石油管道脉冲远场涡流信号特征分析与处理
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摘要
脉冲远场涡流检测相较于常规远场涡流检测可提供更多的时频信息以用于被测管道分析,因此脉冲远场涡流检测在石油管道内检测技术中具有更广泛的应用前景。通过分析管道内脉冲远场涡流检测信号的时域信息,得出电压负峰值更适合作为实际检测中缺陷分析的特征量,并且用基于脉冲远场涡流的检测仪器进行了测试分析与验证。通过ANSYS模拟实际有缺陷管道内的脉冲远场涡流检测,并提取电压负峰值作为特征量,得出当发射线圈处于缺陷位置时,检测特征信号亦会产生变化,出现伪峰。通过设置双检测线圈达到消除发射线圈附近缺陷对电压负峰值的影响,在分析中发现双检测线圈由于不同位置对电压负峰值的影响可以通过零均值归一化的方法消除。零均值归一化方法在脉冲涡流检测中的应用具有重要意义,其不仅可以消除线圈位置对检测信号带来的影响,亦将检测信号映射到统一尺度。所提出的方法通过ANSYS仿真和实际管道实验得到验证,提高了脉冲远场涡流技术在管道检测中的实用性。
Compared with conventional remote field eddy current testing(RFECT), the pulsed remote field eddy current testing(PRFECT) can provide more time-frequency domain information that can be used for the analysis of the tested pipes, it has a better application prospect in the in-pipe testing of ferromagnetic oil pipes. Through analyzing the time-domain information of the PRFECT signals in ferromagnetic pipes, this paper obtains the conclusion that the peak inverse voltage of PRFECT is more suitable to be used for the feature quantity of defect analysis in practical testing. And more, the conclusion is tested, analyzed and verified with the test equipment based on PRFECT. Through simulating the PRFECT in the real pipe with defect using ANSYS and extracting the peak inverse voltage as the feature quantity, it is found that when the transmitting coil is located in the defect position, the detected signal changes and spurious peak occurs. The influence of the defect near the transmitting coil on the peak inverse voltage is eliminated through setting double pick-up coils. To eliminate the spurious peaks, double pick-up coils are set in the transition zone to obtain time shifted signals. Based on the time shifted signals, a method is proposed to remove the spurious peaks and eliminate the errors with zero-mean normalization. The zero-mean normalization method is of great significance in pulsed eddy current testing, it can not only eliminate the influence of coil position on the detected signal, but also map the detected signal to a uniform scale. The method proposed in this paper was verified through ANSYS simulation and real pipe experiment, which improves the practicability of PRFECT in pipeline testing.
Compared with conventional remote field eddy current testing(RFECT), the pulsed remote field eddy current testing(PRFECT) can provide more time-frequency domain information that can be used for the analysis of the tested pipes, it has a better application prospect in the in-pipe testing of ferromagnetic oil pipes. Through analyzing the time-domain information of the PRFECT signals in ferromagnetic pipes, this paper obtains the conclusion that the peak inverse voltage of PRFECT is more suitable to be used for the feature quantity of defect analysis in practical testing. And more, the conclusion is tested, analyzed and verified with the test equipment based on PRFECT. Through simulating the PRFECT in the real pipe with defect using ANSYS and extracting the peak inverse voltage as the feature quantity, it is found that when the transmitting coil is located in the defect position, the detected signal changes and spurious peak occurs. The influence of the defect near the transmitting coil on the peak inverse voltage is eliminated through setting double pick-up coils. To eliminate the spurious peaks, double pick-up coils are set in the transition zone to obtain time shifted signals. Based on the time shifted signals, a method is proposed to remove the spurious peaks and eliminate the errors with zero-mean normalization. The zero-mean normalization method is of great significance in pulsed eddy current testing, it can not only eliminate the influence of coil position on the detected signal, but also map the detected signal to a uniform scale. The method proposed in this paper was verified through ANSYS simulation and real pipe experiment, which improves the practicability of PRFECT in pipeline testing.
引文
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[12] 徐志远,林章鹏,袁湘民,等.管道弯头缺陷检测外置式远场涡流探头设计[J]. 仪器仪表学报,2017,38(5):1119-1125.XU ZH Y,LIN ZH P,YUAN X M,et al. External remote field eddy current probe for defect detection at pipe elbows[J]. Chinese Journal of Scientific Instrument,2017,38(5):1119-1125.
[13] KIM D,UDPA L,UDPA S. Remote field eddy current testing for detection of stress corrosion cracks in gas transmission pipelines[J]. Material Letters,2004,58(15):2102- 2104.
[14] FALQUE R, VIDALCALLEJA T, MIRO J V. Defect detection and segmentation framework for remote field eddy current sensor data[J]. Sensors, 2017, 17(10): 2276
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[18] ULAPANE N, ALEMPIJEVIC A, VIDAL T C. Pulsed eddy current sensing for critical pipe condition assessment[J]. Sensors, 2017, 17(10): 2208.
[19] SOPHIAN A, TIAN G Y, FAN M B. Pulsed eddy current non-destructive testing and evaluation: A review[J]. Chinese Journal of Mechanical Engineering, 2017, 30(3): 1-15.
[20] YANG B F,LI X CH. Pulsed remote field technique used for nondestructive inspection of ferromagnetic tube[J]. NDT & E International,2013(53):47- 52.
[21] LUO Q W,SHI Y B,WANG ZH G,et al. Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes[J]. Review of Scientific Instruments,2016,87(10): 104707.
[22] LUO Q W,SHI Y B,WANG ZH G,et al. Method for removing secondary peaks in remote field eddy current testing of pipes[J]. Journal of Nondestructive Evaluation,2017,36(1):1-11.
[23] 罗清旺,师奕兵,王志刚,等.一种基于远场涡流的管道大面积缺陷定位检测方法[J]. 仪器仪表学报,2015,36(12):2790- 2797.LUO Q W,SHI Y B,WANG ZH G,et al. Location and inspection method for large area pipe defect based on RFEC testing[J]. Chinese Journal of Scientific Instrument,2015,36(12):2790- 2797.
[24] 张芸,张伟,师奕兵,等. 基于远场涡流的管道局部缺陷定量评估方法[J]. 仪器仪表学报,2016,(3):623- 631.ZHANG Y,ZHANG W,SHI Y B,et al. Research on local defects quantification of pipes based on RFEC testing[J]. Chinese Journal of Scientific Instrument,2016,37(3):623- 631.
[25] KETHWAS A,JHARIA B. Image de-nosing using fuzzy and wiener filter in wavelet domain[C]. IEEE International Conference on Electrical Computer and Communication Technologies,2015:1- 5.
[26] ZHANG X, FENG X. Multiple-step local Wiener filter with proper stopping in wavelet domain[J]. Journal of Visual Communication & Image Representation, 2014, 25(2): 254- 262.
[2] ONG Z C, ENG H C, NOROOZI S. Non-destructive testing and assessment of a piping system with excessive vibration and recurrence crack issue: An industrial case study[J]. Engineering Failure Analysis, 2017(82): 280- 297
[3] 廖达伟. 管道无损检测技术的新进展[J]. 电子测量与仪器学报,2012,26(增刊1):4-7.LIAO D W. Advances of the nondestructive examination technology of buried pipelines[J]. Journal of Electronic Measurement and Instrument, 2012, 26(Suppl.1):4-7.
[4] 黄松龄,王哲,王坤,等.管道电磁超声导波技术及其应用研究进展[J]. 仪器仪表学报,2018,39(3):1-12.HUANG S L,WANG ZH,WANG K,et al. Review on advances of pipe electromagnetic ultrasonic guided waves technology and its application[J]. Chinese Journal of Scientific Instrument,2018,39(3):1-12.
[5] LEE C,PARK S. Damage visualization of pipeline structures using laser-induced ultrasonic waves[J]. Structural Health Monitoring,2015,14(5):475- 488.
[6] 杨理践,张晓丹,高松巍,等. 超声波在管道防腐层剥离内检测中的传播特性研究[J]. 电子测量与仪器学报,2018,32(1):9-18.YANG L J,ZHANG X D,GAO S W,et al. Research on the propagation characteristics of ultrasonic wave in the detection of pipeline coating[J]. Journal of Electronic Measurement and Instrumentation,2018,32(1):9-18.
[7] SHI Y,ZHANG C,LI R,et al. Theory and application of magnetic flux leakage pipeline detection[J]. Sensors,2015,15(12):31036-31055.
[8] LIU B, HE L Y, ZHANG H, et al. The axial crack testing model for long distance oil - gas pipeline based on magnetic flux leakage internal inspection method[J]. Measurement, 2017(103): 275- 282.
[9] TODOROV E. Measurement of electromagnetic properties of heat exchanger tubes[J]. NDT & E International, 2012, 48(2): 63-69.
[10] DESJARDINS D, KRAUSE T W, CLAPHAM L. Transient eddy current method for the characterization of magnetic permeability and conductivity[J]. NDT & E International, 2016, 80(2): 65-70.
[11] HILL S, DIXON S. Localization of defects with time and frequency measurements using pulsed arrays[J]. NDT & E International, 2014, 67(8): 24-30.
[12] 徐志远,林章鹏,袁湘民,等.管道弯头缺陷检测外置式远场涡流探头设计[J]. 仪器仪表学报,2017,38(5):1119-1125.XU ZH Y,LIN ZH P,YUAN X M,et al. External remote field eddy current probe for defect detection at pipe elbows[J]. Chinese Journal of Scientific Instrument,2017,38(5):1119-1125.
[13] KIM D,UDPA L,UDPA S. Remote field eddy current testing for detection of stress corrosion cracks in gas transmission pipelines[J]. Material Letters,2004,58(15):2102- 2104.
[14] FALQUE R, VIDALCALLEJA T, MIRO J V. Defect detection and segmentation framework for remote field eddy current sensor data[J]. Sensors, 2017, 17(10): 2276
[15] CHEN Y B,ZHENG J,LUO W J. Remote field eddy current testing technology for ferromagnetic heat exchanger tubes[C]. ASME Pressure Vessels and Piping Conference,2012:237- 239.
[16] ZHANG W, SHI Y B, LI Y J, et al. A study of quantifying thickness of ferromagnetic pipes based on remote field eddy current testing [J]. Sensors, 2018, 18(9):2769.
[17]VASI?D,BILAS V,AMBRU?KIM C.Pulsed eddycurrent nondestructive testing of ferromagnetic tubes[J].IEEE Transactions on Instrumentation&Measurement,2004,53(4):1289-1294.
[18] ULAPANE N, ALEMPIJEVIC A, VIDAL T C. Pulsed eddy current sensing for critical pipe condition assessment[J]. Sensors, 2017, 17(10): 2208.
[19] SOPHIAN A, TIAN G Y, FAN M B. Pulsed eddy current non-destructive testing and evaluation: A review[J]. Chinese Journal of Mechanical Engineering, 2017, 30(3): 1-15.
[20] YANG B F,LI X CH. Pulsed remote field technique used for nondestructive inspection of ferromagnetic tube[J]. NDT & E International,2013(53):47- 52.
[21] LUO Q W,SHI Y B,WANG ZH G,et al. Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes[J]. Review of Scientific Instruments,2016,87(10): 104707.
[22] LUO Q W,SHI Y B,WANG ZH G,et al. Method for removing secondary peaks in remote field eddy current testing of pipes[J]. Journal of Nondestructive Evaluation,2017,36(1):1-11.
[23] 罗清旺,师奕兵,王志刚,等.一种基于远场涡流的管道大面积缺陷定位检测方法[J]. 仪器仪表学报,2015,36(12):2790- 2797.LUO Q W,SHI Y B,WANG ZH G,et al. Location and inspection method for large area pipe defect based on RFEC testing[J]. Chinese Journal of Scientific Instrument,2015,36(12):2790- 2797.
[24] 张芸,张伟,师奕兵,等. 基于远场涡流的管道局部缺陷定量评估方法[J]. 仪器仪表学报,2016,(3):623- 631.ZHANG Y,ZHANG W,SHI Y B,et al. Research on local defects quantification of pipes based on RFEC testing[J]. Chinese Journal of Scientific Instrument,2016,37(3):623- 631.
[25] KETHWAS A,JHARIA B. Image de-nosing using fuzzy and wiener filter in wavelet domain[C]. IEEE International Conference on Electrical Computer and Communication Technologies,2015:1- 5.
[26] ZHANG X, FENG X. Multiple-step local Wiener filter with proper stopping in wavelet domain[J]. Journal of Visual Communication & Image Representation, 2014, 25(2): 254- 262.
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