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.

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.

针对铝合金结构服役过程中的疲劳裂纹监测问题,提出了一种基于光纤光栅传感阵列的疲劳裂纹实时监测方法。首先,结合扩展有限元技术获得裂纹扩展过程的应变场分布特征,进行传感器布局设计;其次,通过疲劳加载实验获取加载次数、裂纹长度对波长峰峰值的响应特征,采用三参数指数法进行疲劳扩展a-N(其中N为加载次数,a为裂纹长度)曲线拟合;在实验数据基础上,采用梯度提升回归树算法搭建疲劳损伤预测模型,并将其与线性回归、支持向量两种方法进行对比,选取可释方差、平均绝对误差、平均方差、决定系数和五折交叉验证等多种指标进行模型评估。结果表明,梯度提升回归树算法对疲劳裂纹长度的预测效果最佳。

建立一种能够快速、定量检测掺假普洱茶中香豆素、香兰素、乙基麦芽酚三种常见香精的方法。利用傅里叶变换近红外光谱技术结合偏最小二乘法对香精掺假普洱茶进行定量分析。分别建立三种掺假香精成分的定量分析模型,并对比基于不同预处理方法和未经光谱预处理的定量分析模型的预测能力。结果表明:结合不同光谱预处理方法实现的针对香豆素、香兰素和乙基麦芽酚三种香精的预测均方根误差分别为0.1461,0.1678,0.1800,预测决定系数分别为0.7989,0.7350,0.6938,三种香精的检测限为0.2 mg/g。近红外光谱技术结合偏最小二乘定量分析方法可以实现掺假普洱茶中三种香精成分的快速检测分析。

以航天器中结构的形态感知与可视化重构为研究背景,提出了一种基于准分布光纤光栅传感器网络的板状结构变形监测系统和坐标转换曲面重构算法。首先利用ABAQUS有限元分析软件对四边固支平板结构中心点加载的变形状态进行仿真分析,确定了光纤光栅传感器的位置;研究并分析了光纤光栅的应变检测原理以及基于坐标变换的三维曲面重构算法;最终搭建了一套变形检测系统并进行了相关实验。结果表明,测量点变形量的均方根误差≤0.04 mm,相对误差≤3.5%,该系统可用于航天器板状结构的变形监测。

通过建立校正集样本不同的模型Ⅰ与模型Ⅱ来研究温度对水泥生料近红外光谱模型的影响,其中模型Ⅰ中的建模样本为温度一致的样本,模型Ⅱ中的建模样本为温度变化的样本,建模方法采用偏最小二乘法。对比两组模型的预测结果可知,模型Ⅱ中SiO2、Al2O3、Fe2O3、CaCO3的预测方均根误差与模型Ⅰ相比分别减小了78.3%、26.4%、42.9%、60.4%。实验结果表明:温度变化会导致预测结果产生一定的误差。在校正集中加入温度不同的样本进行建模,可以降低预测误差,使近红外光谱模型更好地应用于生产现场。

研究高斯光束经螺旋相位板和轴棱锥产生高阶贝塞尔-高斯涡旋光束的离轴传输情况,对于离轴高阶贝塞尔-高斯光束的成因、 光强分布操控、光斑定位等实际应用具有一定的理论指导意义。利用菲涅尔衍射积分的卷积算法(Triple fast Fourier transform, T-FFT)对离轴高阶贝塞尔-高斯涡旋光束进行仿真分析,着重研究了螺旋相位板和轴棱锥的错位参数、拓扑荷数 以及传输距离等参数对光束带来的影响。分析表明:离轴高阶贝塞尔-高斯光束具有不均匀的光强分布,由于轴棱锥的偏移, 光束会整体发生偏移,传输不同距离光强不均匀分布情况不同,不同的拓扑荷数只影响光斑的扩展,螺旋相位板和轴棱锥离 轴参量值的多种组合会导致多种不同的光强分布情况,甚至出现暗核偏移。

A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

声发射技术是结构损伤检测的重要手段, 声发射源定位是损伤检测的首要环节。时差定位技术具有快速、高效、精确的特点, 以此设计了由菱形阵列光纤布拉格光栅(FBG)传感器构成的声发射定位系统。采用小波变换和传统阈值法提取特征信号, 结合互相关法获得传感器间的信号到达时差, 然后根据几何定位模型求解非线性方程组得到声源可能存在的位置, 最后根据时差的正负特性进一步确定声源的准确位置, 有效避免了伪声源的情况。在铝合金板上, 以对角线为48 cm×48 cm的监测区域进行了10组测试实验验证, 平均误差为1.29 cm。

An in-line fiber Fabry-Perot interferometer (FPI) based on the hollow-core photonic crystal fiber (HCPCF) for refractive index (RI) measurement is proposed in this paper. The FPI is formed by splicing both ends of a short section of the HCPCF to single mode fibers (SMFs) and cleaving the SMF pigtail to a proper length. The RI response of the sensor is analyzed theoretically and demonstrated experimentally. The results show that the FPI sensor has linear response to external RI and good repeatability. The sensitivity calculated from the maximum fringe contrast is –136 dB/RIU. A new spectrum differential integration (SDI) method for signal processing is also presented in this study. In this method, the RI is obtained from the integrated intensity of the absolute difference between the interference spectrum and its smoothed spectrum. The results show that the sensitivity obtained from the integrated intensity is about –1.34×10⁵ dB/RIU. Compared with the maximum fringe contrast method, the new SDI method can provide the higher sensitivity, better linearity, improved reliability, and accuracy, and it’s also convenient for automatic and fast signal processing in real-time monitoring of RI.