基于时延估计的石油管道安全预警定位技术研究
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摘要
随着石油管道运输的不断发展,石油管道安全预警问题成为当前石油管道运输的一项重要内容。输油管道由于建造工艺、自然灾害以及人为破坏等原因所造成的泄漏及破损,极大地影响了石油管道的正常运输,给人们的生产生活带来了诸多不便。石油管道安全预警系统是解决该问题的一个行之有效的途径。该系统的技术核心是如何及时有效地对威胁管道安全的事件信号进行检测和定位。本文针对这一难点问题,结合课题组的研究内容,抓住预警系统的数据采集、分类、处理三个环节,利用时延估计的方法对管道安全事件进行检测定位,取得了较好的效果。具体工作内容为：
(1)根据光纤管道安全预警系统采集的数据特点,提取出光纤传感器检测信号中事件信号的特征,并提出了同步性参数概念作为识别事件信号的重要特征,该特征对于确定原始信号中是否包含事件信号以及确定事件信号发生的时刻具有重要意义；
(2)研究了适用于该系统的时延定位算法及其改进算法(WGCC算法),提高时延估计准确性及精度；
(3)根据统计学原理,制订了时延估计结果的置信度方案,能够实时给出每个异常事件时延值的可信度；
(4)通过时延结果概率密度融合技术克服单次估计不稳定的缺点,得到的定位精度基本控制在与准确时延值偏差0.3个点之内,大幅提高系统定位的可靠性。
With the continuous development of the oil pipeline transportation, the pipeline safety problems are becoming the important part of transportation task. The oil pipeline leakage and sabotage due to low manufacturing process technology, natural disasters or human destruction greatly affect the normal transport of pipeline, which cause great inconvenience to the normal production and life. The pipeline safety alarm system is one of the methods to solve the problems. The core technology of the system is how to detect and locate the harmful events to pipeline in time. The paper related to a practical project aims to solve the difficulties. The alarm system including three parts (data detection, classification and processing) uses the time delay algorithms to detect and locate the abnormal events. The main works include the following issues:
(1) After analyzing the features of system data, a new method is proposed to detect event signal using extracted signal characters, such as the synchronism parameter. The detection method is helpful to discover and pick up the event data;
(2) The WGCC algorithm is used to estimate the time delay and position more accurately precisely;
(3) According to the statistics theory, the confidence level scheme is used to judge the TDE results;
(4) Because one single TDE result is unstable, the probability density fusion technology is used which significantly improve the reliability of position system. The position precision is generally controlled within 0.3 sampling interval.
(1)根据光纤管道安全预警系统采集的数据特点,提取出光纤传感器检测信号中事件信号的特征,并提出了同步性参数概念作为识别事件信号的重要特征,该特征对于确定原始信号中是否包含事件信号以及确定事件信号发生的时刻具有重要意义；
(2)研究了适用于该系统的时延定位算法及其改进算法(WGCC算法),提高时延估计准确性及精度；
(3)根据统计学原理,制订了时延估计结果的置信度方案,能够实时给出每个异常事件时延值的可信度；
(4)通过时延结果概率密度融合技术克服单次估计不稳定的缺点,得到的定位精度基本控制在与准确时延值偏差0.3个点之内,大幅提高系统定位的可靠性。
With the continuous development of the oil pipeline transportation, the pipeline safety problems are becoming the important part of transportation task. The oil pipeline leakage and sabotage due to low manufacturing process technology, natural disasters or human destruction greatly affect the normal transport of pipeline, which cause great inconvenience to the normal production and life. The pipeline safety alarm system is one of the methods to solve the problems. The core technology of the system is how to detect and locate the harmful events to pipeline in time. The paper related to a practical project aims to solve the difficulties. The alarm system including three parts (data detection, classification and processing) uses the time delay algorithms to detect and locate the abnormal events. The main works include the following issues:
(1) After analyzing the features of system data, a new method is proposed to detect event signal using extracted signal characters, such as the synchronism parameter. The detection method is helpful to discover and pick up the event data;
(2) The WGCC algorithm is used to estimate the time delay and position more accurately precisely;
(3) According to the statistics theory, the confidence level scheme is used to judge the TDE results;
(4) Because one single TDE result is unstable, the probability density fusion technology is used which significantly improve the reliability of position system. The position precision is generally controlled within 0.3 sampling interval.
引文
[1]吴晓.基于声传感器阵列的油气管道内检测器地面标记跟踪技术研究[D].(博)天津：天津大学精密仪器与光电子工程学院,2010.
[2]周琰.分布式光纤管道安全检测技术研究[D].(博)天津：天津大学精密仪器与光电子工科学院,2006.
[3]吴俊.长途油气管道破坏预警的干涉型分布式光纤传感系统定位技术研究[D].(硕)重庆：重庆大学光电工程学院,2007.
[4]林蕾.基于萨格奈克原理的分布式光纤长途油气管道破坏预警系统关键技术研究[D].(硕)重庆：重庆大学光电工程学院,2009.
[5]马庆万.基于振动原理的石油管道泄漏报警系统研究[D].(硕)黑龙江：大庆石油学院,2010.
[6]付道明,孙军,贺志刚等.国内外管道泄漏检测技术研究进展[J].石油机械,2004,32(3)：48-51.
[7]于喜元,楼俊君,杨平.管道超声波检测器的应用与发展趋势[J].油气储运,2003(4)：35-37.
[8]姜涛.管道泄漏检测与定位的应用研究[D].(硕)哈尔滨：哈尔滨工程大学,2008.
[9]陈华波,涂亚庆.输油管道泄漏检测方法综述[J].管道技术与设备,2000(1)：38-41.
[10]袁军国.分布式马赫-泽德干涉仪的原理与应用研究[D].(博)武汉：华中科技大学,2006.
[11]陈志刚,张来斌,王朝晖等.基于分布式光纤传感器的输气管道泄漏检测方法[J].传感器与微系统,2007,26(7)：108-110.
[12]张志鹏,W. A. Gambling光纤传感器原理[M].北京：中国计量出版社,1990.
[13]Stephanus J. Spammer, Pieter L. Swart. Merged Sagnac-michelson interferometer distributed disturbance detection [J]. Journal of lightwave technology,1997,15：972-976.
[14]钱建华.关于中国石化油气管道发展的思考[J].油气储运,2003,22(9)：18-21.
[15]汪向阳.基于地震波检测的管道安全预警系统[D].(硕)天津：天津大学精密仪器与光电子工程学院,2008.
[16]A Stephenne, B Champagne. Cepstral prefiltering for time delay estimation in reverberant environments [C]. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'95), May 1995. USA:IEEE,1995,5:3055-3058.
[17]胡广书.数字信号处理——理论、算法与实现(第二版)[M].北京：清华大学出版社,2003.
[18]冯炜,纪奕才.应用倒谱域滤波的TDR波形分析[J].电子与信息学报,2009,31(12).
[19]杨德森,时洁,刘伯胜.基于倒谱分析的水声信号被动定位时延估计算法研究[J].系统仿真学报,2009,21(2)：610-616.
[20]张德会,陈光冶.复倒谱域语音信号去混响研究[J].声学技术,2009,28(1).
[21]王宏禹,邱天爽.自适应噪声抵消与时间延迟估计[M].大连：大连理工大学出版社,1999.
[22]C. H. Knapp, G. C. Carter. The generalized correlation method for estimation of time delay [J]. IEEE Trans. Acoustics, Speech, and Signal Processing,1976,24(4):320-327.
[23]尹成友,徐善驾,王东进.时延估计的克拉美罗下界的渐近分析[J].应用科学学报,1998,16(2)：140-148.
[24]R. Cusani. Performance of fast time delay estimators [J]. IEEE Trans. Acoustics, Speech, and Signal Processing, vol.37,1989(5):757-759.
[25]L. R. Rabiner, M. J. Cheng, A. E. Rosenberg et al. A comparative performance study of several pitch detection algorithms [J]. IEEE Trans. Acoustics, Speech, and Signal Processing,1976,24(5):399-418.
[26]G. Jacovitti, G. Scarano. Discrete time techniques for time delay estimation [J]. IEEE Trans. Signal Processing,1993,41 (2):525-533.
[27]Jingdong Chen, Jacob Benesty. Performance of GCC-and AMDF-Based Time-Delay Estimation in Practical Reverberant Environments [J]. EURASIP Journal on Applied Signal Processing,2005(2005):25-36.
[28]沙岚.无线电无源定位中窄带信号时延估计方法研究[D].(硕)大连：大连理工大学,2009.
[29]Gao Yang, Qiu Tiangshuang. A Xarrowband Time Delay Estimating Based on Correlation Coefficient [J]. Journal of Systems Engineering and Electronics,2009,20(2):1-5.
[30]鲁铁定,陶本藻.基于整体最小二乘法的线性回归建模和解法[J].武汉大学学报(信息科学版),2008,33(5).
[2]周琰.分布式光纤管道安全检测技术研究[D].(博)天津：天津大学精密仪器与光电子工科学院,2006.
[3]吴俊.长途油气管道破坏预警的干涉型分布式光纤传感系统定位技术研究[D].(硕)重庆：重庆大学光电工程学院,2007.
[4]林蕾.基于萨格奈克原理的分布式光纤长途油气管道破坏预警系统关键技术研究[D].(硕)重庆：重庆大学光电工程学院,2009.
[5]马庆万.基于振动原理的石油管道泄漏报警系统研究[D].(硕)黑龙江：大庆石油学院,2010.
[6]付道明,孙军,贺志刚等.国内外管道泄漏检测技术研究进展[J].石油机械,2004,32(3)：48-51.
[7]于喜元,楼俊君,杨平.管道超声波检测器的应用与发展趋势[J].油气储运,2003(4)：35-37.
[8]姜涛.管道泄漏检测与定位的应用研究[D].(硕)哈尔滨：哈尔滨工程大学,2008.
[9]陈华波,涂亚庆.输油管道泄漏检测方法综述[J].管道技术与设备,2000(1)：38-41.
[10]袁军国.分布式马赫-泽德干涉仪的原理与应用研究[D].(博)武汉：华中科技大学,2006.
[11]陈志刚,张来斌,王朝晖等.基于分布式光纤传感器的输气管道泄漏检测方法[J].传感器与微系统,2007,26(7)：108-110.
[12]张志鹏,W. A. Gambling光纤传感器原理[M].北京：中国计量出版社,1990.
[13]Stephanus J. Spammer, Pieter L. Swart. Merged Sagnac-michelson interferometer distributed disturbance detection [J]. Journal of lightwave technology,1997,15：972-976.
[14]钱建华.关于中国石化油气管道发展的思考[J].油气储运,2003,22(9)：18-21.
[15]汪向阳.基于地震波检测的管道安全预警系统[D].(硕)天津：天津大学精密仪器与光电子工程学院,2008.
[16]A Stephenne, B Champagne. Cepstral prefiltering for time delay estimation in reverberant environments [C]. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'95), May 1995. USA:IEEE,1995,5:3055-3058.
[17]胡广书.数字信号处理——理论、算法与实现(第二版)[M].北京：清华大学出版社,2003.
[18]冯炜,纪奕才.应用倒谱域滤波的TDR波形分析[J].电子与信息学报,2009,31(12).
[19]杨德森,时洁,刘伯胜.基于倒谱分析的水声信号被动定位时延估计算法研究[J].系统仿真学报,2009,21(2)：610-616.
[20]张德会,陈光冶.复倒谱域语音信号去混响研究[J].声学技术,2009,28(1).
[21]王宏禹,邱天爽.自适应噪声抵消与时间延迟估计[M].大连：大连理工大学出版社,1999.
[22]C. H. Knapp, G. C. Carter. The generalized correlation method for estimation of time delay [J]. IEEE Trans. Acoustics, Speech, and Signal Processing,1976,24(4):320-327.
[23]尹成友,徐善驾,王东进.时延估计的克拉美罗下界的渐近分析[J].应用科学学报,1998,16(2)：140-148.
[24]R. Cusani. Performance of fast time delay estimators [J]. IEEE Trans. Acoustics, Speech, and Signal Processing, vol.37,1989(5):757-759.
[25]L. R. Rabiner, M. J. Cheng, A. E. Rosenberg et al. A comparative performance study of several pitch detection algorithms [J]. IEEE Trans. Acoustics, Speech, and Signal Processing,1976,24(5):399-418.
[26]G. Jacovitti, G. Scarano. Discrete time techniques for time delay estimation [J]. IEEE Trans. Signal Processing,1993,41 (2):525-533.
[27]Jingdong Chen, Jacob Benesty. Performance of GCC-and AMDF-Based Time-Delay Estimation in Practical Reverberant Environments [J]. EURASIP Journal on Applied Signal Processing,2005(2005):25-36.
[28]沙岚.无线电无源定位中窄带信号时延估计方法研究[D].(硕)大连：大连理工大学,2009.
[29]Gao Yang, Qiu Tiangshuang. A Xarrowband Time Delay Estimating Based on Correlation Coefficient [J]. Journal of Systems Engineering and Electronics,2009,20(2):1-5.
[30]鲁铁定,陶本藻.基于整体最小二乘法的线性回归建模和解法[J].武汉大学学报(信息科学版),2008,33(5).