Estimation of Fatigue Life of Long-Span Bridge by Considering Vehicle-Bridge Coupled Vibration
To estimate the fatigue life of long-span steel bridge more accurately, this paper proposes a method for estimating the fatigue life of long-span bridges by considering vehicle-bridge coupled vibration. Firstly, the universal equation of vehicle-bridge vibration is derived based on triaxial standard multi-scale model of fatigue vehicle and bridge, and relevant program for vehicle-bridge coupled vibration is programmed. Secondly, a method for estimating the fatigue life of long-span steel bridge is proposed based on fracture mechanics theories, and the analysis process is expounded in details. Finally, the method for estimating fatigue life proposed in this paper is verified by taking a double pylon cable- stayed bridge with orthotropic steel bridge deck slab as an example.
Spectra of Road Surface Roughness on Bridges
The power spectral density (PSD) of road surface roughness on highway bridges is presented. Eighty-four lines of 56 bridges were measured and the road surface roughness was measured by surveyor's level. The PSD is assumed by a stationary normal probability process with a zero mean value, and is calculated by a maximum entropy method (MEM) to a measured value of road surface roughness. Numerical examples are presented to obtain the information of road surface roughness on bridges in spectral characteristics, and to give the appropriate PSD using the dynamic response analysis of bridges under moving vehicles.
ANALYSIS OF BOLT′S ANCHORING QUALITY BASED ON WAVELET NEURAL NETWORK
The dynamic response of bolt achieved by impact-echo method can be effected easily by some factors.It′s difficult to classify bolt′s anchoring quality according to the dynamic response of bolt.In this paper,a new analytical method of bolt′s dynamic response is put forward.The new analytical method combing with advantages of wavelet analysis and artificial neural network is presented.Firstly,the dynamic response of bolt by numerical simulation software FLAC3D is obtained.Secondlyt,he features are extracted from the dynamic response of bolt by wavelet analysis.Thirdlyt,hese features are fed into the artificial neural network for training.Finallyt,his artificial neural network to classify the bolt′s anchoring quality intelligent according to the dynamic response of bolt is employed.In order to validate this new analytical method,some practical signals of bolt′s dynamic response are used for the test.The results indicate that the new analytical method is practicable.