| Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data |
| |
| 作者姓名： | 韩文花 Que Peiwen |
| |
| 作者单位： | Institute of Automatic Detection, Shanghai Jiaotong University, Shanghai 200030, P.R. China |
| |
| 基金项目： | 高比容电子铝箔的研究开发与应用项目 |
| |
| 摘 要： | With the widespread application and fast development of gas and oil pipeline network in China, the pipeline inspection technology has been used more extensively. The magnetic flux leakage （MFL） method has established itself as the most widely used in-line inspection technique for the evaluation of gas and oil pipelines. The MFL data obtained from seamless pipeline inspection is usually contaminated by the seamless pipe noise （SPN）. SPN can in some cases completely mask MFL signals from certain type of defects, and therefore considerably reduces the detectability of the defect signals. In this paper, a new de-noising algorithm called wavelet domain adaptive filtering is proposed for removing the SPN contained in the MFL data. The new algorithm results from combining the wavelet transform with the adaptive filtering technique. Results from application of the proposed algorithm to the MFL data from field tests show that the proposed algorithm has good performance and considerably improves the detectability of the defect signals in the MFL data.
|
| 关 键 词： | 管道检测 磁通泄漏 MFL 数据处理 离散小波变换 |
| 收稿时间： | 2004-12-09 |
Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data |
| |
| Han Wenhua,Que Peiwen.Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data[J].High Technology Letters,2006,12(2):170-174. |
| |
| Authors: | Han Wenhua Que Peiwen |
| |
| Abstract: | With the widespread application and fast development of gas and oil pipeline network in China, the pipeline inspection technology has been used more extensively. The magnetic flux leakage (MFL) method has established itself as the most widely used in-line inspection technique for the evaluation of gas and oil pipelines. The MFL data obtained from seamless pipeline inspection is usually contaminated by the seamless pipe noise (SPN). SPN can in some cases completely mask MFL signals from certain type of defects,and therefore considerably reduces the detectability of the defect signals. In this paper, a new de-noising algorithm called wavelet domain adaptive filtering is proposed for removing the SPN contained in the MFL data. The new algorithm results from combining the wavelet transform with the adaptive filtering technique. Results from application of the proposed algorithm to the MFL data from field tests show that the proposed algorithm has good performance and considerably improves the detectability of the defect signals in the MFL data. |
| |
| Keywords: | pipeline inspection magnetic flux leakage data discrete wavelet transform wavelet domain adaptive filtering seamless pipe noise |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
