CN116337944A - High-density electrical measurement system for landslide monitoring - Google Patents
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Abstract
The invention provides a high-density electrical measurement system for landslide monitoring, which comprises: the acquisition unit is arranged in a to-be-monitored area of a mountain slope and is used for acquiring apparent resistivity of each monitoring point in the to-be-monitored area; the measuring terminal is electrically connected with the acquisition unit; the communication unit is in wireless communication connection with the measurement terminal; the cloud server is in wireless communication connection with the communication unit; the cloud server comprises a data processing unit and is used for acquiring monitoring data of the area to be monitored after preprocessing the apparent resistivity. The system of the invention performs data transmission in a wireless communication mode and performs data acquisition and processing through the cloud server, thereby greatly reducing the input of manpower, effectively improving the working efficiency, and simultaneously, performing data acquisition and processing in an intelligent mode, and effectively improving the data processing efficiency.
Description
Technical Field
The invention relates to the technical field of landslide monitoring, in particular to a high-density electrical method measuring system for landslide monitoring.
Background
At present, the landslide is monitored by a high-density resistivity method, the landslide is monitored in a specific area through a set field detection system, and the existing method needs monitoring personnel to constantly collect data collected by a detection device, then the data are collected and analyzed, so that the manpower input is increased, and meanwhile, the working efficiency is greatly reduced.
Disclosure of Invention
In view of the above, the invention provides a high-density electrical measurement system for landslide monitoring, which aims to solve the problem of how to improve the working efficiency when landslide monitoring is performed.
In one aspect, the present invention provides a high density electrical measurement system for landslide monitoring, comprising:
the acquisition unit is arranged in a to-be-monitored area of a mountain slope and is used for acquiring apparent resistivity of each monitoring point in the to-be-monitored area;
the measuring terminal is electrically connected with the acquisition unit and is used for receiving the apparent resistivity acquired by the acquisition unit;
the communication unit is in wireless communication connection with the measurement terminal;
the cloud server is in wireless communication connection with the communication unit, and the measurement terminal transmits the received apparent resistivity to the cloud server through the communication unit; wherein,,
the cloud server includes:
the data processing unit is used for preprocessing the apparent resistivity to obtain monitoring data of the area to be monitored, obtaining apparent resistivity change rates of all the monitoring points based on the monitoring data, obtaining an apparent resistivity contour section chart based on the apparent resistivity change rates, and determining the sensitivity degree of soil at each monitoring point position to rainfall reaction according to the apparent resistivity contour section chart.
Further, the data processing unit includes:
and the monitoring data preprocessing module is used for preprocessing the apparent resistivity after acquiring the apparent resistivity to acquire gridding data and determining the monitoring data based on the gridding data.
Further, the monitoring data preprocessing module includes:
the distortion point processing module is used for obtaining first data after eliminating the distortion point data in the apparent resistivity;
and the gridding processing module is used for acquiring the gridding data after gridding the first data by adopting a triangle network interpolation method.
Further, the data processing unit further includes:
the apparent resistivity change rate determining module is used for calculating the apparent resistivity change rate rho of each monitoring point δ The apparent resistivity change rate ρ δ Calculated according to the following formula:
wherein ρ is δ For apparent resistivity rate of change ρ 0 For the apparent resistivity reference value ρ i Video for the ith measurementThe resistivity value, Δρ, is the difference between the i-th measured apparent resistivity value and the apparent resistivity reference value.
A time sequence graph establishing module for establishing a time sequence graph according to the apparent resistivity change rate rho of each monitoring point δ Establishing a time sequence curve chart;
and the processing module is used for determining the information of the change of the soil resistivity value along with the soil water content according to the time sequence curve slope of the time sequence curve graph.
Further, the processing module is further configured to calculate a timing curve slope k of the timing graph according to the following formula:
k＝tanα
where k is the slope of the timing curve, and α is the angle between the tangent to the midpoint of the timing curve and the x-axis.
Further, the processing module is further configured to, when determining information of a change of a soil resistivity value with a soil moisture content according to a time sequence curve slope of the time sequence graph, include:
when alpha is an obtuse angle, k is smaller than 0, the slope of the time sequence curve is negative, and the soil moisture content is increased and the apparent resistivity value is reduced due to rainfall;
when alpha is an acute angle, k is more than 0, the slope of the time sequence curve is positive, and the soil moisture content is reduced and the apparent resistivity value is increased due to drought.
Further, the data processing unit further includes:
the contour line section diagram establishing module is used for establishing a contour line section diagram of the apparent resistivity according to the change rate of the apparent resistivity, displaying the distribution of the apparent resistivity of the whole monitoring section based on the contour line section diagram of the apparent resistivity, and displaying the electrical characteristics of the low-resistance and high-resistance distribution; wherein,,
the apparent resistivity contour section map includes distribution characteristics of apparent resistivity change rates in horizontal and vertical directions, and the apparent resistivity contour section maps are arranged in chronological order.
Further, the contour profile creation module is further configured to, when creating the apparent resistivity change rate profile, include:
and selecting the absolute value of the difference value of the maximum and minimum apparent resistivity change rates of each monitoring point in the monitoring period as the maximum change amount of the absolute value, and drawing the map.
Further, the data processing unit further includes:
and the time sequence curve chart establishing module is used for establishing a time sequence curve chart of the apparent resistivity change rate according to the apparent resistivity change rate of each monitoring point so as to display different areas of the apparent resistivity change rate.
Further, when the time sequence curve chart is established, the time sequence curve chart establishment module extracts specific and regular monitoring point data in the vertical direction and the horizontal direction to draw the time sequence curve chart of the apparent resistivity change rate.
Compared with the prior art, the method has the beneficial effects that the apparent resistivity of each monitoring point in the area to be monitored is collected, the monitored data of the area to be monitored is obtained after the apparent resistivity is preprocessed, the apparent resistivity change rate of each monitoring point is obtained based on the monitored data, the apparent resistivity contour section view is obtained based on the apparent resistivity change rate, and the sensitivity of soil at each monitoring point position to rainfall reaction is determined according to the apparent resistivity contour section view. The system of the invention performs data transmission in a wireless communication mode and performs data acquisition and processing through the cloud server, thereby greatly reducing the input of manpower, effectively improving the working efficiency, and simultaneously, performing data acquisition and processing in an intelligent mode, and effectively improving the data processing efficiency.
Furthermore, the invention can effectively reflect the trend of the change of the apparent resistivity of the high and low resistance bodies along with the fluctuation of the water content of the soil, thereby comprehensively knowing the earth electricity characteristics of the change of the apparent resistivity along with time in the monitoring period.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a first functional block diagram of a high density electrical measurement system for landslide monitoring provided by an embodiment of the present invention;
FIG. 2 is a second functional block diagram of a high density electrical measurement system for landslide monitoring provided by an embodiment of the present invention;
FIG. 3 is a third functional block diagram of a high density electrical measurement system for landslide monitoring provided by an embodiment of the present invention;
FIG. 4 is a bitmap of raw data points provided by an embodiment of the present invention;
FIG. 5 is a chart of data points with distortion points removed according to an embodiment of the present invention;
FIG. 6 is a diagram of a grid data point bitmap after triangle differentiation according to an embodiment of the present invention;
FIG. 7 is a graph showing the slope of a timing chart according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of mapping data and contour cross-section according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1, the embodiment provides a high-density electrical measurement system for landslide monitoring, which comprises an acquisition unit, a measurement terminal, a communication unit and a cloud server, wherein the acquisition unit is arranged in a to-be-monitored area of a landslide, and is used for acquiring the apparent resistivity of each monitoring point in the to-be-monitored area; the measuring terminal is electrically connected with the acquisition unit and is used for receiving the apparent resistivity acquired by the acquisition unit; the communication unit is in wireless communication connection with the measurement terminal; and the cloud server is in wireless communication connection with the communication unit, and the measurement terminal transmits the received apparent resistivity to the cloud server through the communication unit.
As will be understood, apparent resistivity refers to the resistivity of a material or rock in a subsurface electrical survey. It refers to the ratio of the distance between the electrodes to the depth of the medium being measured. In this application, electrodes are used to be placed underground and current is passed through them, and then the resistivity is calculated by measuring the potential difference between the electrodes, and the apparent resistivity is converted into the apparent resistivity by taking into consideration the ratio of the distance between the electrodes and the depth of the medium to be measured. Due to the influence of factors such as underground medium complexity and electrode distance, the apparent resistivity reflects the electrical characteristics of soil more accurately, and an important basis is provided for landslide detection.
Specifically, as shown in fig. 2, the cloud server includes a data processing unit, where the data processing unit is configured to pre-process the apparent resistivity to obtain monitoring data of the area to be monitored, obtain an apparent resistivity change rate of each monitoring point based on the monitoring data, obtain an apparent resistivity contour section map based on the apparent resistivity change rate, and determine a sensitivity degree of soil at each monitoring point position to rainfall reaction according to the apparent resistivity contour section map.
The high-density remote monitoring system in the embodiment improves a field observation system on the basis of a high-density resistivity method. Firstly, burying cables and electrodes laid on the original ground below soil, and ensuring that each measurement belongs to the same point. The electrode is connected with a special clamping seat arranged on a cable wire through a cable lead and a fixing clamp, one end of the cable wire is connected with a wiring port of a multi-channel electrode converter, a signal output end of the multi-channel electrode converter is connected with a signal input end of the measurement and control host, an RS232 serial communication interface of the measurement and control host is connected with the wireless transmission device, and the other end of the wireless transmission device is connected with a remote computer and used for transmitting measured data to the remote computer.
In the embodiment, a high-density electrical system is used for realizing remote wireless data transmission through the Internet, a PC end is used for remote control, an electrical measurement support color block diagram is imaged in real time, and measurement completion automatically generates a contour map, measuring point information, measurement progress and running pole diagram all-round display measurement information. The measurement data is automatically stored, the generated file can be directly used for inversion of RES2DINV into a graph, and a power supply at the instrument end is remotely managed without on-site power supply on or off of personnel.
The embodiment can be implemented by collecting landslide monitoring data according to the frequency of 1-3 times/day. A long period of monitoring is performed.
According to the invention, the apparent resistivity of each monitoring point in the area to be monitored is acquired, the monitored data of the area to be monitored is acquired after the apparent resistivity is preprocessed, the apparent resistivity change rate of each monitoring point is acquired based on the monitored data, the apparent resistivity contour section diagram is acquired based on the apparent resistivity change rate, and the sensitivity of soil at each monitoring point position to rainfall reaction is determined according to the apparent resistivity contour section diagram. The system of the invention performs data transmission in a wireless communication mode and performs data acquisition and processing through the cloud server, thereby greatly reducing the input of manpower, effectively improving the working efficiency, and simultaneously, performing data acquisition and processing in an intelligent mode, and effectively improving the data processing efficiency.
Referring to fig. 3, specifically, the data processing unit includes a monitoring data preprocessing module, where the monitoring data preprocessing module is configured to, after obtaining the apparent resistivity, preprocess the apparent resistivity to obtain gridding data, and determine the monitoring data based on the gridding data.
Specifically, the monitoring data preprocessing module comprises a distortion point processing module and a gridding processing module, wherein the distortion point processing module is used for acquiring first data after eliminating distortion point data in the apparent resistivity; the gridding processing module is used for acquiring the gridding data after gridding the first data by adopting a triangle network interpolation method.
Specifically, the triangle net interpolation method is to construct a triangle net by the coordinates and the attribute values of known points, the common method is a Delaunay triangulation algorithm, then calculate the attribute values of the unknown points according to the triangles on the triangle net, and the preferred method is to calculate the attribute values of the points according to the coordinates and the attribute values of three vertexes of the triangle by using a gravity center interpolation method or a gravity center coordinate interpolation method.
As shown in fig. 4-6, the preprocessing of the apparent resistivity includes distortion point processing and gridding processing.
In the actual measurement process, the electric field of the high-density electric method is interfered by the interaction between electrodes and other uncertain factors, so that some data are generally inconsistent with the actual data, and a sectional view of pseudo-abnormal resistance is caused; if the grounding resistance of the grounding electrode is too large, the size of the current source circuit is directly influenced, the measurement precision of potential difference is further influenced, the measurement period is influenced, and abnormal reading instability or error abnormality occurs to cause interference to abnormal interpretation. In the case where the measurement condition cannot be improved, only data can be recorded, and then erroneous data points or distortion points are deleted. The method adopts Swedish high-density processing software Res2dinv to process the apparent resistivity, and directly eliminates the distortion points.
The high-density electrical method monitoring equipment adopts a temperature nano device to continuously collect data, the point position of each layer of data is changed due to the reason of pole running, and meanwhile, the point position of each layer of data is missing due to the elimination of distorted points, so that the original data or the data with the elimination of distortion are subjected to gridding treatment by a triangle network interpolation method in the later period, so that the original data or the data with the elimination of distortion are changed into regular gridding data, and the information of the point positions at different depths in the vertical direction is conveniently obtained.
Specifically, the data processing unit further comprises a visual resistivity change rate determining module, a time sequence curve chart establishing module and a processing module.
Apparent resistivity change rateThe determining module is used for calculating the apparent resistivity change rate rho of each monitoring point δ The apparent resistivity change rate ρ δ Calculated according to the following formula:
wherein ρ is δ For apparent resistivity rate of change ρ 0 For the apparent resistivity reference value ρ i For the i-th measured apparent resistivity value, Δρ is the difference between the i-th measured apparent resistivity value and the apparent resistivity reference value.
It can be appreciated that the apparent resistivity reference value ρ 0 The method has two determining modes, namely, the change of the soil moisture content value is stable when the rainy season or the drought season is avoided as much as possible, the change of the apparent resistivity value is relatively small, and the fluctuation of the apparent resistivity change value is small, so that when the rainy season or the drought season is reached, the apparent resistivity change value presents positive and negative values due to the fluctuation of the soil moisture content and is distributed uniformly; and secondly, selecting time as close as possible to the monitoring start-stop time.
The time sequence curve chart establishment module is used for establishing a time sequence curve chart according to the apparent resistivity change rate rho of each monitoring point δ And (6) establishing a time sequence curve chart.
The processing module is used for determining the information of the change of the soil resistivity value along with the soil water content according to the time sequence curve slope of the time sequence curve graph.
In particular, as shown in connection with fig. 7, the processing module is further configured to calculate a timing curve slope k of the timing graph according to the following equation:
k＝tanα
where k is the slope of the timing curve, and α is the angle between the tangent to the midpoint of the timing curve and the x-axis.
Specifically, the processing module is further configured to, when determining information of a soil resistivity value changing with a soil moisture content according to a time sequence curve slope of the time sequence graph, include:
when alpha is an obtuse angle, k is smaller than 0, the slope of the time sequence curve is negative, and the soil moisture content is increased and the apparent resistivity value is reduced due to rainfall;
when alpha is an acute angle, k is more than 0, the slope of the time sequence curve is positive, and the soil moisture content is reduced and the apparent resistivity value is increased due to drought.
The larger the included angle between the tangent line at the midpoint of the time sequence graph and the x-axis is, the larger the slope is, otherwise, the smaller the included angle is, the smaller the slope is. When the angle is acute, k is more than 0, and the slope is positive; the angle is obtuse, k is less than 0, and the slope is negative.
The slope of the curve in the time sequence graph with k smaller than 0 is negative, which indicates that the rainfall exists to increase the water content of the soil and the apparent resistivity value is reduced; and the slope of the curve in k & gt 0 is positive, which indicates that drought exists to reduce the water content of soil and increase the apparent resistivity. Neither the start of the positive or negative slope starts from a zero value, but corresponds to the start of rainfall or drought. Therefore, the slope of the curve can more illustrate the consistency of the apparent resistivity change rate value and the change of the soil water content.
Specifically, the data processing unit further comprises a time sequence curve chart establishment module, wherein the time sequence curve chart establishment module is used for establishing a time sequence curve chart of the apparent resistivity change rate according to the apparent resistivity change rate of each monitoring point so as to display different areas of the apparent resistivity change rate.
Specifically, when the time sequence curve chart is established, the time sequence curve chart establishment module extracts specific and regular monitoring point data in the vertical direction and the horizontal direction to draw the time sequence curve chart of the apparent resistivity change rate.
The time sequence graph mainly focuses on the positive and negative values in the graph and the change of the slope of the curve, because the positive and negative values reflect the information presented by the soil resistivity value along with the change of the soil water content. The negative high probability in the time sequence graph indicates that rainfall leads to increase of soil moisture content and leads to decrease of soil apparent resistivity value, and the positive high probability indicates that drought leads to decrease of soil moisture content and leads to increase of soil apparent resistivity value.
Specifically, the data processing unit further comprises a contour line section diagram establishing module, wherein the contour line section diagram establishing module is used for establishing a contour line section diagram of apparent resistivity according to the change rate of the apparent resistivity, displaying the distribution of the apparent resistivity of the whole monitoring section based on the contour line section diagram of the apparent resistivity, and displaying the electrical characteristics of low-resistance and high-resistance distribution; wherein,,
the apparent resistivity contour section map includes distribution characteristics of apparent resistivity change rates in horizontal and vertical directions, and the apparent resistivity contour section maps are arranged in chronological order.
The contour line section diagram establishing module is further configured to, when establishing the apparent resistivity change rate section diagram, include: and selecting the absolute value of the difference value of the maximum and minimum apparent resistivity change rates of each monitoring point in the monitoring period as the maximum change amount of the absolute value, and drawing the map.
In the above embodiment, according to the apparent resistivity or the change rate value calculated by the apparent resistivity, in order to make the data more intuitively reflect the change rule of the earth resistivity affected by the water content, the change rule contained in the data is extracted and mined from different aspects to more intuitively reflect the monitoring result, and mainly two types of graphs, namely, the sectional view of the contour line of the apparent resistivity change rate and the time sequence graph of the apparent resistivity change rate, are drawn. The contour section chart of the apparent resistivity change rate can show the distribution of the apparent resistivity of the whole monitoring section, and the electrical characteristics of low resistance and high resistance distribution are displayed; the apparent resistivity change rate timing graph may display different regions of apparent resistivity change rate.
The apparent resistivity profile includes a distribution of apparent resistivity rates in the horizontal and vertical directions. The visual resistivity sectional diagrams are arranged according to the time sequence, and compared with the rainfall and soil moisture content curve diagrams, the trend of the change of the high-resistance visual resistivity and the low-resistance visual resistivity along with the fluctuation of the soil moisture content can be reflected from the sectional diagrams, so that the ground electric characteristics of the change of the visual resistivity along with the time in the monitoring period can be comprehensively known.
And (3) drawing a chart piece by taking the absolute value of the difference between the maximum rate of change and the minimum rate of change of each measuring point in the monitoring period as the maximum variation of the absolute value, so that the sensitivity of soil at different positions to rainfall reaction can be reflected.
Referring to fig. 8, in the construction of the apparent resistivity change rate timing graph, since the high density electrical monitoring data is distributed in an inverted triangle, the measuring points are different for each column and each row in the vertical and horizontal directions: in the horizontal direction, the number of measurement points is smaller as the depth increases, the number is 57 at most, and the number is 3 at least; in the vertical direction, the most measuring points on the axis of the measuring line gradually decrease towards two ends, namely 19 measuring points and 1 measuring point. The data subjected to gridding treatment is more regular, and the data of different depths of the same point location and the data of different point locations of the same depth can be conveniently extracted. Compared with the apparent resistivity section, the time sequence graph is formed by extracting specific and regular measuring point data in the vertical direction and the horizontal direction, so that more local details can be reflected, and more detail change characteristics can be conveniently mined from the apparent resistivity data. More details in the vertical and horizontal directions were used to analyze some of the characteristics of apparent resistivity changes.
In some embodiments of the present application, a high-density electrical measurement system for landslide monitoring may further include a warning unit, where the warning unit presets a visual resistivity safety threshold a, and the warning unit is electrically connected to the data processing unit and acquires data in the data processing unit. When one or more points in the detection data acquired by the data processing unit are lower than the apparent resistivity safety threshold A, the warning unit performs early warning and judges the apparent resistivity change rate, when the apparent resistivity change rate is continuously negative in a period of time, the warning unit alarms and continuously monitors the point, and the warning unit can analyze the apparent resistivity change phenomenon of the point according to the sensitivity of the point to rainfall reaction so as to discharge the problem of abnormal detection of the system.
It can be understood that adding the warning unit in this application can in time make the reaction when data are unusual, utilizes apparent resistivity and apparent resistivity change rate can effectively detect mountain landslide phenomenon, verifies the testing result according to the sensitivity degree of soil to rainfall reaction, has promoted the system and has detected the accuracy, has effectively promoted data reliability.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. A high density electrical measurement system for landslide monitoring, comprising:
the acquisition unit is arranged in a to-be-monitored area of a mountain slope and is used for acquiring apparent resistivity of each monitoring point in the to-be-monitored area;
the measuring terminal is electrically connected with the acquisition unit and is used for receiving the apparent resistivity acquired by the acquisition unit;
the communication unit is in wireless communication connection with the measurement terminal;
the cloud server is in wireless communication connection with the communication unit, and the measurement terminal transmits the received apparent resistivity to the cloud server through the communication unit; wherein,,
the cloud server includes:
the data processing unit is used for preprocessing the apparent resistivity to obtain monitoring data of the area to be monitored, obtaining apparent resistivity change rates of all the monitoring points based on the monitoring data, obtaining an apparent resistivity contour section chart based on the apparent resistivity change rates, and determining the sensitivity degree of soil at each monitoring point position to rainfall reaction according to the apparent resistivity contour section chart.
2. A high density electrical measurement system for landslide monitoring of claim 1 wherein the data processing unit comprises:
and the monitoring data preprocessing module is used for preprocessing the apparent resistivity after acquiring the apparent resistivity to acquire gridding data and determining the monitoring data based on the gridding data.
3. The high-density electrical measurement system for landslide monitoring of claim 2 wherein the monitoring data preprocessing module comprises:
the distortion point processing module is used for obtaining first data after eliminating the distortion point data in the apparent resistivity;
and the gridding processing module is used for acquiring the gridding data after gridding the first data by adopting a triangle network interpolation method.
4. The high density electrical measurement system for landslide monitoring of claim 2 wherein the data processing unit further comprises:
the apparent resistivity change rate determining module is used for calculating the apparent resistivity change rate rho of each monitoring point δ The apparent resistivity change rate ρ δ Calculated according to the following formula:
wherein ρ is δ For apparent resistivity rate of change ρ 0 For the apparent resistivity reference value ρ i For the i-th measured apparent resistivity value, Δρ is the difference between the i-th measured apparent resistivity value and the apparent resistivity reference value;
a time sequence graph establishing module for establishing a time sequence graph according to the apparent resistivity change rate rho of each monitoring point δ Establishing a time sequence curve chart;
and the processing module is used for determining the information of the change of the soil resistivity value along with the soil water content according to the time sequence curve slope of the time sequence curve graph.
5. The high-density electrical measurement system for landslide monitoring of claim 4 wherein the processing module is further configured to calculate a timing curve slope k of the timing graph based on the formula:
k＝tanα
where k is the slope of the timing curve, and α is the angle between the tangent to the midpoint of the timing curve and the x-axis.
6. The high-density electrical measurement system for landslide monitoring of claim 5 wherein,
the processing module is further configured to, when determining information of a soil resistivity value changing with a soil moisture content according to a time sequence curve slope of the time sequence graph, include:
when alpha is an obtuse angle, k is smaller than 0, the slope of the time sequence curve is negative, and the soil moisture content is increased and the apparent resistivity value is reduced due to rainfall;
when alpha is an acute angle, k is more than 0, the slope of the time sequence curve is positive, and the soil moisture content is reduced and the apparent resistivity value is increased due to drought.
7. The high-density electrical measurement system for landslide monitoring of claim 4 and wherein the data processing unit further comprises:
the contour line section diagram establishing module is used for establishing a contour line section diagram of the apparent resistivity according to the change rate of the apparent resistivity, displaying the distribution of the apparent resistivity of the whole monitoring section based on the contour line section diagram of the apparent resistivity, and displaying the electrical characteristics of the low-resistance and high-resistance distribution; wherein,,
the apparent resistivity contour section map includes distribution characteristics of apparent resistivity change rates in horizontal and vertical directions, and the apparent resistivity contour section maps are arranged in chronological order.
8. The high-density electrical measurement system for landslide monitoring of claim 7 wherein,
the contour line section diagram establishing module is further configured to, when establishing the apparent resistivity change rate section diagram, include:
and selecting the absolute value of the difference value of the maximum and minimum apparent resistivity change rates of each monitoring point in the monitoring period as the maximum change amount of the absolute value, and drawing the map.
9. The high-density electrical measurement system for landslide monitoring of claim 7 and wherein the data processing unit further comprises:
and the time sequence curve chart establishing module is used for establishing a time sequence curve chart of the apparent resistivity change rate according to the apparent resistivity change rate of each monitoring point so as to display different areas of the apparent resistivity change rate.
10. The high-density electrical measurement system for landslide monitoring of claim 9 wherein the timing graph creation module, when creating the apparent resistivity change rate timing graph, draws specific, regular monitoring point data in both the vertical and horizontal directions for the drawing of the apparent resistivity change rate timing graph.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116612609A (en) * | 2023-07-21 | 2023-08-18 | 湖北通达数科科技有限公司 | Disaster early warning method and system based on landslide hazard prediction |
| CN117558117A (en) * | 2024-01-12 | 2024-02-13 | 山东省煤田地质规划勘察研究院 | Intelligent landslide monitoring and early warning device and method based on pseudo-random signal excitation method |
| CN117688353A (en) * | 2024-02-04 | 2024-03-12 | 核工业(天津)工程勘察院有限公司 | Multistage verification processing method for underground engineering detection of high-density data |
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2023
- 2023-04-24 CN CN202310445603.1A patent/CN116337944A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116612609A (en) * | 2023-07-21 | 2023-08-18 | 湖北通达数科科技有限公司 | Disaster early warning method and system based on landslide hazard prediction |
| CN116612609B (en) * | 2023-07-21 | 2023-11-03 | 湖北通达数科科技有限公司 | Disaster early warning method and system based on landslide hazard prediction |
| CN117558117A (en) * | 2024-01-12 | 2024-02-13 | 山东省煤田地质规划勘察研究院 | Intelligent landslide monitoring and early warning device and method based on pseudo-random signal excitation method |
| CN117558117B (en) * | 2024-01-12 | 2024-05-31 | 山东省煤田地质规划勘察研究院 | Intelligent landslide monitoring and early warning device and method based on pseudo-random signal excitation method |
| CN117688353A (en) * | 2024-02-04 | 2024-03-12 | 核工业(天津)工程勘察院有限公司 | Multistage verification processing method for underground engineering detection of high-density data |
| CN117688353B (en) * | 2024-02-04 | 2024-04-30 | 核工业(天津)工程勘察院有限公司 | Multistage verification processing method for underground engineering detection of high-density data |
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