特征点压缩算法在分布式光纤桩基检测中的应用

Application of feature point compression algorithm to pile foundation detection using distributed optical fiber

布里渊散射光时域反射测量技术(BOTDR/A)是一种重要的分布式光纤感测技术。采用BOTDR/A技术进行分布式光纤桩基检测时,海量的检测数据需要平滑去噪。介绍了分布式光纤桩基检测中最常用的感测光纤埋设工艺、海量检测数据的特点、平滑去噪在检测数据处理分析方面的作用,并据此提出了特征点压缩算法(一种新的平滑去噪方法)的概念和实现流程;结合工程实测数据,分析了该法的平滑去噪效果,验证了该法的实际应用情况。研究结果表明:该方法用于桩基检测数据处理是十分有效的,与常规算法对比,该方法简单高效,能够在不丢失检测数据特征趋势的同时对数据进行较好的平滑去噪,实际应用达到了满意的效果,其结果可在分布式光纤桩基检测的数据处理中推广应用。

Brillouin optical time domain reflectometer/analysis （BOTDR/A） is one kind of important distributed optical fiber sensing technology. Using the BOTDR/A-based distributed optical fiber technology to detect deformation of pile foundation, the vast amounts of detection data need smoothing and denoising. The paper introduces most frequently used embedded techniques of the sensing optical fiber, the characteristics of detection data, the role of massive data smoothing and denoising on the detection data handle and analysis. We developed the concept and proposed the implementation process of the feature point compression algorithm （a new smoothing and denoising method）. Based on data measured from practical engineering, the smoothing and denoising effect of the method is analyzed, and its applicability is also verified. The results show that the proposed method is simple and efficient in processing the data from pile foundation detection, compared with the conventional algorithm, it can smooth and denoise data without losing the characteristics trend of detected data, and can achieve satisfactory results as expected. It can be applied to the distributed data processing of optical fiber pile foundation detection.