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CLASSIFICATION OF ACOUSTIC EMISSION SIGNAL SOURCES USING GENETIC PROGRAMMING

机译:基于遗传规划的声发射信号源分类

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Genetic Programming (GP) is used to classify the Acoustic Emission (AE) signal to different source of signals. GP has the ability to discover the relationship among the observed data and express them mathematically. GP based technique has an advantage over conventional statistical technique like maximum likelihood estimate, nearest neighbor classifier and etc, because they are distribution free i.e. no a priori knowledge is required about the distribution of data. The data is obtained through an AE test using pulse, pencil and spark signal source on the surface of solid steel block. The signal parameters are measured using AET 5000 system, A set of expert system like rules is extracted from the GP. These rules are used directly to classify the AE signals. Classification of AE signal using genetic programming is found to be effective.
机译:遗传编程(GP)用于将声发射(AE)信号分类为不同的信号源。 GP能够发现观测数据之间的关系并以数学方式表达它们。基于GP的技术相对于常规统计技术(如最大似然估计,最近邻分类器等)具有优势,因为它们是无分布的,即不需要有关数据分布的先验知识。数据是通过使用实心钢块表面上的脉冲,铅笔和火花信号源通过AE测试获得的。使用AET 5000系统测量信号参数。从GP中提取一组专家系统(如规则)。这些规则直接用于对AE信号进行分类。发现使用遗传程序对AE信号进行分类是有效的。

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