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16篇 您的检索式:作者名="SUI Qingmei"
    题名 作者 年代 出处 被引量
1Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network显示文摘增强的塑料(CFRP ) 组织的碳纤维的一个损坏鉴定系统用纤维布拉格被调查栅栏(FBG ) 传感器和背繁殖(BP ) 神经网络。FBG 传感器被使用构造察觉到的网络检测活跃使活动产生的结构的动态反应信号。损坏鉴定模型基于 BP 神经网络被造。Fourier 变换提取的动态信号特征是输入,并且损坏状态是模型的产量。而且,损坏被把 lumped 群众交给不同重量而不是导致真实损坏模仿,它被证实由有限元素分析(FEA ) 可行。最后,损坏鉴定系统与 300 公里在一个 CFRP 盘子上被验证 ?????????? 偍 ?????????? 瀠? 偍 ??? ‰ ?慐 吗??Xiangyi GENG Shizeng LU Mingshun JIANG Qingmei SUI Shanshan LV Hang XIAO Yuxi JIA Lei JIA 2018Photonic Sensors2018,8,2:9
2Response Analysis of Ultrasonic Sensing System Based on Fiber Bragg Gratings of Different Lengths显示文摘在最近的年里,纤维布拉格栅栏(FBG ) 广泛地为考虑到它超越常规传感器的唯一的优点监视的实际结构的健康在超声的察觉被使用了。尽管 FBG 成功地在超声的检查被测试了, FBG 的敏感上的栅栏长度的效果超声的察觉到系统还有待于被分析。因此用模拟模型,有不同长度栅栏的超声的察觉到系统的敏感上的主要影响因素是首先调查了。在下列实验,有六不同长度 FBG 的察觉到的系统的超声的回答分别地被获得。理论分析和试验性的结果将为察觉到系统的基于 FBG 的超声、声学的排放的敏感改进是有用的。Dandan PANG Qingmei SUI 2014Photonic Sensors2014,4,3:3
3Same Origin Three-Dimensional Strain Detection FBG Sensor Based on Elliptical Ring and Its Optimization显示文摘以便完成一样的起源三维的 3D 紧张测量,一个三维的 3D 纤维布拉格栅栏 FBG 紧张传感器在这份报纸被建议。这个传感器的金属结构被三枚椭圆的戒指与不同几何参数填写。所有这些椭圆的戒指保证这个传感器完成一样的起源 3D 紧张察觉并且增加紧张测量系数。这个传感器的一个理论计算模型被建立。有限元素方法被利用优化这个传感器并且验证理论模型的正确性。在传感器优化以后, 1 公里基于考虑高紧张察觉系数和结构力量被选择为这个传感器的激进的厚度。为了推进,获得这个传感器的察觉特征,刻度实验被执行。是这个传感器的敏感元素被选择为被最少的方形的方法要分析的标本的核心的 FBG1 的试验性的数据。当 FBG1 的波长被外部应力改变时, FBG2 和 FBG3 的波长把就一点变化被纤维解调仪器 SM125 也许引起了。这个传感器的那么敏感的元素 FBG1, FBG2,和 FBG3 没为三维的察觉有串音问题。在数据分析以后, FBG1 的测量系数是 0.05 nm/N。同样, FBG2 和 FBG3 的系数分别地是 0.045 nm/N 和 0.39 nm/N。所有这些数据证实没有串音问题,这个传感器能完成一样的起源 3D 紧张测量并且有某些实际应用程序。Shanchao JIANG Jing WANG Qingmei SUI Qinglin YE 2015Photonic Sensors2015,5,2:2
4One Novel Type of Miniaturization FBG Rotation Angle Sensor With High Measurement Precision and Temperature Self-Compensation显示文摘以便完成旋转角度测量,小型化纤维布拉格的一种新奇类型有高测量精确的栅栏(FBG ) 旋转角度传感器和温度自我赔偿在这份报纸被建议并且学习。FBG 旋转角度传感器主要包含元素(FBG1 和 FBG2 ) ,三角形的伸臂横梁,和旋转角度转移的二核心敏感元素。在理论,建议传感器能由二个核心敏感元素(FBG1 和 FBG2 ) 的互补完成温度自我赔偿,并且它让无穷的天使大小与 2 rad 时期二部曲变化到旋转角度转移的功能元素。基于介绍联合工作过程, FBG 旋转天使传感器的理论计算模型被建立,并且一个原型的刻度实验也被执行获得它的测量表演。在试验性的数据分析以后, FBG 旋转角度传感器原型的测量精确是 0.Shanchao JIANG Jing WANG Qingmei SUI 2018Photonic Sensors2018,8,1:1
5Straight-line tracking control of ships based on ADRC显示文摘LIU Wenjiang SUI Qingmei ZHOU Fengyu 2010Journal of Shandong University(Engineering Science)2010,40,6:1
6Acoustic Emission Source Linear Localization Based on an Ultra-Short FBGs Sensing System显示文摘声学的排出物(AE ) 线性地点系统被建议,它作为 AE 传感器采用了纤维布拉格栅栏(FBG ) 。栅栏长度什么时候比 AE 波长短得多,被表明 FBG 波长能作为静态的盒子被调制。另外,一个改进 AE 地点方法基于 Gabor 小浪变换(WT ) 和阀值分析被代表。方法作为 AE 传感器用超短波的 FBG 传感器基于一个悦耳的狭窄乐队的激光讯问系统通过 AE 线性地点实验被证明。实验的结果证明 86% 线性地点错误是不到 10 公里。Zhongwei JIN Mingshun JIANG Qingmei SUI Faye ZHANG Lei JIA 2014Photonic Sensors2014,4,2:1
7Sliding backstepping control for ship course with nonlinear disturbance observer显示文摘LIU Wenjiang SUI Qingmei XIAO Hairong 2011Journal of Infor- mation & Computational Science2011,,8:1
8Enhanced thermoelectric performance in Ti(Fe, Co, Ni)Sb pseudoternary Half-Heusler alloys显示文摘TiFe0.5Ni0.5Sb-based half-Heusler compounds have the intrinsic low lattice thermal conductivity and the adjustable band structure.Inspired by the previously reports to achieve both p-and n-type components by tuning the ratio of Fe and Ni based on the same parent TiFe0.5Ni0.5Sb,we selected Co as the amphoteric dopants to prepare both n-type and p-type pseudo-ternary Ti(Fe,Co,Ni)Sb-based halfHeusler alloys.The carrier concentration,as well as the density of states effective mass was significantly increased by Co doping,contributing to the enhanced power factor of 1.80 mW m^(-1) K^(-2) for n-type TiFe0.3Co_(0.2)Ni_(0.5)Sb and 2.21 mW m^(-1) K^(-2) for p-type TiFe_(0.5)Co_(0.15)Ni_(0.35)Sb at 973 K.Combined with the further decreased lattice thermal conductivity due to the strain field and mass fluctuation scattering induced by alloying Hf on the Ti site,peak ZTs of 0.65 in n-type Ti0.8Hf_(0.2)Fe_(0.3)Co_(0.2)Ni_(0.5)Sb and 0.85 in ptype Ti0.8Hf_(0.2)Fe_(0.5)Co_(0.15)Ni_(0.35)Sb were achieved at 973 K,which is of great significance for the thermoelectric power generation applications.Qingmei Wang Xiaodong Xie Shan Li Zongwei Zhang Xiaofang Li Honghao Yao Chen Chen Feng Cao Jiehe Sui Xingjun Liu Qian Zhang 2021Journal of Materiomics2021,7,4:0
9Development of High Temperature Acoustic Emission Sensing System Using Fiber Bragg Grating显示文摘在处于监视的结构的健康(SHM ) 的一些应用,声学的排放(AE ) 察觉技术在高温度环境被使用。在这份报纸,察觉到系统的 high-temperature-resistant AE 基于纤维布拉格栅栏(FBG ) 被开发传感器。一个新奇高温度 FBG AE 传感器与传统的 FBG AE 传感器相比与高 signal-to-noise 比率(SNR ) 被设计。有纤维长度也理论上并且试验性地被调查的不同察觉到的设计传感器的产量回答。优秀 AE 察觉结果用从 25 ~ 200 在一个温度范围上察觉到系统的建议 FBG AE 被获得。试验性的结果显示察觉到系统罐头很好的这 FBG AE 在在高温度检测区域的 AE 满足应用程序要求。Dandan PANG Qingmei SUI Ming WANG Dongmei GUO Yaozhang SAI 2018Photonic Sensors2018,8,1:0
10Intelligent Fault Diagnosis Method of Rolling Bearings Based on Transfer Residual Swin Transformer with Shifted Windows显示文摘Due to their robust learning and expression ability for complex features,the deep learning(DL)model plays a vital role in bearing fault diagnosis.However,since there are fewer labeled samples in fault diagnosis,the depth of DL models in fault diagnosis is generally shallower than that of DL models in other fields,which limits the diagnostic performance.To solve this problem,a novel transfer residual Swin Transformer(RST)is proposed for rolling bearings in this paper.RST has 24 residual self-attention layers,which use the hierarchical design and the shifted window-based residual self-attention.Combined with transfer learning techniques,the transfer RST model uses pre-trained parameters from ImageNet.A new end-to-end method for fault diagnosis based on deep transfer RST is proposed.Firstly,wavelet transform transforms the vibration signal into a wavelet time-frequency diagram.The signal’s time-frequency domain representation can be represented simultaneously.Secondly,the wavelet time-frequency diagram is the input of the RST model to obtain the fault type.Finally,our method is verified on public and self-built datasets.Experimental results show the superior performance of our method by comparing it with a shallow neural network.Haomiao Wang Jinxi Wang Qingmei Sui Faye Zhang Yibin Li Mingshun Jiang Phanasindh Paitekul 2024Structural Durability & Health Monitoring2024,18,2:0
11Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method显示文摘Fatigue crack prediction is a critical aspect of prognostics and health management research.The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth,and it is widely used to predict the state of fatigue crack.This paper proposes a method of lamb wavebased early fatigue microcrack prediction with the aid of particle filters.With this method,which the changes in signal characteristics under different fatigue crack lengths are analyzed,and the state-and observation-equations of crack extension are established.Furthermore,an experiment is conducted to verify the feasibility of the proposed method.The Root Mean Square Error(RMSE)of the three different resampling methods are compared.The results show the system resampling method has the highest prediction accuracy.Furthermore,the factors affected by the accuracy of the prediction are discussed.Gaozheng Zhao Changchao Liu Lingyu Sun Ning Yang Lei Zhang Mingshun Jiang Lei Jia Qingmei Sui 2022Structural Durability & Health Monitoring2022,16,1:0
12Array FBG sensing and 3D reconstruction of spacecraft configuration显示文摘In this paper, a plate shape perception technique based on quasi-distributed fiber Bragg grating(FBG) array and space surface reconstruction algorithm is proposed. Firstly, in order to make curvature continuous, the bicubic plane interpolation algorithm is studied. Then, taking the simulated satellite bulkhead structure as the research object, we research the space surface reconstruction algorithm based on orthogonal curvature and coordinate transformation(translation and rotation). Finally, a four-sided fixed plate deformation monitoring system based on quasi-distributed FBG sensors network and surface reconstruction algorithm is built. Many experiments are conducted to verify the reliability and accuracy of the algorithm. The proposed algorithm provides a new method for three-dimensional reconstruction of spacecraft structure.JIANG Yue YAN Jie ZHANG Lei JIANG Mingshun LUO Yuxiang SUI Qingmei 2022Optoelectronics Letters2022,18,4:0
13Visual reconstruction of flexible structure based on fiber grating sensor array and extreme learning machine algorithm显示文摘A visual reconstruction method was proposed based on fiber Bragg grating(FBG)sensors and an intelligent algorithm,aiming to solve the problems of low accuracy and complex reconstruction process in conventional reconstruction methods of flexible structures.Firstly,the wavelength data containing structural strain information was captured by FBG sensors,together with deformation displacement information.Subsequently,a predicted model was built based on an extreme learning machine(ELM)and further optimized by the particle swarm optimization(PSO)algorithm.Different deformation patterns were tested on an aluminum alloy plate,indicating the ability of the predicted model to produce the deformation displacement for reconstruction.The experimental results show that the maximum error can be as low as 0.050 mm,which verifies that the proposed method is feasible and satisfied with the deformation monitoring of the spacecraft structure.ZHANG Sisi YAN Jie JIANG Mingshun SUI Qingmei ZHANG Lei LUO Yuxiang 2022Optoelectronics Letters2022,18,7:0
14HCPCF-Based In-Line Fiber Fabry-Perot Refractometer and High Sensitivity Signal Processing Method显示文摘同轴的纤维 Fabry-Perot 干涉仪(FPI ) 基于为折射索引(RI ) 的空核心的 photonic 水晶纤维(HCPCF ) ,测量在这份报纸被建议。FPI 被拼接形成到单个模式纤维(SMF ) 的 HCPCF 的短节的两结束并且劈开 SMF 辫子到合适的长度。传感器的 RI 反应理论上被分析并且试验性地示威了。结果证明 FPI 传感器有线性反应到外部 RI 和好重覆性。从最大的穗对比计算的敏感是 -136 dB/RIU。为信号处理的微分集成(SDI ) 方法也是的一个新系列在这介绍了学习。在这个方法, RI 从干扰光谱和它的弄平的光谱之间的绝对差别的综合紧张被获得。结果证明从综合紧张获得的敏感关于 -1.34chemical 分析。另外,象 anti-M 慲楴湯攠晦 ' ?慷 ? 獥慴汢獩敨 ? 牡畯摮ㄠ ? ‥潦 ? 潢桴 ? 塏? 那样的 Sertoli 房间标记的本地化 ? 湡 ? 呍 ? 整档楮畱獥 ? 桷牥慥? 汦潵敲 ' 諟I倡 A 祡? 桳睯摥愠栠杩敨 ? 敬敶 ? ㄨ ????? 佄 ?? 猠潨敷 ?? 潬敷 ? 楬業? 景搠瑥 ' 虡 N 湯??瑡??Xiaohui LIU Mingshun JIANG Qingmei SUI Xiangyi GENG Furong SONG 2017Photonic Sensors2017,7,4:0
15Low Velocity Impact Localization System Using FBG Array and MVDR Beamforming Algorithm显示文摘这份报纸基于纤维布拉格栅栏(FBG ) 建议一个影响本地化系统数组和最小的变化无失真的反应(MVDR ) beamforming 算法。线性 FBG 数组,包含七个 FBG 传感器,被用于检测影响信号。Morlet 小浪变换被申请提取影响信号的狭窄乐队的信号。根据 MVDR beamforming 算法,系统认识到单个影响并且多影响本地化。本地化系统在 500 公里癡 上被验证吗??Yaozhang SAI Mingshun JIANG Qingmei SUI Lei JIA Shizeng LU 2015Photonic Sensors2015,5,4:0
16Reconstruction Technology of Flexible Structure Shape Based on FBG Sensor Array and Deep Learning Algorithm显示文摘A structural displacement field reconstruction method is proposed to aim at the problems of deformation mon-itoring and displacement field reconstruction of flexible plate-like structures in the aerospace field.This method combines the deep neural network model of the cross-layer connection structure with the fiber grating sensor network.This paper first introduces the principle of strain detection of fiber grating sensor,studies the mapping relationship between strain and displacement,and proposes a strain-displacement conversion model based on an improved neural network.Then the intelligent structure deformation monitoring system is built.By controlling the stepping distance of the motor to produce different deformations of the plate structure,the strain information and real displacement information are obtained based on the high-density fiber grating sensor network and the dial indicator array.Finally,based on the deformation prediction model obtained by training,the displacement field reconstruction of the structure under different deformation states is realized.Experimental results show that the mean absolute error of the deformation of the measuring points obtained by this method is less than 0.032 mm.This method is feasible in theory and practice and can be applied to the deformation monitoring of aerospace vehicle structures.Kelong Huang Jie Yan Lei Zhang Faye Zhang Mingshun Jiang Qingmei Sui 2022Structural Durability & Health Monitoring2022,16,2:0
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