CN117148434A - Microseismic signal self-adaptive resolving method based on time sequence contribution graph decomposition - Google Patents
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Abstract
The application provides a microseismic signal self-adaptive resolving method based on time sequence contribution diagram decomposition, which comprises the following steps: when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved; determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved; and determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved. The technical scheme provided by the application can accurately excavate the root signal channel, thereby providing reference for downstream tasks such as follow-up microseismic positioning and the like.
Description
Technical Field
The application relates to the technical field of microseismic monitoring, in particular to a microseismic signal self-adaptive resolving method based on time sequence contribution graph decomposition.
Background
Along with the increase of coal mining depth year by year, various monitoring systems become important components for guaranteeing coal safety production, wherein the microseismic monitoring system is used as an area, real-time and continuous monitoring system, can collect and analyze various vibration signals in real time, and is widely applied to the field of coal mine safety monitoring. However, the monitoring study of microseismic signals in the prior art mainly focuses on two parts: (1) Starting from the mechanical characteristics of the coal rock mass, statistical parameters are formed by means of statistical parameters and comprehensive processing parameters to analyze the micro-seismic energy change and trend. Numerous scholars try to identify microseism events according to microseism characteristics, and theories such as earthquake focus parameters, vibration wave velocity tomography and the like are formed. (2) And judging the microseismic data by a fitting prediction and identification prediction method, and establishing a microseismic data prediction and judgment model by using a multi-linear regression, correlation coefficient, machine learning and other correlation statistical methods. The research in the two aspects is mainly focused on the research on the mechanical characteristics of coal and rock and the micro-seismic single-channel signals, and the methods perform a lot of innovative researches on the micro-seismic state identification by utilizing micro-seismic monitoring data, but a coal mine system is used as a complex dynamic system, the micro-seismic signals contain a large amount of noise, the coal mine environment is complex and changeable, the precision of the conventional micro-seismic signal identification technology is low, and the safety of coal mine workers cannot be guaranteed.
Disclosure of Invention
The application provides a microseismic signal self-adaptive resolving method based on time sequence contribution diagram decomposition, which at least solves the technical problem of lower precision of the existing microseismic signal identification technology.
An embodiment of a first aspect of the present application provides a microseismic signal adaptive resolving method based on time sequence contribution graph decomposition, where the method includes:
when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved;
determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved;
determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved;
and when the monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved is larger than a monitoring threshold value of a predetermined monitoring area, judging that the microseismic state at the moment to be resolved of the monitoring area is a fluctuation state.
Preferably, the determining process of the monitoring threshold value of the monitoring area includes:
acquiring microseismic signal data of each channel at each moment in a historical period of a monitoring area;
determining a first mapping matrix and a second mapping matrix corresponding to the historical period of the monitoring area according to the microseismic signal data and the singular value decomposition method of each channel at each moment in the historical period;
determining a sub-state space of the monitoring area history period according to a first mapping matrix and a second mapping matrix corresponding to the monitoring area history period;
a sub-state space and Hotelling-T 2 Determining a monitoring threshold value of the monitoring area by a checking theorem;
the sub-state space of the monitoring area history period is composed of a first specification matrix and a second specification matrix.
Further, the first canonical matrix has the following calculation formula:
wherein C is a first canonical matrix, J is a fifth mapping matrix, and P is a first mapping matrix;
the second canonical matrix is calculated as follows:
wherein D is a second canonical matrix, L is a sixth mapping matrix,is the second mapping matrix.
Further, the determining process of the monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved includes:
acquiring microseismic signal data of each channel at the moment to be resolved of a monitoring area;
determining a third mapping matrix and a fourth mapping matrix corresponding to the microseismic signal data at the moment to be resolved according to the microseismic signal data of each channel at the moment to be resolved and a singular value decomposition method;
determining a sub-state space corresponding to the microseismic signal data at the moment to be resolved according to the third mapping matrix and the fourth mapping matrix;
determining a monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved according to the sub-state space corresponding to the microseismic signal data at the moment to be resolved;
the sub-state space corresponding to the microseismic signal data at the moment to be resolved consists of a third standard matrix and a fourth standard matrix.
Further, the calculation formula of the monitoring statistical value corresponding to the microseismic signal data at the moment to be calculated is as follows:
in the method, in the process of the application,for the monitoring statistical value corresponding to the microseismic signal data at the time t to be calculated, the +.>For the third canonical matrix->Matrix formed by microseismic signal data from time t to time t+r to be calculated>A matrix formed for the first k columns of the fifth mapping matrix.
Further, the self-adaptive calculating by using the time sequence contribution graph algorithm to obtain the total contribution value of the fluctuation state corresponding to each channel at the moment to be calculated includes:
determining that each channel in the monitoring area is added from the time to be resolved to the time to be resolved according to the microseismic signal data of each channel at the time to be resolved of the monitoring area and the third mapping matrix respectivelyA fluctuation state contribution value at each time instant, wherein +.>The time length is preset;
and determining the total contribution value of the fluctuation state corresponding to each channel at the moment to be resolved according to the fluctuation state contribution value.
Further, the calculation formula of the total contribution value of the fluctuation state corresponding to each channel at the moment to be calculated is as follows:
in the method, in the process of the application,for the total contribution value of the fluctuation states corresponding to the ith channel at the time t to be solved,/>And (3) the total contribution value of the fluctuation state corresponding to the i channel at the moment j to be solved, wherein r is the total number of moments influencing the solution of the moment t to be solved.
Further, the calculation formula of the fluctuation state contribution rate corresponding to each channel at the moment to be calculated is as follows:
in the method, in the process of the application,for the fluctuation state contribution rate corresponding to the ith channel at the time t to be solved, +.>The monitoring statistical value corresponding to the microseismic signal data at the time t to be calculated is obtained.
Further, the determining the microseismic root signal channel of the monitoring area at the time to be resolved according to the fluctuation state contribution rate corresponding to each channel at the time to be resolved includes:
arranging the fluctuation state contribution rates corresponding to the channels at the moment to be solved according to the sequence from large to small to form a contribution rate sequence;
and taking a channel corresponding to the maximum value in the contribution rate sequence as a microseismic root signal channel at the moment to be calculated in the monitoring area.
Further, the method further comprises:
and visually displaying the fluctuation state contribution rate corresponding to each channel at the moment to be solved.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
the application provides a microseismic signal self-adaptive resolving method based on time sequence contribution diagram decomposition, which comprises the following steps: when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved; determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved; determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved; and when the monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved is larger than a monitoring threshold value of a predetermined monitoring area, judging that the microseismic state at the moment to be resolved of the monitoring area is a fluctuation state. According to the technical scheme, the fluctuation degree of each channel can be monitored, monitoring information is enriched, the real-time identification accuracy of the microseismic signals is improved, further the fluctuation root signal channel can be more accurately excavated, reference is provided for downstream tasks such as subsequent microseismic positioning, and the safety of coal mine workers is guaranteed.
Additional aspects and advantages of the application 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 application.
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The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flow chart of a method for adaptive resolving of microseismic signals based on time series contribution graph decomposition according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a method for adaptively resolving microseismic signals based on time-series contribution graph resolution according to an embodiment of the present application;
fig. 3 is a schematic diagram of adaptive adjustment of a timing contribution graph according to an embodiment of the application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The application provides a microseismic signal self-adaptive resolving method based on time sequence contribution diagram decomposition, which comprises the following steps: when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved; determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved; determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved; and when the monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved is larger than a monitoring threshold value of a predetermined monitoring area, judging that the microseismic state at the moment to be resolved of the monitoring area is a fluctuation state. According to the technical scheme, the fluctuation degree of each channel can be monitored, monitoring information is enriched, the real-time identification accuracy of the microseismic signals is improved, further the fluctuation root signal channel can be more accurately excavated, reference is provided for downstream tasks such as subsequent microseismic positioning, and the safety of coal mine workers is guaranteed.
The following describes a microseismic signal adaptive resolving method based on time sequence contribution diagram resolution according to an embodiment of the present application with reference to the accompanying drawings.
Example 1
Fig. 1 is a flowchart of a microseismic signal adaptive resolving method based on time sequence contribution graph decomposition according to an embodiment of the present application, and as shown in fig. 1, the method includes:
step 1: when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved;
in the embodiment of the disclosure, when the monitoring statistic value corresponding to the microseismic signal data at the time to be resolved is greater than a predetermined monitoring threshold value of the monitoring area, namely, a control limit, the microseismic state at the time to be resolved of the monitoring area is determined to be a fluctuation state.
In an embodiment of the present disclosure, the determining the monitoring threshold of the monitoring area includes:
acquiring microseismic signal data of each channel at each moment in a historical period of a monitoring area;
determining a first mapping matrix and a second mapping matrix corresponding to the historical period of the monitoring area according to the microseismic signal data and the singular value decomposition method of each channel at each moment in the historical period;
determining a sub-state space of the monitoring area history period according to a first mapping matrix and a second mapping matrix corresponding to the monitoring area history period;
a sub-state space and Hotelling-T 2 Determining a monitoring threshold value of the monitoring area by a checking theorem;
the sub-state space of the monitoring area history period is composed of a first specification matrix and a second specification matrix.
For example, the sub-state space of the historical period of the monitoring area can be solved by using a canonical variate analysis method, which specifically comprises:
firstly, acquiring microseismic signal data of each channel at each moment in a normal monitoring area history period, and supposing a given microseismic data time sequenceXComprises a common componentNAfter the normalization processing is carried out on the sample data at each moment and m signal channels, a Hankel matrix, namely a first mapping matrix, is constructedPAnd a second mapping matrixFAt a specific momentVectors containing past information arePVector in matrix->，/>The vector containing future information is a vector in the F matrix，/>Wherein->For a predetermined time length, i.e. past and future observation length,/->For microseisms of each channel at e-time in a historical periodSignal data.
The calculation formula for obtaining the first mapping matrix and the second mapping matrix based on the canonical variable analysis theorem is as follows:
based on the first mapping matrix P and the second mapping matrix F, calculating by using a singular value decomposition method:wherein->，/>Whereby a first canonical matrix C can be obtained,and a second canonical matrix D,>u is a first preset matrix, V is a second preset matrix, J is a fifth mapping matrix, L is a sixth mapping matrix,>is the second mapping matrix.
Then according to Hotelling-T 2 Determining the monitoring threshold value of the monitoring area according to a formula by using a test theoremDetermining a monitoring threshold value of the monitoring area, wherein +.>For the monitoring threshold of the monitoring area, +.>For confidence of +.>Hypothesis testing values at that time.
In an embodiment of the present disclosure, the determining process of the monitoring statistic value corresponding to the microseismic signal data at the time to be resolved includes:
acquiring microseismic signal data of each channel at the moment to be resolved of a monitoring area;
determining a third mapping matrix and a fourth mapping matrix corresponding to the microseismic signal data at the moment to be resolved according to the microseismic signal data of each channel at the moment to be resolved and a singular value decomposition method;
determining a sub-state space corresponding to the microseismic signal data at the moment to be resolved according to the third mapping matrix and the fourth mapping matrix;
determining a monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved according to the sub-state space corresponding to the microseismic signal data at the moment to be resolved;
the sub-state space corresponding to the microseismic signal data at the moment to be resolved consists of a third standard matrix and a fourth standard matrix.
For example, the calculation formula of the monitoring statistic value corresponding to the microseismic signal data at the moment to be calculated is as follows:
in the method, in the process of the application,for the monitoring statistical value corresponding to the microseismic signal data at the moment t to be calculated, namely, the state space measurement,/-degree>For the third canonical matrix->Matrix formed by microseismic signal data from time t to time t+r to be calculated>Front of fifth mapping matrixA matrix of k columns.
In an embodiment of the present disclosure, the performing adaptive calculation using a timing sequence contribution graph algorithm to obtain a total contribution value of a fluctuation state corresponding to each channel at a time to be calculated includes:
determining that each channel in the monitoring area is added from the time to be resolved to the time to be resolved according to the microseismic signal data of each channel at the time to be resolved of the monitoring area and the third mapping matrix respectivelyA fluctuation state contribution value at each time instant, wherein +.>The time length is preset;
and determining the total contribution value of the fluctuation state corresponding to each channel at the moment to be resolved according to the fluctuation state contribution value. Exemplary, first, when acquiring microseismic real-time dataYAfter that, can construct，/>It should be noted that, the microseismic signal data at the time t to be calculated may be called real-time microseismic signal data, and meanwhile, since the speed of the sampling point is very fast, one may exist in several milliseconds, which is equivalent to delaying several latest sampling points, but still is real-time under the scale of milliseconds, and the real-time data may be the data from the time t to the time t+r.
Then, useThe real-time contribution of each channel is calculated by self-adaptive adjustment at a plurality of moments. The real-time contribution of the ith channel at the t moment can be influenced by the contributions of the t+1 to the t+r moment, and the real-time contribution of the ith channel at the t moment is adaptively adjusted through algorithm calculation. Contribution value of the ith channel at time t>The formula of (2) is as follows:
in the method, in the process of the application,is->The>Elements, i.eYAt time jiPersonal channel data->Elements constituting the ith row and the kth column of the fifth mapping matrix.
The contribution of the ith channel at the t-th moment can be affected by the subsequent moment, and the adaptive adjustment flow is shown in fig. 2, so that the contribution rate can be adaptively adjusted by using the subsequent moment, for example, the contribution at the t+1 moment is shown in the formulaWherein->Elements constituting the kth column of the 2*i th row of the fifth mapping matrix; and so on to time t+r;
then the total contribution of the ith channel after self-adaptive adjustment at the time tThe following formula is shown:
in the method, in the process of the application,for the ith channel at the time t to be resolvedCorresponding total contribution value of fluctuation states, +.>And (3) for the total contribution value of the fluctuation state corresponding to the i channel at the moment j to be solved, wherein r is the total number of moments influencing the solution of the moment t to be solved, and r is equal to k.
Step 2: and determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved.
In the embodiment of the present disclosure, the calculation formula of the fluctuation state contribution rate corresponding to each channel at the time to be resolved is as follows:
in the method, in the process of the application,for the fluctuation state contribution rate corresponding to the ith channel at the time t to be solved, +.>For the total contribution value of the fluctuation states corresponding to the ith channel at the time t to be solved,/>The monitoring statistical value corresponding to the microseismic signal data at the time t to be calculated is obtained.
Step 3: determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved;
in an embodiment of the present disclosure, the step 3 specifically includes:
arranging the fluctuation state contribution rates corresponding to the channels at the moment to be solved according to the sequence from large to small to form a contribution rate sequence;
and taking a channel corresponding to the maximum value in the contribution rate sequence as a microseismic root signal channel at the moment to be calculated in the monitoring area.
In an embodiment of the disclosure, the method further comprises:
and visually displaying the fluctuation state contribution rate corresponding to each channel at the moment to be solved.
It should be noted that, as shown in fig. 2, a timing contribution graph is introduced on the basis of this, and the influence contribution rate of the multichannel signal is visually displayed.
The specific implementation process of the method for determining the microseismic root-cause signal channel provided by the embodiment of the present disclosure may be as shown in fig. 3.
In summary, the self-adaptive resolving method for microseismic signals based on time sequence contribution graph decomposition provided by the embodiment can monitor the fluctuation degree of each channel, enrich monitoring information, improve the accuracy of microseismic signal real-time identification, further more accurately excavate the source signal channel of fluctuation, provide reference for downstream tasks such as subsequent microseismic positioning and the like, and ensure the safety of coal mine workers.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. The microseismic signal self-adaptive resolving method based on time sequence contribution diagram decomposition is characterized by comprising the following steps of:
when the microseismic state of the monitoring area at the moment to be resolved is a fluctuation state, performing self-adaptive resolving by using a time sequence contribution graph algorithm to obtain a fluctuation state total contribution value corresponding to each channel at the moment to be resolved;
determining the fluctuation state contribution rate corresponding to each channel at the moment to be resolved according to the total fluctuation state contribution value corresponding to each channel at the moment to be resolved;
determining a microseismic root signal channel of the monitoring area at the moment to be resolved according to the fluctuation state contribution rate corresponding to each channel at the moment to be resolved;
and when the monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved is larger than a monitoring threshold value of a predetermined monitoring area, judging that the microseismic state at the moment to be resolved of the monitoring area is a fluctuation state.
2. The method of claim 1, wherein the determining of the monitoring threshold for the monitoring area comprises:
acquiring microseismic signal data of each channel at each moment in a historical period of a monitoring area;
determining a first mapping matrix and a second mapping matrix corresponding to the historical period of the monitoring area according to the microseismic signal data and the singular value decomposition method of each channel at each moment in the historical period;
determining a sub-state space of the monitoring area history period according to a first mapping matrix and a second mapping matrix corresponding to the monitoring area history period;
a sub-state space and Hotelling-T 2 Determining a monitoring threshold value of the monitoring area by a checking theorem;
the sub-state space of the monitoring area history period is composed of a first specification matrix and a second specification matrix.
3. The method of claim 2, wherein the first canonical matrix is calculated as:
wherein C is a first canonical matrix, J is a fifth mapping matrix, and P is a first mapping matrix;
the second canonical matrix is calculated as follows:
wherein D is a second canonical matrix, L is a sixth mapping matrix,is the second mapping matrix.
4. The method of claim 2, wherein the determining the monitoring statistics corresponding to the microseismic signal data at the time to be resolved comprises:
acquiring microseismic signal data of each channel at the moment to be resolved of a monitoring area;
determining a third mapping matrix and a fourth mapping matrix corresponding to the microseismic signal data at the moment to be resolved according to the microseismic signal data of each channel at the moment to be resolved and a singular value decomposition method;
determining a sub-state space corresponding to the microseismic signal data at the moment to be resolved according to the third mapping matrix and the fourth mapping matrix;
determining a monitoring statistical value corresponding to the microseismic signal data at the moment to be resolved according to the sub-state space corresponding to the microseismic signal data at the moment to be resolved;
the sub-state space corresponding to the microseismic signal data at the moment to be resolved consists of a third standard matrix and a fourth standard matrix.
5. The method of claim 4, wherein the calculation formula of the monitoring statistic corresponding to the microseismic signal data at the moment to be resolved is as follows:
in the method, in the process of the application,for the monitoring statistical value corresponding to the microseismic signal data at the time t to be calculated, the +.>As a matrix of the third specification,matrix formed by microseismic signal data from time t to time t+r to be calculated>A matrix formed for the first k columns of the fifth mapping matrix.
6. The method of claim 4, wherein the adaptively calculating using the time sequence contribution graph algorithm to obtain the total contribution value of the fluctuation state corresponding to each channel at the time to be calculated comprises:
determining each channel in the monitoring area from the time to be resolved to the time to be resolved respectively according to the microseismic signal data of each channel at the time to be resolved of the monitoring area and the third mapping matrixEngraving and addingA fluctuation state contribution value at each time instant, wherein +.>The time length is preset;
and determining the total contribution value of the fluctuation state corresponding to each channel at the moment to be resolved according to the fluctuation state contribution value.
7. The method of claim 6, wherein the calculation formula of the total contribution value of the fluctuation state corresponding to each channel at the time to be resolved is as follows:
in the method, in the process of the application,for the total contribution value of the fluctuation states corresponding to the ith channel at the time t to be solved,/>And (3) the total contribution value of the fluctuation state corresponding to the i channel at the moment j to be solved, wherein r is the total number of moments influencing the solution of the moment t to be solved.
8. The method of claim 7, wherein the calculation formula of the fluctuation state contribution rate corresponding to each channel at the time to be resolved is as follows:
in the method, in the process of the application,for the corresponding fluctuation of the ith channel at the time t to be solvedStatus contribution rate->The monitoring statistical value corresponding to the microseismic signal data at the time t to be calculated is obtained.
9. The method of claim 8, wherein the determining the microseismic root-cause signal channel at the time to be resolved in the monitoring area according to the fluctuation-state contribution rates corresponding to the channels at the time to be resolved comprises:
arranging the fluctuation state contribution rates corresponding to the channels at the moment to be solved according to the sequence from large to small to form a contribution rate sequence;
and taking a channel corresponding to the maximum value in the contribution rate sequence as a microseismic root signal channel at the moment to be calculated in the monitoring area.
10. The method of claim 9, wherein the method further comprises:
and visually displaying the fluctuation state contribution rate corresponding to each channel at the moment to be solved.
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