The noise as an undesired phenomenon often appears in the pulsed eddy current testing(PECT)signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the P...The noise as an undesired phenomenon often appears in the pulsed eddy current testing(PECT)signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the PECT signal is the Gaussian noise, since it is caused by the testing environment. A new denoising approach based on singular value decomposition(SVD) is proposed in this paper to reduce the Gaussian noise of PECT signal. The approach first discusses the relationship between signal to noise ratio(SNR) and negentropy of PECT signal. Then the Hankel matrix of PECT signal is constructed for noise reduction, and the matrix is divided into noise subspace and signal subspace by a singular valve threshold. Based on the theory of negentropy, the optimal matrix dimension and threshold are chosen to improve the performance of denoising. The denoised signal Hankel matrix is reconstructed by the singular values of signal subspace, and the denoised signal is finally extracted from this matrix. Experiment is performed to verify the feasibility of the proposed approach, and the results indicate that the proposed approach can reduce the Gaussian noise of PECT signal more effectively compared with other existing approaches.展开更多
In oil and gas extraction,ferromagnetic metal casings serve as critical infrastructure to ensure the safety of hydrocarbon transport.However,under high-temperature and high-pressure conditions,casings buried deep unde...In oil and gas extraction,ferromagnetic metal casings serve as critical infrastructure to ensure the safety of hydrocarbon transport.However,under high-temperature and high-pressure conditions,casings buried deep underground are prone to deformation,twisting,and even rupture due to erosion and corrosion,potentially leading to significant economic losses and safety hazards.Therefore,regular inspection and maintenance of in-service well casings are essential.Pulsed eddy current testing(PECT)has been widely used for casing defect detection owing to its efficiency,non-contact nature,and rich information content.However,the presence of substantial noise during detection degrades the quality of defect detection images.To address this issue,we investigated image processing techniques for casing defect detection images and proposed an image processing algorithm(BIC)based on bidimensional empirical mode decomposition(BEMD),improved wavelet threshold denoising(IWTD),and contrast limited adaptive histogram equalization(CLAHE).The proposed method first applied BEMD-IWTD for noise suppression in defect detection images,followed by CLAHE for image enhancement.To validate the effectiveness of the method,defect detection experiments were conducted on casings with ring-shaped and local defects,and the acquired images were processed.After being processed with the BIC algorithm,ring-shaped defects of different depths could be effectively distinguished,especially the 1 mm and 2 mm deep defects that were previously affected by noise.In the local defect images,small-sized defects difficult to be identified due to noise interference were successfully recognized,and the defect contrast C_(d)was significantly improved.The results demonstrate that the proposed BIC algorithm effectively suppresses the noise in defect detection images,enhances the contrast between defects and the background,and improves defect recognition and detection accuracy,providing reliable image processing support for subsequent defect analysis.展开更多
高速铁路轮轨系统在服役过程中产生的疲劳裂纹是威胁行车安全的重大隐患。传统的无损检测方法难以有效识别处于闭合或半闭合状态的早期微小裂纹,尤其是在列车运行载荷作用下的动态工况。针对这一挑战,本文提出并系统研究了一种基于涡流...高速铁路轮轨系统在服役过程中产生的疲劳裂纹是威胁行车安全的重大隐患。传统的无损检测方法难以有效识别处于闭合或半闭合状态的早期微小裂纹,尤其是在列车运行载荷作用下的动态工况。针对这一挑战,本文提出并系统研究了一种基于涡流脉冲热成像(Eddy Current Pulsed Thermography,ECPT)技术的轮轨疲劳裂纹检测方法。研究首先构建了负载作用下的非稳态疲劳裂纹多物理场模型,通过有限元仿真与实验相结合,深入探究了局部接触(闭合)裂纹的涡流-热响应机理,并揭示了裂纹闭合深度与表面温度场特征(如等温线内凹现象)之间的定量关系。在此基础上,自主研制了适用于车轮与钢轨的动态ECPT检测平台及专用磁轭传感器,并开展了高铁轮轨实物的动态检测试验。结果表明,所提方法不仅能有效区分开口与闭合裂纹,还能对不同深度、不同尺寸的疲劳裂纹进行可靠检出,检出深度范围可达0.35mm至5mm。结合主成分分析(PCA)与张量分解等图像增强算法,显著提升了缺陷的信噪比与可视化效果,为高铁轮轨疲劳裂纹的在线、高效、精准检测提供了重要的理论依据与技术支撑。展开更多
This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This...This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This paper introduces pulsed electromagnetic techniques and their different case studies on defect detection as well as stress characterisation.Experimental tests have been validated and future research plans are discussed.This paper demonstrates pulsed electromagnetic non-destructive testing and evaluation for not only depth information,but also for multiple parameter measurement and multiple integration,which are important for future development.展开更多
文摘The noise as an undesired phenomenon often appears in the pulsed eddy current testing(PECT)signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the PECT signal is the Gaussian noise, since it is caused by the testing environment. A new denoising approach based on singular value decomposition(SVD) is proposed in this paper to reduce the Gaussian noise of PECT signal. The approach first discusses the relationship between signal to noise ratio(SNR) and negentropy of PECT signal. Then the Hankel matrix of PECT signal is constructed for noise reduction, and the matrix is divided into noise subspace and signal subspace by a singular valve threshold. Based on the theory of negentropy, the optimal matrix dimension and threshold are chosen to improve the performance of denoising. The denoised signal Hankel matrix is reconstructed by the singular values of signal subspace, and the denoised signal is finally extracted from this matrix. Experiment is performed to verify the feasibility of the proposed approach, and the results indicate that the proposed approach can reduce the Gaussian noise of PECT signal more effectively compared with other existing approaches.
基金supported by National Natural Science Foundation of China(No.62303385)。
文摘In oil and gas extraction,ferromagnetic metal casings serve as critical infrastructure to ensure the safety of hydrocarbon transport.However,under high-temperature and high-pressure conditions,casings buried deep underground are prone to deformation,twisting,and even rupture due to erosion and corrosion,potentially leading to significant economic losses and safety hazards.Therefore,regular inspection and maintenance of in-service well casings are essential.Pulsed eddy current testing(PECT)has been widely used for casing defect detection owing to its efficiency,non-contact nature,and rich information content.However,the presence of substantial noise during detection degrades the quality of defect detection images.To address this issue,we investigated image processing techniques for casing defect detection images and proposed an image processing algorithm(BIC)based on bidimensional empirical mode decomposition(BEMD),improved wavelet threshold denoising(IWTD),and contrast limited adaptive histogram equalization(CLAHE).The proposed method first applied BEMD-IWTD for noise suppression in defect detection images,followed by CLAHE for image enhancement.To validate the effectiveness of the method,defect detection experiments were conducted on casings with ring-shaped and local defects,and the acquired images were processed.After being processed with the BIC algorithm,ring-shaped defects of different depths could be effectively distinguished,especially the 1 mm and 2 mm deep defects that were previously affected by noise.In the local defect images,small-sized defects difficult to be identified due to noise interference were successfully recognized,and the defect contrast C_(d)was significantly improved.The results demonstrate that the proposed BIC algorithm effectively suppresses the noise in defect detection images,enhances the contrast between defects and the background,and improves defect recognition and detection accuracy,providing reliable image processing support for subsequent defect analysis.
文摘高速铁路轮轨系统在服役过程中产生的疲劳裂纹是威胁行车安全的重大隐患。传统的无损检测方法难以有效识别处于闭合或半闭合状态的早期微小裂纹,尤其是在列车运行载荷作用下的动态工况。针对这一挑战,本文提出并系统研究了一种基于涡流脉冲热成像(Eddy Current Pulsed Thermography,ECPT)技术的轮轨疲劳裂纹检测方法。研究首先构建了负载作用下的非稳态疲劳裂纹多物理场模型,通过有限元仿真与实验相结合,深入探究了局部接触(闭合)裂纹的涡流-热响应机理,并揭示了裂纹闭合深度与表面温度场特征(如等温线内凹现象)之间的定量关系。在此基础上,自主研制了适用于车轮与钢轨的动态ECPT检测平台及专用磁轭传感器,并开展了高铁轮轨实物的动态检测试验。结果表明,所提方法不仅能有效区分开口与闭合裂纹,还能对不同深度、不同尺寸的疲劳裂纹进行可靠检出,检出深度范围可达0.35mm至5mm。结合主成分分析(PCA)与张量分解等图像增强算法,显著提升了缺陷的信噪比与可视化效果,为高铁轮轨疲劳裂纹的在线、高效、精准检测提供了重要的理论依据与技术支撑。
基金Sichuan province Science and Technology department( No. 2011GZ0002 and No. 2013HH0059)the university basic scientific research project( No. ZYGX2013J090 ) for funding the work
文摘This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This paper introduces pulsed electromagnetic techniques and their different case studies on defect detection as well as stress characterisation.Experimental tests have been validated and future research plans are discussed.This paper demonstrates pulsed electromagnetic non-destructive testing and evaluation for not only depth information,but also for multiple parameter measurement and multiple integration,which are important for future development.
