Acciani G, Brunetti G, Fornarelli G, Giaquinto A
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari Via Orabona, 4 70125 Bari, Italy.
Ultrasonics. 2010 Jan;50(1):13-25. doi: 10.1016/j.ultras.2009.07.003. Epub 2009 Jul 14.
In this paper an effective procedure that allows evaluating the dimensions of corrosive flaws on non-accessible pipes is presented. The method is based on the propagation of ultrasound waves, analyzing the informative content of echoes reflected by defects. The approach exploits the properties of the wavelet transform to represent signals by a reduced form. The coefficients of this representation are selected properly by making use of a filter method followed by a genetic algorithm and, then, they feed a neural network classifier which evaluates the dimensions of defects on the pipe under test. Numerical results show low error rates in the evaluation of both angular and axial extension of each flaw. The main advantage offered by the method consists of analyzing long lines of non-accessible pipes, realizing an automatic evaluation of the dimensions of superficial flaws in pipelines.
本文提出了一种有效的程序，可用于评估难以接近的管道上腐蚀缺陷的尺寸。该方法基于超声波的传播，分析缺陷反射回波的信息内容。该方法利用小波变换的特性以简化形式表示信号。通过一种滤波方法，然后结合遗传算法，适当地选择这种表示的系数，然后将其输入到一个神经网络分类器中，该分类器评估被测管道上缺陷的尺寸。数值结果表明，在评估每个缺陷的角度和轴向延伸方面，误差率较低。该方法的主要优点在于能够分析难以接近的长管道线路，实现对管道表面缺陷尺寸的自动评估。
