传统的模极大值序列处理方法虽然可以保留信号特征，但降噪后的信号在奇异点有毛刺和轻微的振荡。
Although traditional processing method of modulus maximum array can retain characteristics of signal, the signal after de-noising exists thorns and slight oscillation at singularity point.
采用矩阵的奇异值分解原理，对曲面最佳适配的灵敏度矩阵进行分解，得到不确定度参数与测点随机误差的关系表达式。
The sensitivity matrix was then decomposed by singular value decomposition (SVD) method, and the relationship between the surface geometric errors and the uncertainty parameters was formulated.
对二值图像进行数学形态处理的检测结果进一步证明了该奇异点分割和检测方案的有效性。
Finally, binary morphological operations are applied to the binary image to get the detection result. The experiment results show that the new scheme is an effective means for anomalies detection.
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