[b]摘要翻译：[/b]
第一部分介绍了智能声发射定位器，第二部分讨论了盲源分离、时延估计和两个同时有源的连续声发射源的定位。复杂飞机框架结构声发射定位是无损检测中的一个难题。本文介绍了一种智能声发射源定位器。该智能定位器由传感器天线和广义回归神经网络组成，解决了基于示例学习的定位问题。在不同的试件上测试了定位器的性能。试验表明，定位的准确性取决于试样中的声速和衰减，测试区域的尺寸，以及存储数据的性质。该智能定位器的定位精度与传统三角法相当，但由于避免了对声线路径的分析，使智能定位器的适用性更广。这是一种很有前途的飞机框架结构声发射无损检测方法。
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[b]英文标题：[/b]
《Intelligent location of simultaneously active acoustic emission sources:
Part I》
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[b]作者：[/b]
T. Kosel and I. Grabec
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[b]最新提交年份：[/b]
2007
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[b]分类信息：[/b]

一级分类：Computer Science 计算机科学
二级分类：Neural and Evolutionary Computing 神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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[b]英文摘要：[/b]
The intelligent acoustic emission locator is described in Part I, while Part II discusses blind source separation, time delay estimation and location of two simultaneously active continuous acoustic emission sources. The location of acoustic emission on complicated aircraft frame structures is a difficult problem of non-destructive testing. This article describes an intelligent acoustic emission source locator. The intelligent locator comprises a sensor antenna and a general regression neural network, which solves the location problem based on learning from examples. Locator performance was tested on different test specimens. Tests have shown that the accuracy of location depends on sound velocity and attenuation in the specimen, the dimensions of the tested area, and the properties of stored data. The location accuracy achieved by the intelligent locator is comparable to that obtained by the conventional triangulation method, while the applicability of the intelligent locator is more general since analysis of sonic ray paths is avoided. This is a promising method for non-destructive testing of aircraft frame structures by the acoustic emission method.
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[b]PDF链接：[/b]
https://arxiv.org/pdf/0704.0047.pdf