bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of photon orbit around magnetic black holes coupled to nonlinear electrodynamics
Authors: Habibina A S. , Ramadhan H. S.
Published: June 2022

In this work we study the orbit of light particles around a asymptotically at, magnetically charged black hole which is coupled to a model of nonlinear form of Maxwell electrodynamics. The matter source is characterized by two parameters, β and γ, which determine the behaviour of photon around the corresponding spacetime. We serve the effective potential and analyse its change by varying the charge and the model parameter. Finally, we solve its orbit equation and show how photon moves according to the black hole potential.
Numerical Investigation of Freeze Valve Melting Behavior in Molten Salt Reactor using OpenFOAM
Authors: Riupassa Robi Dany , Basar Khairul , Novitrian  , Waris Abdul
Published: June 2022

Molten Salt Reactor (MSR) used a freeze valve to handle accident conditions when the reactor overheated and the active safety control systems failed. The freeze valve will melt if the reactor core temperature increases and exceeds the freeze valve’s melting temperature. In this research, a numerical investigation of freeze valve melting behavior was conducted. Freeze valve geometry used geometry proposed by Oak Ridge National Laboratory (ORNL) in Molten Salt Reactor Experiment (MSRE) and also used in test loop facility in Shanghai Institute of Applied Physics (SINAP) to develop Thorium Molten Salt Reactor (TMSR). The material used FLiNaK salt (LiF-NaF-KF, 46.5-11.5-42.0 mol %). Numerical calculation performs using OpenFOAM. BuoyantPimpleFoam was used to analyze the heat transfer mechanism. Isothermal phase-change simulated by adding solidificationMeltingSource terms into fvOptions as a flexible framework in OpenFOAM.
Improvement of Tobacco Collection Line and Storage Logistics System
Authors: Sheng Xiaohe , Wang Rui , Zhu Yi , He Xiaoqiang , Guo Ge
Published: June 2022

To innovate the traditional cigarette collection mode of manual unloading, open stacking and lower informatization, adopt the new cigarette packaging frame system and storage logistics system of the flue-cured tobacco. Take advantage of lifting platform, slope conveyor, roller conveyor, belt conveyor, automatic sampling device, shaping and framing device, palletizer, electric forklift, tobacco frame, assemble them to finish ten production line. After actual production, ten production lines running can complete the unloading and framing task of five cigarette trucks at the same time, another five trucks make preparation for the next mission. 3200 loads can be unloaded in an average of one hour. According to the design capacity, the unloading efficiency of one line is increased by about 20% year-on-year, rate of tobacco crushing is decreased by about 0.165%. The new tobacco collection and storage logistics system model can reduce tobacco crushing effectively, improve the efficiency of tobacco industry commerce handover and information data’s utilize.
Research and Implementation of the Transmission Efficiency of LEO Remote Sensing Satellite Based on Variable Coding Modulation
Authors: Jie He , Lei Shi , Wei Qiao , Jingyang Zhang , Xiaodong Wu , Zhenli Yin , Zhen Qin
Published: June 2022

Orbit characteristics of LEO remote sensing satellite determine that its downlink capability is limited by transit visual time, the limited number of transit times a day greatly limits the efficiency of satellite transmission. Because the satellite-ground transmission distance will change with the elevation angle of the ground station and the change of the satellite azimuth and elevation angle when the satellite transits, the traditional satellite can't make full use of the link margin in order to ensure the transmission of the longest distance, too much link allowance at high elevation when using fixed modulation mode. Therefore, based on variable coding modulation, the real-time transmission distance is obtained by using servo controller and intelligent calculation method on satellite, through simulation analysis and threshold analysis setting, this paper proposes a more optimized data transmission system design, which can save a lot of satellite-ground link margin and improve the satellite-ground transmission efficiency by about 30%.
Neural Network Application in Dispersion Curve Inversion of Seabed Geoacoustic Parameters
Authors: Zhang Peng , Pan Xiang
Published: June 2022

This paper estimates seabed shear-wave velocities and the thickness of the surface sediments using Scholte wave dispersion curves extracted from data. Common surface wave dispersion curve inversion methods are divided into: local linearization methods and global optimization methods. These are model-driven, the inversion process takes a lot of time, and it is easy to get a local optimum, and the inversion results are inaccurate. Aiming at the shortcomings of the existing surface wave dispersion inversion methods, this paper introduces an inversion method based on neural network, and fits the Scholte wave dispersion curve to obtain the geoacoustic parameters of the surface sediments. Neural network inversion is data-driven, and the model is extracted from the data, which can improve the speed and accuracy of surface wave inversion. By simulating the shallow sea model, better results are obtained, and at the same time, the experimental data is used for calculation, the inversion results are close to the traditional methods, and the inversion speed is improved.
Target Recognition of Millimeter-wave Radar based on YOLOX
Authors: Sun Qiang , Chen Xin , Liang Futai , Tang Xiao , He Song , Lu Hao
Published: June 2022

The application of magnetic field detector in the actual road section mainly depends on the layout of these detectors in the actual traffic environment. For example, geomagnetism and coils are easily disturbed by vehicles near the road, resulting in missed or false detection; Video detection equipment depends on weather, visibility and other environmental conditions, and there will be a large degree of missed detection. Compared with the disadvantages of the above sensors, Millimeter-wave Radar has many unique advantages, including insensitivity to light or weather, wider application range compared with vision based technology, and higher accuracy,which makes millimeter-wave radar more outstanding in traffic monitoring applications. This paper presents a detection model of millimeter wave radar spectrum based on YOLOX, which is used to monitor traffic. Firstly, this paper enhances the millimeter-wave radar spectrum data used for training by gray-scale transformation, solves the problem that the Doppler target echo is not obvious, and obtains a clearer target image. Secondly, the latest YOLOX algorithm is used to train 2844 radar spectrum diagrams, and the performance evaluation is carried out to obtain the YOLOX average mAP@0.5 The value is 0.916 and FPS is 35.8. Finally, experiments show that YOLOX algorithm is better than YOLOv5 algorithm mAP@0.5 It is 2.9% higher, which proves the superiority of the algorithm.
Improved Pre-Processing Process of Climate Series Based on Chebyshev Filter
Authors: Zhang Zhenyu , Pan Ziyu
Published: June 2022

In the process of data mining for time series of environmental factors of dendrobium origin, it is difficult to separate the available features because the feature components are too rich and the de-noising method is not feasible, in this paper, we try to improve the pre-processing process of sequence. In this method, we first de centralize the sequence and check the unit root to evaluate the stationarity of the sequence, and then design a band-pass filter to extract the feature components from the sequence in the range of monthly frequency to annual frequency, then, the features of EEMD and correlation coefficients are extracted by using the EEMD Algorithm, which is commonly used in the field of natural sequence decomposition. Finally, the Savitzky-Golay filter is designed to smooth the reconstructed sequence in order to remove the noise introduced by EEMD, the final usable characteristic component is obtained. Compared with EEMD Algorithm, this method is more reasonable in the pre-processing process, and the power distribution in frequency is more concentrated.
Mechanism Study of Bi-Material COPV Structure Based on Composite Structure Design Theory
Authors: ZHAO Ji-peng , YU Bin , OUYANG Rui-jie , MA Tian-ju , GU Sen-dong , YANG Wen-bo , HOU Yan-hui
Published: June 2022

Composite over-wrapped pressure vessels (COPVs) are widely used in aerospace, aviation, army, Navy, nuclear industry and other military and civil fields because of their light weight, high strength, high reliability and safety, leak before burst (LBB) failure mode safety and many other characteristics. Because the aerospace field has very strict requirements on the weight of platform structure products including COPV, it is necessary to improve the mass efficient of COPV and achieve the characteristics of light weight and high strength. In this paper, through the optimization of composite material grid theory algorithm, the relationship between bidirectional stress and internal pressure of cylinder and dome of isotropic material is deduced. On this basis, the grid theory equations of bidirectional stress and internal pressure load of COPV cylinder and dome are deduced, and the wall thickness equations of ordinary rotating curve head, equal tension head and hemispherical head are proposed. According to the grid theory model of membrane stress of COPV cylinder, the author completed the grid theory algorithm derivation of elastic and plastic lined COPV. This paper is the exploration of composite dome structure analysis, which lays a foundation for the subsequent solution of composite dome grid theory.
Moving Object Detection based on Reverse Projection Error Model
Authors: Cao Yang , Yu Hongfei , Yu Meng
Published: June 2022

A novel moving feature point detection method is proposed in this paper in order to solve the problems in existing methods. Firstly, the coordinates of feature points are normalized by using spherical coordinates in order to solve the imaging distortion of the fish-eye camera. Secondly, based on the spherical normalization coordinates of feature points the reverse projection error model of the fish-eye camera is deduced and a moving feature point’s discriminant is derived to improve the detection integrity of moving object. Finally, according to the law of object motion, the detected potential moving feature points are clustered to further remove outliers. Experimental results show the proposed moving feature point detection method has better detection results compared with the commonly used methods.
MORNSUN series DC-DC power module test fixture design
Authors: Wu Han
Published: June 2022

Test fixture is connected with the ATS automatic test system and the power module under test device, is an important component to achieve the power module test, its suitability, precision, opearbility also directly affect the accuracy of the test and the convenience of disassembly. Based on MORNSUN series DC-DC module, this paper aims to design a pin type test fixture with wide applicability, simple structure and convenient operation, and solve the problem of lack of test fixture in the actual test.
Power system fault restoration based on A2C with the consideration of renewables
Authors: Zhang Huanming , Xu Xiaosheng , Li Mengshi , Chen Ziming , Wu Qinghua
Published: June 2022

Although the power system has made great progress in security and stability, it is still difficult to completely avoid the occurrence of large-scale blackouts caused by various accidental factors under the background of high proportion of renewables. In order to improve the rapidity and reliability of power system fault restoration, this paper proposes a power system fault restoration strategy based on the Advantage Actor Critic. Under the premise of ensuring the priority restoration of loads with high demand on the user side, the overall objective function is to take the least total power loss load, the smallest network loss, the smallest restoration cost and the least number of switching operations into consideration. Test results on a modified IEEE39 system have verified the superiority of the model and recovery strategy.
An Active Power Decoupling Topology for Three-phase Four-leg Inverters with Unbalanced Load
Authors: Xie Yuanchao , Wang Fusheng , Liu Heng
Published: June 2022

Traditional three-phase four-leg inverters are widely used in microgrid systems because of their ability to carry unbalanced loads, but unbalanced load currents will cause instantaneous power to contain double-frequency fluctuations, which will affect the normal operation of the microgrid system. In order to solve the above problems, this paper proposes an improved three-phase four-leg topology and its control strategy, so that the secondary pulsating power on the load side can be provided by the decoupling capacitor. Then the working principle of the proposed topology and its control strategy is analyzed, and the relationship between the current stress of the power device and various influencing factors is deduced. Finally, An experimental prototype was built to verify the effectiveness of the proposed solution.
Research on key technologies of multi-source parallel in microgrid
Authors: Zhao You-cheng , Zhu Chang-qing
Published: June 2022

Microgrid system with micro sources with different rated capacity is a research hotspot in the world. This paper aims to discuss the research status of the key technologies of parallel connection between micro sources in microgrid, and briefly introduces the key technologies of parallel connection of micro source inverter with different rated capacity, parallel connection of diesel generator and parallel connection of micro source inverter and diesel generator, which provides a direction for relevant scholars to study the multi-source parallel connection technology in microgrid.
Influence of DC transmission distance on MMC-HVDC stability under weak AC system
Authors: Zhao Caiping , Wang Qiyuan
Published: June 2022

The oscillation problem of MMC-HVDC under weak AC system poses a potential threat to the safe and stable operation of power grid, which is related to both of the AC and DC parameters. By comparing the stability of MMC-HVDC under different AC system strength with different DC transmission distance, it is found that when the AC system strength is too weak, there is a risk of instability under the condition of long DC transmission distance, and the correctness of this conclusion is verified by time-domain simulation. Later, the mechanism analysis of this phenomenon is carried out, the result shows that it is related to the interaction of MMC subsystems when the strength of AC system decreases.
An Active Power Factor Correction Technology for Aircraft
Authors: Pan Liyun , Liu Gang , Sun Qiangang
Published: June 2022

This paper analyzes the influence of harmonics on the system and the importance of power factor correction. According to the requirements of aircraft use, an active power factor correction system based on three phase six switch topology is designed. The article analyzes the working process and control method of the system, then designs a rectifier to convert 220V/400Hz AC power provided by the aircraft to DC power and the power factor of the rectifier is high. Moreover, the performance of the system is tested.
Research on ZigBee Device Recognition Based on Software Defined Radio
Authors: Cheng Kefei , Deng Yujie , Zhang Liang , Cui Xiaotong , Chen Jinghao , Luo Wei
Published: June 2022

In order to solve the problem that ZigBee protocol sniffer analysis is based on proprietary chip platform and cannot obtain radio signal characteristics. A ZigBee protocol packet sniffing recognition method based on software defined radio is proposed. This paper proposes a ZigBee recognition method based on software radio, and analyzes the characteristics of ZigBee protocol messages. The software radio receiving flow diagram is designed to extract the captured message features, and the experimental results of neural network, KNN, decision tree and random forest algorithm are compared. Finally, the decision tree + hybrid classifier achieves 93.1% recognition accuracy, which verifies that the ZigBee recognition method based on software radio proposed in this paper has a good effect.
OLAP analysis of user energy consumption based on multitemporal distribution characteristics
Authors: Liu Bin , Yang Zhengyu , Wu Jiaqing , Gu Jie
Published: June 2022

With the development of databases, online transaction processing (OLTP) can no longer meet the needs of end users for database query and analysis, and the simple query of large databases by SQL can not meet the requirements of end user analysis. Therefore, online analytical processing (OLAP) is proposed. concept. On the one hand, we explained the basic knowledge of OLAP, including OLAP multidimensional data concept, multidimensional data structure, multidimensional data analysis, characteristics, etc. On the other hand, we established an OLAP analysis model of the multi-temporal and spatial distribution characteristics of user energy consumption, which is refined provide support for the analysis of user energy consumption behavior.
Two-dimensional DOA estimation of coherent signals for MIMO Radar Based on tensor decomposition
Authors: Ren Mingjian , Hu Guoping , Zhou Hao , Lin Bin
Published: June 2022

This paper studies the two-dimensional DOA estimation of coherent targets. Subspace algorithm is usually used to solve this problem. Compared with subspace algorithm, tensor decomposition has significant advantages in estimation accuracy and has been widely used in the field of signal processing. However, the research on tensor decomposition algorithm mainly focuses on incoherent targets. Therefore, we study how to use the advantages of tensor decomposition to improve the estimation accuracy of coherent targets. Firstly, we construct the echo signal model corresponding to the “Sum array” of MIMO radar, and then use the spatial smoothing to process the data to solve the problem of covariance rank deficiency. Then a third-order tensor is constructed according to the position relationship of the data. Finally, the DOA can be estimated from the decomposed tensor according to the position relationship of the data. Simulation results show that proposed algorithm has significant advantages in estimation accuracy.
Microgrid Inverter Control Strategy Based on Virtual Synchronous Generator
Authors: Zhang Yuewei , Han Minxiao
Published: June 2022

Study the control strategy of distributed power supply grid-connected based on virtual synchronous generator. Establish the mathematical model of the inverter grid connection and the mathematical model of the virtual synchronous generator control scheme. Study the grid-connected active and reactive power regulation scheme, and analyze the influence of inertia and damping parameters on grid-connected power tracking in detail. A self-synchronous control strategy without phase-locked loop is designed, which simulates the characteristics of synchronous generator’s speed regulation system and excitation system and can seamlessly switch between two operating states of off-grid and on-grid, which is conducive to the improvement of micro-grid stability. Finally, a simple microgrid system is built on the Matlab/Simulink platform. It is verified that the proposed control strategy has good power tracking characteristics and can enable the distributed power supply to switch quickly in different operating modes.
Effects of Tuning Mode on Radiation Performance of VLF Umbrella Transmitting Antenna
Authors: Quan Ying , Xie Hui , Li Haokun , Zhang Xiaoyang
Published: June 2022

In this paper, the tuning principle and two tuning modes of the VLF umbrella transmitting antenna are introduced. The calculation method of radiation resistance and loss resistance in the multi-tuning mode and the calculation formulas of other important radiation parameters are given. FEKO simulation software is used to model and simulate the umbrella-shaped antenna. The radiation parameters of the antenna in different tuning modes are obtained. The effects of different tuning mode on the radiation performance is compared. The results show that the multi-infeed tuning mode can effectively increase the radiation resistance and power capacity of the antenna and improve the radiation efficiency of the VLF antenna.
Establishing the correspondences between 2D UWB positions and image coordinates
Authors: Zhang Qiang , Li Shiqian , Wei Wei , Liu Minchao , Wu Shuang , Qin Xue
Published: June 2022

Ultra wide band (UWB) positioning system and camera are two types of sensors which records positions and images respectively. In many applications, it is expected to fuse the data obtained by the two types of sensors in two different coordinate systems. In this work, we study the problem of establishing the correspondences between 2D UWB positions and image coordinates of a camera. We propose a simple yet effective method which requires simple apparatus and does not need to know in advance the positions of the UWB anchors in camera frame. Experimental results have demonstrated the effectiveness of proposed method.
Design and Implementation of Ultrasonic Gas Leakage Locating System
Authors: Cao Yongle , Wang Dongjian , Zhu Ming , Li Honglie , Peng Taichong , Yuan Xiaojun , Guan Wenyong
Published: June 2022

The leakage of dangerous gas at the gas station may cause explosions and other serious accidents, threatening the safety of workers. This paper designs and implements a gas leakage locating device based on ultrasonic technique. The device can communicate with an intelligent inspection robot which alarms the gas leakage in real time and tracks the leaking sources. This paper first builds a hardware platform, and then realizes a four-channel signal based leak location algorithm by combining decision tree and neural network algorithm of smoothing pre-treatment. Finally, each software module of the gas leak location device is constructed. Testing of the locating capability of the device was completed in practical working environment.
Fault Diagnosis of Transformer Winding Looseness Based on Vibration Signal and GOA-KELM Model
Authors: Wang Chen , Cai Chengming , Du Yanpeng , Ji Zhenglian , Liu Yi , Miao Mingxiang
Published: June 2022

Aiming at the problem that the latent fault of transformer winding looseness is difficult to identify and the diagnosis accuracy is low, a fault diagnosis method based on vibration signal and grasshopper optimization algorithm (GOA) optimization Kernel Extreme Learning Machine (KELM) is proposed in this paper. The method uses the time-domain and frequency-domain characteristics of the vibration signal. First, the time-frequency features of the vibration signals of multiple sensors are extracted, and a multi-sensor time-frequency feature matrix is constructed. Second, the feature matrix is identified and diagnosed by using GOA to optimize the KELM model. Finally, the feasibility and superiority of the proposed method are verified by the experimental data of 110kV transformer. The experimental results show that the method in this paper can successfully identify the looseness of different degrees of windings and the looseness of different phases, and has a higher diagnostic accuracy than the existing algorithms.
Research and Comparative Analysis of Topology Identification Methods
Authors: Yixi Cuomu , Ma Wen , Zhao Yangyang , Chen Yuzhou , Huang Shufan , Xu Zhiwei
Published: June 2022

Topology model is the basis of perceiving power grid state. Wrong topology model will lead to the deviation of state estimation results from the real operation state. Firstly, this paper briefly analyzes the classification and characteristics of topology errors. Secondly, the characteristics of two existing mainstream topology identification methods are compared and analyzed. Then, we analyze the existing topology identification models and methods. Finally, the problems of the existing schemes are summarized. The results show that the mixed integer programming model based on optimization principle can solve topology errors more efficiently.
Design of the five layers large-scale low-orbit communication constellation TT&C system
Authors: Cui Wenhui , Wang Boru , Gan Xi , Gao Yan , Li Nan
Published: June 2022

The large-scale low-orbit constellation TT&C (Telemetry Tracking and Command) requirements are analyzed, and the principles of scalability, low coupling and robustness for the construction of large-scale low-orbit constellation TT&C system are proposed. The five-layer TT&C system framework based on service-oriented and container cloud technology is designed. The resource load balancing and configurability of services of the large-scale constellation TT&C system is realized. The TT&C system model design for the large-scale low-orbit constellation is completed.
An Automatic Aerospace Tracking Data Analysis Method Based on Time Series Curve Shape
Authors: Zhao Shumin , Zhao Mei , Wang Baiyan , Lin Yiyong , Xu Yingchun
Published: June 2022

In the joint test of aerospace tracking, telemetering and command (TT&C) system, the consistency of measured and theoretical data is highly required. How to evaluate the quality of measured data intelligently and efficiently is a hot issue. To address this problem, an automatic data analysis method based on time series curve shape is proposed in this paper. By locating the part of abnormal shape on the curve, the data quality can be quickly evaluated using various pattern recognition algorithms. Finally, several simulation experiments are used to demonstrate the proposed method, which show that the curve shape can be accurately identified and the data quality can be given reasonably.
The online detection system of concentric ring size based on machine vision
Authors: Bu Yakun , Guo Junmei
Published: June 2022

In today’s rapid industrial development, to improve production efficiency and product quality size detection process must be completed in real-time. Aiming at the problems of low production efficiency and large error rate caused by manual detection in the past, this paper proposes an online detection system of concentric ring size based on machine vision and develops a GUI software operation page. This system first processes the image gray level and uses the median filter for image denoising, and further uses Otsu threshold segmentation for image segmentation. Secondly, the Canny edge detection algorithm is used to extract the edge of the ring image. Finally, the radius and coordinates of the ring are measured by the improved Hough transform loop detection. Experiments show that the size measurement error of the measurement system is less than 0.015 mm. This system can meet the requirements of small and medium-sized enterprises for real-time detection of circular products, and improve the accuracy of quality inspection of circular products.
Channel estimation algorithm based on attention mechanism
Authors: An XuDong , Zhao Lei , Wu Han , Zhang QinJuan
Published: June 2022

As the key to wireless communication, channel estimation has become a hot research topic in recent years. In this paper, we propose a deep learning method based on the channel estimation of inverse convolutional network and expanded convolutional network to address the problems that the performance of traditional channel estimation algorithms in orthogonal frequency division multiplexing (OFDM) systems can hardly meet the communication requirements of complex scenarios and are greatly affected by noise. The method constructs a lightweight deconvolutional network using the correlation of channels, and achieves channel interpolation and estimation step by step with a few layers of deconvolutional operations, which achieves channel estimation with low complexity. To improve the estimation performance, an expanded convolutional network is further constructed to suppress the channel noise and improve the accuracy of channel estimation. The simulation results show that the channel estimation can be performed at different signal levels. The simulation results show that the proposed deep learning method based on deconvolution and dilation convolution has lower estimation error and lower complexity than the traditional methods under different signal-to-noise ratios (SNR).
Research on user granularity-level personalized social text generation technology
Authors: Gao Y B , Gao J T , Ma R , Yang L D
Published: June 2022

With the introduction of large-scale pre-trained language models, breakthroughs have been made in text generation technology research. On this basis, in order to assist users to complete personalized creation, this paper proposes a user-level fine-grained control generation model. First, we design the Encoder-Decoder framework based on the GPT2 structure, and model and encode the user’s static personalized information on the Encoder side. Then add a bidirectional independent attention module to receive the personalized feature vector on the Decoder side. The attention module in the original GPT2 structure captures the dynamic personalized features in the user text, namely writing style, expression way, etc. Next, the scores of each attention module are weighted and fused to participate in the subsequent decoding to automatically generate social texts constrained by the user’s personalized feature attributes. However, the semantic sparsity of the user’s basic information will cause occasional conflicts between the generated text and some personalized features. Therefore, we use the Alignment module to perform the secondary enhancement and generation of consistent understanding between the output data of the Decoder and the user’s personalized features, and finally realize the personalized social text generation. Experiments show that compared with the GPT2 baseline model, the fluency of the model is improved by 0.3%-0.6%, and on the basis of no loss of language fluency, the social text generated by the model can have significant user personalization characteristics, among which personalization and consistency the two evaluation indicators of sexuality both increased significantly by 8.4% and 9%.
Stability analysis of a predator-prey model with stage structure
Authors: Pang Qiyue , Gao Yang
Published: June 2022

Many scholars have explored the population dynamics system, functional response, time-delay response, and so on. Based on the existing research, this paper studies a class of predator-prey models with stage structure, time delay, and Holling type-II functional response function. The stability of that model at the positive equilibrium point, the sufficient condition for stability, and the existence of Hopf bifurcation are discus. The model was numerically simulated by taking appropriate parameters and different time delay values, variation diagram of each component, and solution curves were given near the critical value. The results show that the stability of the system will change with the variation of the bifurcation parameter value, and Hopf bifurcation will occur.
A Novel Condenser Vacuum Degree Prediction Model Based on LSTM and MemN2N
Authors: Sun Ziwen , Wang Tao , Lu Yanning , Chen Bo , Jin Yawei , Guan Shipian , Si Jiasheng
Published: June 2022

Condenser vacuum degree prediction of power plants is a challenge task in power system security field. Most existing studies are based on shallow machine learning algorithms, which fail to leverage historical data comprehensively, resulting inaccuracy and unreliable predictions. Therefore, using a serialization model like Recurrent Neural Network to capture time-series information from historical data is necessary. However, these serialization model alone has inherent defects in dealing with long-distance dependence, which may cause historical information forgetting problem. This paper proposes a new prediction model combining LSTM and End-To-End Memory Network (MemN2N). We use LSTM to mine the long-distance dependency information in historical data, and introduce the encoding historical information into the memory pool of MemN2N. MemN2N allows better preservation of historical information for serialization model LSTM, and can make accurate and reliable predictions through soft attention mechanism. Through the experiments on real data from the power plant show that, compared with other prediction models, the model proposed in this paper achieves higher prediction accuracy and has great engineering value.
Condenser Vacuum Degree Prediction Model with Multi-View Information Fusion
Authors: He Pengfei , Zhu Yingjie , Chen Bo , Lu Yanning , Yao Yongling , Xiao Jie , Si Jiasheng
Published: June 2022

Vacuum degree is a crucial factor for the operation of thermoelectric generating set. Existing approaches typically use machine learning algorithms to link the relationship between unit operating data and condenser vacuum degree by focusing on the temporal information within the data, while ignoring the frequency information implied in the historical condenser vacuum degree. To fully use of frequency information and further improve prediction accuracy, we propose a novel condenser vacuum degree prediction model with multi-view information fusion. In specific, the implicit frequency information in the historical vacuum degree sequence is explored via a combination of Variational Mode Decomposition (VMD) and Convolutional Neural Network (CNN). Furthermore, Transformer encoder is used to extract the temporal information from the unit operating data. Finally, the two views information are fused for condenser vacuum degree prediction. Extensive experiments conducted on the real data collected from a power plant demonstrate the superiority of the proposed method over several state-of-the-art methods.
Application of LSTM-LightGBM Nonlinear Combined Model to Power Load Forecasting
Authors: Zhou You , Lin Qing , Xiao Di
Published: June 2022

The accurate prediction of power system load is extremely important for the operation of the power market and the safe operation of the power grid. In order to improve the accuracy of short-term load forecasting of power systems, a combination model based on long short term memory network (LSTM) and light gradient boosting machine (LightGBM) is proposed. The experiment first decomposes historical load data by EMD, uses historical weather data and load data decomposed by EMD to establish LSTM prediction model and LightGBM prediction model respectively, and then these two predicted values are linearly combined to obtain the final predicted value. The electrical load data of the 2016 Electrician Mathematical Contest in Modeling is used as an example to verify. The experimental results show that the LSTM-LightGBM combined model has higher forecasting accuracy and application prospects for power load forecasting than traditional load forecasting methods and standard LSTM and LightGBM load forecasting methods.
Design and Implementation of Groundwater Monitor Based on GPRS Transmitted
Authors: Kuang Xingchen , Wang Laiwei , Yu Wenjing , Liu Xianchun
Published: June 2022

In practical applications, the geological environmental monitoring instruments should have more stringent instrument properties, their resistance to high and low temperature, sealing, corrosion resistance and low power consumption, They are all have higher requirements. While the areas whitout public network coverage are mostly alpine high - altitude areas, the instruments are exposed to relatively harsh geological conditions for a long time. The timely and stable data communication transmission technology is the key technology to ensure stable operation of groundwater dynamic monitoring systems. At present, GSM short message format is mostly used in the groundwater dynamic remote monitoring technology, but this approach is extremely limited in field applications. For obtaining groundwater monitoring parameters not affected by the limitation of public wireless network coverage area, the GPRS satellite positioning and short message technology is adopted, and a kind of data transmission communication apparatus using GPRS satellite is researched. After a large number of indoor debugging and field stability tests, it is proved that the control terminal of groundwater dynamic monitoring and communication developed based on GPRS satellite communication features stable data transmission, low power consumption, good resistance of wind, sand and moisture. It solves the transmission obstacle of groundwater monitoring data in the area without mobile phone signal, and realizes multi - mode groundwater monitoring communication.
The Effect of Plant Densities in System of Rice Intensification (SRI) Method to Water Productivity of Paddy Field in East Sumba, East Nusa Tenggara
Authors: Nugroho B D A , Arif C , Suryandika F , Hapsari U , Nihayah B , Muslihin
Published: June 2022

Principle of System of Rice Intensification (SRI) adapted to local conditions to increase productivity and environmentally friendly. The main component of SRI is single seedling per hill, young seedlings, wider spacing, intermittent irrigation, inter-cultivation, and organic fertilization. This study area of the System of Rice Intensification is in East Sumba Regency, East Nusa Tenggara, which has typical areas like soil texture, bulk density, soil water content, and rainfall. The research aimed to know the effect of plant densities in the System of Rice Intensification (SRI) method on the water productivity of paddy fields. This research initially focused on transplanting very young rice seedlings of 14 days old in two treatments of plants. The densities are broad in a square pattern (30 x 30 cm) and a Jajar Legowo pattern (20 x 10 x 40 cm). The rice was not grown in flooded paddies but moist ground, with intermittent irrigation. When SRI was concerned at a different wider spacing, it discovered the effect on water productivity for paddy fields, especially in East Sumba, East Nusa Tenggara. So that it determined the best wider spacing of the System of Rice Intensification method can apply in the area. The results show that the Jajar Legowo pattern spacing (20 x 10 x 40 cm) has a higher water productivity value of 3,4% than the spacing treatment (30 x 30 cm). Jajar Legowo was 11.9% higher than the spacing treatment (30 x 30 cm).
Hydraulic Performance Evaluation of Low-Cost Gravity-Fed Drip Irrigation Systems Under Constant Head Conditions
Authors: Martinez C G , Wu C L R , Fajardo A L , Ella V B
Published: June 2022

The use of drip irrigation for upland crop production has gained popularity in developing countries due to its relatively high water-use efficiency. To maximize the efficiency of this irrigation method, it is important to evaluate its hydraulic performance in terms of emitter discharge and water distribution uniformity under various operating heads. In this study, the hydraulic performance of two locally available low-cost drip irrigation kits -referred to in this study as Drip Kit A and Drip Kit B - was assessed and compared under constant head conditions. Both drip kits are composed of a 1000-L intermediate bulk container (IBC) tank, 10-m submain line, 20-m lateral lines spaced 0.75 m apart, and cascade labyrinth emitters spaced 0.30 m apart along the laterals. Operating heads of 2.5, 3.5, 4.0, 4.5, 5.0, 5.5 m were used and maintained throughout the trials with the use of an overflowing tank. The submain and lateral lines were levelled (0% slope). Sampling of discharge rates was done for one-third of the total number of emitters for each of the tests performed. Results showed that the overall system emitter discharge rate generally increases with increasing operating head. Moreover, emitters farther from the submain line generated relatively lower discharge rates than those closer to it. Analysis of the experimental data showed that the Christiansen’s coefficient of uniformity (CU), emission uniformity (EU), and coefficient of variation (CV) ranged from 97.5 to 98.5, 95.9 to 97.7, and 0.02 to 0.04 for the drip systems tested. Further statistical analysis also showed that varying the operating heads does not have a statistically significant effect (α=5%) on the CU, EU, and CV of the system. Based on the results, Drip Kit B performed better than Drip Kit A in terms of water distribution uniformity. However, the latter could generate higher emitter discharge rates than the former. For both drip kits, an operating head of 2.5-m is recommendable for a 200 m2 plot, from the practical standpoint. This study has generated important empirical data that could serve as a basis for maximizing the performance efficiency of locally available drip irrigation systems for a more efficient irrigation water management.
The Effect of Biofertilizer from Waste Bioconversion on The Growth of Cocoa Seedlings
Authors: Sasmita K D , Rokmah D N , Sakiroh  , Hafif B , Putra S
Published: June 2022

Organic waste can be a source of environmental pollution if not managed properly. The organic waste transformed by Black Soldier Fly (BSF) larvae produces liquid biofertilizer (LB) containing nutrients and beneficial microbes for plants. This study aims to determine the effect of dosage and frequency of application of liquid biofertilizer on the growth of cocoa seedlings and soil properties. The experiment used a randomized complete block design with seven treatments and four replications. The treatments were a control, LB 3% every two weeks, LB 3% every four weeks, LB 6% every two weeks, LB 6% every four weeks, LB 12% every two weeks, LB 12% every four weeks. The results showed that LB 6% every four weeks was the best treatment in increasing seedling height, stem diameter, and weight of fresh shoot, dry shoot, and dry roots of cocoa seedlings at 20 weeks old compared to other treatment. The application of LB significantly increased soil pH, but not significantly affected on the content of organic C, total N, available P and exchangeable cations at soil. Biofertilizer from bioconversion of organic waste using BSF larvae is suitable to improve the growth of cocoa seedlings.
Techno-economy Analysis of Shallot Seedling Production form TSS (True Shallot Seed) with LCAC (Low Cost Aeroponic Chamber) Technology
Authors: Solahudin M , Sucahyo L , Amarilis S , Purnamasasi L A
Published: June 2022

The decline in the productivity of shallots occurred in almost all areas of shallot production centres in Indonesia. One of the factors in the decline in productivity is that farmers are still dependent on tuber seeds that are produced by themselves from generation to generation without any risk of carrying degenerative diseases from previous shallots. Another problem is that the cost of providing seeds is quite high, reaching 40% of the total production cost, with an average requirement of 1-1.5 tons/hectare. Planting shallots using TSS (True Shallot Seed) is an alternative solution, in terms of seed requirements, only 3-5 kg/ha is needed. However, an initial activity is needed in the form of the production of shallot planting material before it is transferred to the land. This study aims to conduct a technoeconomic analysis of shallot planting material production from TSS with LCAC (Low Cost Aeroponic Chamber) technology. Techno-economic analysis is carried out by calculating the basic costs for producing shallot seeds, and economic analysis related to NPV, IRR, Net BC Ratio and Payback Period. This study uses a scenario design of production scales of 200, 500, 1000 trays, and 1 million seeds on a production schedule of 3 cycles per year and 6 cycles per year. The NPV calculation yields profits ranging from 4,750,650 - 822,448,953 IDR, IRR 9.87 - 65.40% above the discount rate used of 6%. Net B/C ratio 1.12 - 2.24 and initial investment will return to investors in the range of 5.23 to 1.28 years after production starts.
Hydropic Rice Nursery for Rice Transplanting Using Rice Transplanters
Authors: Astika I W , Hartono F F
Published: June 2022

Rice nursery using dapogs requires a series of media preparation activities involving sieving the soil, mixing with organic fertilizer and rice husk charcoal, which are troublesome for the farmers. Another practical method is to grow the rice seedlings in an hydroponic system. The purpose of this research was to develop a hydroponic system to grow rice seedlings until ready for transplanting with rice tranplanters and then to transplant the seedlings with a transplanter. The seedling nursery were designed having 10 level rack with 12 trays on each level. It is designed DFT, NFT and flooding hydroponic systems. Finally flooding system, nutrient concentration rate of 2.4 mS and seed density 5 seeds/cm2 were used in the research as those treatments gave the best results. Light illumination at rack level 1-6 were significantly different from level 7 (the top layer) and consequently level 1-6 suffered from etiolation problems making the seedlings less vigor. Transplanting results showed a wide range of number of clump/hill both at “lees” and “middle” machine setting. Root zone without any soil media made a high friction force when the seedling mat sliding down to the planting fork. A slight media at the bottom of tray might be required as the slippering media.
The effect of temperature distillation on products distribution derived from wood pyrolysis bio-oil
Authors: Irawansyah Herry , Amrullah Apip , Fitrah Jayadi
Published: June 2022

Bio-oil from biomass pyrolysis can be converted to chemicals, solid carbon materials, and syngas by various thermochemical conversion technology methods. Because of the elevated temperature, bio-oil suffers drastic component changes as the first step in these processes. Understanding the impact of heating temperature on bio-oil transformation during the distillation process is critical for practical bio-oil usage. A bio-oil feedstock produced from the pyrolysis of lamtoro wood residue at 500 °C was used in distillation from this work. Complete temperature range analysis of 96, 97, 98, 99, and 100 °C was conducted. Eight typical compounds in bio-oil were precisely quantified by gas chromatography-mass spectroscopy (GC-MS) and FTIR analysis. The results revealed that a common critical point was widely present during the distillation process, which may be attributed to a stable system generated by hydrogen bonding. As a result, the content of acetic acid, 2-Propanone, and phenol was up to 38%, 12%, and 20%, respectively. The detailed distillation characteristics and product distribution provide a comprehensive insight into the reaction process and component enrichment patterns, assisting design and parameter optimization.
Oil Palm Productivity Estimation Based on Landsat 8 Vegetation Index, Rainfall, and Fertilization Dosage at PT PSJ, South Sumatera
Authors: Savitrie N P , Liyantono
Published: June 2022

Estimating oil palm production is one of the essential factors in palm oil management planning which is still done conventionally. This process uses more workers to take data samples from the fields that need more energy and time to get the data. Meanwhile, the yield estimating process could be done using a remote sensing method to save more energy and time on its implementation. This research was conducted to determine the estimation model of oil palm productivity using parameters from the remote sensing method and the company’s data, and determine the relationship between current productivity and the previous data. The parameters used to estimate palm oil productivity are NDVI from Landsat 8, rainfall, rainy days, fertilization dosage, and age of the palm oil tree from the company’s data. These parameters were shifted several other months back (M-1, M-2, M-3, M-6, and M-12) and grouped into 6-Months and 12-Months to estimate the palm oil production. The result showed that using the previous data can estimate oil palm productivity. The data that can be considered to estimate palm oil production is 12 months (M-12) shifted back. Also, using 3 parameters (NDVI value, rainfall, and fertilization dosage) is enough to estimate palm oil production.