Satellite magnetic field data earthquake abnormality detection method based on non-negative matrix decomposition

A technique of non-negative matrix decomposition, magnetic field data, applied in seismic survey, seismology, geophysical survey, etc.

Active Publication Date: 2020-01-10
JILIN UNIV
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Problems solved by technology

[0007] The above technology uses the traditional method to remove the influence of solar and geomagnetic activi

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  • Satellite magnetic field data earthquake abnormality detection method based on non-negative matrix decomposition
  • Satellite magnetic field data earthquake abnormality detection method based on non-negative matrix decomposition
  • Satellite magnetic field data earthquake abnormality detection method based on non-negative matrix decomposition

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[0095] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0096] see figure 1 As shown, a seismic anomaly detection method based on non-negative matrix factorization of satellite magnetic field data, the method includes:

[0097] a. Read the magnetic field data of the satellite, and remove invalid data according to the flag;

[0098] b. The original data is the data after removing invalid data minus the CHAOS-6 magnetic field model data, and calculate the first-order difference of the result;

[0099] c. Perform short-time Fourier transform on the difference data to construct a non-negative time-frequency amplitude matrix corresponding to the magnetic field data;

[0100] d. Us...

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Abstract

The invention relates to a satellite magnetic field data seismic abnormality detection method based on non-negative matrix decomposition. The method comprises a step of removing invalid data accordingto a flag bit and subtracting CHAOS-6 magnetic field model data, and solving a first-order difference of a result to obtain differential data, a step of performing short-time Fourier transform on thedifferential data to construct a non-negative time-frequency amplitude matrix corresponding to magnetic field data, a step of decomposing the non-negative time-frequency amplitude matrix by using a non-negative matrix decomposition method and separating a local influence component generated by an earthquake from a global influence component generated by a sun activity and a geomagnetic activity,a step of selecting the local influence component generated by the earthquake according to an energy ratio and carrying out abnormal track judgment on the component through an over-limit rate method,and a step of accumulating the number of abnormal orbits every day and detecting earthquake abnormality according to the degree of deviation from a background fitting straight line. According to the invention, all data obtained by measurement can be reserved and utilized to research the earthquake, and at the same time, components more related to the earthquake activity can be obtained to effectively perform earthquake abnormality detection.

Description

technical field [0001] The invention belongs to the field of earthquake monitoring, and specifically relates to a non-negative matrix decomposition-based seismic anomaly detection method for satellite magnetic field data. Background technique [0002] Seismic anomalies refer to abnormal phenomena before and after an earthquake, including geomagnetic, geoelectric, gravity and other geophysical anomalies near the epicenter. Researchers often detect seismic anomalies by measuring the above physical quantities and studying their anomalies. Measurement methods mainly include ground stations and satellite monitoring. Satellite monitoring has been widely studied because of its wide measurement range and proven ability to detect seismic anomalies. Among them, the magnetic field data measured by satellites has been extensively studied. At present, the influence of solar and geomagnetic activities on the data is excluded by selecting nighttime data and removing data with high solar a...

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Application Information

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IPC IPC(8): G01V1/28G01V1/00G01V3/08G01V3/38
CPCG01V1/008G01V1/28G01V3/081G01V3/38
Inventor 朱凯光樊蒙璇李凯艳贺小丹池成全于紫凝孙慧慧
Owner JILIN UNIV
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