基于小波神经网络的铝合金硬度定量无损检测研究

Quantitative Nondestructive Testing of Metal Hardness Using Wavelet Network

针对铝合金硬度与初始磁导率的非线性问题,应用小波神经网络理论,提出了一种基于小波神经网络的硬度定量无损检测方法.用WGF-Ⅰ电磁检测仪进行一次检测,提取特征信号,建立硬度特征信号与LY12铝合金硬度的非线性映射,可直接输出工件的硬度值.实验表明,小波神经网络可以定量检测LY12铝合金硬度,其HRB硬度检测最大误差为±0.8,将小波网络应用于电磁无损检测具有可靠性.

Aimed at the unlinear relation between the degree of hardness of alluninium and initial magnetic permeability, this paper puts forward a kind of quantitative nondestructive testing method of the metal hardness using wavelet network, with the WGF -I electromagnetism instrument to test, withdrawing the characteristic signal, applying wavelet network theories, establish the degree of hardness characteristic signal and degree of hardness unlinear mapping, and the hardness of aluniniun alloy can be directly displayed. It is by simulated experiment proved that wavelet network can carry out quantitative tests of the hardness of LY12 aluminium alloy, the precision of the hardness being about HRB ±0.8.