. This paper mainly introduces the application of laser tracking system in electrical control and programmable controller, and looks forward to the development prospect of laser tracking detection technology.
Transient simulation model and process simulation analysis of fast cut back process in thermal power plant
Authors: Ruling Huang , Lin Li , Qing Cao , Yan Gao , Tao Luan 
Published: February 2021

Abstract
Fast Cut Back (FCB) technology of large thermal power plant can maintain the isolated operation of auxiliary power after the units are disconnected from the power grid. FCB unit can immediately cut off all external loads without turbine or boiler shutdown in case of large power grid failure, and supply power immediately as the external power grid fault eliminated, which has a very important impact on improving the stability and the recovery speed of the power grid system. Therefore, it is necessary to establish a dynamic mathematical model of thermal power plant to simulate FCB process. According to the principle of mass and energy balance, a dynamic mathematical model of 1050 MW thermal power unit was established. The model considered the change trends of main steam pressure and temperature caused by the action of main steam valve and high-pressure (HP) bypass valve in FCB process, and the action characteristics of safety valve and pressure control valve (PCV) valve in FCB system. This model provides a reference for the simulation and control of FCB process in thermal power unit.
Kinematics analysis of pneumatic soft manipulator
Authors: Shan Lijun , Li Yunfei 
Published: February 2021

Abstract
A software mechanical grabbing device is designed to deal with space debris. The robotic arm is composed of unit segments of modular design, and the kinematic model of the unit segments of the mechanical arm is established by simplifying it into a cantilever beam model. The relationship among the driving space, joint space, and operation space of the unit section is analyzed, and its kinematics equations are established.
A survey of recommendation systems based on deep learning
Authors: Liu Baichuan , Zeng Qingtao , Lu Likun , Li Yeli , You Fucheng 
Published: February 2021

Abstract
Faced with massive amounts of data, people may not be able to choose the items they like. The recommendation system came into being, and it has achieved a breakthrough for a long time. Using deep learning can mine the hidden attributes of users' items and integrate them well, bringing new changes to the recommendation system. This article describes the deep learning-based recommendation system and the traditional recommendation system, and analyzes their advantages and disadvantages.
Fault Stage Feature Extraction Method Based on Antinoise Gradient Operator Morphological Filters
Authors: Haibing Zhang , Dongshan Ruan 
Published: February 2021

Abstract
The cyclical impact signal aroused by mechanical fault contains feature information, such as fault type and fault stage. However, a transient impact component is usually modulated on the fundamental frequency and mixed with a large amount of noise. Thus, it is difficult to be extracted effectively. A feature extraction method of faults stage is presented based on morphological filter theory. An antinoise morphological gradient operator is applied to signal filtering. This operator can weaken the noise and clearly highlight the impact characteristics of different fault stages. The kurtosis of the spectrum band, including the passing frequencies of mechanical components, is used to differentiate fault stages. The applications on simulation signals and bearing test data indicate that this method can realize accurate extraction of fault characteristic frequency submerged in noise and effective distinction of different fault stages.
PMSG Wind turbine grid-connected pre-synchronization technology based on virtual impedance
Authors: Meng Zi Shu , Lu Yong Geng 
Published: February 2021

Abstract
With the integration of large-scale wind power, the inertia of the whole grid system is reduced. Therefore, virtual synchronous machine (VSG) technology has become a new strategy for wind power integration. In view of the fact that the VSG grid connected control of permanent magnet direct drive wind turbine does not consider the constraints of grid connection conditions, a scheme combining VSG technology with pre synchronization technology is proposed in this paper. VSG technology is still used in the PWM control of grid connected inverter. However, considering that there is no deviation between the phase angle of output voltage and the phase angle of grid voltage, it is impossible to judge whether the grid connection conditions are met or not when there is no deviation between the phase angle of output voltage and that of grid voltage.
Design of the self-oscillating loop of the optically pumped cesium magnetometer
Authors: Xue Liyue , Dong Haobin , Luo Wang , Ge Jian , Liu Huan 
Published: February 2021

Abstract
The self-oscillating loop is an important part of the optically pumped cesium magnetometer, and its working characteristics directly determine the accurate measurement of external magnetic field. The design of the self-oscillating loop has been discussed in this paper, including a signal conditioning circuit, a phase shifter and a frequency meter. It can be used to precisely improve the accuracy of resonance signal in a wide range of frequencies from 50 kHz to 350 kHz. The relative error of our system is less than 0.5×10−6 and it has a good prospect in the optically pumped cesium magnetometer.
Research on 3D digital design of AC filter field application in Qingnan ± 800kV converter station
Authors: Ran Ruijiang 
Published: February 2021

Abstract
Qingnan ± 800kV converter station AC filter bank adopts the improved "Tian" type layout scheme. Through the summary in different majors’ modeling, equipment layout, two-dimensional drawing and material statistics methods, the design efficiency and quality can be effectively improved. However, at present, the data transmission between 3D design software and some professional calculation software is not smooth, and a large number of models run slowly after the final assembly. Some software functions are more cumbersome and other issues are still restricting the development of 3D design. This needs to constantly optimize the software function and design process, promote the development of 3D digital design mature.
Mechanical Design and Electrical Experiment of Large Current Connector for Transformer Terminal and Drain Wire in Distribution Network
Authors: Wei Song , Hong Xiang , Qing Zhou , Fangxing Chen , Gang Chen , Miao Huang 
Published: February 2021

Abstract
The terminal and the drain wire of distribution transformers are generally connected by bolts, which appears not only reliable, convenient and simple in connection and assembling, but also easy to disassemble. However, the bolt connection is prone to fail, and it is easy to loosen under force. In this paper, a bolt-free quick connection design is proposed, which introduces a large current connector plug-in structure between the voltage side terminals of the transformer and the drainage line instead of the existing bolt connection. Through the experiments performed, the performance test indicators of the large-current connector after being connected to the transformer seems to meet the requirements, and is suitable for extreme environment with humidity, dust, ultraviolet rays and other harsh, which effectively improves the flexibility and convenience of the distribution transformers operation.
Research on fuzzy control of permanent magnet synchronous motor for a mobile robot
Authors: Huanhuan Ren , Zhang Lizhong , Su Chengzhi , Jian Sun , Liu Daoxue 
Published: February 2021

Abstract
In this paper, a biped robot powered by permanent magnet synchronous motor (PMSM) is proposed, and each leg of the robot is a 6-degrees of freedom (DOF) parallel mechanism. Due to highly nonlinear characteristics of the leg structure, the conventional PID control strategy based on trial-error process cannot maintain the high performance of the PMSM. In order to improve the robustness of PMSM servo system and the dynamic stability of the robot, the PID controller based on fuzzy theory is developed. Fuzzy PID controller can improve the tracking accuracy and load rejection capability of PMSM, which makes the real-time system response faster without overshoot. The simulation results show that compared with conventional PID, fuzzy PID can reduce position tracking error of PMSM and deal with the external disturbance effectively.
Research on Anti-pinch Control Strategy of Window Start-up Phase based on Ripple Motor
Authors: Cheng Anyu , Long Tianci , Cheng Zhu , Liu Chang 
Published: February 2021

Abstract
The anti pinch area of power windows is generally 4 mm-200 mm based on ripple motor. However, the problem of excessive anti-pinch force is most likely to occur when starting at 4mm during the process of window operation. Aiming at this problems, this strategy takes current, current change rate and start-up time that can characterize the start-up phase of the window as input according to the characteristics of fuzzy control that has better recognition for unstable starting current. Then, according to the actual engineering experience is used as a fuzzy rule to make a decision on the current start-up state of the window. Finally, the state is used as the input for the anti-pinch control strategy. The compensation mechanism based on the Freeplay is added to the strategy. The current state is used to design the current threshold to realize the control of the anti-pinch force during the start-up phase. The results show that the strategy can effectively reduce the anti-pinch force in the start-up phase, it can make the anti-pinch force less than 100N and meet the requirements of GB11552-2009.
Automated COVID-19 Detection and Diagnosis Framework Based on Severity Assessment
Authors: Chen Xiaohan , Wen Hongqiao , Wu Shengzong , Lan Weishun , Zheng Rong 
Published: February 2021

Abstract
Computed tomography (CT) has been an important complementary indicator in the diagnosis of coronavirus disease 2019 (COVID-19). The pandemic of COVID-19 has led to a sharp increase in the number of suspected cases, which puts great pressure on radiologists. A computer-supported assisting methodology is essential to get the preliminary diagnosis regarding the pneumonia infection. In this paper, we proposed a deep learning framework for COVID-19 diagnosis and severity assessment using chest CT. The framework can not only distinguish COVID-19 patients from healthy people, but also assess the severity of patients as early or progressive stage, which makes patients with different conditions in baseline test get reasonable allocation of medical resources. The framework is composed of two modules: segmentation module and diagnosis module. Segmentation module is designed to extract the regions of interest and calculate the opacity percentage, while diagnosis module is utilized to identify suspect cases and divide them into three categories: health, early stage, and progressive stage. A total of 150 CT exams were used to train and test. An F1 score of 95.44% for COVID-19 detection and an F1 score of 90.87% for severity assessment are obtained. We also evaluated the influence of the opacity percentage calculated by the segmentation module on the classification results. By using the opacity percentage characteristic, the accuracy is improved from 94.16% to 97.42%.
Test configuration optimization method based on NSGA2-MOPSO algorithm
Authors: Yun Lin 
Published: February 2021

Abstract
Test configuration optimization is an important part in the process of testability design. In order to be close to the reality, this paper chooses to carry out the test optimization selection under the condition of unreliable test. Under this condition, Test configuration optimization is essentially a multi-objective optimization problem. Therefore, this paper establishes a mathematical model of the problem with test cost, test quantity and false alarm rate as optimization objectives. In this paper, the multi-objective particle swarm optimization algorithm and NSGA2 algorithm are comprehensively analyzed. According to the advantages and disadvantages of the two algorithms, NSGA2-MOPSO algorithm is proposed to solve the test optimization selection problem. The results show that the NSGA2-MOPSO algorithm has good performance and high practicability.
Missing data filling method based on linear interpolation and lightgbm
Authors: Huang Guilin 
Published: February 2021

AbstractIn the context of the rapid development of integrated energy and the digital transformation of power grids, data is playing an increasingly important role in the safe operation of power grids. To deepen the value of data application and ensure the accuracy of data application, this paper proposes a data filling method that combines linear interpolation and LightGBM (Light Gradient Boosting Machine) in response to the missing phenomenon in the source network data collection process. The process can generally be divided into 2 steps: First, linear interpolation is exploited to process short-term missing data. Then the LightGBM can be used to process long-term missing data. In the process of using LightGBM, linear interpolation is used to interpolate the independent variables of the input model. Through the above process, the data for the missing ratio could be obtained, which can then be used to complete all data filling in order from high to low. Through actual data test, this method has better data filling performance.
Residual life prediction of mining cables based on RBF neural network
Authors: Wu Weili , Yang Jing , Li Lei , Fan Wenling 
Published: February 2021

Abstract
The RBF (Radial basis Function) neural network forecasting model is constructed for the mine cable life prediction problem. According to the mine cable in line with the characteristics of accelerated life test, the temperature and the dielectric loss factor are chosen as the model input. In order to solve the problem that the number of training samples is too small and detection samples cannot be constructed, the dielectric loss factor and aging time in each temperature segment collected are linearly interpolated to generate a large number of simulation data as training target vectors, and the RBF neural network is established for life prediction. Then the predicted life value is compared with the design life of the cable for verification. The result confirms that the RBF neural network model can reflect the relationship between the dielectric loss factor and residual life under a certain humidity and the different levels of temperature, which has certain practical significance for the prediction of cable insulation life.
Application of the denoising technique based on improved FastICA algorithm in cross-correlation time delay estimation
Authors: Shi Junhe , Yan Hua , Wei Yuankun 
Published: February 2021

Abstract
Cross-correlation is a common time delay estimation method. However, in the actual measurement environment, the near-end and far-end sensors are often disturbed by the correlated noise, which seriously affects the accuracy of time delay estimation and even leads algorithm is proposed, and the steepest descent is introduced to reduce the sensitivity of FastICA algorithm to initial values. The useful acoustic data and disturbing acoustic data were measured respectively in a simulated granary. From these data, the signals contaminated by noise were generated by a mixing matrix and used for testing the performance of the proposed method. The testing results show that the proposed method can effectively suppress the influence of correlated noise on cross-correlation time delay estimation, and improve the accuracy of estimation.
An approach based on statistical features for extracting human actions from multivariate time series
Authors: Gui Jun , Qin Zhaobo , Jia Danping , Zhu Jianguang 
Published: February 2021

Abstract
Extracting system behavior from the multivariate time series collected by sensors is more challenging. If regarded people as system, the various physical actions can be considered as different states of the system. Our intention was to produce a simple, flexible and accurate method for clustering multivariate time series to obtain the system state. Previously, we proposed a distribution-based state extraction method (DBSE) that can effectively extract motion from the multivar-iate time series of human leg activities. In this paper, we propose an Auto-segmented state extraction method (AS-DBSE) by improving the size of the segmented window to adapt to more complex situations. The method uses vectors composed of statistical feature parameters to represent time series. It uses distance as the similarity measure and clusters these vectors to get the state of the system. We have proved the effectiveness and simplicity of this method through research on human arm activity data. Finally, compared with clustering based on Toeplitz inverse covariance (TICC) and symmetric non-negative matrix factorization (SymNMF), the results of the new method are more satisfactory.
Adaptive bluetooth indoor positioning system based on greedy strategy
Authors: Ding Xin , Dai Yawen 
Published: February 2021

Abstract
In order to solve the problem that current bluetooth indoor positioning system has low positioning accuracy in dynamic environment and can’t unable to adapt to dealing with complex situation of anchor circle, this paper proposes an adaptive bluetooth indoor positioning system based on greedy strategy. The system uses the deployed bluetooth to intelligently sense the real-time environment and measure the ibeacon signal attenuation model to reduce the ranging error caused by dynamic change of environment. In addition, the three anchor circles of the weighted centroid positioning into three groups and two different anchor circles are one group, and greedy strategy is used for getting the better weighted objects when each group of circles are intersected, or separated, or contained. Finally, the sum of the reciprocal radius of each group of anchor circles is used as the weight to obtain the estimated coordinates of unknown nodes. To verify the effectiveness of the positioning system by case study, the results show that the average error value is 0.60m. Compared with the centroid localization algorithm and weighted centroid algorithm, the system has the advantages of intelligent environment perception, higher positioning accuracy, and adaptive algorithm for dealing with various situations of anchor circle.
Grasping Prediction Algorithm Based on Full Convolutional Neural Network
Authors: Feng Kaiyue , Wei Wu , Yu Qiuda , Liu Qinglun 
Published: February 2021

Abstract
Robot grasping is a very frontier and important research direction in the field of robotics. In order to solve the problem of the robot's real-time capture, reduce the time of the visual processing, we proposed a two-stage Convolutional Neural Network structure whose design is simple, with less training parameters, improving the efficiency of the visual system. Using rotation and translation to expand the Cornell fetching dataset. The best model at Cornell grasp test set has achieved 88% of forecast accuracy compared with 73% accuracy rate on one stage network. Moreover, our model size is 0.51MB, speed at 30 FPS on GPU inferencing.
The BOW image retrieval algorithm based on the longest common word string constraint
Authors: Me Mingyu , Zhang Jiangzhou , Li Yang , Wang Shuai 
Published: February 2021

Abstract
This paper adds the spatial and semantic relations of the "visual dictionary", the longest common visual word string constraint in the image based on the BoW model. The image is represented at the vocabulary level and the phrase level at the same time. This algorithm can better represent the content of the image, thereby improving the quality of image retrieval. Experiments verify that compared with the BoW model, the accuracy of the BoW image retrieval model based on the longest common word string constraint is well optimized.