机构地区: 华南理工大学机械与汽车工程学院
出 处: 《压力容器》 2007年第11期9-13,63,共6页
摘 要: 在压力容器、热交换管道等关键设备结构的无损评价中,裂纹型缺陷形状的确定非常重要。首先采用一种小波分析方法对采集的裂纹涡流检测信号进行了预处理,减少了非缺陷噪声信号并提取了缺陷信号特征,然后采用神经网络方法对裂纹形状进行了重构,重构结果表明该方法具有快速、精确的优点。同时讨论了该方法的不足之处并提出了解决思路。 The reconstruction of crack profiles is getting more important in the NDE (nondestructive evaluation) of critical structures, such as pressure vessel, tubes in heat exchanges. First a wavelet transform signal processing technique is used to reduce the noise and nondefect signals from the collected signals of crack, then based on artificial neural network method, the crack profiles are reconstructed and the results validate this method has many advantages, such as speedy and precision. The drawback of this method is also discussed and the measures to overcome it are proposed.