基于声发射的木材裂缝数量辨识研究OA北大核心

A method for identifying the number of wood cracks based on acoustic emission is proposed for wood crack distances.Firstly,four cracks of 1 mm×9 mm(length×height)are artificially made in sequence on the specimen,and an acousitic emission(AE)signal is generated on one side of the crack by folding the lead,and the sensor is placed on the other side with a signal sampling frequency set to 2 MHz.Then,the number of decomposition layers K and the penalty factor α of the variational modal decomposition(VMD)are determined by the particle swarm algorithm(PSO),and the original signals are decomposed into the intrinsic mode func-tion(IMF)with different frequencies.tFive groups of signals are then randomly selected for VMD decomposition,and the matrix com-posed of the decomposed IMFs is subjected to singular value decomposition(SVD)to obtain the corresponding singular value vectors,and then the standard matrix is composed of the five groups of singular value vectors.Finally,from the measured AE signals,the Ma-halanobis distance is calculated with the standard matrix,respectively,and the number of cracks is determined based on the principle of minimum discrimination.The results show that the AE signal features can be easily extracted by the PSO-VMD-SVD method and the number of cracks can be discriminated by calculating the Mahalanobis distance,and the correct rate of discrimination is 92%.