New defect characterization mass map in fringe reflection method
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摘要:
使用相移法测量物体形貌时，质量导引法在相位解包裹中起着重要作用。在检测高反光待测物表面缺陷时，相移条纹调制度常用来识别表面缺陷。本文通过将Sobel梯度与条纹调制相结合，提出了新的缺陷表征质量图，即调制度-Sobel梯度偏差质量图（modulation-sobel gradient variance，MSGV）。将解包裹相位图和原始相位图的均方根误差、峰值信噪比、信噪比3个性能作数据对比，对相位解包裹数据进行模拟测试。结果显示，MSGV的平均峰值信噪比较调制度-相位梯度偏差质量图（modulation-phase gradient variance，MPGV）提升了约1.97%，均方根误差减小了约2.91%。表明本文提出的MSGV算法相对于传统算法有一定优越性，具有更高的抗噪性和更低的解包裹误差。将所提出的方法对鼓型滚子曲面进行缺陷检测与定位，结果表明，MSGV能更好地显示出缺陷的轮廓信息。
Abstract:In the process of measuring the topography of objects by the phase-shift method, the mass-guided method plays an important role in the phase unwrapping. In the detection of surface defects of high-reflective object, the phase-shift fringe modulation is often used to identify surface defects. A new defect characterization mass map was proposed by combining Sobel gradients with fringe modulation, namely modulation-sobel gradient variance (MSGV) mass map. The root-mean-square error, peak signal-to-noise ratio, and signal-to-noise ratio of the unwrapped phase map and the original phase map were compared to simulate and test the phase unwrapped data. The results show that the average peak signal-to-noise ratio of MSGV is improved by about 1.97% compared to the modulation-phase gradient variance (MPGV) mass map, and the root-mean-square error is reduced by about 2.91%, which indicates that the proposed MSGV algorithm has certain advantages compared with the traditional algorithms, with higher noise immunity and lower unwrapping error. The proposed method was used to detect and locate the defects on the surface of the drum roller. The results show that the MSGV can better display the contour information of defects.
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Keywords:
- phase-shift fringes /
- mass map /
- modulation degree /
- defect detection
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图 2 模拟干涉条纹图和包裹相位图
Figure 2. Simulated interference fringe pattern and wrapped phase image
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图 5 添加无效区域前后的包裹相位图
Figure 5. Wrapped phase images before and after adding invalid regions
表 1 四种相位展开算法的性能参数对比
Table 1 Comparison of performance parameters of four phase-unwrapping algorithms
PDV MGV MPGV MSGV SNR 6.4643 6.0755 37.2173 38.2827 PSNR 23.2293 22.8405 53.9823 55.0476 RMSE 3.0913 3.3809 0.2095 0.2034 
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