首页|期刊导航|高技术通讯（英文版）|Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data
高技术通讯（英文版）2006，Vol.12Issue(2)：170-174,5.
Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data
Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data
摘要
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.关键词
pipeline inspection/magnetic flux leakage data/discrete wavelet transform/wavelet domain adaptive filtering/seamless pipe noiseKey words
pipeline inspection/magnetic flux leakage data/discrete wavelet transform/wavelet domain adaptive filtering/seamless pipe noise分类
信息技术与安全科学引用本文复制引用
Han Wenhua,Que Peiwen..Wavelet domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data[J].高技术通讯（英文版）,2006,12(2):170-174,5.基金项目
Supported by the High Technology Research and Development Programme of China ( No. 2001AA602021). （ No. 2001AA602021）
