基于Lyapunov指数的电阻点焊声音混沌时间序列识别

Identification of Chaos Time Series of Acoustic Emission Signals from Resistance Spot Welding Process Based on Lyapunov Exponent

以混沌理论为基础,对电阻点焊声音信号进行了分析与研究,通过计算8种不同焊接规范下时间序列的最大Lyapunov指数,发现点焊声音信号中的Lyapunov指数均大于0,揭示了声音信号中存在混沌现象,该研究为点焊质量的判断和预测开辟了有效的途径.此外,采用经典欧式几何方法描述声音信号误差较大,提出了用曲线盒维数作为特征值来量化具有混沌特性的点焊声音信息,结果表明,盒维数能反映点焊质量微小变化,可提高质量检验的准确性.

Based on chaos theory, 8 states of acoustic emission signals were studied to calculate the largest Lyapunov exponents from acquired time series data in the process of spot welding. According to calculating results, the largest Lyapunov exponents were all above zero, which revealed the chaos characteristics of acoustic emission signals. The result indicated a method to evaluate and predict the quality. The box counting dimension was implemented to quantitatively describe the characteristics of the acoustic emission signals because classical Euclidean geometry can＇t depict it exactly. The results indicate that the box counting dimension of acoustic emission signal can reflect the tiny change of spot welding quality to improve the accuracy of monitoring.