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为了获取特种材料表面特有的激光散斑特征,建立了一套实验室内模拟远场测量系统。利用锁相放大器进行弱信号探测。采用小波分析的方法对数据进行了预处理,采用神经网络算法对实验数据进行了自动分类识别。实验结果表明,特种材料表面激光散斑的空间强度分布可以作为识别特种材料的依据之一,并为特种材料的识别提供了一种新的有效途径。
In order to acquire the characteristic of laser speckle on the surface of special materials, a set of laboratory simulated far-field measurement system was established. Using lock-in amplifier for weak signal detection. The method of wavelet analysis was used to preprocess the data and the neural network algorithm was used to classify the experimental data automatically. The experimental results show that the spatial intensity distribution of laser speckle on the surface of special materials can be used as a basis to identify special materials and provide a new effective way to identify special materials.