| 刘轩宇,李 鹏,张立豪,林事力,纵 彪.联合 TCT 和 W-SpSF 的气体泄漏定位[J].电子测量与仪器学报,2023,37(5):215-222 |
| 联合 TCT 和 W-SpSF 的气体泄漏定位 |
| Gas leak location using TCT and W-SpSF |
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| DOI： |
| 中文关键词: 气体泄漏定位 DOA TCT 加权子空间拟合 稀疏表示 |
| 英文关键词:gas leakage location DOA TCT weighted subspace fitting sparse representation |
| 基金项目:江苏省重点研发计划社会发展项目(BE2015692)资助 |
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| Author | Institution |
| Liu Xuanyu | 1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology,2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science & Technology |
| Li Peng | 1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology,2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science & Technology |
| Zhang Lihao | 1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology,2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science & Technology |
| Lin Shili | 1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology,2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science & Technology |
| Zong Biao | 1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology,2. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science & Technology |
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| 中文摘要: |
| 为提高基于声学检测压力气体漏源定位方法在强噪声干扰下定位运算收敛速度和定位精度,提出一种基于加权子空间
拟合(WSF)准则的宽带测向稀疏表示模型(W-SpSF),将模型与双边相关变换算法(TCT)相结合,通过聚焦运算得到聚焦频率
处的协方差矩阵,并作为稀疏恢复的数据,最终实现 DOA 定位,得到漏源的位置。 定位过程中,采用加权子空间拟合降低噪声
的敏感程度。 分别在仿真和实验室模拟环境中对算法进行测试,经仿真结果表明,在加入强噪声干扰条件下,相比于同类算法
的运算速度提升最低 50%,定位误差减少 20%,在实测环境下,本文搭建了 8 元声传感器阵列的声源定位系统,针对气瓶模拟泄
漏能够实现定位,且漏源定位速度快,证明了算法在实际环境中的可行性。 |
| 英文摘要: |
| In order to improve the convergence speed and positioning accuracy of the pressure gas leakage source localization method
based on acoustic detection under strong noise interference, this paper proposes a wideband direction finding sparse representation model
(W-SpSF) based on weighted subspace fitting (WSF) criterion. The model is combined with the bilateral correlation transform algorithm
(TCT), and the covariance matrix at the focusing frequency is obtained by focusing operation. As the sparse recovery data, the DOA
positioning is finally realized and the location of the leakage source is obtained. In positioning process, weighted subspace fitting is used
to reduce the sensitivity of noise. In this paper, the algorithm is tested in the simulation and laboratory simulation environment
respectively. The simulation results show that under the condition of adding strong noise interference, the operation speed of the
algorithm is increased by 50% and the positioning error is reduced by 20% compared with the similar algorithm. In the measured
environment, this paper builds a sound source positioning system of 8-element acoustic sensor array, which can realize positioning for the
simulated leakage of gas cylinders, and the leakage source positioning speed is fast, which proves the feasibility of the algorithm in the
actual environment. |
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