The strain-temperature cross-sensitivity problem easily occurs in the engineering strain monitoring of the self-sensing embedded with fiber Bragg grating (FBG) sensors. In this work, a theoretical investigation of the strain-temperature cross-sensitivity has been performed using the temperature reference grating method. To experimentally observe and theoretically verify the problem, the substrate materials, the preloading technique, and the FBG initial central wavelength were taken as main parameters. And a series of sensitivity coefficients calibration tests and temperature compensation tests have been designed and carried out. It was found that when the FBG sensors were embedded on different substrates, their coefficients of the temperature sensitivity were significantly changed. Besides, the larger the coefficients of thermal expansion (CTE) of substrates were, the higher the temperature sensitivity coefficients would be. On the other hand, the effect of the preloading technique and FBG initial wavelength was negligible on both the strain monitoring and temperature compensation. In the case of similar substrates, we did not observe any difference between temperature sensitivity coefficients of the temperature compensation FBG with one free end or two free ends. The curves of the force along with temperature were almost overlapped with minor differences (less than 1%) gained by FBG sensors and pressure sensors, which verified the accuracy of the temperature compensation method. We suggest that this work can provide efficient solutions to the strain-temperature cross-sensitivity for engineering strain monitoring with the self-sensing element embedded with FBG sensors.

The deformation and reconstruction of the composite propeller under the static load in the laboratory is studied so as to provide the basic research for the deformation and reconstruction of the underwater deformed propeller. The fiber Bragg grating (FBG) sensor is proposed to be used for strain monitoring and deformation reconstruction of the carbon fiber reinforced polymer (CFRP) propeller, and a reconstruction algorithm of structural curvature deformation of the CFRP propeller based on strain information is presented. The reconstruction algorithm is verified by using variable-thickness CFRP laminates in the finite element software. The results show that the relative error of the reconstruction algorithm is within 8%. Then, an experimental system of strain monitoring and deformation reconstruction for the CFRP propeller based on the FBG sensor network is built. The propeller blade is loaded in the form of the cantilever beam, and the blade deformation is reconstructed by the strain measured by the FBG sensor network. Compared with the blade deformation measured by three coordinate scanners, the reconstruction relative error is within 15%.

Glass has been widely used as an important component in structures such as reflection glass curtainwalls, high speed trains, and landscape glass bridges with advantages of transparent and easy to clean, which are exposed to extreme weather conditions and external loads. Over time, these factors can lead to a damage of glass. So the health status of glass structure is critical, which should be routinely monitored to improve safety and provide reliable maintenance strategy. In this paper, fiber Bragg grating (FBG) sensors are used to monitor glass damage based on the fact that the main components of both the optical fiber and the glass are silica, which hints that both optical fiber and glass have the similar mechanical properties. Furthermore, the diameter of FBG installed on the glass structure is small, which has little effect on the beauty of glass. In order to validate the feasibility of the damage monitoring method, one common glass panel model with two-side fixations is loaded impact and static loads respectively, on the upper and lower surfaces of which four FBG sensors and two resistance strain gages are installed. A comparison study among the measured strains from the FBG sensors, those from the resistance strain gages, and those calculated from finite element model (FEM) analysis is conducted and the result obtained with experiments agrees with the element result. Test results show that the FBG sensors can effectively measure the glass deformation or damage under the impact and static load.

设计了一种在预应力钢绞线中心丝上设置倾斜凹槽封装光纤光栅的自感知钢绞线, 以解决体内预应力钢绞线其它传感器无安装空间, 易碎断导致封装成活率低以及监测量程不够等技术难题.理论分析了不同凹槽倾角封装的光纤光栅传感器的监测应变与钢绞线应变, 根据复合材料剪滞模型理论建立了二者之间的应变关系.以倾角为变化参数, 研制了系列光纤光栅自感知钢绞线, 并对其进行张拉试验, 测定光纤光栅传感器量程的变化情况.试验结果表明：该方法能有效扩大光纤光栅传感器的监测量程, 当倾斜角度为30°时, 所能监测的应变范围与0°相比, 提高了44%.采用该技术, 利用光纤光栅传感器对某高速公路预应力箱梁的施工张拉及服役进行实时监测, 传感器成活率为100%, 同时将光纤光栅的理论及标定应变关系与现场张拉及二次张拉的数据进行对比, 误差均在5%以内.该技术实现了对体内预应力钢绞线施工张拉和服役全生命周期的监测.

光纤布拉格光栅(FBG)传感网络具有功能多样化和规模庞大化的发展趋势，对其可靠性和可扩展性提出了更高的要求。文章提出了一种新颖的基于正方形传感单元(SSU)的多环FBG传感网络，首先分析了光开关在FBG传感网络中的作用；接着描述了SSU网络的构建过程及光在内环与外环中的传输过程；然后设计了一种用于故障修复的远程节点；最后详细分析了链路故障时，该网络的故障修复过程并且定量讨论了其扩展性。结果表明，该网络至少可以修复一个链路故障，同时发生两个故障时，修复效果也比较好，具有很高的可靠性及可扩展性。

载荷识别在结构健康监测中的地位十分重要,为了在结构健康监测的同时利用最优化算法对系统进行有效控制,提出了一种基于光纤光栅(FBG)传感器和卡尔曼滤波器的载荷识别算法。该算法建立在卡尔曼滤波器的基础上,以FBG传感器测得的应变值作为观测信号,通过卡尔曼滤波器产生的增益矩阵、新息序列和协方差矩阵,利用最小二乘算法实时估计载荷的大小。此算法只需采集前一时刻的估计值和当前时刻的观测值即可估计出当前时刻的载荷,无需存储和读取大量数据。同时,基于卡尔曼滤波器在进行结构健康监测的同时能够应用最优化算法对系统进行控制。为了对识别算法进行验证,采用梁系统作为仿真和试验对象,通过FBG传感器测得的应变值识别载荷。结果表明,所提动态载荷识别算法能够很好地抑制噪声,具有良好的稳定性和实时性。

考虑现有光纤布拉格光栅(FBG)传感器的应变传递理论均未考虑传感器对基体应变的影响, 本文针对FBG传感器粘贴于薄板的情况研究了薄板的应变传递理论。由于光纤应变与薄板应变并不相等, 故研究了光纤应变与薄板应变之间的关系以提高FBG传感器的测量精度。建立了粘贴于薄板表面的FBG传感器应变传递理论, 分析了FBG传感器与薄板之间的相互作用; 利用有限元法(FEM)和实验法验证了理论的正确性。最后, 分析了薄板参数对应变传递率的影响。结果显示: FEM解与理论解的误差在4%以内, 实验值和理论解误差在5%以内, 应变传递率随着薄板厚度和弹性模量的增加而逐渐增大。该理论模型完全满足FBG传感器精度要求, 对其实际应用具有一定的指导意义。

使用单个光杠杆监测传感器应变时, 传感器两端的被夹持部位受力后易与电子万能试验机的夹持器产生滑移。为了消除滑移影响以提高测试精度, 本文使用两套光杠杆建立了测量弹性受力部位呈非等截面的光纤布拉格光栅(FBG)传感器等效应变系数ηεeff的实验测量系统。测试时, 将两套光杠杆的平面反射镜分别安放在传感器弹性受力部位两侧的固定端端面上,测量出两个固定端在受力变形后的相对位移和相应的FBG中心波长变化量。然后, 使用曲线拟合法和累加均值法对实验测得的数据进行处理来获得ηεeff。建立了仿真模型, 得到了ηεeff预估值并与实测值进行了对比。结果显示: 实验测得的ηεeff为0.681 7 με /pm, 精度为0.91%, 与仿真获得的预估值0.672 0 με/pm相差仅为1.42%。该方法满足了准确测量非等截面结构FBG传感器应变系数的要求。

This study introduces the optimization of the fiber Bragg grating (FBG) network and the load identification. Current researches on the optimal placement and reliability of the FBG network and the static load identification are generally analyzed. And then, the optimal placement of sensors and reliability of the FBG network are studied. Through the analysis of structural response characteristics, the general rules of sensors placement in structural static response parameters monitoring are proposed. The probability calculation is introduced, and the numerical analyses of the FBG sensor network reliability of several simple topologies are given.