| 一种油管缺陷量化识别技术 |
| |
| 引用本文： | 王太勇,胡世广,杨涛,秦旭达,赵坚. 一种油管缺陷量化识别技术[J]. 中国机械工程, 2005, 16(20): 1802-1804,1820 |
| |
| 作者姓名： | 王太勇 胡世广 杨涛 秦旭达 赵坚 |
| |
| 作者单位： | 天津大学,天津,300072 |
| |
| 基金项目： | 天津市自然科学基金资助项目(993802411) |
| |
| 摘 要： | 对油管缺陷量化识别技术进行了研究,基于缺陷分类,通过分析缺陷漏磁信号,选取了信号特征量并进行了分类;利用人工神经网络解决了信号特征量与缺陷几何外形特征之间的非线性映射问题;建立了基于特征分类的油管缺陷量化识别模型。实验表明,该技术能满足油管缺陷量化识别精度要求,应用前景广泛。
|
| 关 键 词： | 油管 量化识别 信号特征 神经网络 |
| 文章编号： | 1004-132X（2005）20-1802-03 |
| 收稿时间： | 2004-07-22 |
| 修稿时间： | 2004-07-22 |
A Technology of Quantitative Recognition for Oil Well Tubing Defects |
| |
| Wang Taiyong,Hu Shiguang,Yang Tao,Qin Xuda,Zhao Jian. A Technology of Quantitative Recognition for Oil Well Tubing Defects[J]. China Mechanical Engineering, 2005, 16(20): 1802-1804,1820 |
| |
| Authors: | Wang Taiyong Hu Shiguang Yang Tao Qin Xuda Zhao Jian |
| |
| Affiliation: | Tianjin University, Tianjin, 300072 |
| |
| Abstract: | The technology of quantitative recognition for oil well tubing defects was studied.By analyzing magnetic flux leakage signals of the defects,the characteristic quantities of the signals were figured out and classified on the basis of defect classification.A neural network was applied to deal with the problem of nonlinear mapping between the characteristic quantity of the signals and the geometrical characteristic of defects.Based on the classification of signal characteristic,a model of quantitative recognition for oil well tubing defects was built.Experiments show that this technology will find a wide application with its ability of being able to satisfy the accuracy requirements of quantitative recognitions for oil well tubing defects. |
| |
| Keywords: | oil well tubing quantitative recognition signal characteristic neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
