WO2023028982A1 - 一种基于多源异构数据融合的格构式塔架结构水平双向位移重构方法 - Google Patents

一种基于多源异构数据融合的格构式塔架结构水平双向位移重构方法 Download PDF

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WO2023028982A1
WO2023028982A1 PCT/CN2021/116423 CN2021116423W WO2023028982A1 WO 2023028982 A1 WO2023028982 A1 WO 2023028982A1 CN 2021116423 W CN2021116423 W CN 2021116423W WO 2023028982 A1 WO2023028982 A1 WO 2023028982A1
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displacement
strain
lattice tower
point
horizontal
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付兴
张庆
任亮
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大连理工大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M7/00—Vibration-testing of structures; Shock-testing of structures
    • G01M7/02—Vibration-testing by means of a shake table
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0025—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of elongated objects, e.g. pipes, masts, towers or railways
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0041—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0066—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by exciting or detecting vibration or acceleration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]

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  • the invention belongs to the field of lattice tower structure health monitoring technology and signal analysis, and in particular relates to a multi-source heterogeneous data fusion method for horizontal bidirectional displacement reconstruction of a lattice tower structure.
  • the purpose of structural health monitoring is to evaluate the health status of the structure and give a reference on whether the structure needs to be maintained, which plays a vital role in the safe operation of large-scale infrastructure during service.
  • lattice towers have played an important role in the construction of signal base stations, transmission line engineering and meteorological monitoring. It is extremely necessary to carry out relevant research on structural health monitoring of lattice towers.
  • Dynamic displacement is one of the key parameters to evaluate the safety performance of structures. It has been widely valued because it provides information directly related to structural deformation. However, it is difficult to directly measure dynamic displacement due to its complex structural characteristics and cost Measurement, indirect reconstruction of dynamic displacement using existing common data such as acceleration and strain deserves further study.
  • the present invention proposes a data fusion method suitable for the horizontal two-way displacement reconstruction of the lattice tower structure.
  • the filtering algorithm processes acceleration and strain derived displacements to calculate horizontal bidirectional dynamic displacements with higher sampling rate and precision, which provides a new method for indirect measurement of horizontal bidirectional dynamic displacements of lattice tower structures.
  • the invention provides a new data fusion method for the reconstruction of the horizontal two-way displacement of the lattice tower structure, and provides a new idea for the indirect measurement of the horizontal two-way dynamic displacement of the lattice tower structure.
  • the technical scheme of the present invention Simplify the lattice tower into a thin-walled three-dimensional variable-section cantilever beam, use the two-dimensional strain-displacement mapping method to calculate the horizontal two-way displacement with a low sampling rate, and finally use the multi-rate Kalman filter algorithm to It is fused with the horizontal two-way acceleration to obtain the horizontal two-way displacement with a high sampling rate; the steps are as follows:
  • the y-direction acceleration a y and the calculated y-direction displacement u y of the displacement point to be measured collected by the acceleration sensor are used as a set of state variables, and the z-direction acceleration a z and the calculated z-direction displacement u z are used as another set
  • the state variables are respectively input into the multi-rate Kalman filter algorithm to reconstruct the final high-sampling-rate horizontal bidirectional dynamic displacement.
  • KIM J, KIM K, SOHN H Autonomous dynamic displacement estimation from data fusion of acceleration and intermittent displacement measurements[J]. Mechanical Systems and Signal Processing, 2014, 42(1-2): 194-205 .
  • the proposed two-dimensional strain-displacement mapping method can directly calculate the horizontal bidirectional dynamic displacement of the corresponding sampling rate from the strain, which solves the problem that it is difficult to directly calculate the displacement from the strain;
  • the proposed data fusion method takes acceleration and strain derived displacement as input values, and only needs to install strain and acceleration sensors on the lattice tower to realize horizontal bidirectional displacement reconstruction with high sampling rate;
  • the method can comprehensively utilize the information of various sensors to realize the fusion of multi-source heterogeneous data, and can measure the horizontal bidirectional dynamic displacement of the lattice tower in real time.
  • Fig. 1 is the flowchart that the present invention implements
  • Fig. 2 is the sensor layout of the lattice tower; (a) is the front view of the lattice tower, in which the circle represents the strain sensor, the box is the horizontal bidirectional acceleration sensor, and the X axis also represents the imaginary neutral layer; (b) It is the side view of the lattice tower, where the X-axis also represents the imaginary neutral layer.
  • the embodiment of the present invention proposes a data fusion method for horizontal bidirectional displacement reconstruction of a lattice tower structure.
  • both the establishment of the lattice tower numerical model and the transient analysis can use self-programming or related commercial software.
  • This embodiment takes the widely used finite element analysis software ANSYS as an example to realize the data fusion method in
  • the application of the lattice type tower structure is specifically described as follows in conjunction with the flow process shown in Figure 1 and the technical solution of the present invention:
  • the lattice structure tower of the embodiment is a self-supporting iron tower with a total height of 34m, which is made of Q235 equilateral angle steel.
  • the finite element model of the iron tower is established by ANSYS software, the BEAM188 unit is selected to simulate the lattice tower members, the rigid connection nodes are used to simplify the connection between the components, and the ideal elastic-plastic model is adopted for the steel constitutive structure.
  • a total of 8 strain measurement points are arranged on the left and right main materials, and at the same time, they are arranged at the junction of the tower head and the tower body 1 bidirectional acceleration measuring point, which is also the point to be measured for displacement.
  • the vibration mode coordinates are solved respectively, and the method is the least square method.
  • the number of strain measuring points on each main material of the lattice tower is at least 4; second, the same number of strain measuring points need to be arranged at the same position on two adjacent main materials Third, the transient analysis technology is a mature and well-known technical means in the field, and the establishment of the numerical model of the lattice tower and the transient analysis can all use self-programming or related commercial software.

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  • Aviation & Aerospace Engineering (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)

Abstract

本发明属于格构式塔架结构监测技术和信号处理领域，公开了一种基于多源异构数据融合的格构式塔架结构水平双向位移重构方法，将格构式塔架简化为薄壁的三维变截面悬臂梁，使用二维应变-位移映射法计算出低采样率的水平双向位移，最后利用多速率卡尔曼滤波算法将其和水平双向加速度融合获取高采样率的水平双向位移。本发明的数据融合方法所需传感器数量少，计算过程简单，计算结果精确，具有很强的操作性和实用性。

Description

一种基于多源异构数据融合的格构式塔架结构水平双向位移重构方法 技术领域
本发明属于格构式塔架结构健康监测技术和信号分析领域，尤其涉及一种格构式塔架结构水平双向位移重构的多源异构数据融合方法。
背景技术
结构健康监测的目的是对结构的健康状况进行评估，就是否需要维护结构给出参考，对大型基础设施在服役期间的安全运营起着至关重要的作用。近年来，格构式塔架在信号基站建设、输电线路工程和气象监测中扮演着重要角色，对格构式塔架开展结构健康监测的相关研究是极其必要的。动态位移是评价结构安全性能的关键参数之一，由于提供了直接和结构变形相关的信息得到了广泛重视，但格构式塔架因其自身复杂的结构特点和成本原因难以实现动态位移的直接测量，利用现有的诸如加速度和应变等常见数据间接重构动态位移值得深入研究。
在过去的几十年中，学者们在动态位移重构的研究上做了很多工作。例如，采用估计初速度的方法纠正加速度双重积分误差，分段计算结构的静态响应，但对于如何分段，还没有统一的指导原则。详见PARK K T,KIM S H,PARK H S,et al.The determination of bridge displacement using measured acceleration[J].Engineering Structures,2005,27(3):371-378。此外，应变数据也被用于重构动态位移。使用简支梁的理论位移振型和光纤光栅传感器测得的应变估计桥梁振动位移，或者使用分布式光纤光栅传感器采集的应变和位移-应变关系来估计旋转结构的形状。详见SHIN S,LEE S U,KIM Y,et al.Estimation of bridge displacement responses using FBG sensors and theoretical mode shapes[J].Structural Engineering and Mechanics,2012,42(2):229-245.和KIM H I,KANG L H,HAN J H.Shape estimation with distributed fiber Bragg grating sensors for rotating structures[J].Smart Materials and Structures,2011,20(3):035011。通过使用卡尔曼滤波算法融合激光多普勒测振仪的速度和和激光雷达的位移来实时估计动态位移，改善了激光雷达精度差、采样率低的缺点，获得了高采样率和高 精度的动态位移。详见KIM K,SOHN H.Dynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering[J].Mechanical Systems and Signal Processing,2017,82:339-355。然而已有数据融合方法仅适用于等截面梁结构的单向位移重构，不适用于格构式塔架这种变截面结构，并且实际结构产生的大都是由水平双向位移合成的动态位移。针对格构式塔架结构这种复杂结构的水平双向位移重构尚没有对应的数据融合方法。
针对已有数据融合方法只适用于等截面梁单向位移重构的不足，本发明提出了一种适用于格构式塔架结构水平双向位移重构的数据融合方法，核心在于沿塔身高度范围内均匀布置应变传感器，以及在位移待测点布置加速度传感器，然后将应变沿平面内和平面外振动方向分解，分别使用应变-位移映射法计算出应变导出位移，采用成熟的多速率卡尔曼滤波算法处理加速度和应变导出位移以计算出更高采样率和精度的水平双向动态位移，为间接测量格构式塔架结构水平双向动态位移提供新的方法。
发明内容
本发明为格构式塔架结构水平双向位移重构提供了一种新的数据融合方法，给格构式塔架结构水平双向动态位移的间接测量提供新思路。
本发明的技术方案：将格构式塔架简化为薄壁的三维变截面悬臂梁，使用二维应变-位移映射法计算出低采样率的水平双向位移，最后利用多速率卡尔曼滤波算法将其和水平双向加速度融合获取高采样率的水平双向位移；步骤如下：
(1)在格构式塔架左右两根主材上沿高度均匀布置2M个应变传感器，应变传感器个数最少为8个；在位移待测点处布置1个水平双向加速度传感器；
(2)将应变传感器采集到的数据{ε left} M×1和{ε right} M×1按两个振动的主方向分解为{ε y} M×1和{ε z} M×1，y、z分别为格构式塔架沿平面内和平面外振动的方向；
Figure PCTCN2021116423-appb-000001
Figure PCTCN2021116423-appb-000002
(3)分别使用随机子空间(SSI)方法处理分解后的应变数据，并根据处理结果画出稳定图，再根据所得稳定图判断参与振动的振型阶数n，n为自然数且不超过M，提取两个方向的前n阶应变振型矩阵
Figure PCTCN2021116423-appb-000003
和
Figure PCTCN2021116423-appb-000004
(4)根据格构式塔架计算主材任意一点到两个中性层的水平距离y、z和该点离地面高度x之间的函数关系y(x)和z(x)；
(5)将两个方向的前n阶应变振型分别和应变传感器布置点离地面高度x进行多项式拟合，得到应变振型函数
Figure PCTCN2021116423-appb-000005
和
Figure PCTCN2021116423-appb-000006
然后把
Figure PCTCN2021116423-appb-000007
和
Figure PCTCN2021116423-appb-000008
整体看成函数，并将其分别按泰勒公式展开，对展开结果做双重积分并代入格构式塔架结构底部固接的边界条件，得到位移振型函数
Figure PCTCN2021116423-appb-000009
和
Figure PCTCN2021116423-appb-000010
Figure PCTCN2021116423-appb-000011
Figure PCTCN2021116423-appb-000012
Figure PCTCN2021116423-appb-000013
Figure PCTCN2021116423-appb-000014
(6)在格构式塔架的应变振型矩阵
Figure PCTCN2021116423-appb-000015
和
Figure PCTCN2021116423-appb-000016
以及正交分解后的应变数据{ε y} M×1和{ε z} M×1已知的情况下，由最小二乘法解出格构式塔架在振动过程中的模态坐标{q y} n×1和{q z} n×1；
Figure PCTCN2021116423-appb-000017
Figure PCTCN2021116423-appb-000018
(7)将格构式塔架上位移待测点的高度坐标x分别代入两个位移振型函数
Figure PCTCN2021116423-appb-000019
和
Figure PCTCN2021116423-appb-000020
得到相应的位移振型函数值，并将所得位移振型函数值和模态坐标相乘得到该点的低采样率动态位移u y和u z；
(8)将加速度传感器采集到的位移待测点的y向加速度a y和计算的y向位移u y作为一组状态变量，z向加速度a z和计算的z向位移u z作为另一组状态变量，分别输入多速率卡尔曼滤波算法以重构出最终的高采样率水平双向动态位移。 卡尔曼滤波算法详见KIM J,KIM K,SOHN H.Autonomous dynamic displacement estimation from data fusion of acceleration and intermittent displacement measurements[J].Mechanical Systems and Signal Processing,2014,42(1-2):194-205。
本发明的有益效果：
(1)提出的二维应变-位移映射法可以直接由应变计算出相应采样率的水平双向动态位移，解决了难以直接由应变计算位移的问题；
(2)提出的数据融合方法以加速度和应变导出位移为输入值，只需在格构式塔架上安装应变和加速度传感器即可实现高采样率的水平双向位移重构；
(3)该方法可综合利用多种传感器的信息，实现多源异构数据的融合，并且可以实时测量格构式塔架水平双向动态位移。
附图说明
图1为本发明实施的流程图；
图2为格构式塔架传感器布置图；(a)为格构式塔架正视图，其中圆圈代表应变传感器，方框为水平双向加速度传感器，X轴也代表假想中性层；(b)为格构式塔架侧视图，其中X轴也代表假想中性层。
具体实施方式
为使得本发明的发明目的、特征、优点能够更加的明显和易懂，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，下面所描述的实施例仅仅是本发明一部分实施例，而非全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。
请参阅图1至图2，本发明实施例为格构式塔架结构的水平双向位移重构提出了一种数据融合方法。
实施案例数据来源：详见ZHANG Q,FU X,REN L,et al.Modal parameters of a transmission tower considering the coupling effects between the tower and lines[J].Engineering Structures,2020,220:110947。
在本发明实施例中，格构式塔架数值模型的建立和瞬态分析均可采用自编程序或相关商业软件，本实施例以广泛使用的有限元分析软件ANSYS为例实现数据融合方法在格构式塔架结构的应用，结合图1所示的流程和本发明的技术方案具体描述如下：
(1)实施例格构式塔架为一座总高34m的自立式铁塔，采用Q235等边角钢制成，铁塔结构信息详见“ZHANG Q,FU X,REN L,et al.Modal parameters of a transmission tower considering the coupling effects between the tower and lines[J].Engineering Structures,2020,220:110947.”中“Fig.6”。利用ANSYS软件建立铁塔有限元模型，选用BEAM188单元模拟格构式塔架杆件，采用刚接节点简化构件间的连接，钢材本构采用理想弹塑性模型。
由于数据融合方法中的二维应变-位移映射法需要考虑前三阶振型，本实施例中在左右两根主材上共布置8个应变测点，同时在塔头和塔身交界处布置1个双向加速度测点，该点也是位移待测点。按照设计图纸建立的格构式塔架数值模型。
(2)本实施例施加的y向荷载和z向荷载详见“ZHANG Q,FU X,REN L,et al.Modal parameters of a transmission tower considering the coupling effects between the tower and lines[J].Engineering Structures,2020,220:110947.”中“Fig.6”。ANSYS软件分析的求解类型为“antype,trans”，施加荷载求解完成后便可提取应变测点的应变响应和加速度响应，应变采样率设置为10Hz，加速度采样率设置为100Hz。将应变传感器采集到的数据按两个主振动的主方向分解，然后使用SSI方法处理正交分解后的应变响应，假设阶数设为100，提取识别的应变振型和相应的高度坐标。
(3)按照格构式塔架的尺寸计算出主材任意一点到两个中性层的水平距离y、z和该点离地面高度x之间的函数关系，本例中为一次函数关系。
(4)将两个方向上的应变振型分别和格构式塔架高度坐标进行多项式拟合得到应变振型函数，并把
Figure PCTCN2021116423-appb-000021
和
Figure PCTCN2021116423-appb-000022
整体看成函数，并将其按泰勒公式展开， 对展开结果做双重不定积分并代入边界条件得到位移振型函数
Figure PCTCN2021116423-appb-000023
和
Figure PCTCN2021116423-appb-000024
(5)由正交分解后的应变响应和两个方向上的应变振型分别解出振型坐标，方法为最小二乘法。
(6)将位移待测点的高度坐标分别代入位移振型函数求得函数值，并分别将位移振型函数值和振型坐标相乘得到水平双向的低采样率动态位移。
(7)使用已有的多速率卡尔曼滤波算法分别处理两个方向的低采样率动态位移和加速度，即可得到高采样率的水平双向动态位移。
使用本发明时需要注意：第一，格构式塔架每根主材上应变测点数量至少为4个；第二，需要在两根相邻主材上的相同位置布置相同数量的应变测点；第三，瞬态分析技术为领域内成熟且公知的技术手段，格构式塔架数值模型的建立和瞬态分析均可采用自编程序或相关商业软件。
以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围。

Claims (1)

  1. 一种基于多源异构数据融合的格构式塔架结构水平双向位移重构方法，其特征在于，将格构式塔架简化为薄壁的三维变截面悬臂梁，假设中性层位于两根主材中间，使用二维应变-位移映射法由应变直接计算出低采样率位移，将低采样率位移和加速度作为卡尔曼滤波算法的输入值求解高采样率水平双向动态位移；步骤如下：
    (1)在格构式塔架两根相邻主材上沿高度均匀布置2M个应变传感器，应变传感器个数最少为8个，在位移待测点处布置1个水平双向加速度传感器；
    (2)将应变传感器采集的应变响应按平面内和平面外振动的方向分解，使用随机子空间方法分别处理分解后的应变数据{ε y} M×1和{ε z} M×1，并根据处理结果画出稳定图，再根据所得稳定图判断参与振动的振型阶数n，n为自然数且不超过M，提取前n阶应变振型矩阵
    Figure PCTCN2021116423-appb-100001
    和
    Figure PCTCN2021116423-appb-100002
    (3)根据格构式塔架结构计算主材任意一点到两个中性层的水平距离y、z和该点离地面高度x之间的函数关系y(x)和z(x)；
    (4)将前n阶应变振型分别和应变传感器布置点离地面高度x进行多项式拟合，得到应变振型函数
    Figure PCTCN2021116423-appb-100003
    和
    Figure PCTCN2021116423-appb-100004
    然后把
    Figure PCTCN2021116423-appb-100005
    和
    Figure PCTCN2021116423-appb-100006
    整体看成函数，并将其按泰勒公式展开，对展开结果做双重积分并代入格构式塔架结构底部固接的边界条件，得到位移振型函数
    Figure PCTCN2021116423-appb-100007
    和
    Figure PCTCN2021116423-appb-100008
    (5)在格构式塔架的应变振型矩阵
    Figure PCTCN2021116423-appb-100009
    和
    Figure PCTCN2021116423-appb-100010
    以及正交分解后的应变数据{ε y} M×1和{ε z} M×1已知的情况下，由最小二乘法解出格构式塔架在振动过程中两个方向上的模态坐标{q y} n×1和{q z} n×1；
    (6)将格构式塔架上位移待测点的高度坐标x分别代入位移振型函数
    Figure PCTCN2021116423-appb-100011
    和
    Figure PCTCN2021116423-appb-100012
    得到相应的位移振型函数值，并将所得位移振型函数值和模态坐标相乘得到该点的低采样率动态位移u y和u z；
    (7)将加速度传感器采集到的位移待测点的y向加速度a y和计算的y向位移u y作为一组状态变量，z向加速度a z和计算的z向位移u z作为另一组状态变量， 分别输入多速率卡尔曼滤波算法以重构出最终的高采样率水平双向动态位移。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117892598A (zh) * 2024-03-13 2024-04-16 浙江大学海南研究院 一种用于海上风机塔筒的增强逆有限元形状传感重建系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160286286A1 (en) * 2015-03-23 2016-09-29 SmarTower Systems, LLC Remote tower monitoring
CN107103111A (zh) * 2017-03-02 2017-08-29 西安电子科技大学 基于应变传感器的电子装备功能形面特征点位移场重构方法
CN108413921A (zh) * 2018-04-09 2018-08-17 西安工程大学 一种输电线路铁塔塔材变形在线监测系统及监测方法
WO2019159042A1 (en) * 2018-02-16 2019-08-22 Site S.P.A. Con Socio Unico System and method for automated monitoring of suspended road infrastructures, such as flyovers, bridges and viaducts
CN112461190A (zh) * 2020-11-13 2021-03-09 合肥工业大学 一种桥梁变形重构方法

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11414859B2 (en) * 2019-05-24 2022-08-16 Big Time Investment, Llc Method and apparatus for monitoring a building

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160286286A1 (en) * 2015-03-23 2016-09-29 SmarTower Systems, LLC Remote tower monitoring
CN107103111A (zh) * 2017-03-02 2017-08-29 西安电子科技大学 基于应变传感器的电子装备功能形面特征点位移场重构方法
WO2019159042A1 (en) * 2018-02-16 2019-08-22 Site S.P.A. Con Socio Unico System and method for automated monitoring of suspended road infrastructures, such as flyovers, bridges and viaducts
CN108413921A (zh) * 2018-04-09 2018-08-17 西安工程大学 一种输电线路铁塔塔材变形在线监测系统及监测方法
CN112461190A (zh) * 2020-11-13 2021-03-09 合肥工业大学 一种桥梁变形重构方法

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SHIN, SOOBONG; LEE, SUN-UNG; KIM, YUHEE; KIM, NAM-SIK: "Estimation of bridge displacement responses using FBG sensors and theoretical mode shapes", STRUCTURAL ENGINEERING AND MECHANICS, TECHNO-PRESS, TAEJON,, KR, vol. 42, no. 2, 31 December 2012 (2012-12-31), KR , pages 229 - 245, XP009544202, ISSN: 1225-4568, DOI: 10.12989/sem.2012.42.2.229 *
ZHANG QING; FU XING; REN LIANG; JIA ZIGUANG: "Modal parameters of a transmission tower considering the coupling effects between the tower and lines", ENGINEERING STRUCTURES, ELSEVIER, AMSTERDAM, NL, vol. 220, 29 June 2020 (2020-06-29), AMSTERDAM, NL , XP086225759, ISSN: 0141-0296, DOI: 10.1016/j.engstruct.2020.110947 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117892598A (zh) * 2024-03-13 2024-04-16 浙江大学海南研究院 一种用于海上风机塔筒的增强逆有限元形状传感重建系统
CN117892598B (zh) * 2024-03-13 2024-06-07 浙江大学海南研究院 一种用于海上风机塔筒的增强逆有限元形状传感重建系统

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