阅读说明：本技术 基于saa监测的地裂缝活跃性分析方法及装置 (Ground fracture activity analysis method and device based on SAA monitoring ) 是由 刘祥磊 苏珊 马静 于 2019-09-10 设计创作，主要内容包括：本发明公开了一种基于SAA监测的地裂缝活跃性分析方法及装置,所述方法将由SAA监测取得地裂缝活动的原始时序位移信号分解成一系列简单子信号、再利用相关系数对简单子信号降噪处理,得到对应的有效子信号；对获取得到的有效子信号进行叠加得到重构的有效时序位移信号,并对有效时序位移信号进行分解、得到一系列对应的有效简单子信号；计算并获取每一个有效简单子信号的瞬时能量；对所有简单子信号的瞬时能量进行叠加,得到代表地裂缝活动整体强度的瞬时总能量。根据本发明的基于SAA监测的地裂缝活跃性分析方法实施例提高了地裂缝活动有效监测的精度,还提高了对其活跃性分析的准确性,从而降低地裂缝对城市建设和人居安全的危害性。(The invention discloses a method and a device for analyzing the activity of a ground fracture based on SAA monitoring, wherein the method decomposes an original time sequence displacement signal of the ground fracture activity obtained by the SAA monitoring into a series of simple sub-signals, and then carries out noise reduction processing on the simple sub-signals by utilizing a correlation coefficient to obtain corresponding effective sub-signals; superposing the obtained effective sub-signals to obtain reconstructed effective time sequence displacement signals, and decomposing the effective time sequence displacement signals to obtain a series of corresponding effective simple sub-signals; calculating and obtaining the instantaneous energy of each effective simple sub-signal; and superposing the instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the integral intensity of the ground fracture activity. According to the method for analyzing the activity of the ground fissure based on the SAA monitoring, the precision of effective monitoring of the activity of the ground fissure is improved, and the accuracy of analyzing the activity of the ground fissure is also improved, so that the harm of the ground fissure to urban construction and human settlement safety is reduced.)

1. a method for analyzing activity of a ground fracture based on SAA monitoring, which is characterized by comprising the following steps:

Acquiring original time sequence displacement signals of an upper plate and a lower plate of a ground fissure obtained by SAA monitoring;

Decomposing the original time sequence displacement signal into a series of simple sub-signals;

carrying out noise reduction processing on each simple sub-signal by utilizing a correlation coefficient to obtain a series of corresponding effective sub-signals;

Superposing all the obtained effective sub-signals to obtain a reconstructed effective time sequence displacement signal, and decomposing the effective time sequence displacement signal into a series of corresponding effective simple sub-signals;

Calculating and acquiring the instantaneous energy of each effective simple sub-signal according to the effective simple sub-signals;

and superposing the acquired instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the overall intensity of the earth fracture activity.

2. the method of claim 1, wherein the decomposing the original timing shift signal into a series of simple sub-signals specifically comprises:

Finding out all local extreme points according to the original time sequence displacement signal;

Acquiring midpoints of adjacent extreme points, and acquiring midpoints of left and right boundaries by adopting an interpolation method;

respectively constructing two corresponding interpolation curves by using odd midpoints and even midpoints, and acquiring each average value of the two interpolation curves according to time sequence;

According to a set allowable error or a maximum screening frequency as a termination judgment condition, sequentially judging whether the absolute value of the average value is greater than the allowable error or whether the current screening frequency is less than the maximum screening frequency according to a time sequence;

when the absolute value corresponding to the average value is judged to be larger than the allowable error or the current screening frequency is smaller than the maximum screening frequency, generating a corresponding eigenmode function;

When the absolute value corresponding to the average value is judged to be smaller than the allowable error or the current screening frequency is judged to be larger than the maximum screening frequency, taking a difference value obtained by subtracting the average value from the corresponding original time sequence displacement signal as a first time sequence displacement signal for iteration until the set termination judgment condition of the allowable error or the maximum screening frequency is met; thereby generating corresponding eigenmode functions;

Using the difference between the original time sequence displacement signal and the generated first eigenmode function as a second time sequence displacement signal to carry out iteration until the last residual error item is smaller than any extreme value; after iteration is completed, a series of corresponding eigenmode functions are generated to be used as a series of simple sub-signals obtained by decomposing the original time sequence displacement signals.

3. The method of claim 2, wherein the denoising each of the simple sub-signals using the correlation coefficient to obtain a series of corresponding valid sub-signals specifically comprises:

calculating to obtain a correlation coefficient between each simple sub-signal and the corresponding original time sequence displacement signal;

finding out a critical point at which the correlation coefficient gradually decreases to be gradually increased according to the obtained correlation coefficient;

and removing the components of the simple sub-signals before the critical point as noise to obtain a series of corresponding effective sub-signals.

4. An apparatus for analyzing activity of ground fracture based on SAA monitoring, comprising:

The original signal acquisition module is used for acquiring original time sequence displacement signals of an upper disk and a lower disk of the ground fissure, which are acquired by SAA monitoring;

The decomposition module is used for decomposing the original time sequence displacement signal into a series of simple sub-signals;

The noise reduction processing module is used for carrying out noise reduction processing on each simple sub-signal by utilizing the correlation coefficient to obtain a series of corresponding effective sub-signals;

The reconstruction and re-decomposition module is used for superposing all the obtained effective sub-signals to obtain reconstructed effective time sequence displacement signals and decomposing the effective time sequence displacement signals into a series of corresponding effective simple sub-signals;

The instantaneous energy calculation module is used for calculating and acquiring the instantaneous energy of each effective simple sub-signal according to the effective simple sub-signals;

And the instantaneous total energy calculation module is used for superposing the acquired instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the integral intensity of the earth fracture activity.

5. The SAA-monitoring-based ground fracture activity analysis device of claim 4, wherein the decomposition module specifically comprises:

The extreme point acquisition unit is used for finding out all local extreme points according to the original time sequence displacement signal;

a midpoint acquisition unit, configured to acquire midpoints between adjacent extreme points, and acquire midpoints of left and right boundaries by using an interpolation method;

The device comprises an interpolation curve construction and average value acquisition unit, a data acquisition unit and a data acquisition unit, wherein the interpolation curve construction and average value acquisition unit is used for constructing two corresponding interpolation curves by using odd midpoints and even midpoints respectively and acquiring each average value of the two interpolation curves according to time sequence;

the judging unit is used for sequentially judging whether the absolute value of the average value is greater than the allowable error or whether the current screening frequency is less than the maximum screening frequency according to a time sequence according to a set allowable error or the maximum screening frequency as a termination judging condition;

An eigenmode function generating unit, configured to generate a corresponding eigenmode function when it is determined that the absolute value corresponding to the average value is greater than the allowable error or the current screening frequency is less than the maximum screening frequency;

a first iteration unit, configured to, when it is determined that the absolute value corresponding to the average value is smaller than the allowable error or the current screening frequency is greater than the maximum screening frequency, perform iteration using a difference obtained by subtracting the average value from an original time series displacement signal corresponding to the average value as a first time series displacement signal until a termination determination condition of the set allowable error or the maximum screening frequency is satisfied; thereby generating corresponding eigenmode functions;

a second iteration unit for iterating using the difference between the original time series shifted signal and the generated first eigenmode function as a second time series shifted signal until the last residual term is less than any one extremum value; after iteration is completed, a series of corresponding eigenmode functions are generated to be used as a series of simple sub-signals obtained by decomposing the original time sequence displacement signals.

6. The apparatus of claim 5, wherein the noise reduction processing module specifically comprises:

the correlation coefficient calculation unit is used for calculating and obtaining a correlation coefficient between each simple sub-signal and the corresponding original time sequence displacement signal;

a critical point searching unit, configured to find a critical point at which the correlation coefficient gradually decreases to a gradually increasing value according to the obtained correlation coefficient;

and the noise removing unit is used for removing the components of the simple sub-signals before the critical point as noise to obtain a series of corresponding effective sub-signals.

7. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the SAA monitoring-based earth fracture activity analysis method of any of claims 1-3.

8. a computer storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method of any of claims 1 to 3 for SAA-based monitoring of activity of earth fractures.

Technical Field

the invention relates to a ground fracture activity analysis technology, in particular to a ground fracture activity analysis method and device based on SAA monitoring.

Background

the ground crack is a geological disaster, namely, the ground cracks under the influence of natural or man-made factors. The ground cracks have the characteristics of strong concealment and great harmfulness, can directly destroy various engineering constructions such as linear engineering, water conservancy facilities and urban buildings, and meanwhile severely restricts urban planning, effective utilization of land, development and utilization of underground water and development of underground space.

Because the scale, cause and the like of the ground fissure are different, in the prior art, three monitoring means for the ground fissure are mainly provided, namely leveling measurement, Global Positioning System (GPS) monitoring and interferometric synthetic aperture radar (InSAR) measurement. Leveling is a traditional ground deformation monitoring technology, can provide high-precision ground settlement measurement at a selected position, and has the advantages of simplicity in operation and low cost. However, the manual field investigation and measurement has a large workload and a long period, and complete formation fracture deformation information is difficult to obtain in both time and space. Secondly, the GPS monitoring has the advantage of high precision in the aspect of three-dimensional positioning, and the three-dimensional absolute deformation of monitoring points in a monitoring area can be obtained, however, due to the limitation of various factors, the arranged GPS monitoring points are always limited, and the ground fracture deformation of the whole area is difficult to effectively obtain.

The InSAR technology has the advantages of high spatial resolution, all-time and all-weather, and the like, and is successfully applied to a plurality of geological disaster monitoring projects. The InSAR technique can provide the monitored ground fracture deformation sequence results in the form of an annual average deformation rate graph, and further detect the change of ground fracture activity. However, since the InSAR technology lacks an absolute reference position during monitoring and lacks an effective means for eliminating interference errors such as atmosphere, the accuracy of the deformation amount of the earth fracture obtained by the InSAR technology is not high.

It can be seen from the above that the above three ground crack activity monitoring technologies in the prior art are greatly influenced by the terrain and the land range, so that the monitoring result is not reliable enough. Therefore, the invention provides a ground fracture activity analysis method based on the problems, so as to improve the effective monitoring precision of ground fracture activity and improve the activity analysis accuracy, thereby reducing the harmfulness of ground fractures to urban construction and human settlement safety.

disclosure of Invention

the present invention is directed to solving, at least to some extent, one of the technical problems in the related art. Therefore, the first purpose of the invention is to provide a method for analyzing the activity of the earth fracture based on SAA monitoring.

The second purpose of the invention is to provide a ground fracture activity analysis device based on SAA monitoring.

A third object of the invention is to propose a computer device.

A fourth object of the invention is to propose a computer storage medium.

to achieve the above object, in a first aspect, a method for analyzing activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention includes:

Acquiring original time sequence displacement signals of an upper plate and a lower plate of a ground fissure obtained by SAA monitoring;

Decomposing the original time sequence displacement signal into a series of simple sub-signals;

Carrying out noise reduction processing on each simple sub-signal by utilizing a correlation coefficient to obtain a series of corresponding effective sub-signals;

Superposing all the obtained effective sub-signals to obtain a reconstructed effective time sequence displacement signal, and decomposing the effective time sequence displacement signal into a series of corresponding effective simple sub-signals;

calculating and acquiring the instantaneous energy of each effective simple sub-signal according to the effective simple sub-signals;

And superposing the acquired instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the overall intensity of the earth fracture activity.

In a second aspect, an apparatus for analyzing activity of earth fracture based on SAA monitoring according to an embodiment of the present invention includes:

the original signal acquisition module is used for acquiring original time sequence displacement signals of an upper disk and a lower disk of the ground fissure, which are acquired by SAA monitoring;

the decomposition module is used for decomposing the original time sequence displacement signal into a series of simple sub-signals;

The noise reduction processing module is used for carrying out noise reduction processing on each simple sub-signal by utilizing the correlation coefficient to obtain a series of corresponding effective sub-signals;

the reconstruction and re-decomposition module is used for superposing all the obtained effective sub-signals to obtain reconstructed effective time sequence displacement signals and decomposing the effective time sequence displacement signals into a series of corresponding effective simple sub-signals;

the instantaneous energy calculation module is used for calculating and acquiring the instantaneous energy of each effective simple sub-signal according to the effective simple sub-signals;

and the instantaneous total energy calculation module is used for superposing the acquired instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the integral intensity of the earth fracture activity.

In a third aspect, a computer device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for analyzing activity of earth fracture based on SAA monitoring as described above when executing the computer program.

In a fourth aspect, a computer storage medium according to an embodiment of the present invention stores thereon a computer program, wherein the program is executed by a processor to implement the method for analyzing activity of earth fracture based on SAA monitoring as described above.

According to the method and the device for analyzing the activity of the ground fracture based on the SAA monitoring, provided by the embodiment of the invention, the original time sequence displacement signals of the ground fracture activity obtained by the SAA monitoring are decomposed into a series of simple sub-signals, and then the simple sub-signals are subjected to noise reduction treatment by utilizing correlation coefficients to obtain corresponding effective sub-signals; superposing the obtained effective sub-signals to obtain reconstructed effective time sequence displacement signals, and decomposing the effective time sequence displacement signals to obtain a series of corresponding effective simple sub-signals; calculating and obtaining the instantaneous energy of each effective simple sub-signal; and superposing the instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the integral intensity of the ground fracture activity. According to the method for analyzing the activity of the ground fissure based on the SAA monitoring, the precision of effective monitoring of the activity of the ground fissure is improved, and the accuracy of analyzing the activity of the ground fissure is also improved, so that the harm of the ground fissure to urban construction and human settlement safety is reduced.

additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.

FIG. 1 is a flow chart of a method for analyzing the activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention;

FIG. 2 is a flowchart of step S102 of a method for analyzing activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention;

FIG. 3 is a flowchart of step S103 of a method for analyzing activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of an apparatus for analyzing activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of the structure of one embodiment of the computer device of the present invention.

the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.

influenced by the terrain and land range, three main ground fracture activity monitoring technologies in the prior art: the leveling, Global Positioning System (GPS) monitoring and interferometric synthetic aperture radar (InSAR) technologies have unreliable monitoring results.

generally, the ground fracture activity is influenced by various external forces, and when external forces in different directions act on the ground fracture at the same time, the ground fracture may not generate displacement activity, but the ground fracture is in an active state at the moment. Therefore, the activity analysis of the earth fracture directly using the time series displacement data is unreliable. In order to further analyze the activity rule of the ground fracture, the invention provides a ground fracture activity analysis method based on the instantaneous total energy of time sequence displacement data. The method for analyzing the instantaneous energy activity mainly comprises the following steps: the method comprises the steps of actually measured signal decomposition, correlation coefficient noise reduction, signal reconstruction and secondary decomposition, eigenmode function (IMF) instantaneous energy solving and instantaneous total energy superposition. Therefore, the invention aims to improve the precision of effective monitoring of ground fissure activity and improve the accuracy of activity analysis of the ground fissure activity, thereby reducing the harmfulness of the ground fissure on urban construction and human settlement safety.

Referring to fig. 1, fig. 1 is a flowchart illustrating an embodiment of a method for analyzing an activity of a ground fracture based on SAA monitoring according to an embodiment of the present invention, where only portions related to the embodiment of the present invention are shown for convenience of description.

When the invention is implemented, the method for analyzing the activity of the ground fracture based on the SAA monitoring specifically comprises the following steps:

S101, acquiring original time sequence displacement signals of an upper disk and a lower disk of the ground fissure obtained by SAA monitoring.

And S102, decomposing the original time sequence displacement signal into a series of simple sub-signals.

S103, carrying out noise reduction processing on each simple sub-signal by utilizing the correlation coefficient to obtain a series of corresponding effective sub-signals.

s104, superposing all the obtained effective sub-signals to obtain a reconstructed effective time sequence displacement signal, and decomposing the effective time sequence displacement signal into a series of corresponding effective simple sub-signals.

And S105, calculating and acquiring the instantaneous energy of each effective simple sub-signal according to the effective simple sub-signals.

and S106, superposing the acquired instantaneous energy of all the simple sub-signals to obtain the instantaneous total energy representing the overall intensity of the earth fracture activity.

specifically, the Array type displacement sensor SAA (SAA for short) can be buried in the ground fissure by a method different from the method for monitoring the ground fissure in the past, so that the real-time deformation information in the ground fissure can be obtained, the activity rule and the influence factors of the ground fissure can be more effectively analyzed, the economic loss caused by ground fissure disasters can be reduced, and the personal and property safety can be guaranteed. The array type displacement sensor SAA is an array type displacement sensor based on a micro-electro-mechanical system, the interior of the array type displacement sensor is composed of a three-axis micro-electro-mechanical system (MEMS) accelerometer, the three-dimensional coordinates of a measured target can be continuously measured, the data sampling frequency can be obtained once in an hour, and the precision can reach +/-1.5 mm/32 m.

further, as shown in fig. 2, the step S102 specifically includes:

S201, finding out all local extreme points according to the original time sequence displacement signal.

S202, acquiring the middle points adjacent to the extreme points, and acquiring the middle points of the left boundary and the right boundary by adopting an interpolation method.

S203, two corresponding interpolation curves are respectively constructed by using the odd midpoints and the even midpoints, and each average value of the two interpolation curves is obtained according to time sequence.

And S204, sequentially judging whether the absolute value of the average value is greater than the allowable error or whether the current screening frequency is less than the maximum screening frequency according to a time sequence according to the set allowable error or the maximum screening frequency as a termination judgment condition.

S205, when the absolute value corresponding to the average value is judged to be larger than the allowable error or the current screening frequency is smaller than the maximum screening frequency, generating a corresponding eigenmode function.

And S206, when the absolute value corresponding to the average value is judged to be smaller than the allowable error or the current screening frequency is judged to be larger than the maximum screening frequency, taking a difference value obtained by subtracting the average value from the corresponding original time sequence displacement signal as a first time sequence displacement signal for iteration until the termination judgment condition of the set allowable error or the maximum screening frequency is met, and generating a corresponding eigenmode function.

and S207, using the difference value of the original time sequence displacement signal and the generated first eigenmode function as a second time sequence displacement signal to iterate until the last residual error item is smaller than any extreme value. After iteration is completed, a series of corresponding eigenmode functions are generated to be used as a series of simple sub-signals obtained by decomposing the original time sequence displacement signals.

The original time-series displacement signal obtained by the SAA is decomposed into a series of simple sub-signals by the algorithm of the above steps S201 to S207. Specifically, when the original time sequence displacement signal is decomposed into simple signals representing each section of frequency, the simple signals reflect the essential characteristics of the original time sequence displacement signal to a certain extent.

When the invention is implemented, the specific algorithm steps are as follows:

s1021, starting;

S1022, acquiring an original time sequence displacement signal curve S (t), and acquiring all local extreme points of the S (t) curve;

S1023, acquiring midpoints adjacent to the extreme points, and acquiring (n +1) midpoints of left and right boundaries of the S (t) curve by adopting an interpolation method;

S1024, constructing two corresponding interpolation curves by using odd midpoints and even midpoints respectively, and obtaining an average value L of each of the two interpolation curves according to a time sequence;

S1025, setting an allowable error epsilon and a maximum screening frequency kappa as termination judgment conditions;

s1026, judging whether the absolute value | L | of the average value L is larger than an allowable error epsilon or whether the current screening frequency is smaller than a set maximum screening frequency kappa; if yes, go to step S1027, otherwise go to step S1028;

s1027, generating a corresponding jth eigenmode function IMF;

S1028, calculating the difference S (t) ═ S (t) -L, and performing iteration by substituting the calculated S (t) into step S1022;

S1029, substituting the difference S (t) between the original time sequence shift signal and the jth eigenmode function M into S (t) -M, and performing iteration in step S1022 until the last residual term is smaller than any extremum value;

And S1030, ending.

after the iteration of the algorithm is completed, corresponding m eigenmode functions IMF are generated to be used as a series of simple sub-signals obtained by decomposing the original time sequence displacement signal and a trend item. When the original time sequence displacement signal is decomposed into simple sub-signals representing each section of frequency, the simple sub-signals reflect the essential characteristics of the original time sequence displacement signal to a certain extent.

Further, as shown in fig. 3, the step S103 specifically further includes:

s301, calculating to obtain a correlation coefficient between each simple sub-signal and the corresponding original time sequence displacement signal.

S302, according to the obtained correlation coefficient, finding out a critical point that the correlation coefficient gradually decreases to gradually increase.

And S303, removing the components of the simple sub-signals before the critical point as noise to obtain a series of corresponding effective sub-signals.

specifically, in the process of monitoring ground cracks by using the SAA sensor, noise is inevitably generated due to the influence of various environmental factors such as traffic, ground motion and the like, so that the accuracy of the obtained original time series displacement signal is reduced. Therefore, the complex original time-series displacement signal is decomposed into a plurality of simple sub-signals, which must include corresponding effective signals and noise signals. The invention adopts correlation analysis to carry out noise reduction processing on all the obtained simple sub-signals. The invention uses the correlation coefficient to determine the component of the eigenmode function IMF occupied by the noise, and removes the component to achieve the noise reduction effect.