CN116202432A - Intelligent regional landslide monitoring and management method - Google Patents
Intelligent regional landslide monitoring and management method Download PDFInfo
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- CN116202432A CN116202432A CN202310400486.7A CN202310400486A CN116202432A CN 116202432 A CN116202432 A CN 116202432A CN 202310400486 A CN202310400486 A CN 202310400486A CN 116202432 A CN116202432 A CN 116202432A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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Abstract
The invention belongs to the landslide monitoring field, relates to a data processing technology, and is used for solving the problem that the existing landslide monitoring management method cannot carry out distribution analysis on landslide risk areas, in particular to an intelligent regional landslide monitoring management method, which comprises the following steps: carrying out regional landslide monitoring analysis on the monitoring area, setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in the monitoring area, dividing the monitoring area into a plurality of sub-areas, calculating monitoring coefficients of the sub-areas, and judging whether landslide monitoring results of the sub-areas are qualified or not through the monitoring coefficients of the sub-areas; according to the invention, regional landslide monitoring analysis can be performed on a monitored area through the regional monitoring module, and horizontal displacement, gear wall displacement and anti-skid rod displacement can be monitored through the horizontal monitoring point, the gear monitoring point and the anti-skid monitoring point respectively, so that various displacement parameters are comprehensively analyzed and processed to obtain a monitoring coefficient.
Description
Technical Field
The invention belongs to the field of landslide monitoring, relates to a data processing technology, and particularly relates to an intelligent regional landslide monitoring management method.
Background
Landslide monitoring belongs to natural disasters and prevention and cure disciplines, and main monitoring contents include: various crack development processes at different parts of the slope, rock and soil mass relaxation and local collapse and settlement and uplift activities; various underground and ground deformation displacement phenomena; groundwater level, water quantity, water chemistry characteristics; tree inclination and various building deformations; external environmental changes such as rainfall and seismic activity: animal activity is abnormal. Through the work, related data and data are obtained, and basis is provided for landslide prediction and disaster prevention.
The existing landslide monitoring and managing method can only observe and analyze various landslide precursor phenomena through landslide parameters, and record various works in the landslide forming activity process; however, the function of carrying out distribution analysis on the landslide risk area is lacking, so that a treatment scheme cannot be formulated in a targeted manner aiming at the distribution characteristics of the risk area, and the landslide monitoring treatment efficiency is low.
Aiming at the technical problems, the application provides a solution.
Disclosure of Invention
The invention aims to provide an intelligent regional landslide monitoring and managing method which is used for solving the problem that the existing landslide monitoring and managing method cannot perform distribution analysis on landslide risk areas;
the technical problems to be solved by the invention are as follows: how to provide an intelligent regional landslide monitoring and managing method capable of carrying out distribution analysis on landslide risk areas.
The aim of the invention can be achieved by the following technical scheme:
an intelligent regional landslide monitoring and managing method comprises the following steps:
step one: regional landslide monitoring analysis is carried out on the monitored area: setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in a monitoring area, dividing the monitoring area into a plurality of sub-areas, calculating monitoring coefficients of the sub-areas, and judging whether landslide monitoring results of the sub-areas are qualified or not according to the monitoring coefficients of the sub-areas;
step two: monitoring and analyzing the overall landslide risk of the monitored area: marking the ratio of the number of dangerous areas to the number of subareas as a dangerous coefficient, establishing a monitoring set of the monitoring coefficients of all subareas, performing variance calculation on the monitoring set to obtain a fluctuation coefficient, and judging whether the overall landslide risk of the monitoring area meets the requirement or not according to the numerical values of the dangerous coefficient and the fluctuation coefficient;
step three: and acquiring the central point positions of the monitoring area and the central point positions of all the dangerous areas, marking the central point positions as the monitoring points and the dangerous points respectively, carrying out distribution simulation analysis on the dangerous points, and obtaining dangerous characteristics of the monitoring area.
As a preferred embodiment of the present invention, in the step one, the process of acquiring the monitoring coefficient of the sub-area includes: and carrying out horizontal displacement monitoring on landslide at the horizontal monitoring points to obtain water shift values, carrying out displacement monitoring on gear walls at the gear monitoring points to obtain wall shift values, carrying out displacement monitoring on anti-slip monitoring points to obtain rod shift values, summing and averaging water shift values of all the horizontal monitoring points in the subarea to obtain average value, summing and averaging wall shift values of all the gear monitoring points in the subarea to obtain wall shift data, summing and averaging rod shift values of all the gear monitoring points in the subarea to obtain rod shift data, and carrying out numerical calculation on the water shift data, the wall shift data and the rod shift data to obtain monitoring coefficients of the subarea.
As a preferred embodiment of the present invention, in the step one, a specific process for determining whether the landslide monitoring result of the sub-area meets the requirement includes: the monitoring threshold value is obtained through the storage module, and the monitoring coefficient is compared with the monitoring threshold value: if the monitoring coefficient is smaller than the monitoring threshold value, judging that the landslide monitoring result of the subarea is qualified, and marking the corresponding subarea as a safety area; if the monitoring coefficient is greater than or equal to the monitoring threshold value, judging that the landslide monitoring result of the subarea is unqualified, marking the corresponding subarea as a dangerous area, sending the position information of the dangerous area to a monitoring management platform, and sending the received position information of the dangerous area to a feature analysis module and a mobile phone terminal of a manager by the monitoring management platform.
As a preferred embodiment of the present invention, in the second step, the specific process of determining whether the overall landslide risk of the monitored area meets the requirement includes: the dangerous threshold and the fluctuation threshold are obtained through the storage module, and the dangerous coefficient and the fluctuation coefficient are compared with the dangerous threshold and the fluctuation threshold respectively: if the risk coefficient is smaller than the risk threshold, judging that the overall landslide risk of the monitoring area meets the requirement, and sending an overall qualified signal to a monitoring management platform by an overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is greater than or equal to the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is external damage, and sending an external damage signal to a monitoring management platform by the overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is smaller than the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is natural influence, and sending a natural influence signal to a monitoring management platform by the overall monitoring module; and the monitoring management platform receives the external damage signal or the natural influence signal, generates a characteristic analysis signal and sends the characteristic analysis signal to the characteristic analysis module.
As a preferred embodiment of the present invention, in the third step, the process of acquiring the angle data JD of the dangerous point includes: sequentially connecting the dangerous points with the monitoring points to obtain a plurality of dangerous line segments, marking the dangerous line segment with the minimum length value as a standard line segment, and marking the angle value of an included angle formed by the dangerous line segment and the standard line segment as angle data; the length data CD of the dangerous point is the length value of the dangerous line segment.
In a third step, as a preferred embodiment of the present invention, the specific process of performing the distribution simulation analysis on the dangerous points includes: establishing a rectangular coordinate system by taking angle data JD as an X axis and length data CD as a Y axis, dividing a first quadrant in the rectangular coordinate system into a plurality of analysis panels, acquiring the number of dangerous points in the analysis panels and marking the dangerous points as dangerous values, marking the analysis panels with the dangerous values not smaller than the dangerous threshold as dangerous panels by a storage module, sequentially connecting the central points of the dangerous panels in a left-to-right and bottom-to-top sequence to obtain a plurality of associated line segments, acquiring the associated threshold by the storage module, comparing the length values of the associated line segments with the associated threshold, and marking dangerous features of a monitoring area by a comparison result.
As a preferred embodiment of the present invention, in the step three, the specific process of comparing the length value of the associated line segment with the associated threshold value includes: if the length value of the associated line segment is smaller than the association threshold value, judging that the dangerous panels at the two ends of the associated line segment have association characteristics, and marking a dangerous area corresponding to a dangerous point in the dangerous panel with the association characteristics as an association area; if the length value of the associated line segment is greater than or equal to the associated threshold value, judging that the dangerous panels at the two ends of the associated line segment do not have associated features; if the number of the associated areas is zero, marking the dangerous features of the monitoring areas as scattered, and sending a scattered treatment signal to a monitoring management platform by a feature analysis module, wherein the monitoring management platform sends the scattered treatment signal to a mobile phone terminal of a manager after receiving the scattered treatment signal; if the number of the associated areas is not zero, the dangerous features of the monitoring areas are marked as concentrated, the feature analysis module sends concentrated treatment signals to the monitoring management platform, and the monitoring management platform sends the concentrated treatment signals to mobile phone terminals of management staff after receiving the concentrated treatment signals.
The intelligent regional landslide monitoring and managing system is used as a preferable implementation mode, and is applied to an intelligent regional landslide monitoring and managing system and comprises a monitoring and managing platform, wherein the monitoring and managing platform is in communication connection with a regional monitoring module, an integral monitoring module, a characteristic analysis module and a storage module;
the regional monitoring module is used for carrying out regional landslide monitoring analysis and sending the position information of the dangerous region to the monitoring management platform when the monitoring result of the sub-region is unqualified, and the monitoring management platform sends the received position information of the dangerous region to the characteristic analysis module;
the integral monitoring module is used for monitoring and analyzing the integral landslide risk of the monitoring area and sending a characteristic analysis signal to the characteristic analysis module through the monitoring management platform when the integral landslide risk of the monitoring area does not meet the requirement;
the feature analysis module is used for carrying out treatment feature analysis on the monitoring area after receiving the feature analysis signals, marking dangerous features of the monitoring area and sending the dangerous features of the monitoring area to a mobile phone terminal of a manager through the monitoring management platform.
The invention has the following beneficial effects:
1. the regional landslide monitoring analysis can be carried out on the monitored region through the regional monitoring module, the horizontal displacement, the gear wall displacement and the anti-slip rod displacement can be respectively monitored through the horizontal monitoring point, the gear monitoring point and the anti-slip monitoring point, so that various displacement parameters are comprehensively analyzed and processed to obtain monitoring coefficients, the landslide risk of the sub-region is intuitively fed back through the numerical value of the monitoring coefficients, and early warning protection is timely carried out on the dangerous region with the landslide risk;
2. the overall landslide risk of the monitoring area can be monitored and analyzed through the overall monitoring module, the overall landslide risk is fed back through the proportion of the dangerous area in the monitoring area and the distribution condition of the monitoring coefficients of the subareas, so that the feedback is carried out when the overall landslide risk does not meet the requirement, meanwhile, the risk factors of the landslide risk are marked, management staff can conveniently formulate a corresponding treatment scheme through the risk factors, and the landslide monitoring treatment efficiency is improved;
3. the characteristic analysis module can analyze the treatment characteristics of the monitoring area, and the dangerous characteristics of the monitoring area are marked through the geographical position extraction and the distribution simulation analysis of the dangerous area, so that a targeted treatment scheme is formulated by combining the dangerous characteristics and the risk factors, and the landslide monitoring treatment efficiency is further improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in FIG. 1, the intelligent regional landslide monitoring and management system comprises a monitoring and management platform, wherein the monitoring and management platform is in communication connection with a regional monitoring module, an overall monitoring module, a characteristic analysis module and a storage module.
The regional monitoring module is used for carrying out regional landslide monitoring analysis: setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in a monitoring area, carrying out horizontal displacement monitoring on landslide at the horizontal monitoring points to obtain a water displacement value, wherein the displacement monitoring can be carried out by a laser range finder, the laser range finder is an instrument for accurately measuring the distance from a target by utilizing a certain parameter of modulated laser, the pulse laser range finder emits a beam or a sequence of short pulse laser beams to the target during working, a photoelectric element receives the laser beams reflected by the target, and a timer measures the time from the emission to the reception of the laser beams and calculates the distance from the range finder to the target; the method comprises the steps of performing displacement monitoring on a gear wall at a gear monitoring point to obtain a wall displacement value, performing displacement monitoring on an anti-slip monitoring point to obtain a rod displacement value, dividing a monitoring area into a plurality of subareas, summing up water displacement values of all horizontal monitoring points in the subareas to obtain an average value, marking the average value as water displacement data SY, summing up the wall displacement values of all the gear monitoring points in the subareas to obtain wall displacement data QY, summing up the rod displacement values of all the gear monitoring points in the subareas to obtain the rod displacement data GY, obtaining a monitoring coefficient JC of the subareas through a formula JC=α1SY+α2QY+α3GY, wherein the monitoring coefficient is a numerical value reflecting the landslide risk degree in the subareas, and the larger the numerical value of the monitoring coefficient is, the higher the landslide risk degree in the subareas is represented; wherein, alpha 1, alpha 2 and alpha 3 are all proportional coefficients, and alpha 1 > alpha 2 > alpha 3 > 1; the monitoring threshold value JCmax is obtained through the storage module, and the monitoring coefficient JC is compared with the monitoring threshold value JCmax: if the monitoring coefficient JC is smaller than the monitoring threshold value JCmax, judging that the landslide monitoring result of the subarea is qualified, and marking the corresponding subarea as a safety area; if the monitoring coefficient JC is greater than or equal to the monitoring threshold value JCmax, judging that the landslide monitoring result of the subarea is unqualified, marking the corresponding subarea as a dangerous area, sending the position information of the dangerous area to a monitoring management platform, and sending the received position information of the dangerous area to a feature analysis module and a mobile phone terminal of a manager by the monitoring management platform; regional landslide monitoring analysis is carried out on the monitoring area, horizontal displacement, gear wall displacement and anti-slip rod displacement can be monitored through the horizontal monitoring point, the gear monitoring point and the anti-slip monitoring point respectively, so that comprehensive analysis processing is carried out on various displacement parameters to obtain monitoring coefficients, visual feedback is carried out on landslide risks of the sub-area through the numerical value of the monitoring coefficients, and early warning protection is timely carried out on dangerous areas with landslide risks.
The overall monitoring module is used for monitoring and analyzing the overall landslide risk of the monitored area: marking the ratio of the number of dangerous areas to the number of subareas as a dangerous coefficient, establishing a monitoring set of the monitoring coefficients of all subareas, calculating variance of the monitoring set to obtain a fluctuation coefficient, acquiring a dangerous threshold and a fluctuation threshold through a storage module, and comparing the dangerous coefficient and the fluctuation coefficient with the dangerous threshold and the fluctuation threshold respectively: if the risk coefficient is smaller than the risk threshold, judging that the overall landslide risk of the monitoring area meets the requirement, and sending an overall qualified signal to a monitoring management platform by an overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is greater than or equal to the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is external damage, and sending an external damage signal to a monitoring management platform by the overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is smaller than the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is natural influence, and sending a natural influence signal to a monitoring management platform by the overall monitoring module; the monitoring management platform receives the external force damage signal or the natural influence signal, generates a characteristic analysis signal and sends the characteristic analysis signal to the characteristic analysis module; the overall landslide risk of the monitoring area is monitored and analyzed, the overall landslide risk is fed back through the proportion of the dangerous area in the monitoring area and the distribution condition of the monitoring coefficients of the subareas, so that the overall landslide risk is fed back when the overall landslide risk does not meet the requirement, meanwhile, risk factors of the landslide risk are marked, management staff can conveniently formulate corresponding treatment schemes through the risk factors, and landslide monitoring treatment efficiency is improved.
The feature analysis module is used for carrying out treatment feature analysis on the monitoring area after receiving the feature analysis signals: the method comprises the steps of obtaining the central point positions of a monitoring area and the central point positions of all dangerous areas, marking the central point positions as monitoring points and dangerous points respectively, obtaining angle data JD and length data CD of the dangerous points, and obtaining the angle data JD of the dangerous points, wherein the obtaining process comprises the following steps: sequentially connecting the dangerous points with the monitoring points to obtain a plurality of dangerous line segments, marking the dangerous line segment with the minimum length value as a standard line segment, and marking the angle value of an included angle formed by the dangerous line segment and the standard line segment as angle data; the length data CD of the dangerous point is the length value of the dangerous line segment; and carrying out distribution simulation analysis on the dangerous points: establishing a rectangular coordinate system by taking angle data JD as an X axis and length data CD as a Y axis, dividing a first quadrant in the rectangular coordinate system into a plurality of analysis panels, acquiring the number of dangerous points in the analysis panels and marking the dangerous points as dangerous values, acquiring a dangerous threshold value through a storage module, marking the analysis panels with the dangerous values not smaller than the dangerous threshold value as dangerous panels, sequentially connecting the central points of the dangerous panels from left to right and from bottom to top to obtain a plurality of associated line segments, acquiring the associated threshold value through the storage module, and comparing the length values of the associated line segments with the associated threshold value: if the length value of the associated line segment is smaller than the association threshold value, judging that the dangerous panels at the two ends of the associated line segment have association characteristics, and marking a dangerous area corresponding to a dangerous point in the dangerous panel with the association characteristics as an association area; if the length value of the associated line segment is greater than or equal to the associated threshold value, judging that the dangerous panels at the two ends of the associated line segment do not have associated features; if the number of the associated areas is zero, marking the dangerous features of the monitoring areas as scattered, and sending a scattered treatment signal to a monitoring management platform by a feature analysis module, wherein the monitoring management platform sends the scattered treatment signal to a mobile phone terminal of a manager after receiving the scattered treatment signal; if the number of the associated areas is not zero, marking the dangerous features of the monitoring areas as concentrated, and sending a concentrated treatment signal to a monitoring management platform by a feature analysis module, wherein the monitoring management platform receives the concentrated treatment signal and then sends the concentrated treatment signal to a mobile phone terminal of a manager; analyzing the treatment characteristics of the monitoring area, extracting the geographical position of the dangerous area, and marking the dangerous characteristics of the monitoring area through distribution simulation analysis, so that a targeted treatment scheme is formulated by combining the dangerous characteristics and the risk factors, and the landslide monitoring treatment efficiency is further improved.
Example two
As shown in fig. 2, an intelligent regional landslide monitoring and managing method includes the following steps:
step one: regional landslide monitoring analysis is carried out on the monitored area: setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in a monitoring area, respectively monitoring horizontal displacement, gear wall displacement and anti-slip rod displacement through the horizontal monitoring points, the gear monitoring points and the anti-slip monitoring points, dividing the monitoring area into a plurality of sub-areas, calculating monitoring coefficients of the sub-areas, and visually feeding back landslide risks of the sub-areas through the numerical values of the monitoring coefficients;
step two: monitoring and analyzing the overall landslide risk of the monitored area: marking the ratio of the number of dangerous areas to the number of subareas as a dangerous coefficient, establishing a monitoring set of the monitoring coefficients of all subareas, calculating variance of the monitoring set to obtain a fluctuation coefficient, judging whether the overall landslide risk of the monitoring area meets the requirement or not according to the numerical values of the dangerous coefficient and the fluctuation coefficient, marking the risk factors of the landslide risk, and facilitating management personnel to formulate a corresponding treatment scheme through the risk factors;
step three: acquiring the central point positions of the monitoring area and the central point positions of all the dangerous areas, marking the central point positions as monitoring points and dangerous points respectively, carrying out distribution simulation analysis on the dangerous points, and obtaining dangerous characteristics of the monitoring area; and a targeted treatment scheme is formulated by combining the dangerous characteristics and the risk factors, so that the landslide monitoring and treatment efficiency is further improved.
An intelligent regional landslide monitoring management method comprises the steps of during operation, carrying out regional landslide monitoring analysis on a monitored area: setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in a monitoring area, comprehensively analyzing and processing each displacement parameter to obtain a monitoring coefficient, and intuitively feeding back landslide risks of the sub-area through the numerical value of the monitoring coefficient; monitoring and analyzing the overall landslide risk of the monitored area: marking the ratio of the number of dangerous areas to the number of subareas as a dangerous coefficient, establishing a monitoring set of the monitoring coefficients of all subareas, calculating variance of the monitoring set to obtain a fluctuation coefficient, judging whether the overall landslide risk of the monitoring area meets the requirement or not according to the numerical values of the dangerous coefficient and the fluctuation coefficient, marking the risk factors of the landslide risk, and facilitating management personnel to formulate a corresponding treatment scheme according to the risk factors, so that the landslide monitoring treatment efficiency is improved; acquiring the central point positions of the monitoring area and the central point positions of all the dangerous areas, marking the central point positions as monitoring points and dangerous points respectively, carrying out distribution simulation analysis on the dangerous points, and obtaining dangerous characteristics of the monitoring area; and a targeted treatment scheme is formulated by combining the dangerous characteristics and the risk factors, so that the landslide monitoring and treatment efficiency is further improved.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula jc=α1×sy+α2×qy+α3×gy; collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding monitoring coefficient for each group of sample data; substituting the set monitoring coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 5.38, 3.47 and 2.64 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding monitoring coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the monitoring coefficient is in direct proportion to the value of the water shift data.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean 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 invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (8)
1. An intelligent regional landslide monitoring and managing method is characterized by comprising the following steps:
step one: regional landslide monitoring analysis is carried out on the monitored area: setting a plurality of horizontal monitoring points, gear monitoring points and anti-slip monitoring points in a monitoring area, dividing the monitoring area into a plurality of sub-areas, calculating monitoring coefficients of the sub-areas, and judging whether landslide monitoring results of the sub-areas are qualified or not according to the monitoring coefficients of the sub-areas;
step two: monitoring and analyzing the overall landslide risk of the monitored area: marking the ratio of the number of dangerous areas to the number of subareas as a dangerous coefficient, establishing a monitoring set of the monitoring coefficients of all subareas, performing variance calculation on the monitoring set to obtain a fluctuation coefficient, and judging whether the overall landslide risk of the monitoring area meets the requirement or not according to the numerical values of the dangerous coefficient and the fluctuation coefficient;
step three: and acquiring the central point positions of the monitoring area and the central point positions of all the dangerous areas, marking the central point positions as the monitoring points and the dangerous points respectively, carrying out distribution simulation analysis on the dangerous points, and obtaining dangerous characteristics of the monitoring area.
2. The intelligent regional landslide monitoring and management method according to claim 1, wherein in the step one, the process of obtaining the monitoring coefficient of the sub-region includes: and carrying out horizontal displacement monitoring on landslide at the horizontal monitoring points to obtain water shift values, carrying out displacement monitoring on gear walls at the gear monitoring points to obtain wall shift values, carrying out displacement monitoring on anti-slip monitoring points to obtain rod shift values, summing and averaging water shift values of all the horizontal monitoring points in the subarea to obtain average value, summing and averaging wall shift values of all the gear monitoring points in the subarea to obtain wall shift data, summing and averaging rod shift values of all the gear monitoring points in the subarea to obtain rod shift data, and carrying out numerical calculation on the water shift data, the wall shift data and the rod shift data to obtain monitoring coefficients of the subarea.
3. The intelligent regional landslide monitoring and management method according to claim 2, wherein in the first step, the specific process of determining whether the landslide monitoring result of the sub-region meets the requirement comprises: the monitoring threshold value is obtained through the storage module, and the monitoring coefficient is compared with the monitoring threshold value: if the monitoring coefficient is smaller than the monitoring threshold value, judging that the landslide monitoring result of the subarea is qualified, and marking the corresponding subarea as a safety area; if the monitoring coefficient is greater than or equal to the monitoring threshold value, judging that the landslide monitoring result of the subarea is unqualified, marking the corresponding subarea as a dangerous area, sending the position information of the dangerous area to a monitoring management platform, and sending the received position information of the dangerous area to a feature analysis module and a mobile phone terminal of a manager by the monitoring management platform.
4. The intelligent regional landslide monitoring and managing method according to claim 1, wherein in the second step, the specific process of determining whether the overall landslide risk of the monitored region meets the requirement comprises: the dangerous threshold and the fluctuation threshold are obtained through the storage module, and the dangerous coefficient and the fluctuation coefficient are compared with the dangerous threshold and the fluctuation threshold respectively: if the risk coefficient is smaller than the risk threshold, judging that the overall landslide risk of the monitoring area meets the requirement, and sending an overall qualified signal to a monitoring management platform by an overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is greater than or equal to the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is external damage, and sending an external damage signal to a monitoring management platform by the overall monitoring module; if the risk coefficient is greater than or equal to the risk threshold value and the fluctuation coefficient is smaller than the fluctuation threshold value, judging that the overall landslide risk of the monitoring area does not meet the requirement and the risk factor is natural influence, and sending a natural influence signal to a monitoring management platform by the overall monitoring module; and the monitoring management platform receives the external damage signal or the natural influence signal, generates a characteristic analysis signal and sends the characteristic analysis signal to the characteristic analysis module.
5. The intelligent regional landslide monitoring and managing method according to claim 1, wherein in the third step, the process of acquiring the angle data JD of the dangerous point includes: sequentially connecting the dangerous points with the monitoring points to obtain a plurality of dangerous line segments, marking the dangerous line segment with the minimum length value as a standard line segment, and marking the angle value of an included angle formed by the dangerous line segment and the standard line segment as angle data; the length data CD of the dangerous point is the length value of the dangerous line segment.
6. The intelligent regional landslide monitoring and management method of claim 5, wherein in step three, the specific process of performing distribution simulation analysis on dangerous points comprises: establishing a rectangular coordinate system by taking angle data JD as an X axis and length data CD as a Y axis, dividing a first quadrant in the rectangular coordinate system into a plurality of analysis panels, acquiring the number of dangerous points in the analysis panels and marking the dangerous points as dangerous values, marking the analysis panels with the dangerous values not smaller than the dangerous threshold as dangerous panels by a storage module, sequentially connecting the central points of the dangerous panels in a left-to-right and bottom-to-top sequence to obtain a plurality of associated line segments, acquiring the associated threshold by the storage module, comparing the length values of the associated line segments with the associated threshold, and marking dangerous features of a monitoring area by a comparison result.
7. The intelligent regional landslide monitoring and management method of claim 6 wherein in step three, the specific process of comparing the length value of the associated line segment with the associated threshold value comprises: if the length value of the associated line segment is smaller than the association threshold value, judging that the dangerous panels at the two ends of the associated line segment have association characteristics, and marking a dangerous area corresponding to a dangerous point in the dangerous panel with the association characteristics as an association area; if the length value of the associated line segment is greater than or equal to the associated threshold value, judging that the dangerous panels at the two ends of the associated line segment do not have associated features; if the number of the associated areas is zero, marking the dangerous features of the monitoring areas as scattered, and sending a scattered treatment signal to a monitoring management platform by a feature analysis module, wherein the monitoring management platform sends the scattered treatment signal to a mobile phone terminal of a manager after receiving the scattered treatment signal; if the number of the associated areas is not zero, the dangerous features of the monitoring areas are marked as concentrated, the feature analysis module sends concentrated treatment signals to the monitoring management platform, and the monitoring management platform sends the concentrated treatment signals to mobile phone terminals of management staff after receiving the concentrated treatment signals.
8. The intelligent regional landslide monitoring and managing method according to claim 1, which is characterized by being applied to an intelligent regional landslide monitoring and managing system and comprising a monitoring and managing platform, wherein the monitoring and managing platform is in communication connection with a regional monitoring module, an integral monitoring module, a characteristic analysis module and a storage module;
the regional monitoring module is used for carrying out regional landslide monitoring analysis and sending the position information of the dangerous region to the monitoring management platform when the monitoring result of the sub-region is unqualified, and the monitoring management platform sends the received position information of the dangerous region to the characteristic analysis module;
the integral monitoring module is used for monitoring and analyzing the integral landslide risk of the monitoring area and sending a characteristic analysis signal to the characteristic analysis module through the monitoring management platform when the integral landslide risk of the monitoring area does not meet the requirement;
the feature analysis module is used for carrying out treatment feature analysis on the monitoring area after receiving the feature analysis signals, marking dangerous features of the monitoring area and sending the dangerous features of the monitoring area to a mobile phone terminal of a manager through the monitoring management platform.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116416761A (en) * | 2023-06-07 | 2023-07-11 | 西北大学 | Mountain landslide intelligent deformation supervisory system based on data analysis |
| CN116504031A (en) * | 2023-06-27 | 2023-07-28 | 西北大学 | Monitoring data processing method for landslide |
| CN117541234A (en) * | 2023-12-04 | 2024-02-09 | 南京新鸿运物业管理股份有限公司 | Engineering maintenance diagnosis system and method based on big data |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116416761A (en) * | 2023-06-07 | 2023-07-11 | 西北大学 | Mountain landslide intelligent deformation supervisory system based on data analysis |
| CN116416761B (en) * | 2023-06-07 | 2023-08-15 | 西北大学 | Mountain landslide intelligent deformation supervisory system based on data analysis |
| CN116504031A (en) * | 2023-06-27 | 2023-07-28 | 西北大学 | Monitoring data processing method for landslide |
| CN116504031B (en) * | 2023-06-27 | 2023-08-29 | 西北大学 | Monitoring data processing method for landslide |
| CN117541234A (en) * | 2023-12-04 | 2024-02-09 | 南京新鸿运物业管理股份有限公司 | Engineering maintenance diagnosis system and method based on big data |
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