bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive monitoring cycle classification of centralized monitoring substations based on knowledge map and competitive neural network
Authors: Wang Jian , Zhang Yuze , Xu Yuanfu , Wang Weili , Li Saifeng , Wang Jianzhong 
Published: August 2021

Abstract
The influencing factors of the comprehensive monitoring cycle of the centralized monitoring substation are analyzed, including the voltage level of the substation, the frequency of centralized monitoring defects, equipment operation situation, the importance of the substation, the operation environment and the average load of the equipments. Those information can be obtained by constructing the knowledge map of centralized monitoring. On this basis, a comprehensive monitoring cycle classification method based on competitive neural network is proposed, and machine learning method is used to achieve a scientific and reasonable classification of comprehensive monitoring cycle of the substations. The simulation results show that the method is feasible and effective.
Design of Remote Monitoring System for Pre-Tightening Force of Anchor Bolts
Authors: Panfei Li , Qiankun Chen , Qi Zhou , Defu Zhang 
Published: August 2021

Abstract
Given the broad monitoring range and long monitoring time of anchor bolt loosening of draught fan, and harsh site environment in offshore wind power projects, a remote temperature and pressure monitoring system was designed in this study to realize the real-time wide-range monitoring of anchor bolt loosening of draught fans. The strain pressure transducer and platinum thermistor were used at the test end to acquire the pressure and temperature data, respectively. stm32f103 was used as the master controller in the acquisition system, hierarchical networking was conducted via Modbus protocol, and the long-distance transmission was realized by a fiber optical transceiver. LabVIEW was used by the upper computer to establish the client side to implement the data acquisition, storage and real-time monitoring.
Finite Element Analysis and Buckling Behaviour of I-shaped Beams with RHCFST Upper Flange
Authors: Ji Jing , He Lingjie , Xu Ming , Zhong Meihui , Jiang Liangqin 
Published: August 2021

Abstract
In order to analyse the buckling behaviour of I-shaped beams with rectangular high-strength concrete-filled steel tubular (RHCFST) upper flange, a total of 7 simply-supported beams are designed with height-width ratio of upper flange and span as the main parameters in this paper. Based on ANSYS software, the finite element models are established, and the eigenvalue buckling analysis of seven simply-supported beams are carried out. The buckling loads of the composite beams can be obtained and the influence of height-width ratio of upper flange and span on eigenvalue buckling loads of each order of the beams can be studied. The results show that the buckling loads of each order of the beams can be significantly improved with the decrease of the height-width ratio of upper flange and span. Height-width ratio of upper flange and span have greater influence on high-order buckling load of beams. When the first-order buckling mode of the beam is analysed, overall flexural-torsional buckling occurs and the overall linear displacement and angular displacement reach the maximum at the mid-span position of the beam. It can be concluded that the displacement of the beam is mainly out-of-plane displacement in Z direction, and the rotation of the beam is mainly in X direction. It lays a foundation for further nonlinear buckling analysis of such composite beams.
Automatic sealing technology for solidification line of medium and low level radioactive waste in nuclear powered ships
Authors: fengtian Lin , yu Wang , xuhui Zhou , haoqiang Zhu , jinying Xiong 
Published: August 2021

Abstract
The disposal of medium and low level radioactive waste in nuclear powered ships is increasing day by day. With the increasing requirements for nuclear safety and personnel protection, the intelligent disposal equipment should be improved to fully replace manual operations. The automatic capping technology in this paper can completely replace the original manipulator operation. With it, people can be kept away from dangerous working environments, thereby reducing the dose levels of the general population. The input of the device can also improve the safety and reliability of the whole operation line, thus improving the nuclear safety level of the solidification line.
Research on PD monitoring and location method of automatic directional substation
Authors: Hou Jie , Zhang Yanjun , Xu Su , Zhang Ruiqiang , Li Jiqiang , Xu Changjian 
Published: August 2021

Abstract
The accurate positioning of partial discharge can effectively avoid the occurrence of insulation failure of power equipment, but most of the existing positioning devices are fixed antenna array, which is difficult to achieve multi angle discharge monitoring in space, and the positioning method is single and the positioning accuracy is not high. Therefore, this paper proposes an automatic directional monitoring device for partial discharge source, and proposes a precise positioning method based on fixed point iteration method. With this positioning method as the main method and the automatic directional device as the auxiliary method, the spatial multi angle positioning of partial discharge source is realized. Firstly, PD signal recognition algorithm is used to identify the fault of PD signal, and then the steering gear rotation angle is determined by the angle correlation calculation formula, so as to accurately identify the position and direction of PD source. On this basis, four antenna array positioning algorithm is used to accurately locate PD source. Finally, through the field simulation test, it is found that the angle error of automatic orientation is 3°. The position error of PD source is 0.19m, which verifies the feasibility of the proposed method and device.
Experimental Management Study on Physical Influence Model of Wave Nearshore Mutational Terrain
Authors: Li Ma Chang , Peng Dong , Yong Jing 
Published: August 2021

Abstract
The influence of nearshore mutational terrain on wave was experimentally studied via local-global physical wave model. It was discovered that the influence of submarine topography on wave was mainly manifested by the change in wave height, which was especially apparent when the submarine slope gradient changed greatly and presented approximate mutation. Moreover, the differences of different wave directions and different wave elements in influencing the wave heights with different accumulative frequencies were presented. Therefore, the influence of nearshore mutational terrain on wave should arouse high attention in the engineering construction.
How does the control logic influence the establishment of a data-driven chiller model?
Authors: Qiu Shunian , Li Zhenhai , He Ruikai , Li Jiajie , Li Zhengwei 
Published: August 2021

Abstract
The modelling of chiller performance is critical for chiller optimal control, and fault detection and diagnosis (FDD). Different kinds of chiller models including sophisticated mechanistic models (white-box models), purely data-driven models (black-box models like artificial neural networks, ANN), and semi-physical models (grey-box models like empirical equations) have been proposed and tested. Due to the development of machine learning techniques, data-driven models have become more popular recently. The performance of the established data-driven model (accuracy, robustness, generalization) could significantly affect the model application. To enhance the model performance, a lot of studies have been carried out on investigating and modifying the model structure. However, the influence of the data quality on model training has not been sufficiently studied. When adopting historical data to train models, the data distribution is highly correlated to the control logic. So how does the control logic influence the establishment of data-driven chiller models by affecting the data distribution? In this study, experiments are conducted on an air-cooled chiller under model-free stochastic control to acquire rich and variable operational dataset; then the dataset is grouped into three corresponding to different chiller control logics. Finally, three models trained by three training datasets are evaluated, and the results suggest that when establishing data-driven chiller models, preliminary stochastic operation is cost-effective to acquire rich data for robust chiller modelling.
Study on Water quality Monitoring Method of Jialing River based on Sentinel-2 MSI Sensor Data
Authors: Lv Yingxue , Tian Zhen 
Published: August 2021

Abstract
Remote sensing monitoring has become an important means to evaluate urban water status, which plays the key role in maintaining the balance of urban ecological environment. In this study, based on the Sentinel-2 MSI sensor data, an inversion model of water quality parameters was established to monitor the concentration of chlorophyll a and suspended matter, and turbidity in some sections of the Jialing River. The results show that the inverted water quality parameters in this study are all within the normal range, and remote sensing technology can be effectively applied to regional water quality monitoring.
Development and implementation of standardized measurement and control system
Authors: Yujie Yang , Xian Zhang , Yongyong Duan , Jinsong Xue , Yadong Zhao 
Published: August 2021

Abstract
At present, due to the variety of product models and the increasing production data, the existing single machine based tester can not meet the needs of production. This paper introduce how to design and develop a centralized measurement and control system for servo products through standardized design and craft configuration.
Research on Machine Learning Optimization Algorithm of CNN for FPGA Architecture
Authors: Zhao Xiaodong , Zhang Xunying , Yang Fan , Xu Peiyuan , Li Wantong , Chen Fayang 
Published: August 2021

Abstract
In order to meet the application requirements of deep learning detection and recognition algorithm for Field Programmable Gate Array (FPGA) computing structure, this paper proposes a machine learning optimization algorithm of convolutional neural network (CNN) based on pruning and Int8 quantization. By analyzing the machine learning intelligent recognition network, the Yolo v3 target detection network is selected to verify the optimization algorithm. Aiming at the Yolo v3 network with balanced speed and precision, the optimization algorithm is studied in detail. Based on Amazon Cloud FPGA EC2 instance platform and ZCU104 FPGA hardware platform, machine learning optimization algorithms are used to accelerate the application of Yolo v3 network detection and recognition. Satisfactory results are obtained on both FPGA computing platforms. The experimental results show that the machine learning optimization technology can improve the inference speed of neural network based on both FPGA platforms. The network structure optimized by pruning and Int8 quantization algorithms can achieve high acceleration speed, with very limited accuracy loss.
Fault mode analysis and simulation verification of hydraulic system based on AMEsim
Authors: Ma Qi , Song Dong , Liu Bobing 
Published: August 2021

Abstract
This paper studies the relationship between the fault modes of hydraulic system and their flying parameters according to the principles of hydraulic systems. Based on the study of the working principle and composition architecture of the hydraulic system, the AMEsim software is used to construct a simulation model of the hydraulic system, to analyse the fault modes and mechanisms of key components in the system and their failure effects, and to establish a link between the fault modes and the flying parameters according to which practical evaluation parameters are provided for the subsequent monitoring and handling of system failures.
The design of remote data exchange system for Intelligent pharmacy
Authors: Lan Cao , Xiang Li , Yixuan Sun , Binxia Yuan , Jianbeng Liu 
Published: August 2021

Abstract
To achieve the intelligent management of drugs in pharmacy, a remote data exchange system is designed. Based on Labview, the software of doctor side and pharmacy side is designed. According to the demand of smart pharmacy, the software are divided into various functional modules, and then the workflow of each software module is designed. By using TCP/IP protocol, the remote communication between the doctor and the pharmacy is realized. By using th Access database technology, it can realize the functions of data storage and data real-time display in the whole intelligent pharmacy system. Finally, experiments were performed and the results showed that the doctor can issue prescriptions through this system; Pharmacy can automatically receive prescriptions, and update it to uniform drug database.
Research on calculation model of penetration depth when anchor touches Seabed
Authors: Li Xuedong , Hou Zhiqiang , Lu Juncheng , Yang Dongxu , He Zili , Cao Zhaonian , Zhao Guo-qing 
Published: August 2021

Abstract
In order to provide a reference for the safe buried depth of underwater pipeline in the navigable waters, this paper on the basis of the famous penetration formula, studied the calculation model of ship’s anchor dropped to seabed. The model considers the main factors that affect the penetration depth, such as the type of anchor, the weight, the speed of bottoming and the substrate condition. The model makes clear the bottom coefficient values, shows the method of hall anchor’s velocity of touching bottom and cross sectional area, and combines with the existing cast anchor experiment results to determine the shape factor of anchor. Using the calculation model, typical scenario was calculated and the calculation result of different methods were compared. The results show that the calculation model is better ease and compliance. It is very important to study the factors affecting the penetration of ship anchor and to determine and evaluate the buried depth of underwater pipeline in navigable waters.
Research on grid load model based on SPACK architecture of power big data
Authors: Xin Rui , Jiang Dan , Liu Hong , Chen Xi 
Published: August 2021

Abstract
Big data service is the key to the construction of smart grid, and the method of analyzing electricity consumption behavior based on improved AP clustering and the method of forecasting electricity load based on random forest is proposed. To address the problem of high complexity of AP clustering analysis, the entropy weight method is used to establish the index weights and improve the similarity calculation method to realize the fast and accurate analysis of customers’ electricity consumption behavior. For the problem of power load prediction, the fuzzy C-means method is used to construct the index weights. The fuzzy C-means is used to construct the historical similarity daily sample set, and the random forest is used to predict the electric load. The SPACK multi-level data processing framework is proposed to meet the needs of parallel processing speed for large amounts of data. The simulation results verify the effectiveness of the method proposed in this article and the important guiding price for the Power grid.
Semi-automatic apparatus of the permeability coefficient for cutoff walls in expansive soil areas
Authors: Zhang Min , Shen Xizhong , Lan Yan , Dong Chenghui 
Published: August 2021

Abstract
The permeability coefficient of most cutoff walls with plastic materials is less than 10−6 cm/s, it exceeds the measurement range of the existed devices. For the permeability coefficient testing for cutoff walls with low permeability, there are complex in the automatic system of pressure control, difficult in the keeping stability of hydraulic pressure, high in the measurement precision, leaky in the contact surface between the fixing apparatus and the measured specimen. Firstly, based on the characteristic analysis of cutoff walls, the hydraulic pressure was accurately controlled when the valve of atmospheric pressure control with high precision worked in with the electromagnetic valve, the hydraulic pressure was controlled. Secondly, the shape of inner space for the fixing apparatus of the specimen is developed, the leakage of the contact surface between the fixing apparatus and the specimen was greatly decreased. The test showed that the semi-automatic apparatus could realize automatic control of the hydraulic pressure accurately with the combined action of an electromagnetic valve and a pressure reducing valve, the leakage of the contact surface could be basically avoided. The testing apparatus can be used in penetrability tests and detection of project quality for cutoff walls with low permeability.
Evaluation Model of Grain System Based on AAQN Index System
Authors: Ge Ying , Chen Wen , Zhang Yinxuanye 
Published: August 2021

Abstract
According to UN FAO, global food production in 2019 reached 2.722 billion tons, showing high profitability and efficiency levels[1]. However, while we enjoy fresh and nutritious food, people in Africa and Central Asia are suffering from starvation and nutritional deficiencies. Despite the high profitability and efficiency levels, the existing food systems are challenged by equity and sustainability problems. In order to assess the current food system and propose a rational optimization approach, we propose a linear and hierarchical food system based on the priorities of food flow and distribution. To quantify food security based on food systems, we develop the AAQN Index system to measure the affordability, availability, quality& safety, and natural resources& resilience of a food system based on the Global Food Security Index (GFSI). We select 68 indicators and calculate the indicator weights by combining the entropy weight method (EWM) with GFSI. By systematically clustering the calculated results, we classified the food systems of 113 countries/regions into: excellent, normal, and poor. Then, we adjust the priorities of the Indian food system, a poor food system, to reveal the differences before and after optimization. Finally, by predicting the future AAQN Index of Indian through Grey Relational Analysis.
A Intelligent Portable Manager for Health: Study Design
Authors: Ye Xuewei , Ye Xufang 
Published: August 2021

Abstract
The immune function of the middle-aged and elderly groups is decreased, and they are easy to be infected with the virus, and once infected, they are easy to be turned into acute and critical patients with a high mortality rate. In addition, China’s aging population is becoming more and more serious, and the middle-aged and elderly population is a high incidence of all kinds of respiratory or cardiovascular system diseases. Most middle-aged and elderly people have more than one chronic disease at a time and need medication to treat it, and the type and amount of medication taken daily is often variable. However, due to the common problems of memory loss and blurred vision among middle-aged and elderly people, the various number and types of medication may lead to the possibility of the elderly taking it by mistake, missing or wrong, which may easily lead to the hidden danger of medication safety. This design will be health inspection management, medical interconnection, pharmaceutical affairs management, three main feature set in one, its realization storage service remind, interactivity, and index detection, do medicine detection and the sharing of data, realize the visualization of medical Internet, providing personalized family health management services, and the spread of interactive public medical basic knowledge.
Design of power decommissioning material management system based on RFID technology
Authors: Li Yang , Huang Xiaoming , Lin Minghui , Gao Ming , Yue Heng , Ding Jing 
Published: August 2021

Abstract
Due to the existence of many interference factors, the recognition rate of the existing power decommissioning material management system is low when reading material labels, so a power decommissioning material management system based on RFID technology is designed. In the hardware part, RF transmitting circuit and receiving circuit are designed to collect and process the specific information of decommissioning material tags in real time. In the software part, the main performance requirements of the system are determined according to the business process of power decommissioning materials management. Radio frequency identification technology is used to identify the communication tag of decommissioning electrical materials, and the system function module is designed to realize the data transmission between the system function module and the non-contact communication tag. The experimental results show that the label recognition rate of the system designed in this paper is 10.08% and 6.17% higher than that of the management system based on one-dimensional bar code recognition technology and twodimensional bar code recognition technology, respectively. The system has good ability of reading and identifying the labels of decommissioning materials, which is conducive to improving the information management level of power enterprise.
An enhanced second order prediction using the statistics of image difference signal for HEVC
Authors: Su Xiaoyu 
Published: August 2021

Abstract
This paper presents an enhanced second order prediction (ESOP) algorithm using the statistics of image difference signal. The algorithm can selectively control the residual of the first inter prediction for the second intra prediction. Unlike other second order prediction (SOP) algorithms, our proposed algorithm employs a check-strategy to adaptively select the residual of the first inter prediction for the second intra prediction so that the correlation between residual pixels can be kept close to the allocated accurate prediction as much as possible. Experimental results show that under the same condition, on average, the PSNR is increased by 0.40dB and the bit rate is reduced by 6.15% as compared with traditional second order prediction for QCIF and CIF sequences. This selective algorithm is particularly suitable for dealing with video contents containing complex motions in video compression.
An On-orbit Target Detection Method in Remote Sensing Images for Micro Satellite
Authors: Zhou Qihui , Cui He , Liang Shengming , Li Huiqin 
Published: August 2021

Abstract
Aiming at addressing the contradiction between the information timeliness and on-board computing capacity and data transmission capacity in on-orbit image processing system of small commercial remote sensing satellites, a convolutional neural network based target detection algorithm is proposed. The calculation amount of the model is optimized to 25MFLOPS by using transfer learning, sparse training and weight quantification, while the weight file data is reduced from tens of Mb to 0.5Mb, which makes it possible for small commercial remote sensing satellite to detect target on-orbit quickly, and meets the requirements of the timeliness of remote sensing information.