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中文摘要：
为解决超声检测缺陷精确识别问题,综合运用检测数据和专家知识,研究一种基于置信规则库（belief-rulebase,BRB）和证据推理（evidential reasoning,ER）进行超声检测缺陷识别的方法。提出一种融合多种特征信息的BRB-ER缺陷识别模型,利用最小均方误差算法进行模型初始参数的优化,从而提高缺陷识别的准确性。通过超声检测手段获取某航空材料的缺陷数据,并对所提出识别方法进行验证。试验结果显示：该方法能够准确地进行缺陷识别,并可根据已有的产品缺陷类型进行训练,建立更加准确的缺陷识别模型。
英文摘要：
To improve accuracy in defects recognition by ultrasonic testing, a method of defects recognition based on belief-rule-base （BRB） and evidential reasoning （ER） is proposed according to test data and expert knowledge. Firstly, a new model of defects recognition integrating feature information based on belief-rule-base（BRB） and evidential reasoning（ER） is presented, and then the initial parameters of model are optimized with the minimum mean square error algorithm to improve the accuracy of defects recognition. Finally, ultrasonic testing is used to get the defect data of one aeronautical material and a case study is carried out to illustrate the ability and efficiency of the proposed method. The study results show that the method can recognize defects accurately. A more accurate defects recognition model is established based on exercises on existing product defects.
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