An Optimized Damage Identification Method of Beam Using Wavelet and Neural Network

An optimized damage identification method of beam combined wavelet with neural network is presented in an attempt to improve the calculation iterative speed and accuracy damage identification. The mathematical model is developed to identify the structure damage based on the theory of finite elements and rotation modal parameters. The model is integrated with BP neural network optimization approach which utilizes the Genetic algorithm optimization method. The structural rotation modal parameters are performed with the continuous wavelet transform through the Mexico hat wavelet. The location of structure damage is identified by the maximum of wavelet coefficients. Then, the multi-scale wavelet coefficients modulus maxima are used as the inputs of the BP neural network, and through training and updating the optimal weight and threshold value to obtain the ideal output which is used to describe the degree of structural damage. The obtained results demonstrate the effectiveness of the proposed approach in simultaneously improving the structural damage identification precision including the damage locating and severity.

Analysis of blasting vibration signal of high steep anti-dip layered rock slope

Blasting is one of the most economical and efficient mining methods in open-pit mine production.However,behind the huge benefits,it poses a hidden threat to the quality of slope rock mass,stability of slope,and safety of nearby buildings.In order to explore the influence of blasting vibration on the stability of anti-dip layered rock slopes,herein,the site near the large-scale toppling failure area of Changshanhao gold mine stope of Inner Mongolia Taiping Mining Co.,Ltd.was selected for on-site blasting test and monitoring.The Peak Particle Velocity(PPV)measured at the monitoring point is located on the lower side of the maximum allowable vibration velocity curve that is prepared based on the allowable speed standard evaluation chart in the full frequency domain established by standards practiced in various countries such as German DIN4150,the USBM RI 8507,and Chinese GB6722-2014.This indicates that the blasting vibration has less influence on the location of the monitoring point.The vibration signals obtained in the blasting test were analyzed using the wavelet packet theory,and it was concluded that the blasting vibration signals measured in the anti-dip layered rock slope were mainly concentrated in two frequency bands of 0-80 Hz and 115-160 Hz.The sum of energy of the two frequency bands accounted for more than 99%,wherein,the energy contained in the 0-80 Hz frequency band accounted for more than 85%of the monitoring signals.The vibration signal with 0-80 Hz frequency band monitored at the slope toe was selected for the energy attenuation analysis.The results showed that the energy attenuation decreased in radial,vertical,and tangential directions.Further,the Energy Attenuation Rate per Meter(EARPM)was calculated.In conjunction with the site characteristics analysis,it was found that the energy attenuation rate was significantly affected by the rock mass characteristics of the structural plane.The slope reinforcement project can effectively reduce the absorption of vibration energy by the slope and increase slope stability.