bluuebunny/crossref_metadata_2025_split huggingface dataset:
Total ionizing dose effects on data retention characteristics of 55nm SONOS flash
Authors: Guo Xuanchen , Yue Suge , Li Jiancheng , Zhou Tao , Zha Qichao 
Published: August 2021

Abstract
This paper researched on the effect of different bias conditions on the data retention characteristics of 55nm SONOS flash at a high total dose of 200 Krad(Si). The results show that the degradation of SONOS flash data retention characteristics is the most serious under static bias condition. And the data error rate is positively correlated with read frequency. But overall, the total ionizing dose (TID) has little effect on the data retention characteristics of SONOS flash.
State estimation based on least square support vector
Authors: Li Jiabo , Ye Min , Gao Kangping , Wei Meng , Jiao Shengjie 
Published: August 2021

Abstract
As one of the important parameters of battery management system (BMS), accurate estimation of the state of charge (SOC) of lithium-ion battery (LIB) can ensure the safety of electric vehicles and improve the utilization rate of batteries. A new SOC estimation algorithm based LSSVM is applied. The battery parameters, including current and voltage, which are used as the inputs to estimate SOC. To promote the accuracy of SOC estimation, the SOC estimated at the previous time is taken as the feedback vector to estimate the SOC at the current time. The experimental results show that the proposed model can improve the estimation accuracy of SOC.
Design of intelligent supervision system for metrology center based on UWB technology
Authors: Wei Lei , Yu Jian , Zhao Xingwang , Pan Wei 
Published: August 2021

Abstract
With the comprehensive construction of the provincial metrology center, further digital management requirements are put forward for the daily operation and maintenance inspection work of the automated verification/testing area, the warehouse storage area, the material supporting turnover area and the temporary storage area, and the professional laboratory area. The article explains the UWB (ultra-wide band) technology and its principles and applies it to the smart supervision of the production area. It has developed functions such as basic information management, job attendance, positioning analysis, electronic fence, behavior monitoring, intelligent inspection and data analysis. The digital supervision plan has been verified in the actual production environment.
Research on reliability evaluation method of protection system based on Kaplan-Meier and GO method
Authors: Wang Ting , Chen Kun , Zhang Yanxia , Zhang Kanjun , Du Zhen’an , Xiao Fang 
Published: August 2021

Abstract
In the reliability analysis of the traditional substation protection system, methods such as minimum path set method, fault tree method and Markov method are mostly used. These three methods have disadvantages such as large amount of calculation and strong subjectivity in the application process. Based on the shortcomings of traditional reliability analysis methods, this paper proposes a protection system reliability evaluation method based on survival analysis plus GO method. In view of the problem of timing truncation of the failure data of the protection system and the different time of operation of the protection device, the survival analysis (Kaplan-Meier) method is used to estimate the reliability of the equipment in different time periods, and the GO method is combined to obtain the GO graph of the protection system and GO operation, and then get the reliability of the entire protection system. The results show that the method can quantitatively calculate the reliability of the relay protection system, has the advantages of simplicity, intuitiveness, and easy computer programming. It can be used to analyse the reliability of the relay protection system and guide the design, operation and maintenance of the substation.
A vision based method for humping detection in high-speed laser welding
Authors: Xue Boce , Chang Baohua , Du Dong 
Published: August 2021

Abstract
In this paper a vision based detection method for humping in high-speed laser welding is proposed. A high-speed imaging system is used to capture the images of melt pool in the near-infrared range and the unaffected melt pool region is extracted as the ROI (region of interest) according to the structure of images. The occurrence of humping and positions of humps are determined according to the geometric characteristics of the melt pool in the ROI. Experimental results indicate that the proposed method can detect positions of humps when humping occurs and can also avoid false detection when no humping occurs. The potential of the proposed method is demonstrated for humping control.
Numerical study of a hybrid mode-locked erbium-doped fluoride fiber laser at 2.8 μm
Authors: Luo Meizhen , Tang Pinghua , Ji Haining , Liu Bin , Peng Jie , Tan Chao , Mao Yuliang 
Published: August 2021

Abstract
We numerically investigate a hybrid mode-locked erbium-doped fluoride fiber laser in the mid-infrared region. Based on the coaction of nonlinear polarization rotation (NPR) and semiconductor saturable absorber mirror (SESAM), uniform mode-locked soliton pulse with 155 fs pulse duration, 14.78 kW peak power, and 2.29 nJ pulse energy can be achieved. For comparison, the single SESAM mode-locking and NPR mode-locking of the erbium-doped fluoride fiber laser are simulated, respectively. The effect of all kinds of parameters including gain fiber length, saturable energy of the gain fiber, linear cavity phase delay bias, and small-signal gain on the hybrid mode-locking laser are also investigated.
Tugboat scheduling problem in large container ports: A case study of the Singapore port
Authors: Yu Haocheng 
Published: August 2021

Abstract
In recent years, more and more container ports have become congested because of the large number of visiting ships to the ports. This causes a difficult dispatching and management problem for port operators, that is, the tugboat scheduling problem. To solve the problem effectively from the operational viewpoint, this study proposes an interesting tugboat scheduling problem in a large container port. A mixed-integer linear programming (MILP) model is built for the problem with the objective function of minimizing the total processing cost for container ships. We also consider the constraints of horsepower limitation of tugboats, utilization time limit of tugboats, etc. By using the commercial solver CPLEX to solve the built MILP model in a case study of the Singapore Port, the efficiency of the MILP model is presented. It takes less than 18 hours to reduce the optimality gap to a maximum of 0.9% for solving a real-size instance with 12 tugboats and 100 ships. Moreover, the results of extensive computational experiments also show the applicability and effectiveness of the MILP model to handle real-world tugging operations.
A case study of intelligent manufacturing for key components of vehicles
Authors: Liu Xiaogang , Sun Xinrong , Xu Jinli 
Published: August 2021

Abstract
Currently, most research on intelligent manufacturing stays at the theoretical stage, which can enhance the understanding of smart factory concepts, but it is still difficult to establish a clear strategy for the industry. In this research, cyber-physical system (CPS) is applied to connect the manufacturing equipment of the production system, so as to develop the internet of things (IoT) object layer. Furthermore, a smart factory framework consisting of IoT object layer, CPS network layer, and CPS service layer is developed, connecting the smart shop-floor and the cloud service platform through the industrial network so as to implement the integration of physical manufacturing and virtual manufacturing. This framework is applied in the production of vehicle components, and the results show that the application of this framework in an actual automobile chassis smart factory can greatly improve production efficiency and energy efficiency, reduce enterprise costs, and shorten product development cycles, accelerating the process of enterprise transformation to informatization, digitalization, and intelligence. Since this framework for intelligent manufacturing has been verified under actual conditions, it can be taken as a reference for further development of the framework for intelligent manufacturing.
A simple and effective assembly sequence design method
Authors: Shao Chao , Zhou Yuanzi , Zhang Qiang , Tang Yuhang , Jiang Jun 
Published: August 2021

Abstract
Assembly sequence design is a very complex problem in military enterprises due to the particularity of the military industry and the batch production. This paper proposed a method based on the existing expert knowledge and experience used to plan the assembly sequence. The method of assembly sequence design method is quantitative calculated based on five indexes, including assembly element benchmark index, assembly adjacency index, assembly process complexity index, assembly accuracy index, symmetry index of assembly primitives. And then construct geometric interference matrix to analyze the geometric feasibility of the assembly sequence. Finally, the procedure of assembly process sequence planning of flat-plate fuze is taken as an example to verify the effectiveness of this method. This method is suitable for the assemblies with less number of parts. It has been proved that this method based on the existing expert knowledge and experience, can quickly plan the assembly process sequence of parts.
Investigation of preparation and properties of TiCN coatings by reactive plasma spraying
Authors: Qi Wenyan , Fu Siwei , Li Tian , Ye Fang , Guan Sensen , Chen Shaoyu 
Published: August 2021

Abstract
The TiCN coatings were successfully prepared by means of reactive plasma with spraying self-made composite powder prepared from 150°C to 350°C in the paper. Sucrose was used as a carbon source, using the means of Precursor body carbon, sucrose and titanium powder mixing at high temperature after the heat treatment furnace for carbonization. Finally, the titanium powder was wrapped by the carbon, so the composite powder was mixed more uniform and could react more fully. TiCN coatings could not be synthesized with the composite powder prepared the temperatures of 150°C and 250°C, because the sucrose was not carbonized totally and could not carbonize to synthesize TiCN with Ti and N2 in the process of spraying. TiCN coatings were prepared by spraying the composite powder under heat treatment at 350°C and which composed of Ti and C at a ratio of 1:3. The phase compositions, the morphologies, the hardness and the microstructures were analyzed. The results showed that TiCN coating was consisted of TiC0.2N0.8 phase and a few of TiN, the hardness of TiCN coating could reach 1000HV, the friction coefficient is about 0.45, the wear resistance of TiCN coating was lower compared with TiC coating because of the looser structure and the lower hardness.
Intelligent instrument fault diagnosis and prediction system based on digital twin technology
Authors: Gao Dawei , Liu Peng , Jiang Shengqian , Gao Xiyu , Wang Kun , Zhao Anran , Xue Yiming 
Published: August 2021

Abstract
In the context of informatization and intelligent manufacturing systems, digital twin technology provides new technical ideas for intelligent decision-making. Aiming at instruments with high cost and low output, this paper develops low-cost high-efficiency fault diagnosis system to realize rapid feedback and fault of fault diagnosis results. The system includes three layers: data layer, control layer and output layer. In the data layer, this uses MEMS sensors and Zigbee wireless transmission network to construct a data link the physical end and the virtual model. In the control layer, this paper stores the collected twin data through cloud technology, extracts and calls relevant data according to the function module and then maps it to the output layer. In the output layer, this paper constructs a characteristics interpretation system, which divides the test set and training set through the dynamic database, to complete the classifier and results output. The results are fed back to the judgment framework and control layer to evaluate the effects of fault diagnosis and prediction, which provides a new method for model optimization.
A framework for planning and scheduling shop floor logistics via cloud-edge collaboration
Authors: Lei Jingyuan , Hui Jizhuang , Ding Kai , Wu Linlin 
Published: August 2021

Abstract
Under the autonomous production mode, the production and operation process of smart shop-floor is operated by manufacturing units themselves. This paper describes a new framework for the order-driven products processing based on cloud-edge collaboration, in which the production-logistics tasks are planned and scheduled by the manufacturing resources at the bottom of smart shop-floor. The key enabled technologies and roadmap are further pointed out. The core idea of autonomous production mode is the autonomous communication and collaboration through an industrial network between all physical resources during production in a shop-floor. It is intended to serve as a reference for the managers while handling the flexible production organization and management based on the dynamic customer requirements.
New statistics for simultaneously machine incipient fault detection and monotonic degradation assessment
Authors: Hou Bingchang , Chen Yikai , Deng Yanqing , Wang Yuting , Wang Dong 
Published: August 2021

Abstract
Machine condition monitoring (MCM) has become an important tool to avoid sudden machine breakdown and gaining more economic profits. Tasks including early fault detection and monotonic degradation assessment are important in MCM. For the incipient fault detection, statistics such as kurtosis, Gini index are widely utilized, but they cannot give an accurately incipient fault detection time, and many fluctuations may exhibit. For the monotonic degradation assessment, root-mean-square are commonly used, however, it is sensitive to energy, and cannot show distinct degradation tendency in an early fault state. Those drawbacks have limited the development of practical MCM algorithms. To address those issues, this paper proposed four parameterized statistics for simultaneously early fault detection and monotonic degradation assessment. The four parameterized statistics can be health indicators and simplify the MCM algorithms, which can be beneficial to the practical MCM applications.
A data-driven approach for capacity estimation of batteries based on voltage dependent health indicators
Authors: Kong Jinzhen , Liu Jie , Chen Yikai , Wang Dong 
Published: August 2021

Abstract
Battery capacity estimation plays an important role in the normal operation of electric vehicles. In this work, we presented a data-driven approach for capacity estimation of batteries based on voltage dependent health indicators. A difference-based model of discharge voltage and capacity was built. Next, two health indicators are constructed from partial voltage curves, and correlations between capacity and health indicators are investigated. Afterward, the capacity estimation approach based on Gaussian process regression model is expounded. To validate the accuracy of the proposed method, a case study is carried out. Results demonstrate that RMSE and RMSPE of capacity estimation are lower than 1% compared with actual capacity.
Research on CLLLC Resonant Bidirectional DC-DC Converter
Authors: Lei Hou , Huizhuo Ma , Xingyu Chen , Kang Zhang 
Published: August 2021

Abstract
Based on the single-phase full-bridge LLC DC-DC converter, the LC series resonant network is introduced in the secondary side of the high frequency transformer to form the bidirectional CLLLC resonant DC-DC converter. Firstly, the bidirectional CLLLC resonant DC-DC converter was used for mathematical modeling. By extending the description function, the large-signal steady-state model of the converter was obtained, and the DC voltage gain when the DC-DC converter was running forward was deduced. The gain characteristics and frequency characteristics of the model are compared with those of the basic wave equivalent model. Secondly, the small-signal perturbation model of CLLLC DC-DC converter is modeled, and the small-signal perturbation is brought into the large-signal steady-state solution to obtain the transfer function when the CLLLC resonant converter is running forward. Finally, a 20kW CLLLC DC-DC converter is designed, and the simulation analysis is carried out to verify the correctness of the proposed scheme.
Study of the Modeling and Control Strategy for Active Power Filter
Authors: Huizhuo Ma , Lei Hou , Xingyu Chen , Kang Zhang , Fan Tang , Helin Lian 
Published: August 2021

Abstract
Improvement of active power filter’s performance through the reasonable control strategy is becoming a hot research for various counties’ scholars. In this paper, active power filter model is regarded as a starting point and the modeling process has been introduced in detail. For the following characteristics, such as harmonic current detection must be real-time and accurate, active power filter’s uncertainty and nonlinear, the harmonic current detection method which is based on instantaneous reactive power is used. In this way, harmonic current, reactive and negative sequence current in grid can be accurately tested out. The active power filter which is developed according to this current real-time detection algorithm can balance asymmetrical three-phase load. The simulation model is built in MATLAB/simulink. The simulation results show that this active power filter can be more rapid, accurate compensate harmonic current than the conventional active power filter.
Three-dimensional Simulation of Forced Convective Flow and Heat Transfer in Air-Cooled Motor Stator
Authors: Ma Fan , Dong Haihong , Liao Yigang , Wang Chao 
Published: August 2021

Abstract
The reliable prediction of cooling medium velocity and stator temperature distribution is very important for a running motor to ensure the temperature rise of stator below the limit. In this paper, taking the stator ventilation duct of an air-cooled motor as the research object, a 3D physical model including the iron core, the windings, the stator ventilation duct and the main insulation was established. In order to fully reveal the characteristics of forced convective flow and heat transfer in air-cooled motor stator, the fluid field and temperature field were calculated by using finite volume method. The radial and axial distribution characteristics of the fluid field were analyzed deeply. It’s shown that the velocity decreases in the axial direction on the half of the axial plane and varies greatly in the radial direction. The temperature distribution in the main insulation layer of the stator was elaborated emphatically. The temperature of the insulation material along the length of the slot and the temperature difference between inner and outer insulation were discussed in detail. Based on the experimental results, the reliability of the calculation method was evaluated and the relative error is within 15%.
An Efficient FHE Radix-2 Addition Algorithm in BGV Scheme
Authors: Hou Zongsheng , Zhang Neng , Liu Leibo 
Published: August 2021

Abstract
Fully homomorphic encryption (FHE) is a novel encryption method that can perform operations on encrypted data. The performance of applications based on FHE is still low due to the high computational complexity of operations on the ciphertext. In this paper, we proposed an efficient FHE radix-2 addition algorithm in BGV scheme, called Optimized Cheon’s SIMD Adder. It is an optimization of Cheon’s SIMD Adder. The proposed adder uses the previously calculated results as much as possible to calculate the new result, so that it can keep the circuit depth as 0(log(μ)) and reduce the number of homomorphic multiplications. We also compared the weighted computational complexity (WCC) between this work and Cheon’s. The WCC of this work is only O (μ), while Cheon’s is 0(μ· log (μ)). At the end of the paper, we implemented the proposed addition, which improves the calculation speedup by 1.3 ~ 1.4 times for 8 ~ 512- bit adders compared with Cheon’s SIMD Adder.
A New Radar-Embedded Communication Waveform with Low Computational Complexity
Authors: Zhang Chengan , Li Baoguo , Du Zhiyi 
Published: August 2021

Abstract
Radar-Embedded Communication (REC) is a covert communication technology that utilizes a radio frequency (RF) tag or transponder to embed the communication signal into the radar backscatter. The RF tag must be triggered by the radar signal and quickly generate the required communication waveforms so as to ensure that these communication symbols can be timely and effectively embedded in the radar backscatter pulse. Such an operation poses a great challenge to the response speed of the tag transponder. The traditional method is based on multiple eigenvalue decompositions to generate quasi-orthogonal communication waveforms, which requires a large amount of calculation. This paper proposes a strategy that requires only one eigenvalue decomposition operation. However, such a strategy makes it possible to generate completely orthogonal communication waveforms, and at the same time, it will contribute to a great reduction in the computational pressure of the RF tag. In addition, by simulation analyses, the communication waveform design strategy proposed in this paper does not take the reliability and the low probability of interception (LPI) of the waveform as the cost. On the contrary, under some conditions, communication reliability and LPI characteristics can be improved.
Improved Chinese Short Text Classification Method Based on ERNIE_BiGRU Model
Authors: Cheng Xue , Zhang Chen , Li Qingxu 
Published: August 2021

Abstract
This paper is aimed at traditional word embedding models and Bidirectional Encoder Representations from Transformers (BERT) that cannot learn text semantic knowledge, as well as convolutional neural network (CNN) and Bidirectional long short-term memory (BiLSTM) unable to distinguish the importance of words, proposing an improved Chinese short text classification method based on ERNIE_BiGRU model. Firstly, learning text knowledge and information through the Enhanced Representation through Knowledge Integration (ERNIE) enhances the model’s semantic representation capabilities. Secondly, considering that CNN can only extract local features of the text while ignoring the semantic relevance between contextual information, and the Bidirectional Gating Recurrent Unit (BiGRU) is simpler, has fewer network parameters and faster calculation speed than the BiLSTM, the combination of CNN and BiGRU enables the model to capture both local phrase-level features and contextual structure information. Finally, according to the importance of features, the attention mechanism is used to assign different weights to improve the classification effect of the model. The experimental results show that the ERNIE_CNN_BiGRU_Attention (ECBA) model used in this paper has achieved good results in the task of Chinese short text classification.