大容量高保真海底管道超声检测数据处理技术研究
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摘要
输油管道检测技术是目前国际无损检测领域的研究热点,国内在此方面的研究起步较晚。开展管道检测相关技术和方法的研究具有重大的理论和现实意义。超声检测因其所具有的特点一直受到相关领域专家和学者的高度重视。研制开发适合我国实际状况的管道超声智能检测系统装置,对我国在役油气管道进行全面检测和安全评价具有重大的社会、经济、环境效益。
在管道超声检测中,存在着若干理论和实际问题:超声检测装置的设计,超声检测中的噪声处理,超声数据压缩,管道壁厚检测以及管道超声检测数据的分析等理论与实际问题,论文依托国家海洋资源开发技术主题下资源与环境技术领域中的一项国家海洋863项目“海底管道内爬行器及其检测技术”,针对海底管道的检测要求,为研制具有我国自主知识产权的海洋输油管道超声智能检测系统提供关键技术。
首先介绍了超声测厚的原理以及海底管道超声检测装置的组成。根据检测要求,介绍了适用于海底管道超声检测数据采集与存储装置;根据项目工程样机的性能指标,通过理论分析和计算,确定了管道检测用的超声探头的中心频率,晶片直径,检测的提离距离等重要参数,并综合考虑管道检测的环境因素,为合理选取超声探头提供了必要的依据;通过分析,提出了适用于海底管道检测多通道超声数据的实时采集以及大容量数据的快速存储系统;总结了所设计的超声管道检测数据采集与存储装置的特点。
文章应用经验模式分解方法,对非线性非稳态的超声射频信号进行分解,得到了超声信号的各个固有模态函数分量,根据信号分解的特点,提出了基于能量的分量选择方法达到超声信号去噪的目的,通过仿真研究,验证了该方法具有很好的去噪效果,并且具有自适应性,比较了能量去噪以及阈值去噪两种方法;在此基础上,提出了基于EMD-MMSE的多传感器超声信号处理方法,通过实验验证,该方法优于算术平均融合的结果,并且具有自适应性,更便于计算机实现;针对海底管道超声壁厚检测时得到的超声信号的特点,采用一种典型的非线性滤波方法中值滤波对超声壁厚检测信号进行滤波,通过实验证明它对随机脉冲噪声有良好的抑制作用。
超声阵列进行管道检测时会得到海量的超声数据,文章讲述了几种超声信号压缩的原理与方法。基于变换的超声信号压缩方法中,在使用提升小波变换进行超声信号处理达到最优的压缩目的时,考虑了以下几个方面的因素,小波基的选择,分解层数的确定,阈值的选取等几个因素。通过实际的超声射频信号分析,确定了最佳的参数达到最优的压缩目的;根据超声回波信号的高斯回波模型,介绍了连续小波变换以及最大似然估计的参数估计方法,在匹配追踪算法的的匹配过程中,使用遗传算法来估计时频原子的参数,也就是高斯回波模型函数的参数,文章使用遗传算法实现匹配追踪分解的方法,通过仿真以及实验可以看出,这种方法基本可以搜索到最佳匹配信号结构的参数,并且计算时间比原匹配追踪算法的时间有大幅的降低;文章通过几种无损压缩方法的比较,在考虑压缩时间以及压缩比的情况下,选取Huffman编码来对管道超声检测数据进行实时数据压缩。
文章分析了特殊情况下的管道缺陷测厚工艺,根据不同的检测情况,提出了相应的检测处理方法,根据海底管道超声检测信号,使用FFT方法以及自相关方法进行海底管道壁厚检测,能够达到了检测的要求,在FFT方法的基础上,通过二次FFT方法提高了FFT检测的精度;提出了一种新的特征提取方法,使用Hilbert-Huang变换提取了超声检测信号的时域、频域以及时频域特征;引入专家系统对管道超声数据进行处理,通过推理机访问由产生式规则集建立的管道缺陷知识库,推理判断出管道缺陷的种类以及缺陷的大小,从而达到管道缺陷识别的目的。
为了研究检测工艺和进行检测工艺试验,在实验室阶段制作了一些标准缺陷的样本来满足试验的要求,建立了管道缺陷样本库。对超声探头检测工艺进行了实验,测量结果表明,检测系统能够检测出课题指标要求的缺陷并且满足测量精度要求,缺陷定位和缺陷尺寸测量满足工程要求。为了验证超声检测系统的实时检测能力,建立了一个实验检测系统,并进行了管道数据采集实验,并且进行了实际输油管道检测,通过实验充分说明了超声检测装置能够实时检测以及采集数据,说明了分析软件的有效性。
本文提出的超声信号各种处理方法也可用于其它类似情况的信号处理中。
Currently, offshore pipeline inspection technique is a research hotspot in the international nondestructive evaluation (NDE) field, but it is late for domestic research. The research on technologies, methods, and approaches for pipeline detection makes great theoretical and realistic sense. Experts and scholars attach importance to ultrasonic detection because of its merits.
Based on the high technology research and development program“Offshore pipeline detection device and inspection technology”, ultrasonic signal denoising, ultrasonic data compression, thickness of pipeline detection and pipeline defect recognition are studied deeply according to detection requirement of offshore pipeline. All these provide key technologies for the offline data analysis system of the program.
The theory of ultrasonic thickness measurement and offshore pipeline detection device were introduced firstly. According to performance guideline of offshore pipeline detection device, the pipeline ultrasonic inspection device was designed, the parameters of the center frequency, the wafer diameter, SO were determined by analyzing and caculating. Ultrasonic sensors were selected and inspection transducer device was designed. The ultrasonic data storage system was developed.
The one of key research on ultrasonic non-destructive detection is denoising ultrasonic echo signals. Ultrasonic RF signals are decomposed by empirical mode decomposition and IMFs of ultrasonic signal can be obtained. According to the performance of signal decomposition, the method of component selection based on energy is composed to denoise the ultrasonic signal. The experimental results and discussion demonstrated the usefulness and effectiveness of empirical mode decomposition as a signal processing technique for the analysis of ultrasonic waveforms. This method is adaptive. It is easy to be realized in computer. The multi-sensor data fusion algorithm has been applied to sensor array signal processing. A fusion method based on EMD and noise variance is proposed. Experiments in lab have testified the efficiency of this method. In addition, the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly. Collected and stored data are demodulation signal when thickness of offshore pipeline is detected by ultrasonic sensors array, signal noises represent as pulse noise. By analyzing the performance of pipeline detection ultrasonic signals, the ultrasonic signal is filtered by the median filter, a typical nonlinear filter. Experiments in lab have testified the efficiency of this method.
The theory and method were introduced in this dissertation. Lifting wavelet transform has been used to ultrasonic signal compression. In order to obtain best compression ratio, some factors, such as selection a proper wavelet base, setting the decomposition level number, defining the threshold by wavelet coefficients and so on, must be considered. By analyzing the performance of pipeline detection ultrasonic RF signals, the best parameters were confirmed to get the good compression result. The parameter estimation methods of the continuous wavelet transform and maximum likelihood estimation were introduced in this dissertation. MP based GA is applied to estimate the parameters of atom functions that best represent the detected ultrasonic signal in this dissertation. GA is a numerical optimization method based on the concepts of genetics and natural selection. It is an efficient technique to optimize difficult functions in large search spaces. The simulation signals and experimental results have testified the efficiency of this method. Using LS, it also need spend considerable searching time and find the time-frequency atoms best matched original signal. Genetic algorithm (GA) can estimate the values of the parameter vector, in order to reduce the calculation amount. The collected data must be compressed and saved timely during the inspection. Ultrasonic detecting device requires lossless and real-time (high speed) data compression for the inspection of long time. The method of Huffman coding is selected by comparing some sorts of lossless compression methods.
The algorithms of pipeline thickness detection based on FFT and correlation were expatiated, in order to enhance measurement precision, second FFT method was proposed. The Hilbert-Huang transform was used to extract the signal features of time domain, frequency domain and time frequency domain. The expert system was used to process the ultrasonic data of pileline, defect database was built and the classidication and grade of pipeline defects was deduced.
Because of the offshore pipeline detection entironment variety, the flaws of the pipeline are multiplex. Some standard defect samples were made by experiment machining.Experiments showed that the accuracy of detected time of flight between the transmitted pulse and echo from the pipeline wall as well as the thickness of the pipeline wall was clearly improved. In order to testify the vality of the ultrasonic inspection device, inspection system was built in lab, the experimental results testified the efficiency of the ultrasonic inspection device and data anlysis software.
All the approaches regarding ultrasonic signal feature extraction and information fusion can be used in other similar signal processing cases.
在管道超声检测中,存在着若干理论和实际问题:超声检测装置的设计,超声检测中的噪声处理,超声数据压缩,管道壁厚检测以及管道超声检测数据的分析等理论与实际问题,论文依托国家海洋资源开发技术主题下资源与环境技术领域中的一项国家海洋863项目“海底管道内爬行器及其检测技术”,针对海底管道的检测要求,为研制具有我国自主知识产权的海洋输油管道超声智能检测系统提供关键技术。
首先介绍了超声测厚的原理以及海底管道超声检测装置的组成。根据检测要求,介绍了适用于海底管道超声检测数据采集与存储装置;根据项目工程样机的性能指标,通过理论分析和计算,确定了管道检测用的超声探头的中心频率,晶片直径,检测的提离距离等重要参数,并综合考虑管道检测的环境因素,为合理选取超声探头提供了必要的依据;通过分析,提出了适用于海底管道检测多通道超声数据的实时采集以及大容量数据的快速存储系统;总结了所设计的超声管道检测数据采集与存储装置的特点。
文章应用经验模式分解方法,对非线性非稳态的超声射频信号进行分解,得到了超声信号的各个固有模态函数分量,根据信号分解的特点,提出了基于能量的分量选择方法达到超声信号去噪的目的,通过仿真研究,验证了该方法具有很好的去噪效果,并且具有自适应性,比较了能量去噪以及阈值去噪两种方法;在此基础上,提出了基于EMD-MMSE的多传感器超声信号处理方法,通过实验验证,该方法优于算术平均融合的结果,并且具有自适应性,更便于计算机实现;针对海底管道超声壁厚检测时得到的超声信号的特点,采用一种典型的非线性滤波方法中值滤波对超声壁厚检测信号进行滤波,通过实验证明它对随机脉冲噪声有良好的抑制作用。
超声阵列进行管道检测时会得到海量的超声数据,文章讲述了几种超声信号压缩的原理与方法。基于变换的超声信号压缩方法中,在使用提升小波变换进行超声信号处理达到最优的压缩目的时,考虑了以下几个方面的因素,小波基的选择,分解层数的确定,阈值的选取等几个因素。通过实际的超声射频信号分析,确定了最佳的参数达到最优的压缩目的;根据超声回波信号的高斯回波模型,介绍了连续小波变换以及最大似然估计的参数估计方法,在匹配追踪算法的的匹配过程中,使用遗传算法来估计时频原子的参数,也就是高斯回波模型函数的参数,文章使用遗传算法实现匹配追踪分解的方法,通过仿真以及实验可以看出,这种方法基本可以搜索到最佳匹配信号结构的参数,并且计算时间比原匹配追踪算法的时间有大幅的降低;文章通过几种无损压缩方法的比较,在考虑压缩时间以及压缩比的情况下,选取Huffman编码来对管道超声检测数据进行实时数据压缩。
文章分析了特殊情况下的管道缺陷测厚工艺,根据不同的检测情况,提出了相应的检测处理方法,根据海底管道超声检测信号,使用FFT方法以及自相关方法进行海底管道壁厚检测,能够达到了检测的要求,在FFT方法的基础上,通过二次FFT方法提高了FFT检测的精度;提出了一种新的特征提取方法,使用Hilbert-Huang变换提取了超声检测信号的时域、频域以及时频域特征;引入专家系统对管道超声数据进行处理,通过推理机访问由产生式规则集建立的管道缺陷知识库,推理判断出管道缺陷的种类以及缺陷的大小,从而达到管道缺陷识别的目的。
为了研究检测工艺和进行检测工艺试验,在实验室阶段制作了一些标准缺陷的样本来满足试验的要求,建立了管道缺陷样本库。对超声探头检测工艺进行了实验,测量结果表明,检测系统能够检测出课题指标要求的缺陷并且满足测量精度要求,缺陷定位和缺陷尺寸测量满足工程要求。为了验证超声检测系统的实时检测能力,建立了一个实验检测系统,并进行了管道数据采集实验,并且进行了实际输油管道检测,通过实验充分说明了超声检测装置能够实时检测以及采集数据,说明了分析软件的有效性。
本文提出的超声信号各种处理方法也可用于其它类似情况的信号处理中。
Currently, offshore pipeline inspection technique is a research hotspot in the international nondestructive evaluation (NDE) field, but it is late for domestic research. The research on technologies, methods, and approaches for pipeline detection makes great theoretical and realistic sense. Experts and scholars attach importance to ultrasonic detection because of its merits.
Based on the high technology research and development program“Offshore pipeline detection device and inspection technology”, ultrasonic signal denoising, ultrasonic data compression, thickness of pipeline detection and pipeline defect recognition are studied deeply according to detection requirement of offshore pipeline. All these provide key technologies for the offline data analysis system of the program.
The theory of ultrasonic thickness measurement and offshore pipeline detection device were introduced firstly. According to performance guideline of offshore pipeline detection device, the pipeline ultrasonic inspection device was designed, the parameters of the center frequency, the wafer diameter, SO were determined by analyzing and caculating. Ultrasonic sensors were selected and inspection transducer device was designed. The ultrasonic data storage system was developed.
The one of key research on ultrasonic non-destructive detection is denoising ultrasonic echo signals. Ultrasonic RF signals are decomposed by empirical mode decomposition and IMFs of ultrasonic signal can be obtained. According to the performance of signal decomposition, the method of component selection based on energy is composed to denoise the ultrasonic signal. The experimental results and discussion demonstrated the usefulness and effectiveness of empirical mode decomposition as a signal processing technique for the analysis of ultrasonic waveforms. This method is adaptive. It is easy to be realized in computer. The multi-sensor data fusion algorithm has been applied to sensor array signal processing. A fusion method based on EMD and noise variance is proposed. Experiments in lab have testified the efficiency of this method. In addition, the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly. Collected and stored data are demodulation signal when thickness of offshore pipeline is detected by ultrasonic sensors array, signal noises represent as pulse noise. By analyzing the performance of pipeline detection ultrasonic signals, the ultrasonic signal is filtered by the median filter, a typical nonlinear filter. Experiments in lab have testified the efficiency of this method.
The theory and method were introduced in this dissertation. Lifting wavelet transform has been used to ultrasonic signal compression. In order to obtain best compression ratio, some factors, such as selection a proper wavelet base, setting the decomposition level number, defining the threshold by wavelet coefficients and so on, must be considered. By analyzing the performance of pipeline detection ultrasonic RF signals, the best parameters were confirmed to get the good compression result. The parameter estimation methods of the continuous wavelet transform and maximum likelihood estimation were introduced in this dissertation. MP based GA is applied to estimate the parameters of atom functions that best represent the detected ultrasonic signal in this dissertation. GA is a numerical optimization method based on the concepts of genetics and natural selection. It is an efficient technique to optimize difficult functions in large search spaces. The simulation signals and experimental results have testified the efficiency of this method. Using LS, it also need spend considerable searching time and find the time-frequency atoms best matched original signal. Genetic algorithm (GA) can estimate the values of the parameter vector, in order to reduce the calculation amount. The collected data must be compressed and saved timely during the inspection. Ultrasonic detecting device requires lossless and real-time (high speed) data compression for the inspection of long time. The method of Huffman coding is selected by comparing some sorts of lossless compression methods.
The algorithms of pipeline thickness detection based on FFT and correlation were expatiated, in order to enhance measurement precision, second FFT method was proposed. The Hilbert-Huang transform was used to extract the signal features of time domain, frequency domain and time frequency domain. The expert system was used to process the ultrasonic data of pileline, defect database was built and the classidication and grade of pipeline defects was deduced.
Because of the offshore pipeline detection entironment variety, the flaws of the pipeline are multiplex. Some standard defect samples were made by experiment machining.Experiments showed that the accuracy of detected time of flight between the transmitted pulse and echo from the pipeline wall as well as the thickness of the pipeline wall was clearly improved. In order to testify the vality of the ultrasonic inspection device, inspection system was built in lab, the experimental results testified the efficiency of the ultrasonic inspection device and data anlysis software.
All the approaches regarding ultrasonic signal feature extraction and information fusion can be used in other similar signal processing cases.
引文
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