bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Visual Perception Technology of Autonomous Driving Based on Improved Convolutional Neural Network
Authors: Wang Yucheng , Li Zhihao , Hao Hongye , Yang Hengyu , Zheng Yixin
Published: June 2020

With the continuous development of the world’s scientific and technological level and the continuous progress of society and economy, driverless cars have become the key research targets of the existing automotive industry. Based on the convolutional neural network theory, this paper redesigned the Faster R-CNN network framework to improve the target recognition accuracy and apply it to the unmanned visual perception system. At the same time, the improved algorithm is used to test the cars under different simulated travel conditions. The computer vision system toolbox of MATLAB was used to verify the effectiveness of the algorithm, and the driving scene designer was used to construct multi-sensor fusion and simulated road scenes, and the corresponding visual control system was designed to effectively realize the automatic code generation. The experimental results show that the average detection accuracy of the improved algorithm is higher, the algorithm is more feasible and robust, and it is helpful to promote the development of driverless cars.
The Properties and Application of Poisson Distribution
Authors: Zhao Jing , Zhang Fan , Zhao Chao , Wu Gang , Wang Haitao , Cao Xinyu
Published: June 2020

Poisson distribution is not only a very important distribution in probability theory, but also a useful tool to study the random events. Firstly, this paper gives a simple introduction of Poisson distribution and some characteristics of the Poisson distribution. Secondly, some properties of Poisson distribution are introduced and proved. In the end, some application of Poisson distribution are introduced, such as the application in the rare event and in daily life. We also do some analysis about the application of Poisson distribution.
Research on Terminal Management Technology Based on Distribution Management System
Authors: Yinghua Song , Gang Wang , Zhongwei Li
Published: June 2020

With the continuous development of distribution automation technology and the rapid growth of the number of distribution equipment, this paper analyzes how to carry out the operation management of distribution network equipment and the key technology of application based on the existing distribution management system. The key technologies include the unified management, automatic control and online monitoring of equipment. Through the research of related technologies, the rapid and effective management and control of mass distribution equipment is realized, the management efficiency of equipment is improved, and the technical support means for the rapid construction of distribution network are provided.
Probabilistic Load Forecasting of Adaptive Multiple Polynomial Regression considering Temperature Scenario and Dummy variables
Authors: Li Jiang , Ren Liyang , Wang Baocai , Li Guoqing
Published: June 2020

The monthly or yearly low accurate history data always leads to the low prediction-accuracy for load forecasting. We use temperature data from Sydney, Australia and the New South Wales Natural Load Dataset. To improve the data-based forecasting accuracy and time related scenario, this paper builds an adaptive multiple polynomial regression model considering temperature scenario and dummy variables. These dummy variables are divided into three aspects: trend variables, date variables and temperature variables. Trend variables are used to predict the whole economic development and user habit. Date variables are introduced to deal with the characteristics of working days and holidays. Cubic function for temperature variables from Australia and the New South Wales electric load history data is constructed to describe the relationship between load and temperature scenario. A temperature scenario is generated by considering the different loads of different seasons and the probability search of different scenarios. The load forecasting interval under different scenarios is given and analyzed by using dummy variables. At last, the method is validated based on the history data in a certain area. The prediction result with high accuracy shows clear intuitive and powerful interpreting ability, which can provide reliable decision basis for long term load forecasting. After simulation analysis, the accuracy of load forecasting based on 3-year history increases by 3.8%.
Research on Robust Design and Optimization of Embedded Network Electronic Information System
Authors: Yang Pan , Zhou Xinliang , Zhou Xinliang , Jia Jianhao
Published: June 2020

At present, in the process of designing and optimizing the robustness of embedded network electronic information systems, it is found that many factors in the system have some correlation with robustness, and there are individual differences in the factors affecting robustness, which also have different effects on robustness at the same time. The optimization design of the calculation method for the robustness of the embedded network electronic information system is organically combined with chaos and particle swarm optimization, through experiments and simulations, it proves that the optimized design has high accuracy.
Research on BOM multi-view mapping method orient to aircraft in-service data management
Authors: Cai Shuyu , Hu Die , Fei Yang , Xu Jianxin
Published: June 2020

In order to establish the framework for aircraft life-cycle data management and ensure the efficient implementation of maintenance information management of in-service aircraft, the characteristics of maintenance information management of civil aircraft in service were analyzed. BOM views were classified, and a BOM multi-view model was constructed. By analyzing the main mapping forms of BOM multi-views, the node types of BOM multi-view were defined, the mapping rules of BOM multi-view model were proposed, and the mapping algorithm of BOM multi-view model was designed and implemented. Finally, method validation was performed by the BOM mapping of 48-section torsion box of a certain aircraft. The results show that, the mapping of EBOM to M-BOM is realized effectively, ensuring the full integration of the information management structure in the in-service maintenance phase and the development phase, and ensuring the consistency of the aircraft life-cycle data management framework.
Estimate the number of triangles in real-world graph streams
Authors: Liu Changyu , Zhang Xin
Published: June 2020

Estimating the number of triangles in the graph streams is the basis of data mining, which aims to design an efficient graph stream algorithm to estimate the number of triangles in graph. Real-world graph is a multi-layer graph encompassing multiple distinct types of connectivity. The state-of-the-art approaches that counting triangles mainly focus on a general graph and cannot be applied for multi-layer graph, since duplicated edges across different layers exist. In this paper, we give the concept of several triads and triangles under the multilayer network, which truly reflect the real-world network topology. And we design a new two-stage sample algorithm based on reservoir sampling and triad sampling under real-world graph streams which solve the problem of more data brought by multi-layer networks. The algorithm is also a one-pass algorithm, and it can calculate the number of all types of triangles at the same time. We analyze the expectation and variance of the estimations and show that the algorithm is unbiased and stable. Our experimental results demonstrate that algorithm has good time efficiency and accuracy.
Design of UHF RFID Baseband Chip with Temperature Sensing
Authors: Chu Qi , Xiao Wan’ang , Gao Wanlin , Zhang Yan’e
Published: June 2020

The radio frequency identification (RFID) with temperature sensor can achieve accurate management and body temperature measurement in animal husbandry. It also can improve the efficiency and epidemic prevention. A ultra high frequency (UHF) RFID chip baseband integrated with a specific temperature sensor is designed compliant with “Information Technology Radio Frequency Identification 800/900MHz Air Interface Standard” (GB/T 29768). Firstly, according to the overall function, the unit division and structure design of digital baseband are given. Secondly, a baseband temperature sensor control unit connected with temperature sensor is proposed. Finally, the whole function simulation and experiments on FPGA are completed. The experimental results show that the designed UHF RFID baseband can satisfy the communication of both sides and realize the interaction with the temperature sensor.
An Image Denoising Method Based on Deep Residual GAN
Authors: Wang Ziyuan , Wang Lidan , Duan Shukai , Li Yunfei
Published: June 2020

As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most of them is lack of capability when customers want more perceptual details of the image without information loss. In this paper, a deep residual network based on generative adversarial (GAN) network was proposed to complete the image denoising mission. Firstly, a generative-adversarial network structure based on residual blocks was designed. Secondly, a refined loss function was given to train the GAN network. The well designed loss function can help the generated image to be very close to the clear counterpart (ground truth) while enhancing more details in colours and brightness. Finally, extensive experiments show that our network is not only convincing for images denoising, but also effective for other image process tasks, such as image defogging, medical CT denoising etc., presenting impressive and competitive effects.
Compressive X-ray Tomosynthesis based on Exposure Sequence Optimization
Authors: Dong Wang , Xu Ma , Qile Zhao , Hao Xu , Tingfa Xu
Published: June 2020

X-ray tomosynthesis technique can reconstruct three-dimensional object of interest from two-dimensional projection measurements. This paper proposes a compressive X-ray tomosynthesis imaging method to inspect the moving object on the conveyor. Coding masks are used to modulate the intensity distribution of X-ray sources and reduce the radiation dose. Low-cost uniform linear array detector is used to collect measurement data. Considering the rigid motion of the object, the proposed method uses a dynamic imaging model and a reconstruction framework based on the variation of the sensing geometry. Subsequently, an optimization method is proposed to design the exposure sequence of X-ray sources based on the genetic algorithm. Optimizing the exposure sequence can ameliorate the condition of the ill-posed inverse reconstruction problem. Simulations show that the optimized exposure sequence can effectively improve the reconstruction performance of the compressive X-ray tomosynthesis.
Application analysis of image recognition based on multiple intelligence algorithm
Authors: Jiang Jiyue , Wu Hao , Cui Yang , Cai Yijia , Yu Chenglong , Zhong Ruitao
Published: June 2020

Image recognition technology based on artificial intelligence algorithm has entered a rapid development stage. According to the development and research status at home and abroad, we can see that PCA, ANN, SVN and other technologies can effectively realize the recognition and generation of images, especially the extraction and prediction of face features, classification and recognition. The analysis and application of the generation countermeasure network (GAN) technology is mainly embodied in the realization of the generation and analysis of handwritten numbers, and the accurate prediction of the promotion and application of SVM technology, as well as the comprehensive and accurate analysis of the generation effect. This paper mainly studies the comparative analysis and application of human face database (ORL) through the relevant data. By extracting 50 face samples, 500 face images are produced for recognition analysis and application.
Research on a convolution operation method based on domain transformation in deep learning
Authors: Wang Zhichen , Li Hongliang
Published: June 2020

In deep learning, convolution operation is an important part of convolutional neural network. Various transformations have been used to deal with convolution problems, but complex number operation and the inability to carry out convolution in the DCT domain have been introduced. In this paper, the relationship between DCT transform of output matrix and DCT transform of input matrix is found. At the same time, in view of the reality of partitioning operation in the case of large matrix, the method of overlapping of blocks is introduced. Finally, experiments on LeNet show that the proposed method can achieve the accuracy of the traditional method and can be used in practical applications.
Multi-cognitive network resource allocation based on improved artificial bee colony algorithm
Authors: Li Lu , Zhang Luyong
Published: June 2020

This paper introduces a graph theory model for resource allocation in multi-cognitive wireless network scenarios. Aiming at the problems of low search accuracy and slow convergence speed of the basic artificial bee colony algorithm, an improved bee colony algorithm is proposed. The improved algorithm introduces an adaptive t-distribution mutation strategy. Compared with the original algorithm, the performance of the improved algorithm has greatly improved. At the same time, the improved bee colony algorithm is applied to multi-cognitive wireless network scenarios for resource allocation in the model. The experimental results show that the improved artificial bee colony algorithm can obtain greater system throughput and effectively reduce the performance of multi-cognitive wireless network systems, and can allocate resources more reasonably.
RETRACTED: Construction of Interactive Integrated Communication Marketing System in Big Data Era
Authors: Tang Qi
Published: June 2020

In the era of big data, the interactive communication and marketing framework integrated with massive data and information technology systems is becoming increasingly sophisticated. From the perspective of the overall architecture, to construct an interactive integrated communication marketing system, we must actively expand the big data communication marketing platform and do a good job of analyzing consumer consumption orientation. We need to fully optimize the interactive integrated communication marketing strategy, and do a good job of feedback of marketing results, so as to comprehensively improve marketing profits. Generally speaking, the core of integrated communication marketing is to take the consumer as the guide, make full use of various forms of communication, promote the organic combination of internal communication and external communication, optimize the marketing strategy management mechanism, and ensure long-term marketing effectiveness. This article will briefly discuss the construction plan of the interactive integrated communication marketing system in the era of big data, hoping to provide reference and reference for network marketing management.
Research on Inquiry Teaching of Database Course Based on Big Data
Authors: Mengxia Wang
Published: June 2020

Nowadays, China’s social economy has achieved rapid development compared with the past, and has achieved remarkable achievements. At present, the entire society has entered the era of big data. Based on the background of big data, this article has conducted a full study on how to determine the teaching content and experimental content of database courses. In combination with the actual teaching situation, an inquiry-based teaching method was formulated, and the problems existing in the database classroom teaching were analyzed and effective solutions were put forward. At the same time, it can help students better organize, manage, and store big data, do a good job of technology development, and promote a significant improvement in the comprehensive literacy of software talents.
Research on Life Prediction of IGBT Devices Based on Elman Neural Network Model
Authors: Xing Chao , Xi Xinze , He Xin , Li Shengnan , Liu Mingqun , Li Lie
Published: June 2020

IGBT, as a new generation of composite full-controlled voltage-driven power semiconductor devices, has been widely used in the field of modern power electronics. The study of IGBT device life prediction has important guiding significance for the stable operation and reliability management of power system. In this paper, the Cofin-Manson-Arrhenius extended exponential model based on thermal load is analyzed, and the model parameters are trained and modified by the Elman neural network in order to improve the prediction accuracy of life prediction model. The Coffin-Manson-Arrhenius extension exponential model and the new improved model are simulated and validated by experiments. The results are compared with the actual life of IGBT. It is concluded that the Coffin-Manson-Arrhenius extension exponential model based on Elman neural network has higher accuracy in life prediction than the Coffin-Manson-Arrhenius extension exponential model.
Named Entity Recognition Method of Brazilian Legal Text based on pre-training model
Authors: Wang Zhili , Wu Yufan , Lei Pengbin , Peng Cheng
Published: June 2020

Named entity recognition (NER) is a common task in Natural Language Processing (NLP). To this end, we propose a novel approach based on pre-training model to complete the sequence labeling tasks by learning the large-scale real-world data from Brazilian legal documents. Especially, combining iterated dilated convolution[1] (IDCNN) and Bi-LSTM, we develop the scalable sequence labeling model named Sequence Tagging Model (STM) and extensive experiments validate the effectiveness of STM for NER tasks. Furthermore, compared with the IDCNN-CRF model, the experimental results show that the STM is better and the F1 score is 93.23%, which provides an important basis for NER tasks.
MMV-based OMP for DOA estimation with 1-bit measurement
Authors: Chen Dan , Tian Longwei , Xu Changqing
Published: June 2020

This paper shows a novel scheme for direction-of-arrival (DOA) estimation of narrowband signals. In the scheme, the 1-bit measurement is used to reduce the system cost. A recovery compressed sensing (CS)-based algorithm with multiple measurement vector (MMV) is proposed to make up the information loss. The purposed MMV-OMP algorithm provides a new idea which make the compress sensing framework applicable directly to an MMV model. The effectiveness of the proposed approach is assessed through numerical simulations under different environment configurations. Comparisons with other methods are reported as well.
An Evaluation Method of Combined Forces Electronic Countermeasure Capability based on Grey Relational Analysis
Authors: Fan Ji-song , Xu Jia-wei , Ren Hui
Published: June 2020

Electronic warfare in battlefield is a dynamic game process with incomplete information, in which there are not only complex technical factors, but also a lot of uncertain factors, fuzzy factors or human factors, so it is difficult to model and evaluate its capability. In this paper, the index system of the electronic countermeasure capability of the synthetic army is established, and a method of multi-level grey relational analysis and AHP is used to analyse and evaluate the electronic countermeasure capability of the synthetic army. A complete set of evaluation method steps is put forward and verified by an example. Compared with the past models and methods, they are easy to operate, applicable and scientific in conclusion, which is convenient to analyse and evaluate the electronic countermeasures capability of multiple units. It is of great theoretical significance and practical value for the development of electronic countermeasure capability construction and scientific assessment and evaluation of synthetic forces.
Waste recycling 3D printing and silk-making system
Authors: Huang Ruiting , Yao Qingren , Liu Yi
Published: June 2020

With the continuous development of 3D printing technology, 3D printing has been widely used in various industries. 3D printing has more and more consumables, more and more wastes are generated, and more and more pollution is generated to our environment. This system is based on the single-chip microcomputer, and uses the fuzzy PID algorithm to melt, shape and wire various types of 3D printing consumables at different temperatures. It can recycle 3D printing waste and directly use consumables for printing to reduce environmental pollution and printing cost.
Design of 1Gsps high-speed data acquisition card
Authors: Sun Xiunan , Liu Ming , Liang Hao
Published: June 2020

In order to digitize the High-Frequency signal, a 12-bit 1Gsps RF Sampling data acquisition system is designed. The digital acquisition system includes an Analog-to-Digital Converter (ADC) daughter card and a data processing mother card equipped with Field Programmable Gate Arrays (FPGA) for communication, which has an external DDR3 memory module and a Gigabit Ethernet Interface. It focuses on the hardware system implementation of the daughter card and the realization of data receiving, transferring, and sending based on the FPGA. The test results show that the Effective Number of Bit (ENOB) of the acquisition card is above 9.1 Bits. Both Integral Non-Linear (INL) and Differential Non-Linearity (DNL) are anticipated. It accomplishes the requirements for engineering applications in many fields excellently.
Research on Acoustic Model of Multi-Task Learning for Speech Recognition
Authors: Gong Chunwei , Li Guanyu , Luo Lisai
Published: June 2020

Applying the idea of multi-task learning, this paper proposes a speech recognition acoustic model structure, which can share information between multiple tasks to improve the performance of each task. Applying this structure to the acoustic model modeling of resource-poor languages has achieved good recognition results.
Activity Recognition using 1D convolution from Accelerometers Data
Authors: Wang Jian , Hua liu Xue
Published: June 2020

Aiming at the problem of activity a recognition method based on a convolutional neural network was proposed in this papaer, which can effectively classify 6 types of human movements: Downstaris, Jogging, Sitting, Standing, Upstairs and Working. The network consists of an input layer, two convolutional layers, two pooling layers, a fully connected layer, and an output layer. The sliding window is used to transform the sensor data into a three-channel RGB image format, and the features of the three-axis speed sensor data are automatically extracted to classify each action. The model was reproduced using Tensorflow, and the recognition rate of 89.35% was achieved on the open source database WISDM. The experimental results show that the amplifier has a better effect on human movement recognition.
Chinese long text summarization using improved sequence-to-sequence lstm
Authors: Yao Zanjie , Chen Aixiang , Xie Han
Published: June 2020

Text summarization is an important issue in natural language processing. The existing method has the problem of low accuracy when performing long text summarization. In this paper, We use the LSTM to construct the sequence-to-sequence model, and combine the attention mechanism to process automatic Chinese long text summarization.The experimental results indicate that our method can accurately extract key information from long text, generate high-quality summary.
Joint Delay Reduction and Power of Device for Differentiated Data Transmission in D2D Network
Authors: Song Lan
Published: June 2020

In wireless communication, Device-to-Device (D2D) networks will become more and more common with the popularity of mobile terminals. However, in a D2D network, the processing capabilities of different terminals may be different, and the energy of different terminals is different due to battery life. In order to improve the quality of experience (QoE) of terminals with different processing capabilities and energy, and realize the transmission of differentiated data streams, this paper combines the existing base station retransmission and terminal retransmission algorithms in D2D network. In the transmission process, the data packet is divided into a basic layer and several enhancement layers according to the definition of the data. Based on the link quality, the basic layer data packet is transmitted firstly, then the enhancement layer data packet is transmitted. Moreover, not only the base station retransmits the data packet, but also the terminal that has received the corresponding data packet also participates in the retransmission. In order to extend the average life of the network, we propose the maximum weight packet selection algorithm based on channel quality and terminal energy (MWP-QE). The simulation results show that compared with the existing retransmission algorithm, this algorithm can realize the transmission of differentiated data, reduce the retransmission delay and extend the life of the network.

A post-publication change was made to this article on 17 Jun 2020 to amend the author list.
Information Retrieval Method for Mixed Intrusion of Surveillance Network Based on Big Data
Authors: Zhu YuLin , Meng QingChuan , Hu DaYong , Lu Ziyuan , Li ZhiGang
Published: June 2020

The current surveillance network intrusion information retrieval methods have problems such as low retrieval accuracy, high recall rate, and long retrieval time. Therefore, this paper proposes a hybrid intrusion information retrieval method for monitoring networks based on big data. The genetic algorithm is used to optimize the feature set, and the partial F test is introduced. The optimal subset is selected to form the optimal feature set and the redundant information elimination model is constructed to eliminate redundant information in the mixed intrusion information. Based on the information retrieval theory, the LDA model is used to build the feature set, and model the subject of the document, establish an intrusion information retrieval model, then complete the hybrid network intrusion information retrieval of the monitoring network under big data. The results show that the method proposed in this paper has higher retrieval accuracy, can effectively improve the retrieval efficiency of intrusion information and the average recall rate is about 24%, which is better than other methods.
An Empirical Study of Observation-weighting Method for Mining Actionable Behavioral Rules
Authors: Su Peng , Wang Yufeng
Published: June 2020

Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among a variety types of actionable knowledge, the actionable behavioral rule plays an important and unique role because it can directly and explicitly suggest actions to users to positively influence their behaviors of concerned entities. The problem of mining such rules is a search problem within a framework of support and expected utility. The previous mining approach assumes that each instance which supports a rule has the uniform contribution to the support. However, this assumption is usually violated in practice, and thus will hinder the performance of algorithms for mining such rules. To handle this problem, in this paper, we propose several observation-weighting models for support based on different functions. We further empirically investigate these models. Based on the results of our experimental study, we gain a thorough insight into the selection of various observation-weighting models for this domain.
Modified Minimum Approach Distance Formula for Five Working Used for 500kV Insulated Aerial Vehicles with Double Circuits on the Same Tower
Authors: Chao Chen , Zhenyu Ma , Leijiao Ge , Binbin Wen , Yipin Xu , Jinhui Zhou
Published: June 2020

500kV double circuits on the same tower can effectively improve the natural transmission power and reduce the width of the line corridor, but the electromagnetic environment under the conductor is deteriorated. In order to ensure the safety of the workers in the insulated aerial vehicles and equipment during the live working, this paper firstly calculates the electric field distribution on the operating surface of the 500kV double-circuits truck with the actual line parameters, and then defines the distance coefficient. The existing minimum safe distance formula is modified, and a reference calculation method of the distance coefficient is given in combination with the data in the paper. Finally, the simulation data is used to verify.
Research on Simulation Analysis of Soil Cutting Process by Ditcher
Authors: Zhang Zihan , Song Yuepeng , Ren Longlong , Zhang Hongmei
Published: June 2020

Ditching and fertilizing is the important components of the orchard working. In order to achieve modern agricultural requirements for energy saving and drag reduction, the mechanism of ditching blade on soil during soil cutting process was studied, and the tool structure and parameters were optimized. This paper numerically simulated the soil cutting process of disc type ditcher blade based on SPH method by ANSYS/LS-DYNA. Simulation result showed that the SPH method can directly simulate the whole process of cutting the soil with the ditch cutter. The maximum Von Mises stress and cutting force are 4 MPa and 350N. The Von Mises stress of soil and cutting force had small fluctuation, so that the cutting is stable. The power consumption was approximately 0.35 kW at steady state, and the cutting consumption obtained by theoretical analysis is similar to the simulation result. By theoretical analysis, the viability of SPH method on simulating the soil cutting process of disc type ditcher blade was verified.
Automatic ship detection in SAR Image based on Multi-scale Faster R-CNN
Authors: Zhou Yiqing , Cai Zemin , Zhu Yuting , Yan Jingwen
Published: June 2020

Automatic ship detection of synthetic aperture radar (SAR) images has been widely used in maritime surveillance. SAR images have the characteristics of all-weather, all-day detection. Therefore, many object detection methods ranging from traditional to deep learning techniques have been proposed. However, the objects in large-scale remote sensing images are relatively small, and objects are often appeared at different scales. What’s more, the current ship detection methods are insensitive to small-scale vessels. To solve these problems, a novel multi-scale ship detection method based on a Multi-scale Faster R-CNN network in SAR images is proposed in this paper. Firstly, a multi-scale network is used to decompose the SAR images into a pyramid structure and extract the features. Then, the region proposal network (RPN) is performed using the feature map for each layer to get the proposals that contains ship targets. Finally, these proposals are fed to the classification and regression network to obtain the final detection results. Multi-scale Faster R-CNN achieves the mean average precision(mAP) score 0.986 on the dataset of SAR-Ship-Dataset, which indicates that the proposed method has high detection accuracy and low missing rate.
Optimization of Machining Craft of Engine Block Based on Numerical Control Process Technology
Authors: Baolin Xia
Published: June 2020

This paper introduces the general and numerical control machining technology of the important surface of the engine block, and focuses on the relevant methods and measures to ensure the quality of high-speed milling and boring. Some methods and measures of optimization based on NC machining technology are proposed. The application of optimization in engine block machining cases is briefly listed. To ensure the quality of the engine block, improve its efficiency, and reduce its cost, opinions and suggestions that can be used for reference are provided.
Markov decision process of optimal energy management for plug-in hybrid electric vehicle and its solution via policy iteration
Authors: Fan Jie , Ou Yang , Wang Peng , Xu Lei , Li Zhe , Zhu HongGuo , Zhou Zhou
Published: June 2020

This paper proposes a Markov decision process based optimal energy management strategy for plug-in hybrid electric vehicle with a hybrid energy storage system, which mainly consists of an ultracapacitor, a power battery pack and a DC/DC converter. Firstly, the mathematical model is built for the overall system. Secondly, based on modified worldwide harmonized light duty test cycle, the power transition probability matrix is constructed to describe the Markov property of driver’s power demand in natural driving. Then by combining the stochastic property of driver’s power demand and deterministic state transition of the hybrid powertrain system, the energy management optimization problem is formulated into a typical Markov decision process. Finally, the derived optimization problem is solved by policy iteration and the corresponding optimal control map is generated. The optimality of the solution is investigated and discussed in detail.
Research on frequency domain pulse compression of LFM signal
Authors: Panpan He
Published: June 2020

Pulse compression technology can effectively solve the contradiction between the maximum operating distance and range resolution. LFM is a common means of pulse compression technology. In this paper, the frequency-domain pulse compression of LFM signal is carried out, and the feasibility of frequency-domain pulse compression technology is verified by MATLAB simulation and experimental data.
Method for testing output limit of AVR in AC exciter excitation system
Authors: Zhu Yingfeng , Zhang Yongming , Xie Xiaosu , Yuan Xunkui
Published: June 2020

The excitation system of synchronous generator plays an important role in the static and dynamic stability of power system. ‘Guide for modelling generator excitation system’ requires that the excitation system of new generators should be modelled and remodelled when the excitation system is upgraded. Testing the output limit of AVR is an important content of modelling. Considering inability of tetsing the output limit of AVR in AC exciter excitation system, this paper analyzes the reason using test data firstly, then proposes a new method to test the output limit of AVR, by modifying the maxim firing angle, the output limit can be got, the new method is verified during modelling test of a 145MW generator finally.
Research on tire model parameter identification strategy based on CDTire/3D
Authors: Gao F L , Zhan N , Bu X B , Li X R , Wu Y
Published: June 2020

High accuracy tire modeling is essential to study the automotive fatigue-durability, handling-stability, and NVH performance in the virtual proving ground. Compared with other tire models, CDTire/3D can be directly used in multi-body dynamics simulation, and its linearized version can be adopted in road noise analysis. In consideration of its high generality for cost saving, CDTire/3D has an extensive engineering application prospective in the automotive industry. It is the critical technique to accomplish high-efficiency and high-precision CDTire/3D modeling by investigating the mechanical mechanism of tire and the influence of parameters on all test conditions, based on which a parameter identification strategy is conducted in this paper. The effectiveness of the strategy is verified by a tire modeling case.
Progress and Innovations of Ice Slurry Generation Based on Scraped-surface Method
Authors: Han Zhi , Ma Qingwen , Fang Yunrui , Hua Linhui , Jin ChengKun , Huang Jianghua
Published: June 2020

In recent years, as a new type of ice storage medium, ice slurry has been widely applied in multiple fields. The scraped-surface method has remained the focus of researches, thanks to its advantages such as technical maturity, low cost and stable performance, etc. In this paper, the attributes of ice slurry was briefly introduced and then an analysis and comparison of several common ice slurry generation methods was presented with a summary of the advantages of the scraped-surface method. Then, the current research status of scraping-type ice slurry generation method was introduced. In the final place, this paper would summarizes the existing research fruition and propose a zigzag scraper, and future development and trend are looked forward to.
Steady State Drifting Controller for Rear-Wheel Independent Driving Electric Vehicels
Authors: Huang Chengfeng , Yin Dejun
Published: June 2020

The use of independent driving electric vehicels for extreme sports is a matter to consider. This paper presents a steady-state drift controller for rear-wheel independent driving electric vehicels. The controller is based on linear quadratic regulator technology. A drift equilibrium condition calculator is designed based on the longitudinal force pre-distribution of rear tires and the Pacejka tire model. The results are used as the system reference input. Finally, the CarSim-MATLAB/Simulink co-simulation is carried out to verify the controller.
Field Modification and Application of ODAF Cooling System for 500kV Transformer
Authors: Feng Huo , Jianling Wu , Shangbin Liu , Yonggang Yue
Published: June 2020

A large number of oil flow relays and submersible pumps in the forced oil circulation mode of the main transformer have a huge workload of operation and maintenance. The main transformer of the ODAF cooling system has a large number of oil flow relays, and the submersible pump is prone to malfunction, which resulting in a large amount of maintenance work and the risk of the main transformer being forced to stop. Oil flow baffle and submersible pump running wear debris may affect the normal operation of transformer. This paper, through the field research and application of the transformation of the 500kV main transformer ODAF cooling system, carries out calculation of modification, analysis and calculation of cooling efficiency principle, etc.
Research about the influence of the parameters of the polishing pad on the removal depth of the Al6061 material
Authors: Chen Han , Ji Shijun , Zhao Ji , He Qiuwei
Published: June 2020

Polishing pressure, machining dwell time and tool head spindle speed are the main factors affecting the workpiece cutting depth. In order to analyze the importance of influencing factors, the orthogonal experiment is conducted. The pre-processing is carried out first, and then the formal processing is started. After the formal processing is completed, the cutting depth of each processing point is measured, and the cutting depth under the specified parameters is obtained by subtracting the cutting depth obtained from the pre-processing. Finally, the experimental data show that the average cutting depth is taken as evaluation criteria, and the most important influencing factor is dwell time, followed by polishing force, and spindle rotation speed.
Research on gait design of Hexapod Bionic Robot under damaged condition
Authors: Zhou Zequan , Xu Fenghui , Jia Zhidong , Chen Hao , Shi Qin , Xu Jiangcheng
Published: June 2020

Hexapod robot plays an important role in rescue and relief, battlefield rescue and other occasions. However, due to the influence of environment and other factors, the hexapod robot may be damaged to different degrees, which makes it unable to work normally. This paper studies the gait of hexapod robot under the condition of damage, analyzes the different damaged conditions of hexapod robot, establishes the hexapod robot model under different damaged conditions, studies the gait and stability of hexapod robot under the condition of single-leg damaged, and plans the stable gait suitable for the robot to continue to work. According to the simulation analysis, the four-legged and three-legged gait of the hexapod robot under the condition of single-foot damage which makes itself work normally is obtained. The research method in this paper can be applied to other multi-legged robots under different damage conditions, which has certain significance to improve the working life of these kinds of robots.
A New Research of Detection Device for Smart Wearable Equipment Step Counting Function
Authors: Li Peipei , Zhao Yi , Yang Yanfeng , Liu Yong , Hu Jianyu
Published: June 2020

This article analyzes the current research status of smart wearable devices, proposes a step detection method for the smart wearable device, completes the hardware design and software programming of the device, and develops a test device for step counting function of smart wearable equipment. By testing the relevant products and collecting data, the relevant test results are given. The development of this device provides professional and credible testing data and results to the vast number of consumers and the general public. It can promote the innovation and development of the smart wear industry and deep integration with other industries and technologies. It also has great significance for testing institutions and enterprises.
Vibration response analysis on the sand-wall collision
Authors: Yichen Li , Kai Feng , Zongwen Jia , Gang Liu , Kai Wang , Gang Wang
Published: June 2020

The real-time monitoring of solid particles in pipelines has been widely used in industry, especially during sand production in the petroleum industry. The monitoring result is determined by the vibration force response characteristics of sand-wall collision. In this paper, the process of the sand-wall collision was analyzed by Hertz contact theory, and the main vibration frequency from the sand-wall collision was calculated. The corresponding sand-wall impacting experiment was also investigated. Based on the theoretical and experimental research, the results showed that the main frequency of the sand vibration signal is inversely proportional to the diameter of the sand, and the initial velocity of the sand impact wall has little effect on the main frequency of the vibration signal. Besides, the sand-liquid film-wall experiment and simulation results showed that fluid viscosity little affect the stress transmission under low viscosity (less than 40 mPa·s), and the viscosity has the greatest effect on stress transfer under the high viscosity of 90 mPa·s. The above research lays the foundation for the detection ability of solid particles in pipe flow.
Electromechanical Coupling Modelling of High Speed EMUs with Rotor Field Oriented Control
Authors: Wang Junguo , Yao Zhaoyuan , Haseen M.F. , Zhao Yongxiang
Published: June 2020

According to the theory of vehicle system dynamics and rotor flux-oriented control (RFOC), an electromechanical coupling simulation model of transmission system of high-speed EMUs is established considering the effect of mechanical and electrical characteristics. Firstly, an EMUs multi-body system (MBS) model including is developed by Simpack software based on the structure and parameters of a high-speed EMUs, and a RFOC simulation model of traction transmission system is also built by the Simulink platform. Then two types of models are linked by Simpack co-simulation interface model. Consequently, the electromechanical coupling model of EMUs is developed. The computer simulation method is adopted to simulate the coupling system with RFOC. Simulation results indicate that the proposed model can effectively reveal the change of electrical performance of the high-speed EMUs, the coupling system has a good anti interference performance and robustness.
A Portable Potentiostat for Three-Electrode Electrochemical Sensor
Authors: Ning Z H , Huang J Q , Guo S X , Wang L H
Published: June 2020

This article reports a portable potentiostat based on a three-electrode electrochemical measurement system, which can be powered and communicated through the OTG interface of a smartphone. The system includes the design of the board-level potentiostat circuit, the generation of excitation in common forms required in electrochemical reactions, and the design of signal capture and analysis circuits. The potentiostat applies the positive and negative step-shaped excitations generated by the excitation generating circuit between the working electrode and the reference electrode stably. Through special excitation methods, the stripping current measured by the working electrode is consistent with that of a large electrochemical workstation. By simulating the classical three-electrode electrochemical solution environment impedance model, the constant potential error of the potentiostat was finally tested to be below 30mV through the detection circuit.
Finite element analysis and optimization design for automobile interior door-handle
Authors: Zhang Enguang , Wang Li
Published: June 2020

This paper used NX8.0 to perform parametrization design, motion simulation, finite element analysis, fatigue life analysis and optimization design on the automobile interior doorhandle. Load Transfer Method and Single Body Method were used to analyze the Maximum stress of door-handle. The mechanical properties before and after optimization were compared. Results showed that the maximum stress was reduced by 12.65%, the fatigue life is 3.62E+007 Duty Cycles, and fatigue life met design requirements. All processes were completed under the same software, which ensured the data consistency and improved design efficiency.
Design and Application of Cigarette Maker’s Online Inspection System for Cigarette Appearance
Authors: Lihong Zhang , Yuliang Li , Shuai Yang , Qiang Zhu , Lifeng Fan , Ming Li , Yajuan Zhuang , Junjie Zhang
Published: June 2020

In order to solve the problem that the continuous appearance inspection of the online product of the single-piece can not be carried out during the process, the online appearance inspection system of the cigarette-making unit was designed according to the running characteristics of the machine. The device is mainly composed of a camera control unit, a light source control unit, a signal processing unit and a data communication unit. The system first obtains the cigarette machine production status and single cigarette segmentation signals of continuous cigarettes through an axis encoder. The light source control unit and camera control unit work together to obtain images of a single cigarette at different stations, and perform realtime calculation and integration through the signal processing unit. After the shaft encoder, the processed signal is aligned with the cigarette, and finally the rejection is performed through the rejection valve. The ZJ17 rolling unit and cigarette products with a diameter of 5.4mm, a total length of 84mm, a cigarette length of 54mm, and a filter length of 30mm were tested. The results showed that the online appearance inspection system of the cigarette unit of the rolling unit had a detection accuracy rate of ⩾ 98%, missed rejection rate ⩽ 2%, false rejection rate ⩽ 2%. The device realizes the continuous detection of the appearance of the single product of the spliced product online, and opens up new ideas for the quality assurance of the appearance of the spliced product.