多频涡流无损检测的干扰抑制和缺陷检测方法研究
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摘要
多频涡流检测作为一种涡流无损检测新技术,具有实现检测过程干扰抑制和被检对象多参数检测的优点。本文对多频涡流检测中的信号参数估计及混合运算、同步合成激励峰值因数优化及检测信号谱分析、线性调频激励及检测信号细化谱分析、脉冲激励的多频分析等进行深入研究,并应用于干扰抑制、缺陷检测等方面。主要研究内容及创新如下:
以时谐电磁场理论为基础,探讨了多频涡流检测问题的物理模型和计算方法,并对线圈涡流传感器的感生涡流分布和阻抗特性进行有限元仿真研究。从麦克斯韦方程组出发,对正弦信号激励下的时谐电磁场问题采用电磁位函数进行数学表述。对典型圆柱形线圈涡流传感器,简化为轴对称模型,在轴坐标系下,分析涡流效应对线圈等效阻抗的影响。对任意涡流检测问题,采用有限元法表述其数值计算方法。介绍了常用的多频涡流检测数据处理方法,如线性代数法、相位旋转相减法、频谱分析法等。采用Ansoft Maxwell有限元分析软件,建立涡流检测问题模型,仿真研究了激励频率、提离高度、被检对象厚度、缺陷等对涡流场分布和线圈等效阻抗的影响。
研究了基于参数混合运算的多频涡流检测技术,采用正交锁定放大器实现检测信号参数估计,提出基于线性最小二乘法的检测信号参数估计方法,对管道检测中支撑干扰和双频涡流检测中提离效应的抑制方法进行研究。在多频涡流检测中,当激励信号的频率分量数目较少时,提取各频率分量的两个参数进行混合运算,确定被检对象特性。讨论了采用带通滤波器和正交锁定放大器的多频涡流检测信号参数估计方法,主要采用硬件实现,成本较高。对正弦信号进行线性化处理,提出基于线性最小二乘法的多频涡流检测信号参数估计方法,降低硬件实现成本。对管道检测中的支撑干扰抑制方法进行研究,采用相位旋转相减法,消除了检测过程的支撑干扰,增强了缺陷信号。对双频涡流检测中的提离效应抑制方法进行研究,分析提离和缺陷对各频率分量的影响差异,在检测信号分量图中提出“缺陷区域”,区分提离信号和缺陷信号,从而抑制提离效应。
研究了基于同步合成激励和谱分析的多频涡流检测技术,提出基于遗传算法的多频激励信号峰值因数优化方法,采用矩形激励线圈的涡流传感器,基于谱能量变化实现缺陷长度检测,基于主成分分析法实现缺陷分类。设计矩形激励线圈的涡流传感器,将被检对象表面的涡流场转变为匀强场,通过检测缺陷引起的扰动场,识别缺陷特征参数。在同步合成多频激励信号发生中,频率分量数目的增加必然导致激励信号峰值因数的增大,对涡流传感器驱动电路的工作电压范围要求加宽。文中提出基于遗传算法进行多频激励信号峰值因数优化,定义适应度函数,计算得到各频率分量的优化初始相位。与直接搜索算法相比,其明显提高了搜索速度。采用多频激励后,通过分析多频涡流检测信号的谱能量变化,可以对缺陷长度进行定量检测。当涡流传感器进入缺陷时,检测信号谱能量达到最大值;当涡流传感器离开缺陷时,检测信号谱能量达到最小值。提取最大值和最小值之间的扫描时间,结合涡流传感器的移动速度,即可得到缺陷长度。不同类型的缺陷对多频涡流检测信号中各频率分量影响程度是不同的,即谱图曲线变化趋势不同。采用主成分分析法,降低信号维数,提取特征量,实现缺陷分类。
研究了基于调频激励和细化谱分析的多频涡流检测技术,提出“调制多频涡流检测技术”,并定义谱图能量、谱图重心、谱图峰度、谱图偏度、频谱差峰值频率点等五个特征量,应用于缺陷识别及分类和内部缺陷深度位置识别。文中提出的调制多频涡流检测技术,是将调频信号作为涡流传感器的激励信号,通过对检测信号多级放大,采集并进行细化谱分析,进而实现干扰抑制或者多参数检测。与常规多频涡流检测技术相比,该技术的优点为:采用调频信号,降低了峰值因数;调频信号是多个频率信号的连续激励,避免了多路复用模块的使用,减少了检测时间;将检测信号的离散谱转变为连续谱,易于谱图的特征提取和分析。该技术的不足之处为:如果需要采用各频率分量参数的混合运算进行被检对象特征识别,则该技术不能满足。研究中,激励信号选为常用的线性调频信号,驱动涡流传感器,放大并采集检测信号,采用Chirp-Z变换进行细化谱分析。对检测信号施加Tukey Window函数,有效抑制了其谱图中的纹波。结合检测信号谱图特点,定义谱图能量、谱图重心、谱图峰度、谱图偏度、频谱差峰值频率点等五个特征量用于缺陷的多参数检测。通过涡流检测实验和数据分析,谱图能量可用于缺陷识别;谱图重心、谱图峰度和谱图偏度可用于缺陷分类;频谱差峰值频率点可用于内部缺陷深度位置识别。
将脉冲激励看作一种多频信号,研究了脉冲涡流检测的多频分析方法,在幅频谱中提出“谱相对变化”用于缺陷分类,在相频谱中提出“相位过零点”用于缺陷分类和提离抑制。广义上讲,脉冲涡流检测技术是多频涡流检测技术的一种,其时域分析方法已经得到了比较广泛的研究。文中对脉冲激励信号的占空比和时移位置进行比较选择,并将其看作一组不等幅正弦谐波的合成信号,分析脉冲涡流检测信号的频谱特性。由于脉冲激励信号中各频率分量能量随着频率的增加迅速减小,在检测信号幅频谱中,采用相对变化量能更有效地发现不同类型缺陷对各谐波分量的影响特点。提出“谱相对变化”特征量可有效地应用于脉冲涡流检测中的缺陷分类,其变化明显,物理意义清楚。对于表面缺陷,高频谐波分量的相对变化量恒定或略有上升趋势;而对于内部缺陷,高频谐波分量的相对变化量具有明显的下降趋势。这种变化是由于高频谐波分量的趋肤深度减小导致的。在相频谱中,低频谐波分量的相位值为正,相位值随着频率的增加逐渐减小并变为负,存在一个“相位过零点”。对于不同的提离高度,相位过零点保持不变;对于表面缺陷,相位过零点比无缺陷时变大;对于内部缺陷,相位过零点比无缺陷时变小。但当缺陷较小时,相位过零点的变化比较微弱,缺陷分类作用并不明显。
设计和实现了用于参数混合运算和谱分析的多频涡流检测系统。多频涡流检测系统的设计实现比其它类型涡流检测系统复杂。用于参数混合运算的多频涡流检测系统利用DDS技术发生多路正弦信号并通过加法器合成多频激励信号,采用带通滤波器和正交锁定放大器实现微弱涡流检测信号的参数估计。用于谱分析的多频涡流检测系统采用虚拟仪器技术实现,采用D/A单元发生任意多频激励信号,对微弱涡流检测信号经过充分放大后,采集并进行谱分析。
As one new eddy current nondestructive testing (NDT) technology, multi-frequency eddy current testing (MFECT) has the merits of interference elimination in testing procedure and multi-parameter detection of unit under test (UUT). This paper lucubrated signal parameter estimation and mixing, crest factor optimization of synchronously synthetical excitation and spectrum analysis of testing signals, linear frequency modulation excitation and zoom spectrum analysis of testing signals, multi-frequency analysis of pulsed excitation, et al in MFECT technology, and these are applied in interference elimination, defect detection and so on. The brief of these researches and the novel approaches are as follows:
Based on time harmonic electromagnetic field theory, physical model and calculation method of MFECT are discussed. Induced eddy current distribution and impedance characteristic of the probe coil are simulated and researched with finite element method. According to Maxwell law, time harmonic electromagnetic field problem based on sine signal excitation is expressed mathematically with electromagnetic potential. The typical eddy current testing problem with an aircore coil is simplified and analyzed in cylindrical coordinate, and then the coil’s equivalent impedance affected by eddy current effect is analyzed. The arbitrary eddy current testing problem is expressed and calculated with finite element method. The common data processing methods of MFECT including linear algebra method, phase rotation and subtraction, spectrum analysis method are introduced. The eddy current testing problem is modeled with Ansoft Maxwell finite element software, and then eddy current distribution and coil’s equivalent impedance characteristic influenced by excitation frequency, lift-off height, UUT’s thickness, defects and so on are simulated and researched.
MFECT technology based on parameter mixing is researched. Testing signal’s parameter estimation method based on orthogonal lock-in amplifiers is introduced and a new method based on linear least square method is proposed. Support interference elimination in tube testing and lift-off effect elimination in dual-frequency eddy current testing are researched. When the amount of frequency components is relative small in MFECT, two parameters of each frequency component are extracted and mixed to characterize UUT. Parameter estimation method based on band pass filters and orthogonal lock-in amplifiers is discussed but it takes a high hardware cost. Sine signal linearzed, a new method for MFECT signal’s parameter estimation based on linear least square method is proposed, and it reduces the hardware cost. Support interference elimination method is researched. The support interference is removed based on phase rotation and subtraction, so the defect signal is enhanced. Lift-off effect elimination in dual-frequency eddy current testing is researched. The component variation difference between lift-off and defects is analyzed and the defect zone is proposed to distinguish lift-off signals and defect signals and to realize lift-off effect elimination.
MFECT technology based on synchronously synthetical excitation and spectrum analysis method is researched. Crest factor optimization of the multi-frequency excitation signal based on genetic algorithm is proposed. The eddy current sensor with a rectangular excitation coil is adopted. The length of defects is quantitatively detected based on spectrum energy variation, and the classification of defects is realized based on principal component analysis (PCA). The eddy current sensor with a rectangular excitation coil is designed which can convert eddy current field in the surface of UUT to a uniform field. Defect characteristic can be identified by detecting the disturbance field which arises from defects. When the multi-frequency excitation signal is generated in synchronously synthetical mode, the crest factor of excitation signals will increase with the amount of frequency components rapidly. Therefore, that broadens the work voltage range of eddy current sensor’s driving circuit. An optimization method of excitation signal’s crest factor based on genetic algorithm is proposed. A fitness function is defined and the optimized initial phase of each frequency component is got. Compared with direct search algorithm, this method improves the search speed obviously. When the eddy current sensor is drived with a multi-frequency signal, the length of defects can be quantitatively detected based on spectrum energy variation. The spectrum energy reaches maximum when the eddy current sensor comes into defects. The spectrum energy reaches minimum when the eddy current sensor departs from defects. The length can be calculated with the time span between maximum and minimum and the moving speed of the eddy current sensor. Each frequency component is affected differently and the trend of spectrum curve varies differently when different types of defects are detected. The signal dimension is reduced based on PCA and defect classification is realized.
MFECT technology based on frequency modulation excitation and zoom spectrum analysis method is researched. Modulated MFECT is proposed, and five features including spectrum energy, spectrum barycenter, spectrum kurtosis, spectrum skewness and spectrum difference’s peak frequency point are defined to realize identification and classification of defects and depth detection of inner defects. Modulated MFECT technology proposed in this paper adopts frequency modulation signals as the excitation signal of eddy current sensors. After a multi-level amplification, testing signals are sampled and analyzed in frequency domain to realize interference elimination or multi-parameter detection. Compared with conventional MFECT technology, the crest factor of excitation signals is reduced because of frequency modulation excitation, and the testing time is reduced because that the frequency modulation signal is a continuous excitation of many frequency components and the multiplex module is not needed. As a result, the discrete spectrum of testing signals becomes continuous and it will be easily characterized and analyzed. But this technology can’t satisfy the need of component parameter mixing. The linear frequency modulation is adopted to generate excitation signals and testing signals are amplified, sampled and analyzed with zoom spectrum method (Chirp-Z Transform). Tukey window function is added to testing signals to eliminate ripples in spectrum curves. According to spectrum characteristic, five features such as spectrum energy, spectrum barycenter, spectrum kurtosis, spectrum skewness and spectrum difference’s peak frequency point are defined to realize multi-parameter detection of defects. The eddy current testing experiment shows that spectrum energy can be used to identify defects, spectrum barycenter, spectrum kurtosis, spectrum skewness can be used to classify defects, and spectrum difference’s peak frequency point can be used to detect inner defect’s depth position.
Pulsed excitation is considered as a multi-frequency signal, and multi-frequency analysis method of pulsed eddy current testing (PECT) is researched. Spectrum relative variation (SRV) in amplitude frequency spectrum is proposed to classify defects, and phase cross zero point (PCZP) in phase frequency spectrum is proposed to eliminate lift-off effect and classify defects. Generally speaking, PECT can be considered as a kind of MFECT technology, and its time domain analysis method has been investigated widely. The duty ratio and time shift position of pulsed excitation signals is compared and selected, then the excitation signal is expressed as a series of unequal amplitude harmonics and testing signal’s spectrum characteristic is analyzed. Because the energy of each harmonic component decreases with frequency rapidly, relative variation in testing signal’s amplitude frequency spectrum can be used to reflect the variation characteristic of each harmonic component influenced by different types of defects effectively. SRV in amplitude frequency spectrum is proposed to classify different types of defects. This feature with clearly physical meanings varies obviously. High frequency harmonic component’s SRV of surface defects keeps constant or has a little upward trend, but that of inner defects has an obvious downward trend. The reason is that the skin depth of high frequency harmonic components becomes smaller. In phase frequency spectrum, the phase value of low frequency harmonic components are positive and it decreases with frequency gradually to negative. PCZP is proposed from that. When the lift-off of the eddy current sensor varies, PCZP keeps constant. PCZP of surface defect’s testing signals become bigger than that of no defect. PCZP of inner defect’s testing signals become smaller than that of no defect. When the defects are too tiny, this feature varies a little and the classification function is not evident.
MFECT systems for parameter mixing and spectrum analysis method are designed and implemented. MFECT systems are more complicated than other eddy current testing systems. DDS technology is adopted to generate sine signals in MFECT system for parameter mixing, and these sine signals are added to synthesize the multi-frequency excitation signal. Then the parameters of weak eddy current testing signals are estimated based on band pass filters and orthogonal lock-in amplifiers. MFECT system for spectrum analysis method is realized based on virtual instrument (VI) technology. Arbitrary multi-frequency excitation signals are generated by a D/A module. The weak eddy current testing signal is amplified enough and sampled, and then it is converted to frequency domain and analyzed.
以时谐电磁场理论为基础,探讨了多频涡流检测问题的物理模型和计算方法,并对线圈涡流传感器的感生涡流分布和阻抗特性进行有限元仿真研究。从麦克斯韦方程组出发,对正弦信号激励下的时谐电磁场问题采用电磁位函数进行数学表述。对典型圆柱形线圈涡流传感器,简化为轴对称模型,在轴坐标系下,分析涡流效应对线圈等效阻抗的影响。对任意涡流检测问题,采用有限元法表述其数值计算方法。介绍了常用的多频涡流检测数据处理方法,如线性代数法、相位旋转相减法、频谱分析法等。采用Ansoft Maxwell有限元分析软件,建立涡流检测问题模型,仿真研究了激励频率、提离高度、被检对象厚度、缺陷等对涡流场分布和线圈等效阻抗的影响。
研究了基于参数混合运算的多频涡流检测技术,采用正交锁定放大器实现检测信号参数估计,提出基于线性最小二乘法的检测信号参数估计方法,对管道检测中支撑干扰和双频涡流检测中提离效应的抑制方法进行研究。在多频涡流检测中,当激励信号的频率分量数目较少时,提取各频率分量的两个参数进行混合运算,确定被检对象特性。讨论了采用带通滤波器和正交锁定放大器的多频涡流检测信号参数估计方法,主要采用硬件实现,成本较高。对正弦信号进行线性化处理,提出基于线性最小二乘法的多频涡流检测信号参数估计方法,降低硬件实现成本。对管道检测中的支撑干扰抑制方法进行研究,采用相位旋转相减法,消除了检测过程的支撑干扰,增强了缺陷信号。对双频涡流检测中的提离效应抑制方法进行研究,分析提离和缺陷对各频率分量的影响差异,在检测信号分量图中提出“缺陷区域”,区分提离信号和缺陷信号,从而抑制提离效应。
研究了基于同步合成激励和谱分析的多频涡流检测技术,提出基于遗传算法的多频激励信号峰值因数优化方法,采用矩形激励线圈的涡流传感器,基于谱能量变化实现缺陷长度检测,基于主成分分析法实现缺陷分类。设计矩形激励线圈的涡流传感器,将被检对象表面的涡流场转变为匀强场,通过检测缺陷引起的扰动场,识别缺陷特征参数。在同步合成多频激励信号发生中,频率分量数目的增加必然导致激励信号峰值因数的增大,对涡流传感器驱动电路的工作电压范围要求加宽。文中提出基于遗传算法进行多频激励信号峰值因数优化,定义适应度函数,计算得到各频率分量的优化初始相位。与直接搜索算法相比,其明显提高了搜索速度。采用多频激励后,通过分析多频涡流检测信号的谱能量变化,可以对缺陷长度进行定量检测。当涡流传感器进入缺陷时,检测信号谱能量达到最大值;当涡流传感器离开缺陷时,检测信号谱能量达到最小值。提取最大值和最小值之间的扫描时间,结合涡流传感器的移动速度,即可得到缺陷长度。不同类型的缺陷对多频涡流检测信号中各频率分量影响程度是不同的,即谱图曲线变化趋势不同。采用主成分分析法,降低信号维数,提取特征量,实现缺陷分类。
研究了基于调频激励和细化谱分析的多频涡流检测技术,提出“调制多频涡流检测技术”,并定义谱图能量、谱图重心、谱图峰度、谱图偏度、频谱差峰值频率点等五个特征量,应用于缺陷识别及分类和内部缺陷深度位置识别。文中提出的调制多频涡流检测技术,是将调频信号作为涡流传感器的激励信号,通过对检测信号多级放大,采集并进行细化谱分析,进而实现干扰抑制或者多参数检测。与常规多频涡流检测技术相比,该技术的优点为:采用调频信号,降低了峰值因数;调频信号是多个频率信号的连续激励,避免了多路复用模块的使用,减少了检测时间;将检测信号的离散谱转变为连续谱,易于谱图的特征提取和分析。该技术的不足之处为:如果需要采用各频率分量参数的混合运算进行被检对象特征识别,则该技术不能满足。研究中,激励信号选为常用的线性调频信号,驱动涡流传感器,放大并采集检测信号,采用Chirp-Z变换进行细化谱分析。对检测信号施加Tukey Window函数,有效抑制了其谱图中的纹波。结合检测信号谱图特点,定义谱图能量、谱图重心、谱图峰度、谱图偏度、频谱差峰值频率点等五个特征量用于缺陷的多参数检测。通过涡流检测实验和数据分析,谱图能量可用于缺陷识别;谱图重心、谱图峰度和谱图偏度可用于缺陷分类;频谱差峰值频率点可用于内部缺陷深度位置识别。
将脉冲激励看作一种多频信号,研究了脉冲涡流检测的多频分析方法,在幅频谱中提出“谱相对变化”用于缺陷分类,在相频谱中提出“相位过零点”用于缺陷分类和提离抑制。广义上讲,脉冲涡流检测技术是多频涡流检测技术的一种,其时域分析方法已经得到了比较广泛的研究。文中对脉冲激励信号的占空比和时移位置进行比较选择,并将其看作一组不等幅正弦谐波的合成信号,分析脉冲涡流检测信号的频谱特性。由于脉冲激励信号中各频率分量能量随着频率的增加迅速减小,在检测信号幅频谱中,采用相对变化量能更有效地发现不同类型缺陷对各谐波分量的影响特点。提出“谱相对变化”特征量可有效地应用于脉冲涡流检测中的缺陷分类,其变化明显,物理意义清楚。对于表面缺陷,高频谐波分量的相对变化量恒定或略有上升趋势;而对于内部缺陷,高频谐波分量的相对变化量具有明显的下降趋势。这种变化是由于高频谐波分量的趋肤深度减小导致的。在相频谱中,低频谐波分量的相位值为正,相位值随着频率的增加逐渐减小并变为负,存在一个“相位过零点”。对于不同的提离高度,相位过零点保持不变;对于表面缺陷,相位过零点比无缺陷时变大;对于内部缺陷,相位过零点比无缺陷时变小。但当缺陷较小时,相位过零点的变化比较微弱,缺陷分类作用并不明显。
设计和实现了用于参数混合运算和谱分析的多频涡流检测系统。多频涡流检测系统的设计实现比其它类型涡流检测系统复杂。用于参数混合运算的多频涡流检测系统利用DDS技术发生多路正弦信号并通过加法器合成多频激励信号,采用带通滤波器和正交锁定放大器实现微弱涡流检测信号的参数估计。用于谱分析的多频涡流检测系统采用虚拟仪器技术实现,采用D/A单元发生任意多频激励信号,对微弱涡流检测信号经过充分放大后,采集并进行谱分析。
As one new eddy current nondestructive testing (NDT) technology, multi-frequency eddy current testing (MFECT) has the merits of interference elimination in testing procedure and multi-parameter detection of unit under test (UUT). This paper lucubrated signal parameter estimation and mixing, crest factor optimization of synchronously synthetical excitation and spectrum analysis of testing signals, linear frequency modulation excitation and zoom spectrum analysis of testing signals, multi-frequency analysis of pulsed excitation, et al in MFECT technology, and these are applied in interference elimination, defect detection and so on. The brief of these researches and the novel approaches are as follows:
Based on time harmonic electromagnetic field theory, physical model and calculation method of MFECT are discussed. Induced eddy current distribution and impedance characteristic of the probe coil are simulated and researched with finite element method. According to Maxwell law, time harmonic electromagnetic field problem based on sine signal excitation is expressed mathematically with electromagnetic potential. The typical eddy current testing problem with an aircore coil is simplified and analyzed in cylindrical coordinate, and then the coil’s equivalent impedance affected by eddy current effect is analyzed. The arbitrary eddy current testing problem is expressed and calculated with finite element method. The common data processing methods of MFECT including linear algebra method, phase rotation and subtraction, spectrum analysis method are introduced. The eddy current testing problem is modeled with Ansoft Maxwell finite element software, and then eddy current distribution and coil’s equivalent impedance characteristic influenced by excitation frequency, lift-off height, UUT’s thickness, defects and so on are simulated and researched.
MFECT technology based on parameter mixing is researched. Testing signal’s parameter estimation method based on orthogonal lock-in amplifiers is introduced and a new method based on linear least square method is proposed. Support interference elimination in tube testing and lift-off effect elimination in dual-frequency eddy current testing are researched. When the amount of frequency components is relative small in MFECT, two parameters of each frequency component are extracted and mixed to characterize UUT. Parameter estimation method based on band pass filters and orthogonal lock-in amplifiers is discussed but it takes a high hardware cost. Sine signal linearzed, a new method for MFECT signal’s parameter estimation based on linear least square method is proposed, and it reduces the hardware cost. Support interference elimination method is researched. The support interference is removed based on phase rotation and subtraction, so the defect signal is enhanced. Lift-off effect elimination in dual-frequency eddy current testing is researched. The component variation difference between lift-off and defects is analyzed and the defect zone is proposed to distinguish lift-off signals and defect signals and to realize lift-off effect elimination.
MFECT technology based on synchronously synthetical excitation and spectrum analysis method is researched. Crest factor optimization of the multi-frequency excitation signal based on genetic algorithm is proposed. The eddy current sensor with a rectangular excitation coil is adopted. The length of defects is quantitatively detected based on spectrum energy variation, and the classification of defects is realized based on principal component analysis (PCA). The eddy current sensor with a rectangular excitation coil is designed which can convert eddy current field in the surface of UUT to a uniform field. Defect characteristic can be identified by detecting the disturbance field which arises from defects. When the multi-frequency excitation signal is generated in synchronously synthetical mode, the crest factor of excitation signals will increase with the amount of frequency components rapidly. Therefore, that broadens the work voltage range of eddy current sensor’s driving circuit. An optimization method of excitation signal’s crest factor based on genetic algorithm is proposed. A fitness function is defined and the optimized initial phase of each frequency component is got. Compared with direct search algorithm, this method improves the search speed obviously. When the eddy current sensor is drived with a multi-frequency signal, the length of defects can be quantitatively detected based on spectrum energy variation. The spectrum energy reaches maximum when the eddy current sensor comes into defects. The spectrum energy reaches minimum when the eddy current sensor departs from defects. The length can be calculated with the time span between maximum and minimum and the moving speed of the eddy current sensor. Each frequency component is affected differently and the trend of spectrum curve varies differently when different types of defects are detected. The signal dimension is reduced based on PCA and defect classification is realized.
MFECT technology based on frequency modulation excitation and zoom spectrum analysis method is researched. Modulated MFECT is proposed, and five features including spectrum energy, spectrum barycenter, spectrum kurtosis, spectrum skewness and spectrum difference’s peak frequency point are defined to realize identification and classification of defects and depth detection of inner defects. Modulated MFECT technology proposed in this paper adopts frequency modulation signals as the excitation signal of eddy current sensors. After a multi-level amplification, testing signals are sampled and analyzed in frequency domain to realize interference elimination or multi-parameter detection. Compared with conventional MFECT technology, the crest factor of excitation signals is reduced because of frequency modulation excitation, and the testing time is reduced because that the frequency modulation signal is a continuous excitation of many frequency components and the multiplex module is not needed. As a result, the discrete spectrum of testing signals becomes continuous and it will be easily characterized and analyzed. But this technology can’t satisfy the need of component parameter mixing. The linear frequency modulation is adopted to generate excitation signals and testing signals are amplified, sampled and analyzed with zoom spectrum method (Chirp-Z Transform). Tukey window function is added to testing signals to eliminate ripples in spectrum curves. According to spectrum characteristic, five features such as spectrum energy, spectrum barycenter, spectrum kurtosis, spectrum skewness and spectrum difference’s peak frequency point are defined to realize multi-parameter detection of defects. The eddy current testing experiment shows that spectrum energy can be used to identify defects, spectrum barycenter, spectrum kurtosis, spectrum skewness can be used to classify defects, and spectrum difference’s peak frequency point can be used to detect inner defect’s depth position.
Pulsed excitation is considered as a multi-frequency signal, and multi-frequency analysis method of pulsed eddy current testing (PECT) is researched. Spectrum relative variation (SRV) in amplitude frequency spectrum is proposed to classify defects, and phase cross zero point (PCZP) in phase frequency spectrum is proposed to eliminate lift-off effect and classify defects. Generally speaking, PECT can be considered as a kind of MFECT technology, and its time domain analysis method has been investigated widely. The duty ratio and time shift position of pulsed excitation signals is compared and selected, then the excitation signal is expressed as a series of unequal amplitude harmonics and testing signal’s spectrum characteristic is analyzed. Because the energy of each harmonic component decreases with frequency rapidly, relative variation in testing signal’s amplitude frequency spectrum can be used to reflect the variation characteristic of each harmonic component influenced by different types of defects effectively. SRV in amplitude frequency spectrum is proposed to classify different types of defects. This feature with clearly physical meanings varies obviously. High frequency harmonic component’s SRV of surface defects keeps constant or has a little upward trend, but that of inner defects has an obvious downward trend. The reason is that the skin depth of high frequency harmonic components becomes smaller. In phase frequency spectrum, the phase value of low frequency harmonic components are positive and it decreases with frequency gradually to negative. PCZP is proposed from that. When the lift-off of the eddy current sensor varies, PCZP keeps constant. PCZP of surface defect’s testing signals become bigger than that of no defect. PCZP of inner defect’s testing signals become smaller than that of no defect. When the defects are too tiny, this feature varies a little and the classification function is not evident.
MFECT systems for parameter mixing and spectrum analysis method are designed and implemented. MFECT systems are more complicated than other eddy current testing systems. DDS technology is adopted to generate sine signals in MFECT system for parameter mixing, and these sine signals are added to synthesize the multi-frequency excitation signal. Then the parameters of weak eddy current testing signals are estimated based on band pass filters and orthogonal lock-in amplifiers. MFECT system for spectrum analysis method is realized based on virtual instrument (VI) technology. Arbitrary multi-frequency excitation signals are generated by a D/A module. The weak eddy current testing signal is amplified enough and sampled, and then it is converted to frequency domain and analyzed.
引文
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