摘要
分析了检测信号的频谱分布,采用小波分析的方法提取了能够描述点焊超声波频谱分布特征及功率特征的超声检测特征值.由这些检测特征值构成超声特征矢量,结合BP神经网络的模式识别功能对点焊直径进行精确分类与识别.与传统时域分析方法相比较,具备更高识别能力、更高的识别效率、更少的识别特征以及更小的外部干扰因素.
The spectrum of testing signal for the spot weld test is analyzed and the characteristic vector which can indicate the characteristics of the signal spectrum of ultrasonic signals for spot weld is obtained.Through using the vector as input data,an artificial neural network is proposed to classify the resistance spot welds in the different diameter level.The testing method proposed in the paper has the advantages of higher recognition ability,higher efficiency and smaller interference factors compared to the traditional methods.
出处
《焊接学报》
EI
CAS
CSCD
北大核心
2009年第10期76-80,共5页
Transactions of The China Welding Institution
关键词
电阻点焊
超声检测
神经网络
特征矢量
resistance spot weld
ultrasonic testing
artificial neural network
characteristic vector
