随机荷载识别的理论和实验研究都还十分稀少。
So far, theoretical or experimental studies of random loading identification have rarely been seen in the literature.
这些结论对实际的荷载识别问题有一定的指导意义。
These conclusions have some guidance significances to the practical load identification problems.
如何确定有效的风荷载识别方法是风荷载理论研究的基础。
How to determine the effective wind load identification is the basis for wind load theory.
第二章介绍了移动荷载识别的基本原理和相关知识，包括振型的正交性，模态叠加原理等。
The second chapter introduces the basic principle and the correlation knowledge of moving load identification, including mode shape orthogonality, mode superposition principle and so on.
移动车辆荷载反复作用会导致桥梁疲劳损伤甚至破坏，移动荷载识别是桥梁健康监测的重要措施之一。
Moving loads identification is one of the important measures for health monitoring of bridge because the cyclic action of moving loads may lead to fatigue damage or even failure of the bridge.
基于移动荷载识别理论并根据移动常力轴载特点，提出了一种用于准确识别移动常力轴载的快速算法。
Based on the theory of moving force identification and the characteristic of moving constant axle loads, a new fast and simplified algorithm is proposed for the moving force identification.
研究结果表明，基于动力模型的BP神经网络移动荷载识别方法，能够有效识别简支梁桥与连续梁桥上的移动车载；
The results show that the method of BP neural network used to identify moving force based on the dynamic model can effectively identify the moving force on the simple beams and continuous beams.
要解决这个问题，必须建立作用在桅杆结构上的动力风荷载的识别方法。
In this thesis, the dynamic load identification of guyed mast method in time domain based on modal analysis is analyzed.
将图像识别技术和神经网络(ANN)系统相结合，给出了大跨度结构风荷载的模拟方法。
Through the combination of image recognition technique with ANN system, wind load simulation of long-span structures is presented.
本征正交分解法可以用来识别规则的大跨度空间结构的风荷载。
Proper orthogonal decomposition method can be used to identify wind loads on the rules of long-span space structure.
提出了一种基于BP神经网络的桥上移动荷载的分阶段识别新方法。
A novel BP neural network-based stage identification method for moving loads on bridge is proposed.
基于广义卡尔曼滤波提出了随机荷载作用下桥梁结构物理参数的识别方法。
Based on the extended Kalman filter, an identification method on physical parameters of bridge structures subjected to stochastic loads is proposed.
应用POD法识别作用在结构表面的脉动风荷载的时频域特性。
The proper orthogonal decomposition(POD) technique was applied to identification random wind pressure time or frequency domain specific property.
荷载分步识别技术能够得到较准确的车载位置、速度与大小；
The multi-step identification procedure can exactly identify the locations, velocity and magnitude of the moving force.
采用轴对称动力有限元结合系统识别反分析理论进行路面模量反算，考虑了落锤式弯沉仪（FWD）荷载作用下的路面反应动力效应。
This essay adopts limited units of axial symmetry and theory of system recognizing backcalculation, in which the dynamic effect of the road surface reaction to load of FWD is considered.
提出了一种智能桥梁结构的智能计算方案，并利用人工神经网络法，建立一种识别作用在桥梁结构上荷载的力学反分析法，以此初步实现该方案。
Based on the artificial neural networks, a inverse analysis method is presented to identify both the magnitude and location of the load on bridge structure.
而横向位置和车重参数识别是交通荷载调查至关重要的内容。
The identification of transverse location and vehicle weight is a vital element in the investigation of traffic loads.
而横向位置和车重参数识别是交通荷载调查至关重要的内容。
The identification of transverse location and vehicle weight is a vital element in the investigation of traffic loads.
应用推荐