Special Column-Deep Learning and Image Recognization

Chinese seal recognition method based on flood filling algorithm

DOI:10.16157/j.issn.0258-7998.223130

Author:Zhang Xiang1,Qin Yi1,Dong Zhicheng2,Huang Qilin1,Li Jie1

Author Affilications:1.School of Intelligent Technology and Engineering,Chongqing University of Science and Technology,Chongqing 401331,China; 2.School of Information Science and Technology,Tibet University,Lhasa 850000,China

Abstract:Seal recognition is an indispensable part of the intelligent office. The current stage of seal recognition method is to directly input the scanned electronic documents into the neural network model for identification, facing the problems of unable to accurately locate the position of the seal, low accuracy of bending text recognition. Aiming at the above problems, this paper proposes an efficient stamp text recognition method, which uses the diffuse water filling algorithm to process the grayscale image for seal image feature enhancement, which ensures the accuracy of Chinese seal detection, and introduces the polar coordinate conversion operation to ensure the integrity of text features. In order to evaluate the effectiveness of the proposed method, multiple sets of comparative experiments were carried out in the existing and other network models. Experimental results show that the existing network model fused the text features extracted by the method shows excellent recognition results.
Key word:
flooded fill
feature enhancements
seal image excision
seal text recognition

Ultrasonic classification of hepatic cystic echinococcosis based on Swin Transformer

DOI:10.16157/j.issn.0258-7998.223118

Author:Renaguli·Aihemaitiniyazi1,Miwueryiti·Hailati1,Wang Zhengye1,Yeerxiati·Duolikong2,Yan Chuanbo2

Author Affilications:1.College of Public Health,Xinjiang Medical University,Urumqi 830011,China; 2.College of Medical Engineering Technology,Xinjiang Medical University,Urumqi 830011,China

Abstract:In order to improve the screening and diagnosis efficiency of hepatic hydatid disease, and make up for the shortage of medical resources in some areas, this paper proposes an intelligent typing method of hepatic hydatid disease based on Swin Transformer, which combines the convolution attention mechanism model, and realizes the automatic classification of five types of cystic hydatid disease by learning the whole and local details of images. In order to verify the superiority of the model, the prediction model proposed in this paper is compared with common classification models. The results show that the classification accuracy based on the improved Swin Transformer model can reach 92.6% on the test set. The experimental results show that compared with other algorithms, the improved Swin Transformer network can better classify the ultrasonic images of hepatic cystic echinococcosis, and this method can be extended to other medical applications.
Key word:
deep learning
image classification
hepatic cystic echinococcosis
ultrasonic image
transfer learning

Research on defogging method of license plate image based on improved dark channel prior

DOI:10.16157/j.issn.0258-7998.223211

Author:Shi Dongyang1,Zhang Junlin1,Jia Bing1,Nie Ling1,Yang Huimin2

Author Affilications:1.School of Electrical Engineering,Chongqing University of Science and Technology,Chongqing 401331,China; 2.School of Mathematics and Computing Science,Xiangtan University,Xiangtan 411105,China

Abstract:Aiming at the problem of poor recognition accuracy of license plate recognition system in haze scene, an improved license plate recognition model is proposed. The model uses the improved dark channel apriori defogging algorithm for defogging. Considering the color distortion and other problems when the original defogging algorithm processes the haze image with bright areas, firstly, the atmospheric light value is limited by the threshold value. Secondly, the introduction factor is optimized. And finally, the tolerance mechanism is introduced to correct the transmittance, and the image brightness is adjusted to improve the image visualization effect. The simulation results show that the performance of PSNR, SSIM, enterprise and e improved by 1.934 dB, 0.082, 0.235 and 38.995 respectively. The recognition test of the license plate image before and after defogging shows that the recognition accuracy of the license plate is improved by 22%, which proves the superiority of the proposed model.
Key word:
license plate recognition
color distortion
threshold limit
introducing factors
tolerance mechanism

Small object detection algorithm based on involution prediction head

DOI:10.16157/j.issn.0258-7998.223161

Author:An Henan1,Deng Wucai1,Guan Cong2,Jiang Bangyan2

Author Affilications:1.College of Electronics and Information Engineering,Shenzhen University,Shenzhen 518000,China; 2.Institute of Microscale Optoelectronics,Shenzhen University,Shenzhen 518000,China

Abstract:Aiming at the problems of false positive detection and low recall in the detection of small targets by the general target detection algorithm, a small target detection algorithm IPH(involution prediction head) is proposed, which is applied to the detection head of YOLOv4 and YOLOv5. The experimental results on the VOC2007 data set show that the detection accuracy APs(AP for small objects) of YOLOv4 after using IPH is improved by 1.1% compared with the original algorithm, and the APs on YOLOv5 is improved by 5.9%. Through further verification of the intelligent traffic detection data set, IPH algorithm and desampling can effectively improve the accuracy of small object detection and reduce false positive detection and missed detection.
Key word:
YOLOv4
involution prediction head
small object detection
feature extraction
attention module

MSA-YOLO oil storage tank target detection for remote sensing images

DOI:10.16157/j.issn.0258-7998.223191

Author:Li Xiang1,2,Te Rigen1,2,Zhao Yuheng1,2,Chen Wentao1,2,Xu Guocheng3

Author Affilications:1.Chang Guang Satellite Technology Co.,Ltd.,Changchun 130000,China; 2.Main Laboratory of Satellite Remote Sensing Technology of Jilin Province,Changchun 130000,China; 3.School of Materials Science and Engineering,Jilin University,Changchun 130000,China

Abstract:Crude oil, as an important strategic material, plays an important role in many fields such as my country′s economy and military. This paper proposes an algorithm MSA-YOLO(MultiScale Adaptive YOLO), which is optimized on the basis of the YOLOv4 algorithm, and is experimented based on the remote sensing image dataset mainly based on Jilin-1 optical remote sensing satellite images,to make identification and classification of oil storage tanks. The algorithm optimization contents include: in order to simplify the oil storage tank monitoring model and ensure the efficiency of the model, prune the multi-scale identification module in the network structure of YOLOv4; use the k-means++ clustering algorithm to select the initial anchor frame to accelerate the convergence of the model;use CIoU-NMS-based optimization to further improve inference speed and accuracy. The experimental results show that compared with YOLOv4, the number of parameters of MSA-YOLO model is reduced by 25.84%; the model size is reduced by 62.13%; in the GPU environment of Tesla V100, the training speed of the model is increased by 6 s/epoch, and the inference speed is increased by 15.76 F/s; the average accuracy is 95.65%. At the same time, the MSA-YOLO algorithm shows more efficient characteristics in the comparative experiments of various general target recognition algorithms. The MSA-YOLO algorithm has universal feasibility for accurate and real-time identification of oil storage tanks, and can provide technical reference for remote sensing data in the field of energy futures.
Key word:
computer vision
target recognition
deep learning
YOLO
sorage tank detection

Review and Comment

Technologies and industry trends of intelligent computing chips and suggestions for Beijing

DOI:10.16157/j.issn.0258-7998.222728

Author:Zhu Jing1,2

Author Affilications:1.Beijing International Engineering Consulting Company,Beijing 100055,China; 2.Beijing Semiconductor Industry Association,Beijing 100191,China

Abstract:Intelligent computing chips are hardware carriers that process massive amounts of data and reflect computing capabilities, and are an important support for productivity in the digital economy era. With the large-scale application of new-generation information technologies such as artificial intelligence, 5G, big data, and blockchain, the demand for computing resources in the digital transformation of the industry and the upgrading of industrial intelligence has increased exponentially. In addition, the development of integrated circuits has entered the post-Moore era, and the bottleneck caused by the defects of the current computing architecture(Von Neumann architecture) has become more and more prominent, and the development has been seriously challenged. The integrated computing architecture, new computing paradigms, and new computing devices based on new materials and new processes that meet diverse computing needs have also entered a stage of active innovation, and intelligent computing chips have ushered in a golden age of rapid development. This paper comprehensively analyzes the strategic importance of intelligent computing chips in the digital economy era, the development paths and trends of domestic and foreign technologies, and sorts out the main industrial patterns and development opportunities of intelligent computing at home and abroad.
Key word:
integrated circuit
intelligent computing
computing architecture
key emerging technologies
digital economy

Review and prospect of smart military camp research

DOI:10.16157/j.issn.0258-7998.222678

Author:Zhang Zhicheng,Zhang Ruiquan,Ma Zhao,Dong Yijie,Wu Chengsheng

Author Affilications:National Computer System Engineering Research Institute of China,Beijing 100083,China

Abstract:Firstly, this paper introduces the research background of smart barracks and its importance in the field of national defense. Secondly, combined with the problems and challenges existing in the initial stage of the research and construction of smart barracks, this paper discusses and evaluates the system architecture of smart barracks and the research status and achievements at all levels. Finally, combined with the technical development trend and project construction experience, this paper discusses the future research direction and development trend of smart military camp.
Key word:
smart military camp
research findings
research prospect

Artificial Intelligence

Cross sectional shape prediction of hot rolled strip based on DBN-BP deep neural network

DOI:10.16157/j.issn.0258-7998.223210

Author:Gao Shanfeng,Liu Meihong,Fan Qiuxia

Author Affilications:School of Automation and Software Engineering,Shanxi University,Taiyuan 030006,China

Abstract:With the rapid development of various industrial fields, the market demand for thin specifications, high strength strip products increases rapidly. The cross-section shape of hot rolled strip is the main evaluation index of hot rolled strip product quality. Based on data mining technology, the data in the mill database are analyzed and processed. The data mining technology combines deep belief neural network(DBN) and back propagation(BP) neural network algorithms to construct a prediction model of strip thickness distribution. The DBN-BP algorithm is composed of several restricted Botlzmann machines(RBM) stacked layer by layer, and the weight matrix and bias of the network are obtained by unsupervised layer-by-layer training method for the BP network, while the BP neural network fine-tunes the whole network by means of error back propagation. This method overcomes the disadvantages of BP network falling into local optimum due to random initialization of weight parameters and long training time. Compared with the BP algorithm, the probability of predicting the midpoint thickness error is within ±5.6 μm by the DBN-BP method is 95%, while the prediction error of BP algorithm is within ±11 μm. Through the analysis of the prediction results of the cross-section shape of the strip, it can be seen that the DBN-BP deep learning method has more advantages than the BP algorithm in predicting the edge thickness of the strip.
Key word:
hot rolling
deep learning
strip thickness prediction

Entity alignment based on dynamic graph attention aggregation in multi-hop neighborhood

DOI:10.16157/j.issn.0258-7998.222717

Author:Wang Huansha1,2,Huang Ruiyang1,2,Song Xuhui3,Yu Shiyuan3,Hu Nan3

Author Affilications:1.National Digital Switching System Engineering & Technological R&D Center,Zhengzhou 450002,China; 2.Information Engineering University,Zhengzhou 450002,China;3.Software College,Zhengzhou University,Zhengzhou 450001,China

Abstract:Entity alignment is an important technical method to realize the fusion of knowledge bases from different sources. It is widely used in the fields of knowledge graph and knowledge completion. The existing entity alignment models based on graph attention mostly use static graph attention network and ignore the semantic information in entity attributes, resulting in the problems of limited attention, difficult fitting and insufficient expression ability of the model. To solve these problems, this paper studies the entity alignment method based on the structure modeling of dynamic graph attention. Firstly, the single hop node representation of the target entity is modeled by GCN. Secondly, the multi hop node attention coefficient is obtained and entity modeled by using the dynamic graph attention network, and then the single hop and multi hop node information output by GCN and dynamic graph attention layer is aggregated by layer-wise gating network. Finally, the entity attribute semantic extracted by external knowledge pre training natural language model is embedded and concatenated to calculate similarity. This method has been improved in three types of cross language datasets of DBP15K, which proves the effectiveness of applying dynamic graph attention network and integrating entity attribute semantics in improving entity representation ability.
Key word:
dynamic GAT
graph convolution network
entity alignment
knowledge graph
representation learning

Adaptive tracking algorithm for target based on associated dynamic features

DOI:10.16157/j.issn.0258-7998.212358

Author:Sun Zhicheng1,Dong Yijie2,Hu Ailan2,Zhang Ruiquan2

Author Affilications:1.63861 Troop,Baicheng 137000,China; 2.National Computer System Engineering Research Institute of China,Beijing 100083,China

Abstract:In the complex scene of shooting range test, the test site often involves the changeable natural environment including dust, strong light, occlusion, etc. A single target tracking algorithm associated with dynamic features is proposed to track fast moving targets in this case. Firstly, the gated recurrent unit is used to extract the time series dynamic characteristics of the target which need to be tracked, so as to obtain a set of candidate processing target frames. Then,convolutional network is adopted to extract the depth convolution features of the candidate target frame and determine target position, as well as separating the background convolution features. In the tracking process, the separated background convolution feature map is applied to update network parameters to enhance the robustness and adaptability of network. Experimental results show that the proposed algorithm can adaptively track moving target in the shooting range image acquisition system, which can still maintain excellent robustness and adaptability in the context of complex environment.
Key word:
range test
adaptive tracking
gated recurrent unit
convolutional neural network

Microelectronic Technology

De-skew circuit design for PCIe multi-lane

DOI:10.16157/j.issn.0258-7998.222775

Author:Wang Keyang,Ji Bing,Qu Lingxiang

Author Affilications:China Electronics Technology Group Corporation No.58 Research Institute,Wuxi 214072,China

Abstract:In the process of multi-lane data transmission in PCIe, when the arrival time of data in each lane is inconsistent, the issue of skew will be introduced. In order to ensure that the receiver of each lane can process the received data simultaneously and correctly, it is necessary to preprocess the transmitted data. This paper presents a De-skew logic circuit, which explains how to use synchronous FIFO to realize multi-lane De-skew and complete the corresponding logic design. UVM and VIP technology are used to build a verification platform, the test results verify the correctness and feasibility of the design.Compared with other common solutions, the logic design has comprehensiveness, advantages and reusability.
Key word:
PCIe
De-skew
mult-lane
FIFO

Design of operational amplifier based on signal conditioning chip

DOI:10.16157/j.issn.0258-7998.222743

Author:He Guikun1,Ma Kui1,2,Yang Fashun1,2

Author Affilications:1.College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China; 2.Key Laboratory of Micro-Nano-Electronics of Guizhou Province,Guiyang 550025,China

Abstract:Based on the domestic 40 V bipolar process, a fully differential operational amplifier is designed, which is applied to the driver module of the signal conditioning chip. The amplitude of the output signal of the operational amplifier can be adjusted by an external resistor. The overall circuit structure includes input stage, intermediate stage, output stage, bias circuit, feedback circuit and reference circuit. The input stage adopts a common base amplifier circuit, which has a wide operating frequency band; the intermediate stage adopts a common collector-common emitter circuit structure to improve the voltage gain; the power output stage constitutes a loop integrator and a resistor network that provides common mode feedback, so that the output common mode voltage is concentrated between the positive and negative power supplies, and the output signal amplitude can be adjusted by an external amplitude control resistor. When the power supply voltage is ±15 V, the test results are:the output voltage amplitude range is 1.488 V~18.57 V, the DC offset voltage is -169 mV, the output short-circuit current is 65 mA,and the total harmonic distortion is 41.2 dB.
Key word:
operational amplifier
bipolar
all the difference
amplitude

Measurement Control Technology and Instruments

The application of edge computing in user electric energy data acquire system

DOI:10.16157/j.issn.0258-7998.222645

Author:Huang Junwei,Tao Gongping,Song Guozhuang

Author Affilications:School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications, Chongqing 400065,China

Abstract:With the increasingly close communication between power enterprises and users, the scale of user power information collection is increasing, the types of data collection are increasing, and the requirements for data collection frequency are higher. At present, the research on user power information acquisition system is mostly to optimize the system architecture, and there is little research on the acquisition method. This paper proposes a fast meter reading method based on edge computing, which sinks the computing power and data storage resources to the location close to the data source, and provides low delay and efficient acquisition for the terminal equipment nearby. Compared with the time cost and reliability of traditional meter reading methods, the experimental results show that marginalizing the aggregated data improves the acquisition rate and success rate of intensive user power information.
Key word:
edge computing
user electric energy data acquire
fast meter reading

The rapid construction of space system based on matrix software library

DOI:10.16157/j.issn.0258-7998.222662

Author:Li Ganhua1,2,Fan Henghai1,2,Dong Li1,2,Tai Nengjian1,2

Author Affilications:1.State Key Laboratory of Astronautic Dynamics,Xi′an 710043,China; 2.Xi′an Satellite Control Center,Xi′an 710043,China

Abstract:This paper presented a fast custom made method based on multi-dimensional matrix type software library for the multi-model software construction of space data process center. Firstly, the architecture is introduced for the space data process center system, that is multi-layer and multi-state complex structure satisfied with cloud computation. Secondly, the deployment mode of micro module room is introduced adapt to the computer hardware of the space data process center. And the structure of the system is presented to divide the operation with the operation place, to divide the software management with hardware management. At last, a matrix type dynamic custom software library is presented, which could construct the new application flexibly and customizably, load and unload the satellite management system mirror file quickly. And the process flow of the operation is also introduced for quick generation and management. This method satisfied with the multi-series and the multi-satellite mission requirement of space data process center. The system development cost is reduced effectively and efficiently. And the system operation and maintenance are reduced obviously.
Key word:
complex system
software pipeline
space data center
software library

Communication and Network

Signal detection based on SDNSR-Net deep network for massive MIMO systems

DOI:10.16157/j.issn.0258-7998.222520

Author:Zeng Xiangzhi,Shen Bin,Yang Jian

Author Affilications:School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications, Chongqing 400065,China

Abstract:Massive multiple-input multiple-output(MIMO) systems can effectively improve the spectrum efficiency. When the antenna scale gradually tends to infinity, the minimum mean square error(MMSE) detection algorithm can achieve near-optimal detection performance. However, due to the matrix inversion required in the algorithm, which brings extremely high computational complexity, it is difficult to implement in a massive MIMO system. The Richardson algorithm can achieve the detection performance of the MMSE algorithm in an iterative form without matrix inversion, but the algorithm is greatly affected by its relaxation parameters. In the Richardson algorithm combined with the steepest gradient descent algorithm (SDNSR), the error of the relaxation parameter can be compensated by the gradient descent algorithm, but the computational complexity is increased. This paper firstly uses the idea of deep expansion to map the iterative process of SDNSR to a deep detection network (SDNSR-Net); then, by modifying the network structure and adding trainable parameters,the computational complexity is reduced and the detection accuracy is improved. The experimental results show that SDNSR-Net is superior to other typical detection algorithms in the case of different signal-to-noise ratios and antenna configurations in the uplink massive MIMO system and can be used as an effective detection scheme in practice.
Key word:
massive MIMO system
signal detection
modern driven
deep learning

Modulation recognition method based on fusion of numerical features and image features

DOI:10.16157/j.issn.0258-7998.222686

Author:Qian Lei1,2,Wu Hao1,Zhang Tao1,Zhang Jiang1

Author Affilications:1.The 63rd Research Institute of National University of Defense Technology,Nanjing 210007,China; 2.School of Electronic Science,National University of Defense Technology,Changsha 410073,China

Abstract:In order to solve the problem of low recognition rate of phase shift keying and quadrature amplitude modulation signals when using time-frequency image classification under the condition of low signal-to-noise ratio, this paper proposes a method of signal feature fusion. Firstly, the method calculates the high-order cumulant of the received signal and obtains the one-dimensional numerical eigenvector. Then, the time-frequency diagram of the received signal is obtained by time-frequency analysis, and the one-dimensional image feature vector is extracted by convolution neural network. The two kinds of feature vectors are connected to obtain one-dimensional fusion feature vector. Finally, the fused feature vector is input into the full connection layer and the classification results are output. The simulation results show that under the condition of about 1 dB, the recognition rate of phase shift keying and quadrature amplitude modulation signals can be improved by about 10%~30% compared with the method of single image feature.
Key word:
modulation recognition
high-order cumulant
time-frequency analysis
feature fusion

Research on automatic planning method of TTE network communication link

DOI:10.16157/j.issn.0258-7998.222735

Author:Zheng Xiaopeng1,Zhang Tao2,Wang Xiaohui1

Author Affilications:1.R&D Department China Academy of Launch Vehicle Technology,Beijing 100076,China; 2.School of Software,Northwestern Polytechnical University,Xi′an 710072,China

Abstract:To address the problems of message scheduling and link planning in TTE networks, which rely on manual configuration and are difficult to afford large network structures, a simulation study of the communication link planning method for TTE networks is conducted, and a link planning model is constructed to find the solution to the problem by a new heuristic algorithm, the brainstorming algorithm. Through experimental simulation comparison, the effectiveness of the brainstorming optimization algorithm and its more stable execution than genetic algorithm in the late planning stage are verified, which improves the network transmission efficiency and has a very wide application prospect.
Key word:
time triggered Ethernet
load balancing
heuristic algorithm
genetic algorithm
brainstorming algorithm

Computer Technology and Its Applications

Millimeter wave hidden object detection algorithm based on visual saliency

DOI:10.16157/j.issn.0258-7998.212492

Author:Zhang Keshen,Guo Wenfeng,Wang Hepeng,Ye Xueyi

Author Affilications:School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China

Abstract:In order to solve the problem that the gray level difference between hidden objects and human body in millimeter wave image is small and the shape is changeable, a hidden object detection algorithm based on visual saliency is proposed. After bilateral filtering, combined with OTSU and morphological operation,the algorithm completes the pretreatment to obtain the human body region. And then the foreground is located based on the significance calculation in the frequency domain. After background suppression,the significance map is generated,so the detection is completed. Experimental results show that compared with the typical active millimeter wave imaging detection algorithm, the detection rate of the proposed algorithm increases by 5.87% and 9.08%, respectively, and the proposed algorithm has better detection performance.
Key word:
hidden object
visual salience
image signature
threshold segmentation

Digital control time-delays affected controller design of UPS inverter

DOI:10.16157/j.issn.0258-7998.212483

Author:Rao Gang,Wang Guorui

Author Affilications:1.Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Wuhan University of Science and Technology, Wuhan 430081,China; 2.Precision Manufacturing Institute,Wuhan University of Science and Technology,Wuhan 430081,China

Abstract:In order to accurately design control system of the uninterruptible power supply(UPS) inverter, impact of the delay induced by digital control on the inverter performances is analyzed, and the design method of the inverter system controller considering the delay link is proposed. The mathematical model of the inverter system is established based on the state space averaging method, and the influence of the control delay link on the system stability is analyzed. Aiming at the single-phase UPS inverter power supply, the digital PID double-loop control technology is applied, and a single-phase UPS inverter control algorithm with easy parameter setting is obtained. The generalized Z-transformation theory is introduced to describe the delay link of digital control, and the model of the control system is improved. The modified design method of the digital PID controller parameters considering the delay link is given. Finally, experimental verification is carried out by MATLAB/Simulink simulation and experiment. The experimental results show that the output voltage regulation accuracy of the UPS inverter control system based on the digital PID is less than 1%, and the THD(total harmonic distortion) is less than 2%. When the load end changes suddenly, the time for the system to return to normal is about 1.2 ms. The steady-state performance and dynamic response performance of the inverter system output are effectively improved.
Key word:
digital control
inverter
delay
digital PI
generalized Z transform

Design and implementation of TT&C center system based on integrated cloud architecture

DOI:10.16157/j.issn.0258-7998.222552

Author:Shang Huiping,Chen Yang,Tang Peirong

Author Affilications:Beijing Institute of Tracking,Telecommunications and Technology,Beijing 100094,China

Abstract:As an important part of aerospace mission engineering, the tracking, telemetry and command(TT&C) center system currently adopts technologies such as duplexing, server clusters, disk redundancy, data backup and recovery to ensure the uninterrupted operation, stability and reliability of the aerospace mission system. But there are also such problems such as software and hardware tight-coupling, low resource sharing efficiency, and poor system expansion capabilities, all of which limit the development of the entire aerospace TT&C system. Regarding these problems, in this paper a TT&C center system based on integrated cloud architecture is studied and designed. The system is implemented on-demand customization of services, resource sharing and interoperability, and flexible expansion. Moreover the system is verified by actual aerospace missions.
Key word:
tracking,telemetry and command center
cloud computing
virtualization
services
computing resources

Research on log signal denoising based on PSO optimized wavelet transform

DOI:10.16157/j.issn.0258-7998.223028

Author:Wei Zhenhua1,2,3,Xu Yuefeng2,Liu Zhifeng1,2,3,Shu Zhihao2

Author Affilications:1.Engineering Research Center of Nuclear Technology Application(East China University of Technology), Ministry of Education,Nanchang 330013,China; 2.School of Information Engineering,East China University of Technology,Nanchang 330013,China; 3.Jiangxi Provincial Engineering Laboratory of Radiology Big Data Technology,Nanchang 330013,China

Abstract:Wavelet transform is widely used in the research of logging signal denoising, and the selection of wavelet parameters directly affects the final denoising effect, so it is necessary to design an algorithm to obtain the best wavelet transform parameters of logging signal. In this paper, the random inertia weight strategy is innovatively proposed to change the weight parameters of particle swarm optimization algorithm, which improves the convergence speed of particle swarm optimization algorithm, enhances the ability of searching for optimization, and obtains the optimal wavelet transform parameters. The optimal wavelet transform parameters are applied to the wavelet denoising of soft threshold method, which can effectively separate the useful signal and useless noise. This algorithm can effectively improve the signal-to-noise ratio of logging signal, reduce the root mean square difference, and realize the effective removal of noise in logging signal.
Key word:
logging signal denoising
particle swarm optimization
the wavelet parameters
wavelet transform denoising
soft threshold method

General data processing method and application of space launch command and monitoring system

DOI:10.16157/j.issn.0258-7998.212276

Author:Zhou Gan,Liu Guichong,Shen Zhanyu,Zhou Yu

Author Affilications:National Computer System Engineering Research Institute of China,Beijing 100083,China

Abstract:With the increasing frequency of space launch missions, constant application of new spacecraft and tracking and control equipment, and the urgent demand of multi-level integrated command, it puts forward higher universality and adaptability requirements for space launch command and monitoring system. In order to solve these problems, this paper proposes a novel flexibility data processing method of command and monitoring system. By defining protocol model and topic model in off-line mode, this method realizes the map of the internal and external communication protocol. On the other hand, the component methodology is adopted to accomplish the receiving, parsing, storing, and transmitting operation of external data in online mode. The experimental results show that this method successfully decouples the processing logic and data protocol by using the definition of various models, achieves the flexible information exchange for command and monitoring data without revising the software architecture, and sharply improves the preparation efficiency of the command and monitoring system for space launch missions.
Key word:
space launch
command and monitoring
general
protocol model
topic model

Circuits and Systems

Intelligent storage measurement system of multiple continuous shock wave

DOI:10.16157/j.issn.0258-7998.222774

Author:Wang Maokai,Wang Wenlian,Wang Yu

Author Affilications:Key Laboratory of Instrument Science and Dynamic Measurement,Ministry of Education,North University of China, Taiyuan 030051,China

Abstract:An intelligent storage and measurement system of multiple continuous shock waves based on SRAM and Flash is proposed for the complex environment of continuous experiment of combat. The system uses FPGA as the core controller and the multi-channel intelligent storage of continuous shock wave is realized by using acquisition and storage technology combined with signal trigger identification and marking. The signal conditioning of 4 piezoresistive sensors realizes the automatic adjustment of the baseline, which ensures the flexibility and applicability of the system. Partition storage management of SRAM and pipeline storage of Flash realize the fast storage of data under multi-channel and multi-trigger times.The experimental result indicates that the proposed distributed measurement system can realize the intelligent storage of signals under 4 channels, 1 MS/s sampling rate and 32 consecutive triggers, and can be applied to the continuous explosion shock wave measurement in experiment of combat.
Key word:
shock wave
acquisition and storage
signal conditioning
continuous trigger
intelligent storage

Deep Learning and Image Recognization

6G Microwave Millimeter-wave Technology

Radar Processing Technology and Evaluation

Space-Ground Integrated Technology

Industrial Ethernet Network

5G Vertical Industry Application

High Performance Computing

Innovation and Application of PKS System

FPGA and Artificial Intelligence

Key Technologies for 6G

5G Network Construction and Optimization

RF and Microwave

Edge Computing

Network and Business Requirements for 6G

5G and Intelligent Transportation

5G R16 Core Network Evolution Technology

Satellite Nevigation Technology

5G R16 Evolution Technology

5G Wireless Network Evolution Technology

5G Network Planning Technology

5G Indoor Coverage Technology

5G MEC and Its Applications

5G Co-construction and Sharing Technology

Expert Forum

5G and Emergency Communication

5G Slicing Technology and Its Applications

Industrial Internet

5G Terminal Key Realization Technology

5G and Artificial Intelligence

5G and Internet of Vehicles

Terahertz Technology and Its Application

Signal and Information Processing

Artificial Intelligence

5G Communication

Internet of Things and the Industrial Big Data

Electronic Techniques of UAV System

Power Electronic Technology

Medical Electronics

Aerospace Electronic Technology

Robot and Industrial Automation

ADAS Technique and Its Implementation

Heterogeneous Computing

2016 IEEE International Conference on Integrated Circuits and Microsystems

ARINC859 Bus Technology

FC Network Technology

Measurement and Control Technology of Bus Network

GJB288A Bus

Key Techniques of 5G and Algorthm Implement

IEEE-1394 Bus

Signal Conditioning Technology of Sensors

AFDX Network Technology

Discrete Signal Processing

Energy-Efficient Computing

Motor control

2012 Altera Electronic Design Article Contest