Unequally Interval Data Processing Across Fault Deformation Measurement

Peizhi Wu; Tianhai Liu; Mingyong Lu; Yan Xiong; Leyin Hu; Pingfa Zhang; Jiannong Wen; Hong Ji; Gang Feng

doi:doi:10.11648/j.earth.20221102.11

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Unequally Interval Data Processing Across Fault Deformation Measurement

Peizhi Wu, Tianhai Liu, Mingyong Lu, Yan Xiong, Leyin Hu, Pingfa Zhang, Jiannong Wen, Hong Ji, Gang Feng

Published in Earth Sciences (Volume 11, Issue 2)

Received: 10 March 2022 Accepted: 1 April 2022 Published: 14 April 2022

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Abstract

According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.

Published in	Earth Sciences (Volume 11, Issue 2)
DOI	10.11648/j.earth.20221102.11
Page(s)	29-34
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Cross-Fault Deformation Measurement, Retest Period, Unequal Interval Data, Synchronization Domain, Comparability

References

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[4]	Lu M., Liu T., & Huang B., et al (2011). Discussion of Environment and Monitoring Technology for Cross-Fault Mobile Deformation Monitoring. Journal of Geodesy and Geodynamics, 31 (5), 141-145. doi: 10.14075/j.jgg.2011.05.031.
[5]	Software Technology Group, State Seismological Bureau. The Software System for Earthquake Prediction in China. Beijing: Seismological Press, 1994.
[6]	Jiang J., Li S., & Zhang Y., et al (2000). Earthquake Precursor Information Processing and Software System. Seismological Press.
[7]	Lu Y., Li S., & Deng Z., et al (2002). GIS-Based Seismic Analysis and Forecasting System. Chengdu Cartographic Publishing House.
[8]	Peng Y., Wu A., & Li S., et al (2012). Dynamic Display of Observation Curve on China Earthquake Precursor Network. Journal of Geodesy and Geodynamics, 32 Supp., 49-52. doi: 10.14075/j.jgg.2012.S1.015.
[9]	Qu J., Zhang S., (2014). Study on Cross-Fault Site Information System Based on GIS. Recent Developments in World Seismology, 424 (4), 27-34.
[10]	Lu M., Xiong D., & Yu H., et al (2015). The Building of Temporary Cross-Fault Deformation Basis and Monitoring Data and It’s Environmental Information Database in The Capital Region. Recent Developments in World Seismology, 442 (10), 32-38.
[11]	Liu W., Lu M., & Luo S., et al (2020). Design and Implementation of Data Management and Pre-processing System for Cross-Fault Flow Deformation. Technology for Earthquake Disaster Prevention, 15 (3), 635-642. Doi: 10.11899/zzfy20200318.
[12]	Xu S. (1994). C Common Algorithms. Tsinghua University Press.
[13]	Lu M., Wu P., & Li Q., et al (2019). Software Construction of Data Processing for Cross Fault Flow Deformation. Recent Developments in World Seismology, 486 (6), 14-19.

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APA Style

Peizhi Wu, Tianhai Liu, Mingyong Lu, Yan Xiong, Leyin Hu, et al. (2022). Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sciences, 11(2), 29-34. https://doi.org/10.11648/j.earth.20221102.11

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ACS Style

Peizhi Wu; Tianhai Liu; Mingyong Lu; Yan Xiong; Leyin Hu, et al. Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sci. 2022, 11(2), 29-34. doi: 10.11648/j.earth.20221102.11

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AMA Style

Peizhi Wu, Tianhai Liu, Mingyong Lu, Yan Xiong, Leyin Hu, et al. Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sci. 2022;11(2):29-34. doi: 10.11648/j.earth.20221102.11

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@article{10.11648/j.earth.20221102.11,
  author = {Peizhi Wu and Tianhai Liu and Mingyong Lu and Yan Xiong and Leyin Hu and Pingfa Zhang and Jiannong Wen and Hong Ji and Gang Feng},
  title = {Unequally Interval Data Processing Across Fault Deformation Measurement},
  journal = {Earth Sciences},
  volume = {11},
  number = {2},
  pages = {29-34},
  doi = {10.11648/j.earth.20221102.11},
  url = {https://doi.org/10.11648/j.earth.20221102.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20221102.11},
  abstract = {According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.},
 year = {2022}
}

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TY  - JOUR
T1  - Unequally Interval Data Processing Across Fault Deformation Measurement
AU  - Peizhi Wu
AU  - Tianhai Liu
AU  - Mingyong Lu
AU  - Yan Xiong
AU  - Leyin Hu
AU  - Pingfa Zhang
AU  - Jiannong Wen
AU  - Hong Ji
AU  - Gang Feng
Y1  - 2022/04/14
PY  - 2022
N1  - https://doi.org/10.11648/j.earth.20221102.11
DO  - 10.11648/j.earth.20221102.11
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 29
EP  - 34
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20221102.11
AB  - According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.
VL  - 11
IS  - 2
ER  -

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Author Information

Peizhi Wu

Beijing Earthquake Agency, Beijing, China
Tianhai Liu

National Earthquake Response Support Service, Beijing, China
Mingyong Lu

National Earthquake Response Support Service, Beijing, China
Yan Xiong

Beijing Earthquake Agency, Beijing, China
Leyin Hu

Beijing Earthquake Agency, Beijing, China
Pingfa Zhang

National Earthquake Response Support Service, Beijing, China
Jiannong Wen

Beijing Earthquake Agency, Beijing, China
Hong Ji

Beijing Earthquake Agency, Beijing, China
Gang Feng

Beijing Earthquake Agency, Beijing, China

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Plain Text BibTeX RIS

APA Style

Peizhi Wu, Tianhai Liu, Mingyong Lu, Yan Xiong, Leyin Hu, et al. (2022). Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sciences, 11(2), 29-34. https://doi.org/10.11648/j.earth.20221102.11

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ACS Style

Peizhi Wu; Tianhai Liu; Mingyong Lu; Yan Xiong; Leyin Hu, et al. Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sci. 2022, 11(2), 29-34. doi: 10.11648/j.earth.20221102.11

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AMA Style

Peizhi Wu, Tianhai Liu, Mingyong Lu, Yan Xiong, Leyin Hu, et al. Unequally Interval Data Processing Across Fault Deformation Measurement. Earth Sci. 2022;11(2):29-34. doi: 10.11648/j.earth.20221102.11

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@article{10.11648/j.earth.20221102.11,
  author = {Peizhi Wu and Tianhai Liu and Mingyong Lu and Yan Xiong and Leyin Hu and Pingfa Zhang and Jiannong Wen and Hong Ji and Gang Feng},
  title = {Unequally Interval Data Processing Across Fault Deformation Measurement},
  journal = {Earth Sciences},
  volume = {11},
  number = {2},
  pages = {29-34},
  doi = {10.11648/j.earth.20221102.11},
  url = {https://doi.org/10.11648/j.earth.20221102.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20221102.11},
  abstract = {According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Unequally Interval Data Processing Across Fault Deformation Measurement
AU  - Peizhi Wu
AU  - Tianhai Liu
AU  - Mingyong Lu
AU  - Yan Xiong
AU  - Leyin Hu
AU  - Pingfa Zhang
AU  - Jiannong Wen
AU  - Hong Ji
AU  - Gang Feng
Y1  - 2022/04/14
PY  - 2022
N1  - https://doi.org/10.11648/j.earth.20221102.11
DO  - 10.11648/j.earth.20221102.11
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 29
EP  - 34
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20221102.11
AB  - According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.
VL  - 11
IS  - 2
ER  -

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