基于金属磁记忆效应的井下套管预测故障研究.rar

基于金属磁记忆效应的井下套管预测故障研究

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摘要： 大庆油田的井下套管损坏（套损）严重，近80 %的套损是由于地质因素和工程因素造成的，这些因素使得套管受到非均匀载荷的作用而产生应力集中或者微观裂纹，进而导致套管弯曲、变形或错断。传统的射线，漏磁检测等方法只能检测已经出现裂纹的套管，无法预测由应力集中导致疲劳的早期故障，使得套管寿命预测和预报受到了限制。而金属磁记忆检测技术可以有效判断出套管应力集中区，做到预测和预报早期诊断；利用基于磁记忆效应的检测系统可以快速、准确地检测在役套管的应力集中区所产生的磁记忆信号，从而可快速、准确地判断套管的应力集中区和故障状况。本论文围绕金属磁记忆信号的采集和特征量的提取进行研究，准确确定应力集中区，消除外界噪声的影响。论文主要研究内容包括：
　　1. 介绍了金属磁记忆检测技术的发展历程，阐述了金属磁记忆早期诊断铁磁构件疲劳失效的重要意义。
   2. 金属磁记忆信号是地磁场在套管应力集中区域的“记忆”表现，信号很微弱，且易受到外界噪声污染，从而影响实际应用中对套管损伤程度的准确评估。对井下数据采用数字平滑技术预处理，并利用傅里叶变换进行频谱分析，从而获得磁记忆信号的主要能量集中区。在此基础上，引入切比雪夫低通滤波器对信号进行消噪处理，利用梯度极大值特征准确判断套管的应力集中区。
  3．为了进一步提取磁记忆信号的奇异特征量，从时——频角度对磁记忆信号进行分析。采用一维离散小波变换和自适应阈值方法对信号进行多尺度分解，将信号的低频部分和高频部分全部显示出来。通过与之前的频域分析对比，可知低频部分最为接近原始信号，这样避免了其他频段对磁记忆信号的干扰。
  4. 提出了新的组合特征量诊断方法，通过BP神经网络实现了磁记忆信号特征量和安全等级的非线性关系，保证可靠地判断套管应力集中危险区域。通过实验验证所提方法的有效性和可行性。
   关键词：套管；金属磁记忆；故障；预测；应力集中；小波分析

Casing failure predicting based on magnetic memory
Abstract：The damage of the damaging oilfield of downwhole casing is sever. Nearly 80%of the damage of the casing is due to geological factors and engineering factors which lead to  the casing led to tube bending, deformation or dislocation because of the role of non-uniform load and stress concentration or micro-cracks.traditional method for example ray detection and the detection of the magnetic flux leakage casing cracks can only detect the cracks which has occurred, but not to predict early failure caused by the Stress concentration .The life of the casing and the prediction of the casing are restricted because of the situation.however The metal magnetic memory technology can effectively determine the casing stress concentration area, to predict and forecast the result of early diagnosis .Based on the use of magnetic memory effect detection  the technology can quickly and accurately detect the magnetic memory signals of stress concentration due to the stress concentration area, which which can quickly and accurately determine the casing stress concentration area and fault conditions.main contend of the paper  is about  the collection and feature extraction of metal magnetic memory signal to study which accurately determine the stress concentration area, eliminating the effects of outside noise.The main research contents include:
1 Introduces the development of metal magnetic memory testing technology, describes the importance of early diagnosis of ferromagnetic metal magnetic memory component fatigue failure.
2. Magnetic memory signal is the performance of the memory of the stress concentration area owning to the geomagnetic field. the signal is very weak and vulnerable to external noise pollution, thus affecting the accurate assessment of the extent of damage to the casing during the practical application.Downhole data preprocessing using digital smoothing techniques, and the use of Fourier transform spectral analysis can obtain the stress concentration aera.On this basis, the introduction of Chebyshev low-pass filter the signal denoising using gradient maxima characterized accurately determine stress concentration cannula.
3.In order to extract the singular characteristic quantity of magnetic memory signal, we analysis the signal from the angle of  the time --frerquency. One-dimensional discrete wavelet transform and adaptive threshold method for multi-scale decomposition of the signal, the low-frequency and high-frequency portion of the signal part of the whole show. By contrast with the previous frequency domain analysis, we can see that some of the signal will be most close to the original low-frequency signal, thus avoiding interference with other bands magnetic memory signal.
4. Proposed a new combination of features volume diagnostics, BP neural network to achieve a non-linear relationship between the magnetic memory signal features and security levels can ensure casing stress concentration reliably determine the danger zone. the experiment proposes the method which can verify the effectiveness and feasibility.
Keyword：Casing; Metal magnetic memory; Fult; Forecasting; Stress Concentration; Wavelet analysis

目 录

摘要 I
Abstract II
目 录 1
第-章  绪 论 3
1.1引言 3
1.2研究背景和意义 4
1.3国内外研究现况 4
1.4论文研究内容 8
第二章 金属磁记忆检测套管信号处理方法 9
2.1 磁记忆信号采集 9
2.2  数据实验 9
2.2.1金属套管加力实验设计 9
2.2.1.1 套管加压设施模型设计 10
2.2.1.2  套管加力实验装置 13
2.3原始采样信号分析 14
2.4磁记忆信号的频域分析与滤波 16
2.4.1磁记忆信号的频域结果分析 17
2.4.2磁记忆信号的切比雪夫滤波 18
2.5套管磁记忆信号的小波分析 21
2.5.1套管磁记忆信号的强制去噪 21
2.5.2套管磁记忆信号的阈值去噪 27
第三章  套管应力集中的磁记忆非线性定量反演 33
3.1  金属磁记忆的非线性定量反演 34
3.2  金属磁记忆信号的特征量提取 34
3.3 神经网络 39
3.3.1  BP神经网络算法 39
3.4  实验结果 45
结论 48
参考文献 49