中文摘要：

为解决批量钻削工序质量检测问题，采集各工步加工过程声发射监测信号，提出一种基于声发射信号高阶谱分析的批量钻削质量检测方法。基于统计意义上正常钻削过程声发射信号符合高斯分布的假说，对采集的信号进行小波包消噪后，计算批量钻削工步信号的双谱切片，描述信号偏离高斯分布的程度，并分析其与钻削加工工步质量的映射关系，实现钻削加工工步质量检测。’实验及分析结果表明：基于声发射信号双谱切片提取的信号特征可有效辨别批量钻削工步中的质量不合格品。

英文摘要：

In order to solve the problem of quality detection on batch drilling, after collecting the acoustic emission signal during the working step process, a higher-order spectrum analysis method based on acoustic emission signal is proposed in this paper. According to the hypothesis that the characteristics of acoustic emission signal of an normal drilling process meet the criteria of Gaussian distribution, the wavelet packet method was used to realize de-noising for the acquired acoustic emission signals, and then the bi-spectrum slice of the acoustic emission signal from the batch drilling process was calculated one by one, the statistical dispersion deviated from the Gaussian distribution of these bi-spectrum slices could be obtained. Finally the mapping relationship between the dispersion and the drilling step quality was built to inspect the batch drilling slice of the acoustic emission signal can be used quality. Experimental results and analysis show that the bi-spectrum to identify the unqualified product on batch drilling effectively.