铁氧体裂纹检测自相关处理与多特征辨识方法

Autocorrelation processing and multiple characteristic recognition for ferrite crack detection signal

铁氧体缺陷裂纹严重影响其电气性能,在现代电子信息技术和环保产业大量需求铁氧体材料的背景下,传统人工检测方法已经难以满足产品的检测需求。提出了一种基于初始磁导率的铁氧体裂纹检测新方法,根据铁氧体工件小尺寸、窄初始磁化区的特性,建立检测模型,设计检测工况;针对微弱裂纹脉冲常被干扰淹没,设计双探头传感器,将原有单脉冲信号变为有相关性的双脉冲输出;结合双脉冲信号自相关函数的独有特性,综合多个特征进行裂纹辨识。72组实验数据证明,多特征辨识方法能够准确有效定性区分被检测对象是否存在裂纹。

Crack defects of ferrite affect its electrical properties seriously;under the background of great demand of ferrites in modem electronic information technology and environmental protection industry, traditional manual test methods are difficult to meet the requirement of product testing. This paper presents a new ferrite crack detection method based on the initial permeability. According to the ferrite workpiece characteristics of small size and narrow initial magnetization zone, the detection model is established and the detect condition is designed. Aiming at the fact that the faint crack pulse is often submerged in interference, a dual probe sensor is designed, which uses correlated double pulse output to replace the original single pulse signal. Considering the unique characteristics of the autoeorre- lation function of the double pulse signal, the cracks are identified with multiple characteristic recognition. 72 groups of experiment data show that the multiple characteristic recognition method can accurately, effectively and qualitative- ly distinguish whether the crack exists in the tested object.