小波网络在钢丝绳损伤定量检测中的应用  

Application of Wavelet Neural Network in the Quantitative Inspection of Wire Rope Damage

作　　者：战卫侠[1] 谭继文[1] 

机构地区：[1]青岛理工大学机械工程学院,山东青岛266033

出　　处：《矿山机械》2008年第20期19-21,共3页Mining & Processing Equipment

基　　金：国家自然科学基金项目(50475166)

摘　　要：针对钢丝绳损伤与漏磁场的非线性问题,应用小波神经网络理论,提出了一种铜丝绳损伤定量无损检测方法。对钢丝绳进行检测,消除噪声,提取特征信号,建立损伤特征信号与损伤的非线性映射,可直接输出损伤根数。实验表明,小波神经网络可以定量检测钢丝绳损伤,为铜丝绳无损检测的进一步研究提供了有效的途径。Aiming at the nonlinear relationship between the wire rope damage and magnetic leakage, this paper puts forward a kind of quantitative nondestructive testing method to wire rope damage using the theory of wavelet neural network. By testing, de-noising, extracting the characteristic signals of the wire rope, and establishing the nonlinear mapping of damage characteristic signals and the damage, the number of the damage wire rope can be directly displayed The experiment proves that the wavelet neural network can carry out quantitative inspection of the wire rope damage, which provides an effective method for the farther research of wire rope nondestructive inspection.

关 键 词：小波神经网络 定量检测 钢丝绳 损伤 

分 类 号：TD532[矿业工程—矿山机电]