| Concrete filled steel tubular(CFST)structures have been widely used in engineering due to their high bearing capacity,good ductility and superior seismic performance.Due to the influence of construction quality and environmental factors,the cavitation of concrete filled steel tube often occurs,which seriously threatens the safety of the structure.Therefore,the cavitation detection of concrete filled steel tube is very important.Although there are many cavitation detection techniques for concrete filled steel tubular,there is still a lack of a convenient,fast,economic and effective detection method to identify the cavitation of concrete filled steel tubular.In this paper,the acoustic vibration signal of CFST under transient impact is analyzed,and the cavitation defect of CFST is qualitatively identified by acoustic vibration test and finite element analysis.The acoustic characteristic values are extracted for neural network training,and the quantitative identification of the void side length of CFST is realized,and the feasibility of the method is proved by experimental method.The main research contents are as follows:(1)A construction method of specimen which can simulate the cavitation defect inside CFST in a real and effective way is invented to ensure the accurate manufacture of the cavitation defect;The completed concrete filled steel tube specimens were tested by acoustic vibration method to explore the influence of cavitation defects with different depths and areas and different percussion positions on acoustic vibration signals.The same void defect was detected and analyzed by combined acoustic vibration method,impact echo method and ultrasonic method.It is found that the frequency of the main peak at the edge of the void defect increases compared with that at the center of the defect,and the void depth has little effect on the frequency of the main peak,while the frequency of the main peak of the sound signal decreases with the increase of the void area.The acoustic vibration method can identify the void defect of concrete filled steel tube effectively and has the advantage of convenience and efficiency.(2)The sound field excitation model of CFST member is established to obtain the sound pressure response distribution in the dense area and the empty area.When the excitation load is applied in the void,continuous large acoustic wave will be generated in the air above,while when the load is applied in the dense area,there are small amplitude direct acoustic wave and leakage Rayleigh wave in the sound field.The effective sound pressure and the cepstrum coefficient of Mayer frequency were determined as the characteristic values,and the relationship curves between the effective sound pressure index and the cepstrum coefficient of Mayer frequency and the void size were obtained by analyzing the sound characteristic indexes extracted by simulation under different working conditions.(3)Through finite element modeling,sound characteristic values are extracted as data samples and input into BP neural network to build BP neural network.By comparing the predicted value and expected value error,adjusting the neural network structural parameters,the BP neural network is determined to be a three-layer topology structure,the hidden layer node number is 6,the number of iterations is 500,the learning rate is 0.001,the hidden layer using tansig function,the output layer using Logsig function.The prediction error of the void side length by BP neural network is less than 4.84%,which meets the actual demand.(4)Make concrete filled steel tube specimens,conduct acoustic vibration test for defects with a void side length of 260-460 mm,extract acoustic signal indicators and input them into neural network for verification.The experimental results show that the prediction error is 8.35%,which proves the feasibility of the method for quantitative identification of the void side length of CFST.The research results of this paper provide a new technical approach for the cavitation identification of concrete filled steel tubular,and have certain theoretical value and reference significance for the subsequent research and practical application of the acoustic vibration identification of concrete filled steel tubular cavitation. |