Application of the Spectrum Peak Positioning Technology Based on BP Neural Network in Demodulation of Cavity Length of EFPI Fiber Optical Sensor

An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.

Reflective Ladder Topology Network Based on White Light Fiber-Optic Mach-Zehnder Interferometer

In order to improve the multiplexing capability of the optical sensors based on the lower interferential optic fiber sensing technology and the white light fiber-optic Mach-Zehnder interferometer,reflective ladder topology network ( RLT) with tailored formula was proposed. The topology network consists of 6 rungs sensing elements linked by 5 couplers. Two cases with different choices of couplers were contrasted: one is equal coupling ratio,and the other is tailored coupling ratio. Through the simulation of these two cases,the detailed multiplexing capability was analyzed,and accordingly the experiments were also carried out. The simulation results showed that,the tailored formula enhances the multiplexing capability of the structure. In the first case, the maximum number of sensors which can be multiplexed is 8,and in the other case is 12 fiber optic sensors. The experimental results have a good agreement with numerical simulation results. Thus,it is considered expedient to incorporate RLT into large-scale building,grounds,bridges,dams,tunnels,highways and perimeter security.

Combined Transmission Interference Spectrum of No Core Fiber and BP Neural Network for Concentration Sensing Research

To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.

Anycast Transmission in Routing Modulation Level Spectrum Assignment (RMLSA) Problem on Space Division Multiplexing (SDM) Elastic Optical Networks (EON)

With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.

Loading Localization by Small-Diameter Optical Fiber Sensors

Structural health monitoring(SHM)in service has attracted increasing attention for years.Load localization on a structure is studied hereby.Two algorithms,i.e.,support vector machine(SVM)method and back propagation neural network(BPNN)algorithm,are proposed to identify the loading positions individually.The feasibility of the suggested methods is evaluated through an experimental program on a carbon fiber reinforced plastic laminate.The experimental tests involve in application of four optical fiber-based sensors for strain measurement at discrete points.The sensors are specially designed fiber Bragg grating(FBG)in small diameter.The small-diameter FBG sensors are arrayed in 2-D on the laminate surface.The testing results indicate that the loading position could be detected by the proposed method.Using SVM method,the 2-D FBG sensors can approximate the loading location with maximum error less than 14 mm.However,the maximum localization error could be limited to about 1 mm by applying the BPNN algorithm.It is mainly because the convergence conditions(mean square error)can be set in advance,while SVM cannot.

A Novel Packet Switch Node Architecture for Contention Resolution in Synchronous Optical Packet Switched Networks

Packet contention is a key issue in optical packet switch (OPS) networks and finds a viable solution by including optical buffering techniques incorporating fiber delay lines (FDLs) in the switch architecture. The present paper proposes a novel switch architecture for packet contention resolution in synchronous OPS network employing the packet circulation in FDLs in a synchronized manner. A mathematical model for the proposed switch architecture is developed employing packet queuing control to estimate the blocking probability for the incoming traffic. The switch performance is analyzed with a suitable contention resolution al-gorithm through the computer simulation. The simulation results substantiate the proposed model for the switch architecture.

Design of modified model of intelligent assembly digital twins based on optical fiber sensor network

Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy.

Use Single－chip Computer to Realize Automatic Compensation for Optical Fiber Sensors

Being directed against two kinds of noise in optical fiber sensors,a simple and effective method of automatic compensation for optical fiber sensors is presented.Not only the unstability effect of light source,but also zero drift of photoelectronic devices,can be eliminated or enormously restrained with the aid of this method.In another way,by using single-chip microcomputer,the optical fiber sensor system fabricated is connected to a computer network to realize an automatic compensation.

利用电光FM调制抑制零级中心频带——实现超高频Radio over Fiber通信

提出了一种有效抑制零级中心频带方案,并证实了该方案的可行性,给出了基于该方案的单工Radioover Fiber(RoF)通信系统.通过光通信系统软件Optisystem5.0仿真模拟结果显示:光源发送功率为5dBm,途中无光放大,24GHz的超高频微波信号在色散系数为20ps/nm/km、衰减系数为0.25dB/km的单模光纤中传输,系统码元传输速率可达5Gbit/s、传输距离15km以上.

抑光载波双边带Radio over Fiber双工通信系统设计

提出并模拟证明了基于两个电光相位调制器实现抑光载波双边带(Radio on Fiber,RoF)双工传输系统设计方案.通过改变电光相位调制器的最大相偏量,实现了抑光载波双边带信号传输——使通信带宽加倍,而且很好地控制上下行传输信号的误码率.仿真模拟结果表明,发射功率为3dBm的光信号在无放大、色散系数为20ps/(nm.km)、衰减系数为0.25dB/km的SMF-28单模光纤中传输时,其超高频RF调制信号的频率可达24GHz,数据码元传输速率可达2.5Gbit/s,传输距离40km以上.

通过光电相位调制和光纤光栅滤波实现Radio over Fiber传输系统设计

提出并模拟证明了基于电光相位调制(PM)和布拉格光纤光栅(FBG)实现受抑光载波的双边带(DSBOCS,Double-Sideband with Optical Carrier Suppression)的双向Radio over Fiber(RoF)传输系统网络设计方案.激光光源置于中心站,载有信息的光信号通过光纤到达基站后经FBG分成两路,其中一路是被接收的下行信号,另一路作为上行信号调制后返回中心站.通过FBG,其下行信号不但实现了受抑光载波的双边带———使通信带宽加倍,上行信号作为光源通过电光强度调制,有效地实现信息的上载.仿真结果表明,光源发射功率为3 dBm,无光放大,在色散系数为20 ps/(nm.km),衰减系数为0.25 dB/km的单模光纤中传输,超高频RF信号的频率可达24 GHz,系统码元传输速率可达2.5 Gbit/s、传输距离50 km以上.

配网智能化光纤远程自动切换技术的应用

随着社会经济的发展,光纤远程自动切换技术已经成为配网智能化技术发展的重要组成部分,它的应用可以极大地改善现有的配网光纤通信技术,提升信息传输的效率。文中旨在探索配网智能化光纤远程自动切换技术的基本原理,并介绍了实现该技术的方法,包括两种典型的自动切换装置的设计。此外,文中还分析了该技术在配网光纤传输中的应用,通过引入配网智能化光纤远程自动切换技术,可以实现对配网光纤传输的智能化管理,并有效提高光纤传输及测量的效率,以达到更好的社会效益。

5G时代接入网传输设计

文章分析5G接入网的特点和需求,概述光纤传输技术和无线传输技术等5G接入网传输技术。在此基础上,提出物理站直接接入光交、物理站直接接入基站以及物理站直接接入机房等传输设计方案,探讨5G接入网传输设计面临的挑战及其解决方案。

基于深度学习的光纤振动信号分类研究

管道在城市给排水,油气输送等方面发挥着重要的作用,管道的实时监测十分的重要。本文提出了一种采用深度学习的残差网络,对分布式光纤振动传感系统收集到的光纤振动信号进行分类的技术。将光纤铺设在管道上,将分布式光纤振动传感系统采集到的信号视作一维时间序列,利用格拉米角场对一维时间序列进行编码得到对应的二维图像,将二维图像输入深度学习残差网络进行分类,实现对管道的实时监测。实验结果表明,该方法比直接将一维数据转换为灰度图再输入到深度学习神经网络中具有更高的分类准确率。

Link and Cost Optimization of FTTH Network Implementation through GPON Technology

The motivation behind this work is the need for performance analysis of Al-Gehad/Baghdad“Fiber To The Home”(FTTH) network which is one of the Iraq Telecommunication Post and Company(ITPC) FTTH projectsin2010 in Baghdad City. Based on the detailed study of this project, the design, implementation, and analysis of this network has been putting under consideration through a mathematical model simulated and performance evaluated. The link utilization and number of OLT ports (PON) had been studied and evaluated as a function of cycle time. Cost optimization was done through evaluation the total cost of PON system and who it affected with the number of ONUs (i.e. splitting ratio), as well as cost ratio between EPON and GPON is evaluated. Then GPON system has been optimized to analyze and evaluate the feeder network cost, distribution network cost, and total network cost.

Discussion on the Integrated Communication System of Local Electric Power Network in China

This paper describes current situation and special requirements of local electric power communication network in China. The paper discusses the disadvantages of SDH and fiber loop carrier system applied to electric power communication network. It presents a new Communication System-IDS-2000 integrated digital communication system. The paper introduces the characteristics and application of IDS-2000 system in the local electric power communication network.

浅谈配网自动化光纤通信系统施工技术

为了保证配网自动化光纤通信系统的稳定运行和信号的可靠传输,论文简要介绍了配网自动化光纤通信系统,对配网自动化光纤通信技术在施工过程中的施工要求、关键要点和注意事项进行了探究。

考虑信息泄露影响的光纤传感网络传输数据安全导入方法

为了提高对光纤传感网络传输数据安全传输能力,提出基于信息泄漏加密传输的光纤传感网络传输数据安全导入方法。采用离散混沌时间序列同步调制方法实现对光纤传感网络传输数据导入过程中调制编码处理,根据混沌随机编码特性实现对光纤传感网络传输数据过程中的同步输出稳定性调节和自主随机编码,构建光纤传感网络信息传输泄漏抑制的加密密钥,通过Logistics映射实现对光纤传感网络传输数据导入过程中的信息泄漏加密重传,根据光纤传感网络传输数据的混合敏感密钥表征和算术编码,实现信息泄漏控制和数据安全导入。实验结果表明,采用该方法进行光纤传感网络传输数据导入的加密性能较好,其光纤传感网络传输数据已加密比特序列的识别率为98%,误码率仅为2.7∗10-9%,抗泄漏能力达到了0.970,并且导入后的数据完整度达到了0.996,说明该方法具备了较强的加密效果、抗泄漏能力,实现数据的安全导入和加密传输。

基于分布式光纤的蜂窝夹层结构脱粘损伤监测

航空航天蜂窝夹层结构服役环境恶劣,需要发展相应的结构健康监测技术以保证结构的安全运行。脱粘损伤因发生在内部胶层而难以监测,该文采用埋入胶层的分布式光纤传感器对蜂窝夹层结构脱粘损伤进行监测。在预埋损伤监测试验中采用高强光纤和边界浅槽的方式提高传感器存活效率,得到脱粘损伤应变特征。采用参数化建模方式对不同损伤位置进行大量有限元模拟,加入白噪声后得到含有脱粘损伤特征的13500组数据。将模拟数据代入卷积神经网络进行训练,训练后的网络对试验损伤数据的识别准确率达到98.84%。该方法能够识别20 mm^(2)脱粘损伤,同时定位平均误差小于4 mm。