CN117146888A - Mountain torrent dynamic early warning method and system based on data analysis and processing - Google Patents
Mountain torrent dynamic early warning method and system based on data analysis and processing Download PDFInfo
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Abstract
The invention relates to the technical field of mountain torrent dynamic early warning, and discloses a mountain torrent dynamic early warning method and a mountain torrent dynamic early warning system based on data analysis processing, wherein the mountain torrent dynamic early warning method comprises the steps of monitoring environmental information of a target monitoring area in real time according to monitoring points and a meteorological platform, and calculating environmental safety coefficients of the target monitoring area according to the environmental information; acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, and calculating the terrain safety coefficient of the target monitoring area according to the terrain information; the geological safety coefficient of the target monitoring area is calculated according to the acceleration and the inclination angle generated by the external force of the pile body of the monitoring pile; and acquiring a mountain torrent generation coefficient by integrating the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient, carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient, and sending an early warning signal according to the early warning analysis result. According to the processing of multiple groups of data, the dynamic state of the mountain torrents is comprehensively analyzed, so that the accuracy of mountain torrents disaster early warning is improved.
Description
Technical Field
The invention relates to the technical field of mountain torrents dynamic early warning, in particular to a mountain torrents dynamic early warning method and system based on data analysis and processing.
Background
The mountain torrent disasters have strong burst property, strong regionalization, strong seasonality, high incidence rate and great hazard, and most of the mountain torrent disasters occur at the junction of mountain areas and cities and villages, mainly concentrate on rainy seasons and typhoons, are difficult to predict, forecast and prevent, and are rapid in disaster formation and avoid, so that the damage to residential areas in low-lying areas is particularly serious, and life and property losses such as casualties, house collapse, traffic interruption, farmland damage and the like are easily caused.
At present, a flood disaster early warning mode generally needs to read flood data manually or automatically acquire flood data through a flood disaster monitoring system, and needs to simulate, analyze and early warn the flood data manually; meanwhile, the area of the mountain torrent disaster prevention area is large, the mountain torrent disaster prevention area is affected by terrains and landforms, the local microclimate characteristics are obvious, the monitoring points of the monitoring area of the current mountain torrent disaster prevention area are not distributed enough, the coverage rate is not high, the monitoring facilities for the debris flow and landslide induced by the mountain torrent are also lacked, the monitoring on the dangerous points of the important mountain torrent disasters is not enough, the mountain torrent disaster early warning mode in the prior art is more dependent on manpower, the early warning precision and early warning efficiency cannot be ensured, and the requirements of accurate and efficient early warning and forecasting of the mountain torrents cannot be met.
Disclosure of Invention
The invention aims to provide a mountain torrent dynamic early warning method and system based on data analysis processing, which solve the following technical problems:
how to provide a mountain torrent dynamic early warning method capable of more accurately carrying out mountain torrent disaster early warning.
The aim of the invention can be achieved by the following technical scheme:
a mountain torrent dynamic early warning method based on data analysis processing comprises the following steps:
the environmental information of the target monitoring area is monitored in real time according to the monitoring points and the meteorological platform, environmental parameter data are obtained according to the environmental information, and the environmental safety coefficient of the target monitoring area is calculated according to the environmental parameter data;
acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, acquiring the terrain parameter data according to the terrain information, and calculating the terrain safety coefficient of the target monitoring area through the terrain parameter data;
the method comprises the steps of monitoring acceleration and inclination angle of a pile body of a monitoring pile under external force in real time according to the monitoring pile, and calculating a geological safety coefficient of a target monitoring area through the acceleration and inclination angle of the monitoring pile;
and acquiring a mountain torrent generation coefficient by integrating the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient, carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient, and sending an early warning signal according to the early warning analysis result.
Preferably, the calculation process of the environmental safety coefficient is as follows:
by the formulaCalculating the environmental safety coefficient Env at the time t t ；
Wherein alpha is x The weighting coefficient for the x-th environmental parameter,and n is the number of terms of the environmental parameter, which is the application coefficient of the xth environmental parameter at the time t.
Preferably, the process of acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, acquiring the terrain parameter data according to the terrain information, and calculating the terrain safety coefficient of the target monitoring area according to the terrain parameter data is as follows:
acquiring an image of a target monitoring area, and preprocessing the image of the target monitoring area;
identifying the preprocessed image of the target monitoring area, and respectively calculating the total number of pixels of the bare land image, the total number of pixels of the vegetation image, the total number of pixels of the lake image and the total number of pixels of the image;
calculating a terrain safety coefficient by a formula:
wherein Ter t For the topographic safety coefficient obtained at time t, L t For the total number of pixel points of the bare land image obtained at the time t, Z t For the total number of pixel points of the vegetation image obtained at the time t, H t For the total number of pixels of the lake image obtained at the moment T, T t The total number of the total pixel points of the image obtained at the moment t, t is the time of image acquisition, d 1 D for obtaining the position difference between the barycenter and the initial barycenter of the bare land image 2 D for obtaining the position difference between the center of gravity of the lake image and the initial center of gravity 3 D, to obtain a difference between the center of gravity of the vegetation image and the initial center of gravity Δt To obtain the standard deviation of the position of the center of gravity of the image and the initial center of gravity, beta 1 、β 2 、β 3 And beta 4 Is a specific proportionality coefficient.
Preferably, the process of monitoring acceleration and inclination angle generated by external force of the pile body of the monitoring pile in real time according to the monitoring pile and calculating the geological safety coefficient of the target monitoring area through the acceleration and inclination angle of the monitoring pile is as follows:
arranging monitoring piles in a target monitoring area according to a preset rule, wherein the monitoring piles are provided with control units, and the control units are used for acquiring acceleration a generated by external force on pile bodies of the monitoring piles in real time t And an inclination angle theta t ；
Calculating a geological safety coefficient by a formula:
wherein Geo t For the geological safety coefficient obtained at the moment t, delta theta is a preset angle variation quantity, a 0 For presetting the standard value of acceleration, gamma 1 、γ 2 And gamma 3 Is a specific proportionality coefficient.
Preferably, the calculation process of the mountain torrent generation coefficient is as follows:
by the formula Occ t ＝δ 1 Env t +δ 2 Ter t +δ 3 Geo t Calculating mountain torrent generation coefficient Occ t ；
Wherein delta 1 、δ 2 And delta 3 As the weight coefficient, delta 1 +δ 2 +δ 3 ＝1，δ 3 >δ 1 +δ 2 ，δ 3 >δ 2 >δ 1 。
Preferably, the mountain torrent early warning analysis process according to the mountain torrent generation coefficient comprises the following steps:
coefficient Occ of mountain torrent generation t Comparing the detected signal with a preset threshold value, and judging whether an early warning signal is sent or not:
coefficient of mountain torrent generation Occ t When the preset threshold value is not greater than the preset threshold value, no early warning signal is sent out;
otherwise, a mountain torrent early warning signal is sent.
Preferably, the process of performing the mountain torrent early warning analysis according to the mountain torrent generation coefficient further comprises:
statistics of the time-dependent curve of the coefficient of mountain torrents
Will beComparing with the corresponding standard interval:
if it isThe early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein [ E low ，E up ]And the standard interval corresponding to the mountain torrent generation coefficient is represented.
Preferably, the process of performing the mountain torrent early warning analysis according to the mountain torrent generation coefficient further comprises:
for a pair ofDeriving to obtain variation curve of mountain torrent generation coefficient variation with time>
Will beComparing with the corresponding variation threshold value:
if it isth, the early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein,curve representing the variation of the coefficient of mountain torrents, < ->th represents a threshold of the variation amount of the mountain torrent occurrence coefficient.
A mountain torrent dynamic early warning system based on data analysis processing comprises:
the environment monitoring module is used for monitoring the environment information of the target monitoring area in real time according to the monitoring points and the meteorological platform and acquiring environment parameter data according to the environment information;
the terrain monitoring module is used for acquiring terrain information of a target monitoring area in real time, and acquiring terrain parameter data according to the terrain information, wherein the terrain parameter data comprises a bare area coefficient, a vegetation area coefficient and a lake area coefficient;
the monitoring pile is used for monitoring acceleration and inclination angle generated by external force of the pile body of the monitoring pile in real time;
the data processing module is used for calculating the environmental safety coefficient of the target monitoring area according to the environmental parameter data, calculating the terrain safety coefficient of the target monitoring area according to the terrain parameter data, and calculating the geological safety coefficient of the target monitoring area according to the acceleration and the inclination angle of the monitoring pile;
the data analysis module is used for synthesizing the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient to obtain a mountain torrent generation coefficient, and carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient;
and the early warning module is used for sending out early warning signals according to the early warning analysis result.
The invention has the beneficial effects that:
according to the mountain torrent dynamic early warning method and system based on data analysis processing, through real-time monitoring of environmental, meteorological, topography and geological data, the environmental safety coefficient, the topography safety coefficient and the geological safety coefficient are obtained, the environmental safety coefficient, the topography safety coefficient and the geological safety coefficient are synthesized to obtain the mountain torrent generation coefficient, mountain torrent early warning analysis is carried out according to the mountain torrent generation coefficient, and early warning signals are sent out according to the result of the early warning analysis, so that the mountain torrent dynamic change state is comprehensively analyzed and processed, and the accuracy of mountain torrent disaster early warning is improved.
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The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a flow chart of the mountain torrent dynamic early warning method based on data analysis processing.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Referring to fig. 1, the invention provides a mountain torrent dynamic early warning method based on data analysis processing, which comprises the following steps:
the environmental information of the target monitoring area is monitored in real time according to the monitoring points and the meteorological platform, environmental parameter data are obtained according to the environmental information, and the environmental safety coefficient of the target monitoring area is calculated through the environmental parameter data;
acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, acquiring the terrain parameter data according to the terrain information, and calculating the terrain safety coefficient of the target monitoring area through the terrain parameter data;
the acceleration and the inclination angle of the pile body of the monitoring pile, which are generated by external force, are monitored in real time according to the monitoring pile, and the geological safety coefficient of the target monitoring area is calculated through the acceleration and the inclination angle of the monitoring pile;
and acquiring a mountain torrent generation coefficient by integrating the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient, carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient, and sending out an early warning signal according to the early warning analysis result.
According to the technical scheme, the mountain torrent dynamic early warning method based on data analysis processing is provided, specifically, environmental information of a target monitoring area is monitored in real time according to monitoring points and a meteorological platform, environmental parameter data are obtained according to the environmental information, and environmental safety coefficients of the target monitoring area are calculated through the environmental parameter data, wherein a large number of monitoring points are reasonably planned and laid according to the topography characteristics of the target monitoring area, the problem that the monitoring points of a monitoring area of a mountain torrent disaster prevention area are insufficiently laid and have low coverage rate is solved, the environmental parameter data monitored in real time by the monitoring points comprise but are not limited to wind speed, humidity, soil moisture content data and the like, the environmental parameter data monitored in real time by the meteorological platform are rainfall prediction data, the environmental safety coefficients of the target monitoring area are calculated by integrating a plurality of groups of environmental parameter data, the mountain torrent disaster early warning accuracy is improved, and the wind speed, humidity, soil moisture content data and the like are obtained through corresponding sensors;
acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, acquiring the terrain parameter data according to the terrain information, and calculating the terrain safety coefficient of the target monitoring area through the terrain parameter data, wherein the terrain information comprises a bare area coefficient, a vegetation area coefficient and a lake area coefficient;
the method comprises the steps of monitoring acceleration and inclination angle of a pile body of a monitoring pile under external force in real time according to the monitoring pile, and calculating geological safety coefficient of a target monitoring area through the acceleration and inclination angle of the monitoring pile, wherein the monitoring pile is used for monitoring debris flow, landslide and the like in real time, the lower end of the monitoring pile is fixed in a ground surface soil layer, and a large number of monitoring piles are arranged at mountain hillsides, reservoir dykes and the like which are prone to occurrence of geological disasters according to the topography characteristics of the target monitoring area, so that the problem that the current mountain flood disaster prevention area lacks debris flow and landslide monitoring facilities induced by mountain floods is solved; the monitoring pile is provided with a control unit, the control unit comprises a single chip microcomputer, an acceleration sensor and the like, the single chip microcomputer is connected with the acceleration sensor and used for collecting acceleration data of the acceleration sensor, the inclination angle change of the acceleration sensor is measured through a related algorithm, the geological safety coefficient of a target monitoring area is calculated according to the acceleration and the inclination angle, and when flood disasters are close to outbreaks, the geological disasters such as debris flow and landslide which occur are monitored according to the geological safety coefficient, so that the accuracy of mountain torrent disaster early warning is improved, and a better early warning effect is achieved;
in a comprehensive way, the mountain torrent disaster early warning accuracy is improved by comprehensively analyzing and processing the mountain torrent dynamic change state through the environmental, meteorological, topographic and geological data monitored in real time.
The calculation process of the environmental safety coefficient is as follows:
by the formulaCalculating the environmental safety coefficient Env at the time t t ；
Wherein alpha is x The weighting coefficient for the x-th environmental parameter,and n is the number of terms of the environmental parameter, which is the application coefficient of the xth environmental parameter at the time t.
Through the above technical solution, the present embodiment provides a method for calculating an environmental safety coefficient, specifically, through a formulaCalculating the environmental safety coefficient Env at the time t t Wherein alpha is x Weight coefficient for the xth environmental parameter, +.>For the application coefficient of the xth environmental parameter at the time t, n is the number of items of the environmental parameter, and the environmental parameter data comprise, but are not limited to, wind speed, humidity, soil moisture content data, rainfall prediction data and the like;
it should be noted that the weight coefficients corresponding to the different environmental parameter items are all different, and alpha x The specific values of the mountain floods are obtained and selected according to the different influence degrees of different environmental parameters.
The process of acquiring the topographic information of the target monitoring area in real time according to the topographic detection module, acquiring topographic parameter data according to the topographic information and calculating the topographic safety coefficient of the target monitoring area through the topographic parameter data comprises the following steps:
acquiring an image of a target monitoring area, and preprocessing the image of the target monitoring area;
identifying the preprocessed image of the target monitoring area, and respectively calculating the total number of pixels of the bare land image, the total number of pixels of the vegetation image, the total number of pixels of the lake image and the total number of pixels of the image;
calculating a terrain safety coefficient by a formula:
wherein Ter t For the topographic safety coefficient obtained at time t, L t For the total number of pixel points of the bare land image obtained at the time t, Z t For the total number of pixel points of the vegetation image obtained at the time t, H t For the total number of pixels of the lake image obtained at the moment T, T t The total number of the total pixel points of the image obtained at the moment t, t is the time of image acquisition, d 1 D for obtaining the position difference between the barycenter and the initial barycenter of the bare land image 2 D for obtaining the position difference between the center of gravity of the lake image and the initial center of gravity 3 D, to obtain a difference between the center of gravity of the vegetation image and the initial center of gravity Δt To obtain the standard deviation of the position of the center of gravity of the image and the initial center of gravity, beta 1 、β 2 、β 3 And beta 4 Is a specific proportionality coefficient.
Through the above technical scheme, the embodiment provides a terrain safety factor calculating method, specifically, an image of a target monitoring area is obtained, and preprocessing is performed on the image of the target monitoring area:
acquiring an image of a target monitoring area through an atmospheric layer external optical satellite, transmitting the acquired image to a cloud computing platform, importing a vector file of the target monitoring area when the cloud computing platform receives the image, cutting the image through ArcGIS software to acquire the image of the target monitoring area, preprocessing the image of the target monitoring area, identifying the image of the target monitoring area through a pattern identification technology, respectively identifying a bare land image, a vegetation image and a lake image, recording the bare land image, the vegetation image and the lake image in a normal initial state, and recording initial gravity points of the bare land image, the vegetation image and the lake image;
in the process of impending flood disasters, the gravity center points of the images shift along with the increase of factors such as rainwater and the like, and the shift amount also increases in the process of flood aggravation, the position difference between the gravity center of the images and the initial gravity center, the total number of pixel points of bare land, the total number of pixel points of vegetation, the total number of pixel points of lakes and the total number of pixel points of the images are respectively calculated, and further, the formula is adoptedCalculating a terrain safety factor, wherein Ter t For the topographic safety coefficient obtained at time t, L t For the total number of pixel points of the bare land image obtained at the time t, Z t For the total number of pixel points of the vegetation image obtained at the time t, H t Obtained for time tThe total number of pixels of the lake image is T, the total number of pixels of the image is obtained at the moment T, and T is the time of image acquisition; d, d 1 D for obtaining the position difference between the barycenter and the initial barycenter of the bare land image 2 D for obtaining the position difference between the center of gravity of the lake image and the initial center of gravity 3 D, to obtain a difference between the center of gravity of the vegetation image and the initial center of gravity Δt A positional standard deviation of the center of gravity from the initial center of gravity for the obtained image;
d is the same as Δt Obtained from a plurality of experimental fits, beta 1 、β 2 、β 3 And beta 4 And selecting the preset scaling factors according to different influence degrees of different parameters on the mountain torrents.
The process of monitoring acceleration and inclination angle of the pile body of the monitoring pile under external force according to the monitoring pile in real time and calculating the geological safety coefficient of the target monitoring area through the acceleration and inclination angle of the monitoring pile is as follows:
arranging monitoring piles in a target monitoring area according to a preset rule, wherein the monitoring piles are provided with control units, and the control units are used for acquiring acceleration a generated by external force applied to pile bodies of the monitoring piles in real time t And an inclination angle theta t ；
Calculating a geological safety coefficient by a formula:
wherein Geo t For the geological safety coefficient obtained at the moment t, delta theta is a preset angle variation quantity, a 0 For presetting the standard value of acceleration, gamma 1 、γ 2 And gamma 3 Is a specific proportionality coefficient.
Through the technical scheme, the embodiment provides a geological safety coefficient calculation method, and particularly, the monitoring pile is provided with a control unit, the control unit comprises a singlechip, an acceleration sensor and the like, the singlechip is connected with the acceleration sensor and is used for collecting acceleration data of the acceleration sensor, and inclination angle change of the acceleration sensor is performed through a related algorithmThe measurement is carried out, and in the process of increasing the offset of the gravity center point of each image, the geological damage is also shown to occur, and further, the method is carried out according to the formula Calculating the geological safety coefficient Geo t Wherein, geo t For the geological safety coefficient obtained at the moment t, delta theta is a preset angle variation quantity, a 0 For presetting the standard value of the acceleration, it should be noted that the algorithm of the inclination angle can be implemented by using the algorithm commonly used in the prior art, and the acceleration a is not limited herein t And an inclination angle theta t According to the state calculation of all monitoring piles in the layout, the geological safety state of the whole target monitoring area can be measured by taking average value and other algorithms commonly used in the prior art, and gamma 1 、γ 2 And gamma 3 For the preset proportionality coefficients, delta theta and a 0 Obtained from multiple sets of experimental fits.
The calculation process of the mountain torrent generation coefficient is as follows:
by the formula Occ t ＝δ 1 Env t +δ 2 Ter t +δ 3 Geo t Calculating mountain torrent generation coefficient Occ t ；
Wherein delta 1 、δ 2 And delta 3 As the weight coefficient, delta 1 +δ 2 +δ 3 ＝1，
δ 3 >δ 1 +δ 2 ，δ 3 >δ 2 >δ 1 。
Through the above technical solution, the present embodiment provides a method for calculating a mountain torrent generation coefficient, specifically, through formula Occ t ＝δ 1 Env t +δ 2 Ter t +δ 3 Geo t Calculating mountain torrent generation coefficient Occ t Wherein delta 1 、δ 2 And delta 3 As the weight coefficient, delta 1 +δ 2 +δ 3 =1 according toDifferent settings delta of environmental safety coefficient, terrain safety coefficient and influence degree of geological safety coefficient on mountain torrents 3 >δ 1 +δ 2 ，
δ 3 >δ 2 >δ 1 。
The mountain torrent early warning analysis process according to the mountain torrent generation coefficient comprises the following steps:
coefficient Occ of mountain torrent generation t Comparing the detected signal with a preset threshold value, and judging whether an early warning signal is sent or not:
coefficient of mountain torrent generation Occ t When the preset threshold value is not greater than the preset threshold value, no early warning signal is sent out;
otherwise, a mountain torrent early warning signal is sent.
Through the above technical solution, the present embodiment provides a mountain torrent early warning analysis method, specifically, the mountain torrent generation coefficient Occ t Comparing with a preset threshold value, and judging whether the mountain torrent generation coefficient exceeds the preset threshold value, wherein the preset threshold value is obtained according to a plurality of groups of experimental fitting, so that when the mountain torrent generation coefficient Occ t And when the threshold value is exceeded, indicating that the mountain torrent disaster is likely to happen, and further carrying out early warning.
The mountain torrent early warning analysis process according to the mountain torrent generation coefficient further comprises the following steps:
statistics of the time-dependent curve of the coefficient of mountain torrents
Will beComparing with the corresponding standard interval:
if it isThe early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein [ E low ，E up ]And the standard interval corresponding to the mountain torrent generation coefficient is represented.
Through the above technical scheme, the present embodiment provides a mountain torrent early warning analysis method, specifically, statistics of a mountain torrent occurrence coefficient change curve with timeWill->Comparing with the corresponding standard interval to determine whether the mountain torrent generation coefficient meets the requirement low ，E up ]Representing the standard interval corresponding to the mountain torrent generation coefficient, the state of the geographical environment of the basic target monitoring area is set, so that>When the mountain torrent generation coefficient exceeds the standard, the mountain torrent generation coefficient is indicated to be beyond the standard, and then early warning is carried out.
The mountain torrent early warning analysis process according to the mountain torrent generation coefficient further comprises the following steps:
for a pair ofDeriving to obtain variation curve of mountain torrent generation coefficient variation with time>
Will beComparing with the corresponding variation threshold value:
if it isth, the early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein,curve representing the variation of the coefficient of mountain torrents, < ->th represents a threshold of the variation amount of the mountain torrent occurrence coefficient.
By adopting the technical scheme, the embodiment changes the curve of the coefficient of mountain torrents with timePerforming derivation, namely ++the variation of the mountain torrent generation coefficient variation quantity with time after the derivation>The method and the device have the advantages that the method and the device can be compared with corresponding variable quantity threshold values, whether the mountain torrent occurrence coefficient has the problem of abnormal variable quantity or not can be judged, further, when the mountain torrent occurrence coefficient is in a standard interval but the variable quantity is abnormal, dynamic early warning analysis of mountain torrent disasters is achieved, further, the mountain torrent disasters are timely found at the initial stage of abnormal change of parameters such as environment, weather, topography and geology, further early warning can be timely carried out, and accuracy and efficiency of mountain torrent disasters early warning are improved.
A mountain torrent dynamic early warning system based on data analysis processing comprises:
the environment monitoring module is used for monitoring the environment information of the target monitoring area in real time according to the monitoring points and the meteorological platform and acquiring environment parameter data according to the environment information;
the terrain monitoring module is used for acquiring the terrain information of the target monitoring area in real time, and acquiring terrain parameter data according to the terrain information, wherein the terrain parameter data comprises a bare area coefficient, a vegetation area coefficient and a lake area coefficient;
the monitoring pile is used for monitoring acceleration and inclination angle generated by external force of the pile body of the monitoring pile in real time;
the data processing module is used for calculating the environmental safety coefficient of the target monitoring area according to the environmental parameter data, calculating the terrain safety coefficient of the target monitoring area according to the terrain parameter data, and calculating the geological safety coefficient of the target monitoring area according to the acceleration and the inclination angle of the monitoring pile;
the data analysis module is used for acquiring the mountain torrent generation coefficient by integrating the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient and carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient;
and the early warning module is used for sending out early warning signals according to the early warning analysis result.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (9)
1. A mountain torrent dynamic early warning method based on data analysis processing is characterized by comprising the following steps:
the environmental information of the target monitoring area is monitored in real time according to the monitoring points and the meteorological platform, environmental parameter data are obtained according to the environmental information, and the environmental safety coefficient of the target monitoring area is calculated according to the environmental parameter data;
acquiring the terrain information of the target monitoring area in real time according to the terrain detection module, acquiring the terrain parameter data according to the terrain information, and calculating the terrain safety coefficient of the target monitoring area through the terrain parameter data;
the method comprises the steps of monitoring acceleration and inclination angle of a pile body of a monitoring pile under external force in real time according to the monitoring pile, and calculating a geological safety coefficient of a target monitoring area through the acceleration and inclination angle of the monitoring pile;
and acquiring a mountain torrent generation coefficient by integrating the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient, carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient, and sending an early warning signal according to the early warning analysis result.
2. The mountain torrent dynamic early warning method based on data analysis processing according to claim 1, wherein the calculation process of the environmental safety coefficient is as follows:
by the formulaCalculating the environmental safety coefficient Env at the time t t ；
Wherein alpha is x The weighting coefficient for the x-th environmental parameter,and n is the number of terms of the environmental parameter, which is the application coefficient of the xth environmental parameter at the time t.
3. The mountain torrent dynamic early warning method based on data analysis processing according to claim 2, wherein the process of acquiring the topographic information of the target monitoring area in real time according to the topographic detection module, acquiring the topographic parameter data according to the topographic information, and calculating the topographic safety coefficient of the target monitoring area through the topographic parameter data is as follows:
acquiring an image of a target monitoring area, and preprocessing the image of the target monitoring area;
identifying the preprocessed image of the target monitoring area, and respectively calculating the total number of pixels of the bare land image, the total number of pixels of the vegetation image, the total number of pixels of the lake image and the total number of pixels of the image;
calculating a terrain safety coefficient by a formula:
wherein Ter t For the topographic safety coefficient obtained at time t, L t For the total number of pixel points of the bare land image obtained at the time t, Z t For the total number of pixel points of the vegetation image obtained at the time t, H t For the total number of pixels of the lake image obtained at the moment T, T t The total number of the total pixel points of the image obtained at the moment t, t is the time of image acquisition, d 1 D for obtaining the position difference between the barycenter and the initial barycenter of the bare land image 2 To obtain a lakeThe difference between the center of gravity of the poise image and the initial center of gravity, d 3 D, to obtain a difference between the center of gravity of the vegetation image and the initial center of gravity Δt To obtain the standard deviation of the position of the center of gravity of the image and the initial center of gravity, beta 1 、β 2 、β 3 And beta 4 Is a specific proportionality coefficient.
4. The mountain torrent dynamic early warning method based on data analysis processing of claim 3, wherein the process of monitoring acceleration and inclination angle generated by external force of pile body of the monitoring pile in real time according to the monitoring pile and calculating geological safety coefficient of a target monitoring area through the acceleration and inclination angle of the monitoring pile is as follows:
arranging monitoring piles in a target monitoring area according to a preset rule, wherein the monitoring piles are provided with control units, and the control units are used for acquiring acceleration a generated by external force on pile bodies of the monitoring piles in real time t And an inclination angle theta t ；
Calculating a geological safety coefficient by a formula:
wherein Geo t For the geological safety coefficient obtained at the moment t, delta theta is a preset angle variation quantity, a 0 For presetting the standard value of acceleration, gamma 1 、γ 2 And gamma 3 Is a specific proportionality coefficient.
5. The mountain torrent dynamic early warning method based on data analysis processing according to claim 4, wherein the calculating process of the mountain torrent occurrence coefficient is as follows:
by the formula Occ t ＝δ 1 Env t +δ 2 Ter t +δ 3 Geo t Calculating mountain torrent generation coefficient Occ t ；
Wherein delta 1 、δ 2 And delta 3 As the weight coefficient, delta 1 +δ 2 +δ 3 ＝1，δ 3 >δ 1 +δ 2 ，δ 3 >δ 2 >δ 1 。
6. The mountain torrent dynamic early warning method based on data analysis processing according to claim 5, wherein the mountain torrent early warning analysis is performed according to the mountain torrent occurrence coefficient:
coefficient Occ of mountain torrent generation t Comparing the detected signal with a preset threshold value, and judging whether an early warning signal is sent or not:
coefficient of mountain torrent generation Occ t When the preset threshold value is not greater than the preset threshold value, no early warning signal is sent out;
otherwise, a mountain torrent early warning signal is sent.
7. The method for dynamic early warning of mountain torrents based on data analysis and processing according to claim 6, wherein the process of carrying out mountain torrents early warning analysis according to the mountain torrents generation coefficient further comprises:
statistics of the time-dependent curve of the coefficient of mountain torrents
Will beComparing with the corresponding standard interval:
if it isThe early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein [ E low ，E up ]And the standard interval corresponding to the mountain torrent generation coefficient is represented.
8. The method for dynamic early warning of mountain torrents based on data analysis and processing according to claim 7, wherein the process of carrying out mountain torrents early warning analysis according to the mountain torrents generation coefficient further comprises:
for a pair ofDeriving to obtain variation curve of mountain torrent generation coefficient variation with time>
Will beComparing with the corresponding variation threshold value:
if it isThe early warning analysis meets the requirements;
otherwise, the early warning analysis does not meet the requirements;
wherein,curve representing the variation of the coefficient of mountain torrents, < ->And the variation threshold value of the mountain torrent occurrence coefficient is represented.
9. The mountain torrent dynamic early warning system based on data analysis processing is characterized by comprising:
the environment monitoring module is used for monitoring the environment information of the target monitoring area in real time according to the monitoring points and the meteorological platform and acquiring environment parameter data according to the environment information;
the terrain monitoring module is used for acquiring terrain information of a target monitoring area in real time, and acquiring terrain parameter data according to the terrain information, wherein the terrain parameter data comprises a bare area coefficient, a vegetation area coefficient and a lake area coefficient;
the monitoring pile is used for monitoring acceleration and inclination angle generated by external force of the pile body of the monitoring pile in real time;
the data processing module is used for calculating the environmental safety coefficient of the target monitoring area according to the environmental parameter data, calculating the terrain safety coefficient of the target monitoring area according to the terrain parameter data, and calculating the geological safety coefficient of the target monitoring area according to the acceleration and the inclination angle of the monitoring pile;
the data analysis module is used for synthesizing the environmental safety coefficient, the terrain safety coefficient and the geological safety coefficient to obtain a mountain torrent generation coefficient, and carrying out mountain torrent early warning analysis according to the mountain torrent generation coefficient;
and the early warning module is used for sending out early warning signals according to the early warning analysis result.
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