bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on High Pressure Fine Mist Cultivation Equipment
Authors: Yang Yousheng , Li Xiaoqing , Zheng Yunkai , Wang Yi , Men Daoxin
Published: August 2021

Most of the existing aerosol cultivation equipments are bulky, simple-structured and poor in functional stability. Based on this, the author developed a set of automatic control high-pressure fine mist cultivation device, designed the PLC automatic control circuit, and simulated and tested the temperature and humidity change curves. The test results verify the simulation model and the overall device runs well, among which the spray atomization process, and the temperature field, humidity field and velocity field under three atomization modes are simulated. Three atomization schemes are analyzed, and in the end the optimal one is selected. In comparison, the side-by-side spray is completely covered; the atomization is more sufficient. The results show that the time when the humidity reaches 90% in the same position is different under different initial humidity conditions. The atomization humidity maintenance time in different environments is approximately the same, and can be maintained for 4 to 5 hours. It can be seen from the comparison of the results that the greater the humidity, the shorter the heat exchange time and the faster the heat exchange.
Real-time Pedestrian Detection Algorithm Based on Improved YOLOv3
Authors: Xi Xianchang , Huang Zhikai , Ning Lingyi , Zhang Yang
Published: August 2021

As a research hotspot in the field of current computer vision, pedestrian detection is widely applied to many fields, such as video surveillance and autonomous driving. However, the accuracy of pedestrian detection under video surveillance is poor, and the miss rate of small target pedestrians is high. In this paper, an improves the YOLOv3 algorithm and a YOLOv3-Multi pedestrian detection model had been proposed. First, referring to the residual structure of DarkNet, the shallow features and deep features had been up-sampled and connected to obtain a multi-scale detection layer. Then, according to different special detection categories, the spatial pyramid pool (SPP) is introduced to strengthen the detection of small targets. The experimental results show that our method improves the average accuracy by 2.54%, 6.43% and 8.99%compared with YOLOv3, SSD and YOLOv2 on the VOC dataset.
Retrieval of Suspended Sediment in Songhua River Based on Sentinel-2 Satellite
Authors: Han Xu , Du Chong
Published: August 2021

In view of the current situation that the remote sensing inversion of suspended sediment is mainly based on low spatial resolution satellite data, sentinel-2 satellite data with resolution of up to 10m is used to retrieve the suspended sediment content in Harbin section of Songhua River. And the inversion model is established based on the measured data and remote sensing data. The results show that the fitting degree of b3/(B2 + B4) in the multi band ratio and the measured suspended sediment concentration is the highest, reaching 0.904. The results show that the average relative error between the inversion value and the measured value is 19.88%, and the root mean square error is 0.039g/l. The results show that the suspended sediment content of Songhua River is lower than that of other six rivers in China, and belongs to the less sand river. The sediment content on both sides of the bank is higher than that of the center of the river. In the wide river, the suspended sediment content is low, and the suspended sediment content is higher in the narrow area.
Research on Internet data security and privacy protection
Authors: Ke ZHANG , Yongzhen LI
Published: August 2021

The company's data leakage has always been a very serious problem. Many of the leaked data is the user's personal privacy data, which will bring a lot of trouble to users. In order to improve the security of the storage and use of personal private information in the database, two methods of lightweight private information encryption and social engineering anonymization are proposed to protect database information. We compare the proposed method with the application layer encryption and pre encryption methods. The experimental results show that the proposed method can effectively protect the user's personal privacy data, and can detect and recover the privacy data when managers need it. The storage efficiency of the three methods is close. Therefore, it has good application value in privacy protection.
Research on Kalman Filter for One-dimensional Discrete Data
Authors: Wei Fan , Zhang Zupei , Jia Kunpeng
Published: August 2021

Kalman filter processes the input and observation signals with noise on the basis of linear state space representation to obtain the system state or real signal. In the one-dimensional model, due to the lack of multi-dimensional description of the target, the prior estimate of the state is often the measured value of the previous moment. When the target state changes, the divergence phenomenon will occur. Aiming at the problem that the one-dimensional traditional Kalman filter lacks the target observation dimension, which leads to the divergence or imprecision of the filter, this paper focuses on improving the estimation method of the target state, and proposes a real-time prediction model based on the cascade structure. This model can improve the response of Kalman filter to the change of target state and dynamically adjust the Kalman iterative domain to improve the measurement accuracy. The digital signal filtering simulation is carried out and the performance of the filter is verified based on LabVIEW. Experimental results show that the algorithm can maintain the accuracy and real-time performance of filtering when only one dimension observation results are obtained.
Benefit Analysis of Hydrothermal Processing of Biogas Slurry Applied to Biogas Power Generation Project
Authors: Sun Ke , Liao Dachen , Ye Qiang , Zhang Yuanshang , Chang Xinglan , Xi Shuang , Zhang Tianrong
Published: August 2021

Taking a large-scale anaerobic fermentation biogas power generation project as an example, the biogas slurry was hydrothermal processed and then reused to the anaerobic reactor, so as to reduce the biogas slurry discharge and increase the biogas production. The benefit analysis is carried out on the basis of meeting the requirements of increasing the gas production and the economic benefit as far as possible in the biogas power generation project. Through analyzing the amount of biogas slurry returning to field, the increase of biogas production, and the ammonia nitrogen concentration of the material in the anaerobic reactor, it is concluded that the reasonable amount of hydrothermal processing in this project is 150 t⋅d−1∼200 t⋅d−1 (the ratio of the hydrothermal processing capacity to the material in the anaerobic reactor is 22.4% ∼ 29.9%), which can increase the biogas production to 338.2 Nm3⋅d-1 ∼346.6 Nm3⋅d-1 per ton of dry solid.
Research on Fruit Recognition and Positioning Based on you only look once version4 (YOLOv4)
Authors: Dexiao Kong , Junqiu Li , Jiawen Zheng , Jiale Xu , Qinghui Zhang
Published: August 2021

The recognition and spatial coordinate positioning is an important part of picking equipment of fruits. This paper introduced a method of target detection and pixel learning positioning of fruits based on the Darknet depth framework YOLOv4. We utilized GPU training in Ubuntu 19.10, and used 2000 images of various fruits as the training set for recognition model training, and performed and verified tests in the GPU environment. The results showed that the accuracy of fruit recognition is above 94%, the detection time of a single image is 12.3ms, and the detection rate of the video is 17f/s. The actual test showed that the system has good stability, real-time performance, and correctness of picking objects.
A Survey on Hybrid Energy Systems Market
Authors: Hengtian WU , Hongcai DAI , Weizheng KONG
Published: August 2021

The fast-growing energy needs over the last few years across the world have intensified challenges: how to reduce the generation and operation costs in power systems and, in parallel, to minimize the hydrocarbon emissions. The hybrid energy system (HES) provides overarching opportunities for solutions to aforementioned challenges. The paper starts with the classification of the energy supply and consumer in the market. Next, the HES operations and services are introduced. In the final, the typical market competition relationships of HES energy trading are proposed and analysed.
China Southern Power Grid’s power supply reliability development strategy under digital transformation
Authors: Qiuling Yu
Published: August 2021

Power supply reliability management is a systematic work that requires long-term persistence and continuous improvement. The four factors that restrict the improvement of reliability are: grid, equipment, automation and management. In the long run, the grid structure, equipment quality and automation level of the power grid are the material basis for improving the reliability of power supply. Continuous investment in power grid construction is needed to build a strong and reasonable standardized grid structure, and the application of sturdy and durable high-quality equipment to improve distribution Practical level of electrical automation, improve the ability of the distribution network to transfer power supply, and reduce the failure rate of the distribution network. In view of this, this article mainly analyzes the development strategy of China Southern Power Grid's power supply reliability under the digital transformation.
Design of Algorithm for Forecasting Agricultural Output Quality Based on Genetic Algorithm-Back Propagation Neural Network
Authors: Yuehui Wang , Bin Wen , Xin Liao , Lan Chen
Published: August 2021

Nowadays, agricultural technology is developing rapidly, and the concept of smart agriculture is gradually popularized. Economic development has made consumers pay more attention to the quality of agricultural output, so the prediction of the quality of agricultural output has also become important. This research takes the sugar content level of apples as an example of the quality of agricultural output, combined with the meteorological conditions of each crop period in the apple producing area as an influencing factor, and uses the back propagation neural network optimized by genetic algorithm to establish the quality of agricultural output Algorithm model. The experimental results show that the accuracy of GA-BP predicting apple sugar content grade, MAE and RMSE are 90%, 0.1 and 0.316 respectively, which is more ideal than the traditional method.
Suppression of Doppler Ultrasound Signal Wall Components Based on Local Mean Decomposition Algorithm
Authors: Qinghui Zhang , Junqiu Li , Jian Rong , Jiawen Zheng , Jiale Xu
Published: August 2021

The low-velocity blood flow signal close to the blood vessel wall is very important for the early diagnosis of vascular diseases. To obtain more accurate low-velocity blood flow signals from the Doppler ultrasound echo signal, this paper proposes a carotid artery low-velocity blood flow signal extraction method based on local mean decomposition (LMD). First, the LMD decomposes the original signal into a series of product terms. Then, based on the instantaneous frequency and amplitude, the blood flow stratification index is constructed to subdivide the blood flow and blood vessel wall signals in the product component. Finally, the signal is reconstructed, thereby achieving the suppression of the clutter signal of the blood vessel wall. Experimental results show that this method could effectively obtain low-velocity blood flow signals.
Prediction of dissolved oxygen in marine ranch by Bayes algorithm based on linear sliding window selection
Authors: Sun Jiajun
Published: August 2021

Accurate prediction of water quality in marine ranch can help to avoid the problem of marine mortality caused by changes in water quality and can help to improve the productivity of marine ranch. In order to make effective predictions of water quality parameters, this paper proposes a Bayes-based prediction algorithm based on linear sliding window selection method, and use the model to predict dissolved oxygen data. Comparative experiments with similar algorithms illustrate that the prediction accuracy of this model has improved considerably.
A new near-lossless image information hiding algorithm with controlled hiding capacity
Authors: Zhang Yi , Zhou Quan , Hu Yan-lang , Liu Juan-ni , Liu Rui-hua
Published: August 2021

Image information hiding technology can embed more data without increasing the amount of transmitted data. But in most cases, the information embedding rate is different for different carrier images. To increase the embedding rate, the data will be damaged. In order to improve this problem, a new near-lossless image information hiding algorithm with controlled hiding capacity is proposed, which is referred to as NLH. This method makes the pre-processed data in a specific range to facilitate information hiding by interval transformation and data mapping. According to analysis and calculation, the lossless performance of the proposed algorithm in this paper is better than the LSB algorithm. And the result of simulation shows that this method has a fixed information embedding rate (18.75%/1.5bpp) without more transmitted data, and the original image is restored losslessly or nearly losslessly with the improved transmission efficiency.
Synthetic Aperture Radar Tomography in Urban Area Based on Compressive MUSIC
Authors: Li Hao , Yin Jie , Jin Shuang , Zhu Daiyin , Hong Wen , Bi Hui
Published: August 2021

Synthetic aperture radar (SAR) tomography (TomoSAR) extends the synthetic aperture principle into the elevation for three-dimensional (3-D) imaging. Spectral estimation is the conventional TomoSAR imaging method, such as multiple signal classification (MUSIC). For the sparse elevation distribution, compressive sensing (CS) is a favorable technique for the elevation reconstruction. Compressive sensing multiple signal classification algorithm (CS-MUSIC) is a combination of CS and MUSIC algorithm. It takes the advantage of both conventional spectral estimation and CS technology, and hence overcomes the drawbacks of existing methods and obtains the super-resolution ability. In this paper, the effectiveness of CS-MUSIC in TomoSAR imaging of urban area has been validated by simulated and real TerraSAR-X data. CS-MUSIC algorithm can effectively solve the problem of acquiring high-resolution TomoSAR imaging with small amount of data.
A novel method for parameter identification combining analytical method and optimization algorithm
Authors: Hao Peng , Zhang Yunpeng , Lu Hao
Published: August 2021

Single-diode model is widely used in photovoltaic system modelling and output estimation because of its simplicity and accuracy. This paper proposed a novel method for parameter identification and performance estimation by using measured data. The proposed method combines the analytical method and optimization algorithm to extract the model parameters and considers the deviations of different operating conditions between the measured and estimated data in calculation procedure, which reduces the dimensions of the search space and save computational cost for parameter optimization. The accuracy and effectiveness of the proposed method are validated by large number of experimental data under wide range environmental conditions.
A Comparative Study of Deep Learning Frameworks Based on Short-term Power Load Forecasting Experiments
Authors: Zhang Jingyu , Zhang Yongjun , Lu Yanping
Published: August 2021

This article introduces the results of comparative research on mainstream deep learning frameworks, including PyTorch, Keras, Tensorflow, and MXNet. Analyzed their similarities and differences, and compared their efficiency through short-term power load prediction experiments.
Object Oriented Road Extraction from Remote Sensing Images Using Improved Watershed Segmentation
Authors: Dawei LIU , Shujing GAO
Published: August 2021

A novel object oriented road extraction method is presented for the road extraction from remote sensing images. Firstly, an improved watershed algorithm is adopted for image segmentation, and the spectral, texture and geometric features of the image are fully considered in the segmentation process so as to improve the segmentation accuracy. Then road knowledge base is built and various features of the road are added into the base. Finally, the road extraction purpose is reached by calculating the features of the objects and comparing them with the knowledge base. Experiment results show that the method can achieve higher accuracy and quality in road extraction.
Modular substation intelligent control cabinet temperature control system
Authors: Yin Kang , Huang Xinying , Zhong Tingting , Chen Qingwei , Tong Xingxing
Published: August 2021

When the temperature control system of intelligent control cabinet of modular substation is designed by the current method, the PID controller is not improved, and there are problems such as low temperature prediction accuracy, low temperature tracking accuracy and poor control effect. The design method of temperature control system of intelligent control cabinet of modular substation is proposed. Through FPGA, input circuit, output circuit, man-machine interface, frequency division module five parts constitute the modular substation intelligent control cabinet temperature control system framework, in the temperature control system combined with the predictive function control algorithm to achieve the modular substation intelligent control cabinet temperature control system software system design. The experimental results show that the designed system can control the terminal temperature stably and reduce the temperature fluctuation to a small extent.
Intelligent Fatigue Detection Method in Industrial System Based on Facial Multi-feature Fusion
Authors: Du Xinfei , Xie Juntai , Chen Kun , Gao Jianmin , Liu Yang
Published: August 2021

With the development of science and technology, the complexity of industrial production system has been significantly improved, and higher requirements have been put forward for human safety. Aiming at the contradiction between the intrusiveness and the accuracy of fatigue behavior detection in human factor safety, a multi-feature fusion intelligent fatigue state detection method was proposed. Firstly, the image recognition algorithm was used to accurately obtain the information of facial expression feature points. By analyzing the dynamic characteristics of all the feature points, the facial fatigue features were extracted. Secondly, an experimental scheme was designed to collect and process facial expression feature data, and a dynamic marker model of fatigue characteristics was constructed to form a fatigue index that directly reflected the fatigue degree of the working process. Finally, the neural network regression model was established to fit the characteristic data. Through the comparative analysis of different schemes and various evaluation indexes, the rationality of the fitting results of this method was proved. The experimental results show that this method can reasonably quantify the fatigue index of people under different conditions, and realize the intelligent detection of facial fatigue state.
Temperature Modeling of Reflow Soldering Based on the Heat Transfer Mechanisms
Authors: Tang Zihao , Huang Binshan
Published: August 2021

In the production of integrated circuit boards, electronic components need to be automatically welded to the circuit board by a reflow oven. Reflow oven welding is the core process of producing circuit boards, and the centre temperature of the welding area is extremely important to the quality of the final product of electronic components. Based on the experimental data, we establish a non-steady heat conduction model based on Newton's cooling law, and use the method of least squares to determine the dynamic parameters, and finally use the finite difference method (FDM) to solve the models.

Secondly, the reflow oven speed will also have an impact on the product quality. At the same time, a single-objective linear programming model with the maximum furnace speed is established, then the step size is to perform a fine search to solve the problem.
Dynamic characteristics analysis of XLPE cable charge under different aging degree
Authors: Zhao Tengfei , Nie Yongjie , Cao Min , Li Pengwu , Bai Jianwei
Published: August 2021

To study the dynamic charge characteristics of XLPE cables. In this paper, a Qt test system is built in the laboratory to test the Qt dynamic charge characteristics of different thermal aging samples, and the current characteristics of different aging degrees are obtained according to the charge test differentiation. The experimental results show that the charge value of unaged sample is about 1100 nC, and the charge value of aged sample is about 2000 nC. At the moment of pressurization, the XLPE cable sheet sample flows through a large instantaneous charging current, and the initial current is more than 10−9 orders of magnitude. For the unaged sample, the charge accumulation value and conduction current value of H1 and H2 are better than those of F sample. The analysis shows that due to the insufficient aging degree of the sample, the initial aging stage is in the recrystallizaon stage.
Regulation Performance of Virtual Synchronous Generator Applied in Renewable Energy System
Authors: Qi WeiZhi , Zha Daojun , Wu Tonghua , Dai Wei , Li Xindong , Hou Xiaofan
Published: August 2021

The conventional synchronous generator (SG) can regulate the active and reactive power for frequency and voltage stability, when the system fluctuates. In renewable energy generation system (RES), the stability problem of RES can be solved by adding virtual inertia and damping in the control strategy of the grid-connected inverter. The grid-connected inverter and renewable energy system with this kind of control strategy, called as virtual synchronous generator (VSG), acts as a synchronous generator. In this paper, the topology of grid-connected PV array and energy storage system is proposed. The VSG used in grid-connected inverter, is modelled as stator and rotor model by stator voltage equation and rotor motion equation, respectively. Meanwhile, the VSG control mechanism, based on droop control and model of VSG, can be divided as active power-frequency and reactive power-voltage control. Besides, the system stability is analyzed based on small signal model, for the design of inertia and damping. The simulation model is designed by MATLAB/Simulink for the implementation of VSG. In simulation, it is compared that the dynamic regulation performance of VSG with different control coefficient, such as virtual inertia, virtual damping, droop coefficient and integral coefficient. The optimization for regulation performance in simulation provides an appropriate selection method of the control coefficient for VSG.
Analysis of the mechanism of thermal collapse of MOA valve plates caused by multiple lightning strikes
Authors: Yang Jinming , Ma Yi , Ma Yutang , Pan Hao , Du Han
Published: August 2021

Multiple lightning strikes are a common phenomenon in nature, and their impact on the power system cannot be ignored. MOA is an important device for lightning protection in power systems, but under certain conditions multiple lightning strikes can cause thermal collapse of MOA. In order to study the mechanism of the thermal collapse of MOA valve plates caused by multiple lightning strikes, a microscopic model of zinc oxide crystals was established, the heat transfer performance of zinc oxide crystals was simulated, and the temperature field when the size of zinc oxide crystals and the area of the grain boundary layer was different were compared. In this paper, the mechanism for the thermal collapse of the MOA valve due to thermal stress was analyzed, and the reason why multiple lightning strikes are more likely to cause MOA energy overload than a single lightning strike was explained. This research provides reference for the selection and maintenance of MOA.
Partial discharge detection method for lower porcelain shell of oil paper insulation bushing based on spatial UHF signals
Authors: Li Jiansheng , Wang Shengquan
Published: August 2021

The partial discharge in lower porcelain shell of oil paper insulation bushing is one of the important reasons for transformer failures. Based on the analysis of the oil paper insulation bushing structure characteristics, the finite difference time domain simulation model of the partial discharge in lower porcelain shell is established. And the path of UHF signal of partial discharge is obtained that the signal spreads through the insulation between capacitor screens and oil passage to the outer space. Then the lower porcelain shell partial discharge detection method based on the space UHF signal is proposed and verified.
Process Level Fault Probability Distribution Model of Intelligent Substation Based on Tree Structure
Authors: Shen Diqiu , Zhang Kefeng , Wang Liang , Lu Wenxing , Zhu Qiaojie
Published: August 2021

In order to estimate the probability distribution of process level fault in Smart Substation, a tree based probability distribution model of process level fault in Smart Substation is proposed. Taking 14 years' process level fault data of Smart Substation in a regional power grid as sample data, this paper compares and analyzes various probability models. The probability distribution of process level fault scale of Smart Substation in this area is calculated by using the Boley Tanner branching process model in tree structure. The experimental results show that the model can estimate the probability distribution of process level fault size of Smart Substation well. Under the same confidence requirement, the sample data needed by the method based on the Boley Tanner model to estimate the fault probability distribution is one order of magnitude less than that directly based on the actual fault data.
weighting power quality evaluation based on cloud model and anti-entropy
Authors: Wei Feishen , Xu Qifeng , Xie Nan , Gong Ze
Published: August 2021

There are subjectivity and uncertainty in the general comprehensive evaluation of power quality. And there are problems of randomness and ambiguity in the boundary of power quality classification. Firstly, the subjective weight is obtained based on the cloud model theory. Secondly, the objective weight is obtained based on the improved anti-entropy method. Thirdly, the subjective and objective combined weight is obtained through the moment estimation theory. And then the final score of each observation point is obtained and sorted by the improved TOPSIS. Finally, the effectiveness and feasibility of the method are verified by an example, which provides a new idea for the effective combination assessment of power quality.
Distribution network with distributed power protection setting policy666
Authors: Xin XU , Shirong WANG , Jianan ZHANG
Published: August 2021

When Distributed Generation (DG) is connected to the distribution network, the original network structure will change, leading to various distribution grid protection deviation, the instability of the network appears. In order to guarantee the reliability and economy of power distribution grid, distributed power and full of potential, so access to protection for distributed power grid feature is the need for research. In-depth discussion on the relay protection setting strategy when distributed power sources are connected to the distribution network, and launch a new current protection scheme. Simulated using simulation software PSCAD / EMTDC.To verify its reliability, quick-movement, selectivity and sensitivity, it has strong application significance in practical engineering.
Development of Auxiliary Tools for the Insulation Rod Method in Live Work of 10 kV Distribution Network
Authors: Li Jin-liang , Yang Miao , Li Hong-qing , Liu Ding-guo , Long Chen-hai , Yang Jie , Ren Hui-song , Xiong Zi-xuan , Luo Wen-hui
Published: August 2021

The live work of distribution network can effectively improve the reliability of residential power supply. Live breaking or connecting the drainage line is the most extensive project in the live work of distribution network. Due to the lack of the special fixing tool of the drainage line and the placement tool of insulation rods, the result is that the labor intensity of operators is large and the installation process quality of wire clip is difficult to guarantee in the process of live breaking and connecting the drainage line. Focusing on above problems, the special fixing tool of the drainage line and the portable insulation rod hanger are developed. The specific application method is introduced in this paper. The field application is carried out after the electrical test is qualified. The field application shows that applying the auxiliary tools can effectively reduce the labor intensity and improve the working efficiency.
Comparative study of 0.1Hz very-low frequency withstand voltage test method and traditional method
Authors: Sun Dong , Gao Jinyu , Piao Yongxin , Guo Bo , Qu Chengjia , Gao Zichen , Wang Hongxing
Published: August 2021

The o.1Hz very-low frequency withstand voltage test method has the advantages of small equipment size and low power demand, and is used more and more in the power grid, especially in withstand voltage test. However, the effect of this voltage waveform and the traditional test waveform on the insulation assessment is still unclear. This paper compares the difference between 0.1Hz very-low frequency and DC voltage, resonance voltage and oscillating wave voltage in the withstand voltage test. Research indicates that the 0.1Hz very-low frequency withstand voltage test has good equivalence in cables with mechanical "faults", water tree defects in cables and power frequency, and relatively poor equivalence in terms of needle plate electrode insulation defects.
The research on current rush to air mass in delivery pipeline system with YOUNGS-VOF method
Authors: Jie Fang , chun-jian Cao , mingquan Ding
Published: August 2021

Water hammer with gas often occurs in long delivery pipeline system lager than ordinary water hammer, surface tracking between air and water is important and difficult. In this paper, flow rush to interception air-mass in long water conveyance pipe system is researched on base on surface in between water and gas tracking method of staggered grid dispersed with YOUNGS-VOF, the limited compressibility method of viscous incompressible fluid control equations, and numerical method of ideal gas state equation. The numerical results show that YOUNGS-VOF method can be used to deal with the interface and water hammer is consistent with the theory analysis.
Adaboost-Based Power System Load Forecasting
Authors: Ling WuNeng , Zhang Pan , Li QiuWen , Mo Dong , Luo CuiYun , Li YiMing , Liang ZhenCheng
Published: August 2021

This study presented a penetrating insight into the basic principle of ensemble learning and the ensemble technique Boosting, and deduced the theoretical model and learning principle of the adaptive ensemble learning. Besides, it proposed a Adaboost-based power system load forecasting method, and validated the effectiveness of this method through the empirical forecasting of a provincial medium and long-term load. The calculation example in this paper proves that high-accuracy of medium and long-term load forecasting can be achieved by using Adaboost-based power system load forecasting method.
Numerical simulation of electrical network left ventricular circulatory system with biological valve motion model
Authors: Wu Xiangyu , Zhang Yunpeng , Wang Houfu
Published: August 2021

This paper presents a new concentrated parameter model represented by an electrical network model for cardiovascular dynamics that includes an innovative model of biological heart valve dynamics. We obtained the hemodynamic waveform of the heart by solving the equations of state through programming. The results show that using the biological valve motion model can reflect the phenomenon of blood return flow that is not found in the ideal diode model. This model can simulate the biological characteristics of heart valve reasonably and accurately, and it is simple and easy to control.
Comparative analysis of sealing effect of different hole sealing processes in coal mine
Authors: Xiong Wei
Published: August 2021

In order to improve the concentration of gas extraction from boreholes in Liyazhuang Coal Mine, three different sealing technologies, namely bagged polyurethane sealing, self-expanding sealing device sealing and new expansion cement sealing, were tested in the field. It was found that the new expansion cement sealing was the best for boreholes. Further investigation into the meso-characteristics of the combination of the new type of expansive cement and coal wall shows that the new type of expansive cement for mining has a compact overall structure, strong articulated ability to the coal body, and can effectively seal the hole and fissure of the coal body with superior sealing performance.
Research status and developing trends of gas bearing in recent years
Authors: Zhou Quan , Zhang Yi
Published: August 2021

As one kind of support elements for rotational machines, gas bearings that use air or gas as lubricant, have many attractive advantages such as low power loss, wide work temperature range, high rotating speed and low maintenance cost. However, gas bearings also have some disadvantages including low carrying load at low speed, wear at start-stop procedure, not easy to predict bearing performance due to the complex bearing structure and so on.

The purpose of this paper is to explore the research status of gas bearing based on the Web of Science datasets and related tools, meanwhile, the developing trends emerged in gas bearing are further studied. The results shows that: 1) the top ten productive countries published 85% papers in the studies of gas bearing; 2) there are eight research clusters emerged in the topics analysis visualization and the top three largest clusters are #1 metal mesh foil bearing, #1 bump-type foil bearing and #2 aerostatic thrust bearing respectively; 3) Comparing to other research topics, foil bearings (metal mesh type and bump type)and aerostatic thrust bearing may be further explored in the future. This study presents intuitive state of research of gas bearings and proposes a fresh perspective for relevant researchers to perform research in the future.
Study and Optimization of Full Flow Test Method for Core Safety Injection System
Authors: Lin Jiabing , Wan Jie , Li Junyong , Gao Xiang , Bai Jinchuan
Published: August 2021

Due to the high pressure safety injection full-flow test of the nuclear power plant core safety injection system (RIS), there are problems such as the limit of the pump starting condition, the “blind adjustment” of the valve flow, the test logic defect, and the number of unqualified tests, etc. This research has improved the test principle and operation steps of the RIS high pressure safety injection full-flow periodic test, and describes in detail the comparison between the new scheme and the existing RIS high pressure safety injection full-flow test scheme, and the actual verification effect. The research results show that the optimized RIS high pressure safety injection full-flow test has the advantages of simple logic, easy operation, high qualification rate, and short test period, and it is worthy of popularization and application in this reactor type.
Fault analysis and optimization technology of HP bowl type medium speed coal mill
Authors: Jie Dou
Published: August 2021

HP type medium speed coal pulverizer produced by Shanghai heavy machinery works has been widely used in recent years, with common faults in operation, short maintenance cycle and heavy task. In order to facilitate the staff to complete the maintenance task more quickly and with higher quality, this paper introduces the common faults in HP type bowl type medium speed coal pulverizer in detail from the reality, and analyzes the causes, At the same time, part of the performance optimization scheme of this type of coal mill is introduced.
POTDR based Power Communication Optical Cable Anti External Force Damage Monitoring System
Authors: Huang Zhicai , Yuan Yongshi
Published: August 2021

The traditional system has low recognition accuracy for the vibration signal of optical cable damaged by external force. Therefore, a power communication optical cable anti external force monitoring system based on potdr is designed. In terms of hardware, the modular structure of the system is constructed, the potdr distributed optical fiber sensor and power supply circuit are designed, and the vibration signal of the optical cable is collected. In the aspect of software, optical fiber communication transmits vibration signal, denoises and filters the signal, extracts the state characteristics of optical cable, and monitors whether external force damage occurs. The experimental results show that, compared with the conventional system, the designed system improves the identification accuracy of the vibration signal of the optical cable damaged by external force, and ensures the operation and maintenance management level of the optical cabl.
Automatic Generation System of Distribution Network Switch Test Scheme based on Topology Analysis
Authors: Lei Jiaxing , Guo Yaosong , Xu Zhongyuan , Luo Dashi , Wang Rui
Published: August 2021

With the continuous improvement of the automation level of the distribution network, more and more switches can be controlled remotely. The reliability of switch remote control directly affects the stability of the entire distribution network system, so it is very important to test the switch regularly to ensure that it can be operated remotely in an emergency. At present, the switch test scheme is mainly artificially generated, which is very inefficient, and the review process is simple, which is easy to cause safety problems. This paper proposes an automatic generation system for switch test scheme based on topology analysis, which greatly improves the efficiency of scheme generation, and adds multiple roles for review, which improves the accuracy of the scheme. This system has been applied in practice and achieved good results.
A Non-intrusive loading monitoring method based on Attention mechanism and denoising-Autoencoder
Authors: Duan Qiuyu , Zhang Fei , Ren Xiaoying , Gao Lu
Published: August 2021

This paper built denoising-Autoencoder (dAE), Attention-dAE and transformerbased regression models based on Non-Intrusive Load Monitoring (NILM) and Deep Learning (DL) methods, and uses them in UK-DALE[1] proving on the dataset, the verification results show that the recognition accuracy of adding Attention mechanism and dAE is significantly improved, and the model parameters are greatly reduced.
Research on Grounding Fault of 12-phase Rectifier Generator in Parallel Operation
Authors: Lin Cong , Ye Zhihao , Xiao Han , Wu Benxiang
Published: August 2021

12-phase rectifier generators have been widely used in ship power systems, since they can provide high quality DC voltage. In view of the safety and reliability requirements of power supply during ship navigation, the DC side grounding faults of two paralleled 12-phase rectifier generators are studied through theoretical analysis and simulation analysis. First of all, the DC voltage expression of the 12-phase rectifier generator under normal condition is derived. Secondly, the zero sequence circuits of the DC side grounding fault are studied, the DC voltage is calculated by the phasor method, the DC output current of generator is analyzed by the zero sequence circuits. Finally, the correctness of the analysis method is verified by the simulation model.
Fast detection method of transmission line defects and faults based on airborne laser LiDAR
Authors: Lei Shi , Heng Yang , Lianggang Xu , Yuan Yang , Di Wang , Xianzhe Long , Jian Zhao
Published: August 2021

In view of the fact that it is difficult for transmission line operators to find transmission line defects and accurate location information in time, and in the face of the discovered transmission line defects, they are unable to quickly and accurately return detailed defect information to provide urgent repair to provide rectification solutions, etc., this paper proposes a fast transmission line defect fault detection method based on airborne laser LiDAR, and compares and analyzes it by using laser point cloud data in different periods. It is found that there are some defects such as the interruption of the transmission line channel and the sinking of the tower foundation. Using laser point cloud data, the tilt detection and deformation of poles and towers are found, and large-scale topographic maps are quickly generated to quickly restore the three-dimensional channel environment of transmission lines, so as to provide auxiliary decision-making for transmission line defects and fault rectification schemes. The digital and scientific management of transmission line defects and equipment fault detection are realized through laser point cloud.
Emission Characteristics of Hybrid Electric Bus During Peak Period Based On Remote Monitoring
Authors: Jin-chao Chen , Xiao-wen Zhang , Su Li , Song-bo Qi , Xiao-qing You
Published: August 2021

Based on the OBD remote monitoring system, the real-time data of Tianjin 607 bus is collected, and two representative groups of data are selected for analysis. The results show that the vehicles start and stop frequently during peak period, the frequency of electric motor use increases from 27.72% in off-peak period to 53.72% in peak period, the average driving speed is faster than usual, and the drivers tend to drive more intensely for catching up time. Under the same working conditions, the frequency of electric motor use is positively correlated with the emission reduction benefits brought by the use of hybrid electric vehicles. Under different road conditions, especially in the peak operation, the exhaust temperature is low, which has a greater impact on the actual emission reduction benefits of the electric motor. The key to fundamentally alleviate the emission problem of bus in peak period is to improve the vehicle operation conditions and the conversion rate of SCR system.
Precipitation Simulation from the Cumulus Convection Parameterization Schemes Based on the WRF Model in the Weihe River Basin, china
Authors: Liu Yinge , Cheng Aifang , Hu Haonan
Published: August 2021

Two cumulus convection parameterization schemes, i.e., Kain-Fritsch (K-F) and Grell-3 based on the V4.1.2 Weather Research and Forecasting (WRF) model, were used to simulate the summer precipitation in the Weihe River Basin using hourly precipitation data at the resolution of 5 km and 2 km. the precipitation experiment results at different resolution were compared and analyzed. The root square error and correlation coefficient were used to verify and evaluate the simulation results. The results show that in K-F and Grell-3, the two cumulus model simulations with a resolution of 5 km can explain the spatial distribution pattern of precipitation and the diurnal variation process, and the experimental simulation results are consistent with the actual observations. The summer precipitation simulation in June, July, and August is highly sensitive to the two cumulus parameter schemes of K-F and Grell-3. The simulated precipitation value is higher than the actual value, and the root mean square errors (RMSEs) of K-F and Grell-3 schemes are 5.49-13.29 and 5.69-10.88, respectively. In terms of precipitation simulation, Grell-3 scheme is better than K-F scheme, especially in areas with heavy rainfall. When the resolution is increased to 2 km, the regions with heavy precipitation can be displayed more finely. The influence of water vapor flux and vertical velocity changes on precipitation in the Weihe River is analyzed from two aspects, i.e., water conditions and atmospheric instability. From the simulation results by the K-F scheme, the vertical velocity fluctuations are unstable and strong in the convective area, and the convective rainfall is relatively high. From the simulation results by Grell-3, the vertical velocity is large and increased rapidly, which is conducive to the generation of large-scale heavy precipitation. Both schemes are very sensitive to the simulation of water vapor transport and vertical velocity. This study provides a basis for the research on the adaptability of regional precipitation simulation.
Extraction and Analysis of Temperature data from COSMIC of Pacific Occultation
Authors: Shi Zhuoya , Zheng Wei
Published: August 2021

With the increase of human demand for natural climate research, climate monitoring technology has been greatly developed, and the occultation technology proposed in the field of surveying and mapping provides a more accurate and effective data source for meteorology research. With the destruction of the earth’s ecosphere by pollution, the global climate change has a great impact on human life, so the research on meteorology has been paid more and more attention. The data obtained from GPS radio occultation observations have also become one of the key data sources to record the temperature changes of the atmosphere in tropical regions. The extraction and analysis of temperature data in the western Pacific are very essential. At the same time, it plays an crucial role in China’s climate prediction and disaster warning. It is hoped that by reading the occultation data of the western Pacific in 12 months in 2014, and drawing the isoline map of the lunar season and seasonal temperature values, the change law of global and western Pacific temperature with longitude, latitude and altitude can be analysed.
Binary classification of single qubits using quantum machine learning method
Authors: Yi Teng , Wang Jie , Xu Fufang
Published: August 2021

Machine learning can make predictions on unseen data by extracting information and constructing algorithms and statistical models from the training data, which is highly desirable for speech recognition and computer vision. Quantum computing harnesses the phenomena of quantum mechanics realizing parallel computing, which could solve certain computational problems, such as RSA encryption significantly faster than classical computers. Quantum machine learning is reasonable to enable machine learning faster than that of classical computers by utilizing quantum operations. Binary classification is a typical quantum machine learning task applied to single qubits. Here we present a binary classifier for regions. Firstly, we sample two sets of quantum data points located in the X-Z plane of the Bloch sphere randomly. Then we utilize a single parameterized rotation gate and measure the qubits along the Z axis. We train the hybrid model combined by quantum mdoel and classical Neutral network and regard the corss entropy the predictions of the classical Netural network and labels as the loss function. Based on the above, we present the results of the trained hybrid model to classify new quantum qubits.