数据融合技术在棒材缺陷超声识别中的应用

不同类型的缺陷对不同类型、位置和姿态的超声波换能器的敏感程度不同，数据融合技术可充分利用各种数据的有效特征，提高缺陷识别的可靠度。描述了局部决策和数据融合技术的基本理论，提出了基于后验概率的数据融合方法，以大型棒材锻件缺陷识别为例，通过感知器算法实现了典型缺陷的局部决策自动识别，并通过基于后验概率的数据融合技术提高整体决策的可靠度。

Application of Data Fusion Based Flaw Recognition in Cylinder Ingots

The basic theories of local decisions and data fusion techniques are depicted. The common flaws recognition in heavy cylinder ingots has been studied with data fusion techniques using ultrasonic method. Different flaws have different sensitivity to different type, position and stance of probes, and data fusion techniques can make the full use of the information. Local decisions of each group of transducers can be made through perceptron algorithm according to the time and frequency domain characteristics of flaws. A data fusion based global decision is made in which the criterion is based on the maximum posterior probability of different types of flaws. The recognition results can be improved by using data fusion techniques in decision-order in which three groups of different type, position and stance of transducers are used.