基于小波和支持向量机的桩基缺陷检测技术研究
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摘要
灌注桩基础(简称桩基)是建于地下的钢筋水泥混凝土构件，用于承载桥梁或楼房等土木建筑。由于主观或客观的因素，桩基建造完成之后会存在一定缺陷，桩基缺陷直接影响其承载性能，桩基的承载性能关系到建筑工程的质量、安全和使用寿命。缺陷严重的桩基难以承载额定的建筑负荷，很容易导致重大工程事故的发生，甚至造成人身和国家财产的重大损失。因此，桩基建成后必须对其是否存在缺陷和缺陷程度进行严格的检测，鉴定桩基的质量类别，对缺陷严重的桩基还须进行相应的处理。
我国桩基缺陷检测标准中规定四种方法，分别是低应变应力波反射法(简称应力波反射法)、超声透射法、高应变检测法和钻芯法。其中，应力波反射法是最主要检测方法。虽然应力波反射法存在对桩基缺陷类型、缺陷程度和缺陷位置检测的准确性差的缺点，但是，应力波反射法检测成本低、检测快捷，因此成为目前我国使用最普遍的方法。本文应用小波分析、支持向量机、特征向量的视窗提取以及一维杆件波动等数学理论改进现有的应力波信号的分析方法，以提高桩基缺陷检测的准确性。
依据小波理论和关联度理论，从典型的桩基缺陷波形中提取缺陷子波，构建了专用小波基函数；应用关联度理论和方法确保了专用小波基函数与缺陷子波具有较好的相似性；从而提高专用小波基函数对桩基缺陷分析的准确性和对不同地质环境的适应性。
针对现有特征向量的提取方法存在对信号时间信息缺失和不能识别桩基多处缺陷的不足，本文提出了特征向量的视窗提取方法，阐述了视窗宽度及其平移步长参数的选择原则；针对特征向量的视窗提取方法，构建了特征向量矩阵模型；进行了基于视窗提取的桩基多缺陷检测实验和准确性分析。
依据模式识别理论，利用支持向量机分类性能的优势和桩基缺陷的特点，改进了支持向量机多分类器结构，提出了多层一对一型支持向量机分类器及其模型；对多层支持向量机分类器和PB分类器进行了对比实验和性能分析。
分析了现有桩基缺陷程度测量结果的不确定度因素，利用缺陷分类的功率谱等中间结果，提出了基于功率谱的桩基缺陷位置和缺陷程度的测量方法，为桩基缺陷程度的测量提供了简便有效的方式。
Cast-in-place pile foundation (hereinafter referred to pile foundation) is builtof reinforced concrete underground structures, used for carrying civil constructionsuch as bridges or buildings. Certain pile foundation defects will exist after thecompletion because of the subjective or the objective factors, which directly affectthe pile load-bearing properties related to the quality, safety and service life of theconstruction. The pile foundation with the serious defects can not carry rated loadof the building, it can easily lead to major engineering accidents, or even result insignificant loss of personal and state property. Therefore, after the pile foundation isbuilt, the presence and the extent of defects of pile foundation must be placed onrigorous detection to identify the quality type of the pile foundation. The pilefoundation with the serious defects has to be dealt with accordingly.
There are four detection methods prescribed by the pile foundation defectdetection standard, the low strain stress wave reflected method (referred to as stresswave reflection method), the ultrasonic transmission method, the high straindetection method and the borehole method. The stress wave reflected method is themost important detection methods among them. This method has a disadvantage ofpoor accuracy of detecting the pile foundation type, degree and position. However itis widely used in our country because of its low cost and shortcut. Wavelet analysis,support vector machine, window extraction of feature vector, as well asone-dimensional component and other mathematical theories are applied to improvethe existing stress wave signal analysis methods, which to improve the accuracy ofdetecting result
Based on wavelet theory and relation degree theory, this thesis extracts thedefect wavelet from a typical defect waveform, and constructs pile foundationwavelet function. The relation degree theory and method applied can ensure goodsimilarity between pile foundation wavelet function and defects wavelet, whichimprove the accuracy of detecting results and the adaptability of differentgeological environments by applying pile foundation wavelet function.
The existing feature vector extraction method has the disadvantage of thesignal time information missing and lacking the ability of detecting multi-defect,this thesis proposed the window extraction method of feature vector, explained howto choose the parameters of window width and translational step. The matrix modelof feature vector was built for window extraction method. The experiment and theaccuracy analysis of pile defects detection based on window extraction method were made.
The support vector machine classification performance advantages and thecharacteristics of various pile defects were adopted to improve support vectormachine multiple classifiers structure. The multi-layer one-to-one support vectormachine classifiers and its model based on pattern recognition theory wereproposed. The comparative test and performance analysis between multi-layersupport vector machine classifiers and PB classifiers were carried out.
The Thesis analyzed uncertainty factors of the current pile defect degreemeasurement and proposed the power spectrum based measurement methods of thepile defect location and defect levels by applying the power spectrum of defectclassification and intermediate results, etc. It provide of a simple and effectivemeasurement of the degree of pile defect.
我国桩基缺陷检测标准中规定四种方法，分别是低应变应力波反射法(简称应力波反射法)、超声透射法、高应变检测法和钻芯法。其中，应力波反射法是最主要检测方法。虽然应力波反射法存在对桩基缺陷类型、缺陷程度和缺陷位置检测的准确性差的缺点，但是，应力波反射法检测成本低、检测快捷，因此成为目前我国使用最普遍的方法。本文应用小波分析、支持向量机、特征向量的视窗提取以及一维杆件波动等数学理论改进现有的应力波信号的分析方法，以提高桩基缺陷检测的准确性。
依据小波理论和关联度理论，从典型的桩基缺陷波形中提取缺陷子波，构建了专用小波基函数；应用关联度理论和方法确保了专用小波基函数与缺陷子波具有较好的相似性；从而提高专用小波基函数对桩基缺陷分析的准确性和对不同地质环境的适应性。
针对现有特征向量的提取方法存在对信号时间信息缺失和不能识别桩基多处缺陷的不足，本文提出了特征向量的视窗提取方法，阐述了视窗宽度及其平移步长参数的选择原则；针对特征向量的视窗提取方法，构建了特征向量矩阵模型；进行了基于视窗提取的桩基多缺陷检测实验和准确性分析。
依据模式识别理论，利用支持向量机分类性能的优势和桩基缺陷的特点，改进了支持向量机多分类器结构，提出了多层一对一型支持向量机分类器及其模型；对多层支持向量机分类器和PB分类器进行了对比实验和性能分析。
分析了现有桩基缺陷程度测量结果的不确定度因素，利用缺陷分类的功率谱等中间结果，提出了基于功率谱的桩基缺陷位置和缺陷程度的测量方法，为桩基缺陷程度的测量提供了简便有效的方式。
Cast-in-place pile foundation (hereinafter referred to pile foundation) is builtof reinforced concrete underground structures, used for carrying civil constructionsuch as bridges or buildings. Certain pile foundation defects will exist after thecompletion because of the subjective or the objective factors, which directly affectthe pile load-bearing properties related to the quality, safety and service life of theconstruction. The pile foundation with the serious defects can not carry rated loadof the building, it can easily lead to major engineering accidents, or even result insignificant loss of personal and state property. Therefore, after the pile foundation isbuilt, the presence and the extent of defects of pile foundation must be placed onrigorous detection to identify the quality type of the pile foundation. The pilefoundation with the serious defects has to be dealt with accordingly.
There are four detection methods prescribed by the pile foundation defectdetection standard, the low strain stress wave reflected method (referred to as stresswave reflection method), the ultrasonic transmission method, the high straindetection method and the borehole method. The stress wave reflected method is themost important detection methods among them. This method has a disadvantage ofpoor accuracy of detecting the pile foundation type, degree and position. However itis widely used in our country because of its low cost and shortcut. Wavelet analysis,support vector machine, window extraction of feature vector, as well asone-dimensional component and other mathematical theories are applied to improvethe existing stress wave signal analysis methods, which to improve the accuracy ofdetecting result
Based on wavelet theory and relation degree theory, this thesis extracts thedefect wavelet from a typical defect waveform, and constructs pile foundationwavelet function. The relation degree theory and method applied can ensure goodsimilarity between pile foundation wavelet function and defects wavelet, whichimprove the accuracy of detecting results and the adaptability of differentgeological environments by applying pile foundation wavelet function.
The existing feature vector extraction method has the disadvantage of thesignal time information missing and lacking the ability of detecting multi-defect,this thesis proposed the window extraction method of feature vector, explained howto choose the parameters of window width and translational step. The matrix modelof feature vector was built for window extraction method. The experiment and theaccuracy analysis of pile defects detection based on window extraction method were made.
The support vector machine classification performance advantages and thecharacteristics of various pile defects were adopted to improve support vectormachine multiple classifiers structure. The multi-layer one-to-one support vectormachine classifiers and its model based on pattern recognition theory wereproposed. The comparative test and performance analysis between multi-layersupport vector machine classifiers and PB classifiers were carried out.
The Thesis analyzed uncertainty factors of the current pile defect degreemeasurement and proposed the power spectrum based measurement methods of thepile defect location and defect levels by applying the power spectrum of defectclassification and intermediate results, etc. It provide of a simple and effectivemeasurement of the degree of pile defect.
引文
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