首页|基于压缩感知的井下振动高频测量方法研究

基于压缩感知的井下振动高频测量方法研究

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井下振动信号的高频测量信息能记录有关钻具动态响应的更具体细节,有益于分析诊断井下的异常振动,但是高频测量会产生大量的测量数据,导致井下振动测量设备的数据存储压力非常大.本文提出了一种基于压缩感知技术的井下振动信号的高频测量方法.通过选择性稀疏采集和存储井下振动数据,并利用信号重构算法,恢复高频测量结果.在该方法实现的过程中,提出一种分层抗频谱泄露的傅里叶字典构建和改进的分层追踪OMP信号重构算法,显著降低了信号重构时间.仿真和实验测试结果表明:该方法对振动信号的压缩感知采集效果较好,系统压缩比为18.9,重构分贝误差为52.1 dB.该方法有效减轻了井下振动测量设备的数据存储压力,为获取井下振动的高频测量数据提供了一种新途径.
Research on a signal acquisition method for high-frequency measurement of underground vibration based on compressed sensing technology
The high-frequency measurement data of underground vibration signals can record more specific details about the dynamic response of drilling tools,which is helpful for analyzing and diagnosing abnormal vibrations underground. However,the high-frequency measurement generates a large amount of measurement data,resulting in significant storage pressure for underground vibration measurement equipment. The proposed method uses compressed sensing technology to selectively collect and store sparse underground vibration data and then recover high-frequency measurement results through a signal reconstruction algorithm. In the process of realizing this method,an innovative method of constructing a layered Fourier dictionary against spectrum leakage is proposed,and an improved OMP signal reconstruction algorithm based on layered tracking is researched and realized,which greatly reduces the time required for signal recovery. Simulation and experimental test results demonstrate the method's effectiveness,achieving a system compression ratio of 18.9 and a reconstruction error of 52.1 dB. The proposed method may greatly reduce the data storage pressure of the measuring equipment in the underground,and provides a new way to obtain high-frequency measurement data of underground vibration.

compressed sensingunderground vibrationspare dictionary

方昕、沈澜、李飞、吕方兴

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西安石油大学计算机学院 西安 710065

西安市油气及新能源开发装备智能化重点实验室 西安 710065

西安石油大学电子工程学院 西安 710065

压缩感知 井下振动 稀疏字典

国家自然科学基金企业创新发展联合基金重点项目国家重点研发计划项目陕西自然科学基金青年项目陕西省秦创原"科学家+工程师"团队陕西省高校青年创新团队西安石油大学科研创新团队西安石油大学研究生创新训练项目

U20B20292023YFC28109022023-JC-QN-04052022KXJ-1252022-ZNDXZJ2022KYCXTD01YCS23215358

2024

10.19651/j.cnki.emt.2415491

电子测量技术
北京无线电技术研究所

电子测量技术

CSTPCD北大核心
影响因子：1.166
ISSN：1002-7300
年,卷(期)：2024.47(6)
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