CN112750280A

CN112750280A - Combined type geological disaster professional monitoring and early warning method and device

Info

Publication number: CN112750280A
Application number: CN202011521699.8A
Authority: CN
Inventors: 傅锦荣; 李泽波; 沈旭明; 张永强; 李庄庄; 张清林
Original assignee: Wuhan Dayun Data Technology Co ltd
Current assignee: Wuhan Dayun Data Technology Co ltd
Priority date: 2020-12-21
Filing date: 2020-12-21
Publication date: 2021-05-04
Anticipated expiration: 2040-12-21
Also published as: CN112750280B

Abstract

The invention relates to the technical field of professional monitoring and early warning of geological disasters, in particular to a combined type professional monitoring and early warning method and device for geological disasters, wherein the method comprises the following steps: the server establishes an association relationship between the monitoring devices in advance; the server is connected with the monitoring equipment, and the method comprises the following steps: the server establishes an incidence relation between monitoring devices in advance; the server acquires monitoring data, wherein the monitoring data are acquired from at least two monitoring devices with incidence relation, and the monitoring data comprise state data and/or geological monitoring data of the monitoring devices; the geological monitoring data acquired by the server comprises compensation data and/or geological monitoring data acquired by monitoring equipment with an incidence relation; and judging whether the early warning condition is met or not according to the acquired state data and/or geological monitoring data. The method and the system can analyze the probability of occurrence of the geological disaster under the condition that the monitoring equipment is disconnected, and can timely perform early warning on the disaster.

Description

Combined type geological disaster professional monitoring and early warning method and device

[ technical field ] A method for producing a semiconductor device

The invention relates to the technical field of geological disaster early warning, in particular to a combined type geological disaster professional monitoring and early warning method and device.

[ background of the invention ]

In recent years, the frequency, range, scale and influence of natural disasters such as debris flow, landslides, mountain floods, typhoons, floods, drought and the like have sharply increased in the global range due to climate change. However, China is a country with mountainous areas and active geological structures, the areas endangered by natural disasters are wide, and a large number of people are forced to live in high-risk zones. Every year, tens of thousands of people are threatened by landslide and debris flow, so that great economic loss and casualties are caused, and 7400 thousands of people are threatened by debris flow disasters to different degrees only in China; since 2000, the number of people died due to disasters in China is 739 years, and the economic loss is 42.7 billion yuan every year.

At present, relevant management departments such as natural resource departments, emergency departments and the like in China establish corresponding geological disaster monitoring and early warning systems nationwide, and the geological disaster monitoring and early warning systems can release early warning information in flood seasons and seasons with multiple geological disasters to inform people of evacuation. Usually, geological disaster professional monitoring is based on the data that monitoring devices passback and carries out the early warning after carrying out analysis calculation on this basis, but often when geological disaster is about to take place, the site environment is extremely abominable, can influence the normal operating of the professional monitoring devices who have arranged like ground settlement, underground cavity, earth's surface deformation, sliding surface displacement, mud-rock flow impact etc. make its outage break net fall off the line, after this kind of condition takes place, the equipment that falls off the line just can't passback data again, just also can't carry out the early warning through traditional data calculation's mode.

Meanwhile, professional monitoring equipment is generally expensive, and some regions cannot be provided with the professional monitoring equipment, so that the regions can adopt common cheap monitoring equipment, further, in order to save cost, the arrangement of the monitoring equipment is sparser, and even some common monitoring equipment is removed, so that the loss of part of types of geological monitoring data in the monitoring data is caused, and the loss of part of types of geological monitoring data in the monitoring data in some regions is caused.

To accurately acquire the missing geological monitoring data of the areas, not only the missing geological monitoring data of the areas need to be scientifically calculated through the existing geological monitoring data of the surrounding areas of the areas, but also the surrounding areas used for calculation need to be reasonably selected, namely, reasonable geological disaster detection points are searched, so that the missing compensation data of the areas can be acquired more accurately, and then the server analyzes the probability of occurrence of the corresponding geological disaster through the obtained compensation data and/or the geological monitoring data acquired by the monitoring equipment with the incidence relation and judges whether the geological disaster early warning conditions are met.

In view of the above, overcoming the drawbacks of the prior art is an urgent problem in the art.

[ summary of the invention ]

The technical problem to be solved by the invention is as follows:

traditional geological disaster monitoring is based on the data that professional monitoring equipment reported and analyzes, and judge whether accord with the early warning condition of a certain kind of geological disaster, but in the actual scene, when the calamity is about to take place, the on-the-spot environment is extremely abominable, can cause professional monitoring equipment to appear situations such as outage broken string like ground subsidence, underground cavity, the earth's surface deformation, slip surface displacement and mud-rock flow impact etc. thereby make the professional monitoring equipment who has arranged can't report effectual early warning data to the server, and in time make the early warning and remind.

The problem to be further solved is that professional monitoring equipment is often expensive, and is unlikely to be used for monitoring any geological disaster, so that ordinary cheap monitoring equipment can be selected, or further in order to save cost, the arrangement of the monitoring equipment is sparse, or even a part of the ordinary monitoring equipment is removed, so that the probability of occurrence of the corresponding geological disaster needs to be analyzed through compensation data acquired from surrounding areas and/or geological monitoring data acquired by the monitoring equipment with incidence relation, and whether the geological disaster early warning condition is met is judged.

The invention adopts the following technical scheme:

in a first aspect, the invention provides a composite geological disaster professional monitoring and early warning method, wherein a server is connected with monitoring equipment, and the method comprises the following steps:

the server establishes an incidence relation between monitoring devices in advance;

the server acquires monitoring data, wherein the monitoring data are acquired from at least two monitoring devices with incidence relation, and the monitoring data comprise state data and/or geological monitoring data of the monitoring devices;

judging whether the early warning condition is met or not according to the acquired state data and/or geological monitoring data;

and if the early warning condition is met, generating corresponding early warning reminding information and sending the early warning reminding information.

Preferably, the server establishes an association relationship between monitoring devices in advance, and specifically includes:

the server establishes an incidence relation between corresponding monitoring devices when different geological disasters occur in advance according to the geographical position characteristics and historical disaster data;

the monitoring device with the association relationship comprises: the system comprises common monitoring equipment and/or professional monitoring equipment, wherein the professional monitoring equipment is used for acquiring professional geological monitoring data corresponding to geological disasters;

when a first type of geological disaster occurs, the monitoring equipment with the association relationship is called a first association group, wherein the probability that the state data of the monitoring equipment in the first association group when the first type of geological disaster occurs is a line-dropping state exceeds a preset threshold value;

when a second type of geological disaster occurs, the monitoring devices having the association relationship are called a second association group, wherein the probability that the state data of the monitoring devices in the second association group when the second type of geological disaster occurs is a default state exceeds a preset threshold.

Preferably, the judging whether the early warning condition is met according to the acquired state data and/or geological monitoring data specifically includes:

when the state data of each monitoring device in the first association group is in a disconnection state, if the first association group contains professional monitoring devices corresponding to the first type of geological disaster, the server analyzes that the professional geological monitoring data reported by the professional monitoring devices before disconnection does not exceed an early warning value;

and the server matches the geological monitoring data reported by the common monitoring equipment in the first association group before the disconnection with the geological monitoring data under the corresponding geological disaster scene.

Preferably, when each monitoring device in the second association group is included in the first association group, the server matches the geological monitoring data reported by the common monitoring device in the first association group before the disconnection with the geological monitoring data in the corresponding geological disaster scene, and specifically includes:

if the server analyzes that the matching degree of the geological monitoring data reported by the common monitoring equipment in the first association set before the disconnection and the geological monitoring data in the first type of geological disaster scene exceeds a preset matching value, the server accords with the first type of geological disaster early warning condition;

and if the server analyzes that the matching degree of the geological monitoring data reported by the common monitoring equipment in the first association group before the disconnection and the geological monitoring data in the scene in which the first type of geological disaster and the second type of geological disaster happen simultaneously exceeds a preset matching value, the server accords with the early warning condition of the simultaneous occurrence of the first type of geological disaster and the second type of geological disaster.

Preferably, the judging whether the early warning condition is met according to the acquired state data and/or geological monitoring data specifically further includes:

when the state data of each monitoring device in the first association group is in a disconnection state, if the first association group contains professional monitoring devices corresponding to the first type of geological disaster, and the server analyzes that the professional geological monitoring data reported by the professional monitoring devices before disconnection exceeds an early warning value, the first type of geological disaster early warning condition is met.

Preferably, when each monitoring device in the second association group is included in the first association group, the method determines whether the early warning condition is met according to the acquired state data and/or geological monitoring data, and specifically includes:

when all the monitoring devices in the first association group are common monitoring devices and the state data of all the common monitoring devices are in a disconnection state, the server matches geological monitoring data reported by the common monitoring devices in the first association group before disconnection with geological monitoring data under a corresponding geological disaster scene;

Preferably, the determining whether the server receives data reported by professional monitoring equipment corresponding to the first type of geological disaster includes, when the status data of the monitoring equipment in the first association group shows that at least one monitoring equipment is in an online status, the method specifically includes:

if the data reported by the professional monitoring equipment corresponding to the first type of geological disaster is received, and the professional geological monitoring data reported by the professional monitoring equipment is analyzed by the server and does not exceed the early warning value, the server matches the geological monitoring data acquired by the common monitoring equipment in the online state in the first association group with the geological monitoring data in the first type of geological disaster scene;

and if the server analyzes that the matching degree of the geological monitoring data reported by the common monitoring equipment in the on-line state in the first association group and the geological monitoring data in the first type of geological disaster scene exceeds a preset matching value, the first type of geological disaster early warning condition is met.

Preferably, the determining whether the server receives data reported by professional monitoring devices corresponding to the first type of geological disaster, and when the status data of the monitoring devices in the first association group shows that at least one monitoring device is in an online status, the method specifically includes:

and if the data reported by the professional monitoring equipment corresponding to the first type of geological disaster is received, and the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment exceeds the early warning value, the early warning condition of the first type of geological disaster is met.

Preferably, the method for acquiring the compensation data includes:

the server acquires geographical position information and geological monitoring data of the area A and the surrounding areas, and a database of the surrounding areas is established according to the geographical position information and the geological monitoring data of each area;

randomly picking a database combination from the database set of the peripheral regions, wherein the database combination comprises at least two databases of the peripheral regions, and for geological monitoring data of the same type in the database combination, endowing different weights to the geological monitoring data of the corresponding type of the peripheral regions in the database combination according to different geographic positions of the peripheral regions in the database combination, so as to generate a set of weight values and calculate the geological monitoring data of the corresponding type of the region A; combining and calculating n types of geological monitoring data of the area A by a randomly picked database, and generating n sets of weighted values;

and searching n sets of target database combinations with consistent weight values in different randomly picked database combinations, and calculating the missing compensation data of the area A according to geological monitoring data in the target database combinations.

Preferably, the calculating of the geological monitoring data missing from the area a from the geological monitoring data in the target database combination specifically includes:

calculating corresponding type geological monitoring data of the area A according to geological monitoring data in the target database combination to obtain existing geological monitoring data corresponding to the area A and compensation data of missing geological monitoring data, comparing the existing geological monitoring data of the area A with the corresponding compensation data respectively to obtain average similarity of the existing geological monitoring data of the area A and the corresponding compensation data, and if the average similarity reaches a similarity set threshold, considering that the compensation data of the missing geological monitoring data of the area A calculated through a prediction algorithm is reliable, thereby obtaining the missing geological monitoring data of the area A.

Preferably, the peripheral region includes a region centered on region a, bordering on region a, and/or located close to region a in geographical location.

Preferably, the geographical location information includes one or more of longitude, latitude, landform, terrain, altitude, climate, and geology.

Preferably, the monitoring data comprises different types of geological monitoring data, the geological monitoring data comprising one or more of temperature, humidity, air pressure, water level, rainfall, soil moisture content, osmotic water pressure, stress, displacement, slope deformation amount and slope inclination angle.

Preferably, the compensation data and the existing geological monitoring data are stored in different databases, and when the occurrence trend or the state of a geological disaster needs to be inferred, the data center calls the compensation data and the existing geological monitoring data; and when the missing geological monitoring data needs to be calculated, only the existing geological monitoring data is called.

Preferably, the average similarity specifically is:

the data center respectively compares the existing geological monitoring data of the area A with the corresponding compensation data, calculates different similarities according to different types of the existing geological monitoring data of the area A, and performs mean processing on the different similarities to obtain the average similarity between the existing geological monitoring data of the area A and the corresponding compensation data.

Preferably, the average similarity is compared with the similarity set threshold, if the average similarity is lower than the similarity set threshold, the compensation data is considered to have a certain uncertainty, and the prediction algorithm is adjusted until the average similarity reaches the similarity set threshold, so as to obtain the compensation data missing in the area a.

In a second aspect, the invention further provides a composite geological disaster professional monitoring and early warning device, which comprises at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the program of instructions being configured to perform the composite geological disaster major surveillance and early warning method of any of claims 1-9.

Compared with the prior art, the invention has the beneficial effects that:

according to the method, the incidence relation among the monitoring devices is established in advance through the server, wherein the monitoring devices with the incidence relation are in an offline state with a high probability when a certain geological disaster happens. When a certain kind of geological disasters occur, if the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment before the line is disconnected does not exceed the early warning value, the server matches the geological monitoring data reported by the common monitoring equipment with the incidence relation before the line is disconnected with the geological monitoring data under the corresponding geological disaster scene, so as to judge whether the certain kind of disasters occur or not.

On the other hand, the monitoring equipment with the incidence relation established by the server can be professional monitoring equipment and common monitoring equipment, or common monitoring equipment and common monitoring equipment are correlated, meanwhile, in order to further save cost, a part of the monitoring equipment with the incidence relation is removed, missing geological monitoring data is compensated according to geological monitoring data of the surrounding area, accurate compensation data is obtained, and whether geological disaster early warning conditions are met or not is judged through the compensation data and/or the geological monitoring data collected by the monitoring equipment with the incidence relation;

due to the fact that the number of professional monitoring equipment and/or common monitoring equipment is reduced, the cost of the geological disaster monitoring equipment is effectively reduced.

[ description of the drawings ]

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 is a flow chart of a composite geological disaster professional monitoring and early warning method provided by an embodiment of the invention;

fig. 2 is a schematic diagram of a location arrangement of monitoring set points having an association relationship according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a location arrangement of monitoring set points having an association relationship according to an embodiment of the present invention;

FIG. 4 is a flow chart of a composite geological disaster major monitoring and early warning method provided by the embodiment of the invention;

FIG. 5 is a flow chart of a composite geological disaster major monitoring and early warning method provided by the embodiment of the invention;

FIG. 6 is a flow chart of a composite geological disaster major monitoring and early warning method provided by the embodiment of the invention;

FIG. 7 is a flowchart of a method for acquiring geological disaster monitoring data according to an embodiment of the present invention;

fig. 8 is a schematic diagram of monitoring data of adjacent areas of a geological disaster monitoring data acquisition method according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of data compensation of a geological disaster monitoring data acquisition method according to an embodiment of the present invention;

fig. 10 is a data structure diagram of a geological disaster monitoring data acquisition method according to an embodiment of the present invention;

FIG. 11 is a flow chart of another method for acquiring geological disaster monitoring data according to an embodiment of the present invention;

FIG. 12 is a schematic diagram of an apparatus arrangement of another geological disaster monitoring data acquisition method according to an embodiment of the present invention;

fig. 13 is a schematic data simulation diagram of another geological disaster monitoring data acquisition method according to an embodiment of the present invention;

fig. 14 is a data structure diagram of a method for acquiring geological disaster monitoring data according to an embodiment of the present invention;

FIG. 15 is a flowchart of a method for acquiring geological disaster monitoring data according to an embodiment of the present invention;

fig. 16 is a schematic diagram of monitoring data of adjacent areas of a geological disaster monitoring data acquisition method according to an embodiment of the present invention;

fig. 17 is an architecture diagram of a composite geological disaster professional monitoring and early warning device provided in an embodiment of the present invention.

[ detailed description ] embodiments

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

In the description of the present invention, the terms "inner", "outer", "longitudinal", "lateral", "upper", "lower", "top", "bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are for convenience only to describe the present invention without requiring the present invention to be necessarily constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.

In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

The embodiment 1 of the invention provides a professional monitoring and early warning method for a combined geological disaster, wherein a server is connected with monitoring equipment, and as shown in figure 1, the method comprises the following steps:

step 10, the server establishes an association relationship between monitoring devices in advance, wherein the monitoring devices having the association relationship have a state data with a high probability of being in an offline state when corresponding to a geological disaster occurs, and the high probability can set a preset threshold value according to needs, such as: according to big data analysis, when the first type of disaster occurs, the probability that the state data of the monitoring equipment on certain monitoring point locations is the line-dropping state exceeds a preset threshold value by 99%, and then the monitoring equipment on the monitoring point locations can be considered to have an association relation; the big data is comprehensively analyzed mainly according to the geographical position characteristics and the conditions of disconnection of monitoring equipment and the like when historical disasters occur, the preset threshold value of 99% is only used for illustration, and specific numerical values can be adjusted according to actual needs and are not used for limiting the invention.

Step 20, the server acquires monitoring data, wherein the monitoring data includes data acquired from at least two monitoring devices having an association relationship, and the monitoring data includes state data and/or geological monitoring data of the monitoring devices; the monitoring equipment is divided into professional monitoring equipment and common monitoring equipment; when the monitoring equipment is professional monitoring equipment, the server acquires monitoring data of the professional monitoring equipment, namely state data and geological monitoring data, wherein the professional monitoring equipment can be a seismic monitor (professionally acquires data when an earthquake occurs), debris flow earth sound monitoring equipment (professionally acquires debris flow earth sound vibration signals), a landslide early warning extensometer (generally, the landslide early warning extensometer is arranged on two sides of a ground crack of a landslide and acquires crack opening data) and the like; when monitoring facilities is ordinary equipment, the server acquires that ordinary monitoring facilities's monitoring data is status data and/or geological monitoring data, ordinary monitoring facilities includes environmental monitoring equipment and simple and easy monitoring facilities, and the server acquires environmental monitoring data (the environmental monitoring data of here also belongs to geological monitoring data) and the status data that environmental monitoring equipment gathered, environmental monitoring equipment can be rain gauge, soil moisture meter, water level gauge, thermometer, light intensity measuring apparatu etc.: the simple monitoring equipment mainly reports state data, and a server analyzes whether the simple monitoring equipment is on line or not, wherein the state of the simple monitoring equipment comprises an on-line state and an off-line state; of course, the server not only obtains the monitoring data collected by the monitoring devices having the association relationship, but also obtains the monitoring data of other monitoring devices, which is not described herein any more.

On the basis of the pre-established association relationship between the monitoring devices, the combined type geological disaster professional monitoring and early warning method provided by the embodiment of the invention comprises the following steps:

step 30, judging whether the early warning condition is met or not according to the acquired state data and/or geological monitoring data;

the invention is exemplified by a first type of geological disaster and a second type of geological disaster, and specifically comprises the following steps: before a first-class geological disaster (the first-class geological disaster can be any one of earthquake, debris flow, mountain landslide and the like), the field environment is extremely severe, the situation of power failure and network disconnection can occur in the installed professional monitoring equipment, although the professional monitoring equipment reports the professional geological monitoring data to the server before the situation of power failure and network disconnection occurs, the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment do not exceed the early warning value, the situation of power failure and network disconnection occurs when the professional monitoring equipment does not report effective early warning data to the server, and therefore the server cannot accurately predict the occurrence of the first-class geological disaster. At the moment, the server judges the probability of the first type of geological disaster according to the monitoring equipment with the incidence relation established in advance.

Referring to fig. 2, the specific method is as follows: the monitoring devices with the association relationship in the first association group are respectively arranged at H, I, J, K point locations and L point locations, through big data analysis, when a first-class geological disaster occurs, the probability of disconnection of the monitoring devices arranged at H, I, J, K point locations and L point locations exceeds a preset threshold value 99%, and the probability of disconnection exceeding the preset threshold value 99% is only an example, has no limiting meaning, and can be defined by self in combination with actual scene requirements. The monitoring equipment arranged at the H point location is professional monitoring equipment for monitoring the first-class geological disasters, the monitoring equipment arranged at I, J, K and the monitoring equipment arranged at the L point location are common monitoring equipment, the common monitoring equipment is environment monitoring equipment, and the server can acquire environment monitoring data and state data of the environment monitoring equipment.

Assuming that the monitoring devices at H, I, J, K and L point locations are in a dropped state, the server first analyzes professional geological monitoring data reported by the professional monitoring device at the H point location before the dropped state.

The first condition is as follows:

when the server analyzes that the state data of each monitoring device in the first association group are in the off-line state, if the first association group contains the professional monitoring device corresponding to the first-class geological disaster and the server analyzes that the professional geological monitoring data reported by the professional monitoring device before the off-line state exceeds the early warning value, the first-class geological disaster early warning condition is met.

And step 40, if the early warning condition is met, generating corresponding early warning reminding information, and sending the early warning reminding information.

The server generates corresponding early warning reminding information and sends the early warning reminding information to related personnel, and the related personnel send early warning reminding to the threatened objects in the related areas after receiving the early warning reminding information, wherein the early warning reminding mode can send early warning reminding to the threatened objects in the related areas in a broadcasting, short message reminding or network issuing mode.

Case two:

referring to fig. 2 and 4, when the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment arranged at the point H location before the disconnection does not exceed the warning value, the reason for the disconnection may be caused by the first-class geological disaster, or may be caused by the non-first-class geological disaster such as equipment damage or poor contact, and the probability of the first-class geological disaster needs to be further confirmed: firstly, preliminarily judging the type of the disaster to be a first type of geological disaster according to the incidence relation among monitoring equipment arranged at five point positions, and further analyzing the probability of the first type of geological disaster, wherein the specific method comprises the following steps: analyzing the matching degree between actual environment monitoring data reported by I, J, K and environment monitoring data of an L point location before the L point location is disconnected and environment monitoring data of I, J, K and the L point location under a first type of geological disaster scene corresponding to big data analysis, if the matching degree exceeds a preset matching value, conforming to the first type of geological disaster early warning condition, and assuming that the environment monitoring equipment arranged at the I point location is a rain gauge I; the environment monitoring equipment arranged at the J point is a water level meter J; the environment monitoring equipment arranged at the K point position is a light intensity measuring instrument K; and the environment monitoring equipment of the L-point location equipment is a soil moisture meter L. The actual environment monitoring data reported by the rain gauge I, the water level gauge J, the light intensity measuring instrument K and the soil moisture gauge L before the line drop are respectively rainfall I, water level J, light intensity K and soil moisture L, the environment monitoring data of the rain gauge I, the water level gauge J, the light intensity measuring instrument K and the soil moisture gauge L corresponding to the first-class geological disaster scene of big data analysis are respectively rainfall I1, water level J1, light intensity K1 and soil moisture L1, if the matching degree of the rainfall I and the rainfall I1 exceeds 90%, the matching degree of the water level J and the water level J1 exceeds 90%, the matching degree of the light intensity K and the light intensity K1 exceeds 90%, and the matching degree of the soil moisture L and the soil moisture L1 exceeds 90%, which shows that the actual environment monitoring data reported by the rain gauge I, the water level gauge J, the light intensity measuring instrument K and the soil moisture gauge L before the line drop and the actual environment monitoring data reported by the soil moisture gauge L corresponding to the first-class geological disaster scene, The average matching degree of the environmental monitoring data of the water level meter J, the light intensity measuring instrument K and the soil moisture meter L exceeds 90%, if 90% is a preset matching value, the reason that the monitoring equipment at H, I, J, K and L is disconnected is caused by the first-class geological disaster, but not the disconnection caused by the non-first-class geological disaster such as poor contact or line damage and the like, and the monitoring equipment is in line with the first-class geological disaster early warning condition, and the preset matching value is only used for explanation and is not used for limiting the invention.

According to the incidence relation among the monitoring equipment set up according to five position locations, it is first kind of geological disasters to judge the disaster type of taking place for the first kind of geological disasters tentatively to further carry out the analysis to the probability that first kind of geological disasters takes place, there is another realizable mode still, specifically is: I. j, K, when the probability of the first type of geological disaster is judged according to the actual environment monitoring data reported by the environment monitoring equipment arranged at the L point before the line drop, the importance degrees of the first type of geological disasters are different, so a weighting calculation method can be adopted when the probability of the first type of geological disasters is comprehensively analyzed, firstly, the importance degrees of the first type of geological disasters are judged to be weighted according to the rain gauge I, the water level gauge J, the light intensity measuring instrument K and the soil moisture gauge L, if the light intensity measuring instrument K and the soil moisture meter L have higher importance degree when judging the occurrence of the first type of geological disaster and are respectively endowed with weights of 0.4 and 0.3, the rain gauge I and the water level meter J have lower importance degree when judging the occurrence of the first type of geological disaster and are respectively endowed with weights of 0.2 and 0.1, the method for judging whether the early warning condition of the first type of geological disaster is met after determining the weight of the occurrence probability of the first type of geological disaster by the environment monitoring equipment at different point positions is as follows: firstly, actual environment monitoring data reported by I, J, K and environment monitoring equipment arranged at an L point position before disconnection are respectively matched with environment monitoring data of I, J, K and the environment monitoring equipment arranged at the L point position under a first-class geological disaster scene of big data analysis to obtain corresponding matching degrees, then, the total matching degree is calculated according to weight, and if the total matching degree exceeds a preset matching value, the first-class geological disaster early warning condition is met.

The method specifically comprises the following steps: actual environment monitoring data reported by a rain gauge I, a water level meter J, a light intensity measuring instrument K and a soil moisture meter L before the rain gauge I, the water level meter J, the light intensity K and the soil moisture meter L are respectively rainfall I, water level J, light intensity K and soil moisture L, and environment monitoring data of the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L under the first class of geological disaster scenes of big data analysis are respectively rainfall I1, water level J1, light intensity K1 and soil moisture L1, wherein the matching degree of the rainfall I and the rainfall I1 is I1, the matching degree of the water level J and the water level J1 is J1, the matching degree of the light intensity K and the light intensity K1 is K1, the matching degree of the soil moisture L and the soil moisture L1 is L1, and the total matching degree is calculated: the total matching degree is 0.2I 1+ 0.1J 1+ 0.4K 1+ 0.3L 1, if the total matching degree exceeds a preset matching value, the first-class geological disaster early warning condition is met, the server generates corresponding early warning reminding information and sends the early warning reminding information to related personnel, and the related personnel send early warning reminding to the threatened objects in the related areas after receiving the early warning reminding information, wherein the early warning reminding mode can send early warning reminding to the threatened objects in the related areas in a broadcasting, short message reminding or network issuing mode.

If the total matching degree does not exceed the preset matching value, it is determined that the first type of geological disaster does not occur, and the reason that all the monitoring devices with the association relationship in the first association group are dropped may be the reason that other non-disaster drop such as a problem occurs to the monitoring device line in the first association group, the related personnel may view the monitoring devices in the corresponding area by using an unmanned aerial vehicle, or view the monitoring devices in the corresponding area by using related workers, the weight assignment may be adjusted according to actual needs, and the above description is only one specific embodiment and is not used for limiting the invention.

The server establishes an association relationship between monitoring devices in advance, and specifically includes:

the server establishes an incidence relation between corresponding monitoring devices when different geological disasters occur in advance according to the geographical position characteristics and historical disaster data; the state data of the monitoring equipment with the incidence relation is in an offline state with a high probability when corresponding geological disasters occur, the specific probability can be set according to requirements, and the probability set by the monitoring equipment is called a preset threshold, such as: according to big data analysis, when the first type of disaster occurs, the probability that the state data of the monitoring equipment on certain monitoring point locations is the line-dropping state exceeds a preset threshold value by 99%, and then the monitoring equipment on the monitoring point locations can be considered to have an association relation; the big data is comprehensively analyzed mainly according to geographical location characteristics and conditions of disconnection and the like of monitoring equipment when historical disasters occur, 10 times of first-class geological disasters may occur historically, and when the 10 times of first-class geological disasters occur, the conditions of disconnection of the monitoring equipment in the first association group are also 10 times, at the moment, the monitoring equipment in the first association group is the monitoring equipment with the association relationship, and the method is only used for more clearly explaining how to establish the association relationship among the monitoring equipment, and the preset threshold value of 99% is only used for illustration, and specific numerical values can be adjusted according to actual needs and are not used for limiting the invention.

the monitoring device having an association relationship may specifically be: the monitoring equipment with the incidence relation comprises common monitoring equipment and professional monitoring equipment; the monitoring devices with the association relation are all common monitoring devices.

The judging whether the early warning condition is met according to the acquired state data and/or geological monitoring data specifically comprises the following steps:

when the state data of each monitoring device in the first association group is in a disconnection state, if the first association group contains professional monitoring devices corresponding to the first type of geological disaster, the server analyzes that the professional geological monitoring data reported by the professional monitoring devices before disconnection does not exceed an early warning value; the reason for the disconnection may be caused by the first-class geological disaster, but the professional monitoring equipment has not yet come to report effective early warning information to the server, and the disconnection is also caused by non-first-class geological disasters such as aging of the monitoring equipment itself or poor contact of the monitoring equipment in the first association group, so that the probability of the first-class geological disaster needs to be further confirmed, and at this time, the server matches geological monitoring data reported by the common monitoring equipment in the first association group before the disconnection with geological monitoring data in a corresponding geological disaster scene.

With continuing reference to fig. 2 and 4, the specific implementation is: the monitoring devices with incidence relations in the first association group are respectively arranged at H, I, J, K and L five point locations, wherein the monitoring devices arranged at the H point location are professional monitoring devices for monitoring the first type of geological disasters, the monitoring devices arranged at the I, J, K and L point locations are environment monitoring devices, if the server analyzes that professional geological monitoring data reported by the professional monitoring devices of the H point location device before the line drop does not exceed an early warning value, the probability of the first type of geological disasters needs to be further confirmed, the type of the first type of geological disasters is preliminarily determined according to the incidence relations among the monitoring devices arranged at the five point locations, and the probability of the first type of geological disasters is further analyzed, and the specific method is as follows: analyzing the matching degree between actual environment monitoring data reported by I, J, K and environment monitoring data of an L point location before the L point location is disconnected and environment monitoring data of I, J, K and the L point location under a first type of geological disaster scene corresponding to big data analysis, if the matching degree exceeds a preset matching value, conforming to the first type of geological disaster early warning condition, and assuming that the environment monitoring equipment arranged at the I point location is a rain gauge I; the environment monitoring equipment arranged at the J point is a water level meter J; the environment monitoring equipment arranged at the K point position is a light intensity measuring instrument K; and the environment monitoring equipment of the L-point location equipment is a soil moisture meter L. The actual environment monitoring data reported by the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L before the line drop are rainfall I, water level J, light intensity K and soil moisture L respectively, the environment monitoring data of the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L under the first class geological disaster scene of big data analysis are rainfall I1, water level J1, light intensity K1 and soil moisture L1 respectively, if the matching degree of the rainfall I and the rainfall I1 exceeds 90%, the matching degree of the water level J and the water level J1 exceeds 90%, the matching degree of the light intensity K and the light intensity K1 exceeds 90%, and the matching degree of the soil moisture L and the soil moisture L1 exceeds 90%, which shows that the actual environment monitoring data reported by the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L before the line drop and the rain gauge I, the water intensity measuring instrument J, the soil moisture meter L under the, The average matching degree of the environmental monitoring data of the water level meter J, the light intensity measuring instrument K and the soil moisture meter L exceeds 90%, if 90% is a preset matching value, the reason that the monitoring equipment at H, I, J, K and L is disconnected is caused by a first-class geological disaster instead of disconnection caused by non-first-class geological disasters such as poor contact or line damage, and the early warning condition of the first-class geological disaster is met.

According to the incidence relation among the monitoring equipment set up according to five position locations, it is first kind of geological disasters to judge the disaster type of taking place for the first kind of geological disasters tentatively to further carry out the analysis to the probability that first kind of geological disasters takes place, there is another realizable mode still, specifically is: I. j, K, when the probability of the first type of geological disaster is judged according to the actual environmental monitoring data reported by the environmental monitoring equipment arranged at the point location before the line drop, the importance degrees are different, so a weighting calculation method can be adopted when the probability of the first type of geological disaster is comprehensively analyzed, firstly, weights are given according to the importance degrees of the rain gauge I, the water level gauge J, the light intensity gauge K and the soil moisture gauge L when the first type of geological disaster is judged, if the importance degrees of the light intensity gauge K and the soil moisture gauge L when the first type of geological disaster is judged are higher, the weights are respectively given by 0.4 and 0.3, and the importance degrees of the rain gauge I and the water level gauge J when the first type of geological disaster is judged are lower, and the weights are respectively given by 0.2 and 0.1. After determining the weight of the occurrence probability of the first type of geological disaster, the method for determining whether the first type of geological disaster early warning condition is met by the environment monitoring equipment at different point positions comprises the following steps: firstly, actual environment monitoring data reported by I, J, K and environment monitoring equipment arranged at an L point position before disconnection are respectively matched with environment monitoring data of I, J, K and the environment monitoring equipment arranged at the L point position under a first-class geological disaster scene of big data analysis to obtain corresponding matching degrees, then, the total matching degree is calculated according to weight, and if the total matching degree exceeds a preset matching value, the first-class geological disaster early warning condition is met.

Case three:

referring to fig. 2 and 5, when the status data of each monitoring device in the first association set is in an off-line status, the first association set contains a professional monitoring device corresponding to a first type of geological disaster, however, the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment before the disconnection does not exceed the early warning value, and another scene exists, each monitoring device in the second association group is included in the first association group, and assuming that the monitoring devices having association relations in the first association group are respectively arranged at H, I, J, K and L five points, wherein the monitoring equipment arranged at the H point location is professional monitoring equipment for monitoring the first class of geological disasters, the I, J, K monitoring equipment and the monitoring equipment arranged at the L point location are common monitoring equipment, the common monitoring equipment is environment monitoring equipment, and the environment monitoring equipment arranged at the point I position is assumed to be a rain gauge I; the environment monitoring equipment arranged at the J point is a water level meter J; the environment monitoring equipment arranged at the K point position is a light intensity measuring instrument K; and the environment monitoring equipment of the L-point location equipment is a soil moisture meter L. The monitoring equipment that has the incidence relation among the second association is J, K in the first association and the monitoring equipment fluviograph J, light intensity measuring apparatu K and the soil moisture meter L on the three point positions of L, consequently the monitoring equipment in the first association is the state of falling the line, if server analysis professional monitoring equipment does not exceed when the early warning value in the professional geology monitoring data that reports before falling the line, can tentatively judge that the calamity takes place the type and include: the server is used for matching actual environment monitoring data reported by the environment monitoring equipment in the first association set before the line is disconnected with environment monitoring data in a corresponding geological disaster scene.

If the server analyzes that the matching degree of the environment monitoring data reported by the environment monitoring equipment in the first association set before the disconnection and the environment monitoring data in the first type of geological disaster scene exceeds a preset matching value, the first type of geological disaster early warning condition is met;

the specific implementation mode is as follows: the actual environment monitoring data reported by the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L before the line drop are rainfall I, water level J, light intensity K and soil moisture L respectively, the environment monitoring data of the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L under the first class geological disaster scene of big data analysis are rainfall I1, water level J1, light intensity K1 and soil moisture L1 respectively, if the matching degree of the rainfall I and the rainfall I1 exceeds 90%, the matching degree of the water level J and the water level J1 exceeds 90%, the matching degree of the light intensity K and the light intensity K1 exceeds 90%, and the matching degree of the soil moisture L and the soil moisture L1 exceeds 90%, which shows that the actual environment monitoring data reported by the rain gauge I, the water level meter J, the light intensity measuring instrument K and the soil moisture meter L before the line drop and the rain gauge I, the water intensity measuring instrument J, the soil moisture meter L under the, The average matching degree of the environmental monitoring data of the water level meter J, the light intensity measuring instrument K and the soil moisture meter L is over 90 percent. If 90% is the preset matching value, it is indicated that the reason why the monitoring devices at H, I, J, K and the five L point locations drop lines is caused by the first-class geological disaster, and not the drop lines caused by the non-first-class geological disaster such as poor contact or line damage, and the like, and the preset matching value is merely for explanation and is not used to limit the present invention.

And if the matching degree of the actual environment monitoring data reported by the common monitoring equipment in the first association group before the disconnection and the environment monitoring data in the scene in which the first type of geological disaster and the second type of geological disaster happen simultaneously exceeds a preset matching value, the server accords with the early warning condition of the simultaneous occurrence of the first type of geological disaster and the second type of geological disaster. The method specifically comprises the following steps: the actual environment monitoring data reported by the rain gauge I, the water level gauge J, the light intensity gauge K and the soil moisture gauge L before the line drop are respectively rainfall I, water level J, light intensity K and soil moisture L, the environment monitoring data of the rain gauge I, the water level gauge J, the light intensity gauge K and the soil moisture gauge L under the scene when the first-class geological disaster and the second-class geological disaster happen simultaneously are respectively rainfall I2, water level J2, light intensity K2 and soil moisture L2 after the big data analysis, if the matching degree of the rainfall I and the rainfall I2 exceeds 90%, the matching degree of the water level J and the water level J2 exceeds 90%, the matching degree of the light intensity K and the light intensity K2 exceeds 90%, and the matching degree of the soil moisture L and the soil moisture L2 exceeds 90%, the fact that the actual environment monitoring data reported by the rain gauge I, the water level gauge J, the light intensity gauge K and the soil moisture gauge L before the line drop and the big data analysis result in the actual environment monitoring data of the scene when the first-class geological disaster and the second-class geological disaster happen, The average matching degree of the environmental monitoring data of the water level meter J, the light intensity measuring instrument K and the soil moisture meter L exceeds 90%, and if 90% is a preset matching value, the early warning condition that the first type of geological disaster and the second type of geological disaster happen simultaneously is met.

Case four:

referring to fig. 3, there is another achievable way in the actual scenario, in the past data of historical disaster occurrence, when each monitoring device in the second association group is included in the first association group, the preliminary determination of the type of disaster occurrence includes: in order to further eliminate the possibility of the simultaneous occurrence of the first-class geological disaster or the second-class geological disaster and the first-class geological disaster, in this embodiment, an associated monitoring device M is additionally provided in the second associated group, and it is assumed that the associated monitoring device M is a simple monitoring device, the simple monitoring device M does not drop when the first-class geological disaster occurs, but when the second-class geological disaster occurs, the drop probability is 100%, at this time, the monitoring devices having an associated relationship in the second associated group are a water level meter J, a light intensity measuring instrument K, a soil moisture meter L and the simple monitoring device M, the monitoring devices in the first associated group are professional monitoring devices of an H-point, a rain gauge I, a water level meter J, a light intensity measuring instrument K and a soil moisture meter L, and when the monitoring devices in the first associated group are all in a drop state, and when the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment of the H point location before the disconnection does not exceed the early warning value, preliminarily judging the occurrence type of the disaster to be the first type of geological disaster according to the incidence relation among the monitoring equipment arranged at the five point locations, and further analyzing the occurrence probability of the first type of geological disaster.

As professional monitoring equipment is generally expensive, and cannot be used in some regions, early warning on occurrence of geological disasters needs to be carried out through monitoring data of common monitoring equipment, and when all the monitoring equipment in the first association group are common monitoring equipment and the state data of all the common monitoring equipment is in a disconnection state, the server matches geological monitoring data reported by the common monitoring equipment in the first association group before disconnection with geological monitoring data under a corresponding geological disaster scene;

when each monitoring device in the second association group is included in the first association group, whether the early warning condition is met is judged according to the acquired state data and/or geological monitoring data, and the method specifically further comprises the following steps:

case five:

referring to fig. 2 and 6, the monitoring devices having association in the first association group are respectively disposed at H, I, J, K and five point locations L, where the monitoring devices disposed at H, I, J, K and five point locations L are both common monitoring devices, the common monitoring devices are environment monitoring devices, the server obtains environment monitoring data and state data of the environment monitoring devices, and the monitoring devices having association in the second association group are environment monitoring devices at J, K and three point locations L in the first association group, for example, the environment monitoring devices disposed at H, I, J, K and five point locations L are respectively referred to as: environmental monitoring equipment H, environmental monitoring equipment I, environmental monitoring equipment J, environmental monitoring equipment K, environmental monitoring equipment L, wherein, when environmental monitoring equipment H, environmental monitoring equipment I, environmental monitoring equipment J, environmental monitoring equipment K, environmental monitoring equipment L were the off-line state, can tentatively judge that the calamity emergence type includes: the server is used for matching the environment monitoring data reported by the environment monitoring equipment in the first association set before the connection drop with the environment monitoring data in the corresponding geological disaster scene.

the specific implementation mode is as follows: the actual environmental monitoring data reported by the environmental monitoring equipment H, the environmental monitoring equipment I, the environmental monitoring equipment J, the environmental monitoring equipment K and the environmental monitoring equipment L before the disconnection are respectively environmental monitoring data H3, environmental monitoring data I3, environmental monitoring data J3, environmental monitoring data K3 and environmental monitoring data L3, the environmental monitoring data of the environmental monitoring equipment H, the environmental monitoring equipment I, the environmental monitoring equipment J, the environmental monitoring equipment K and the environmental monitoring equipment L under the first class of geological disaster scenes of big data analysis are respectively monitoring data H4, environmental monitoring data I4, environmental monitoring data J4, environmental monitoring data K4 and environmental monitoring data L4, if the matching degree of the environmental monitoring data H3 and the monitoring data H4 exceeds 90%, the matching degree of the environmental monitoring data I3 and the environmental monitoring data I4 exceeds 90%, the matching degree of the environmental monitoring data J3 and the environmental monitoring data J4 exceeds 90%, the matching degree of the environmental monitoring data K3 and the environmental monitoring data K4 exceeds 90%, the matching degree of the environmental monitoring data L3 and the environmental monitoring data L4 exceeds 90%, it is described that the average matching degree of the environmental monitoring data of the environmental monitoring equipment H, the environmental monitoring equipment I, the environmental monitoring equipment J, the environmental monitoring equipment K and the environmental monitoring equipment L under the first type of geological disaster scene and the environmental monitoring data before the line drop are analyzed to be more than 90% with the big data, if 90% is a preset matching value, the first type of geological disaster early warning condition is met, and the preset matching value of 90% is only for illustration, can be adjusted according to the specific scene requirements, and is not used for limiting the invention.

If the server analyzes that the matching degree of the geological monitoring data reported by the common monitoring equipment in the first association group before the disconnection and the geological monitoring data in the scene in which the first type of geological disaster and the second type of geological disaster happen simultaneously exceeds a preset matching value, the early warning condition of the first type of geological disaster and the second type of geological disaster occurring simultaneously is met, and the specific implementation mode can refer to the above mode, which is not repeated herein.

In an actual scenario, there is another situation, where all monitoring devices in the first associated group are not disconnected, the server first determines whether to receive data reported by professional monitoring devices corresponding to the first type of geological disaster (mainly aiming at determining whether the first associated group includes professional monitoring devices), and when the status data of the monitoring devices in the first associated group indicates that at least one monitoring device is in an online status, the method specifically includes:

case six:

if the data reported by the professional monitoring equipment corresponding to the first type of geological disaster is received (the first association group contains the professional monitoring equipment), but the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment does not exceed the early warning value, the server matches the geological monitoring data obtained by the common monitoring equipment in the online state in the first association group with the geological monitoring data in the first type of geological disaster scene;

with continued reference to fig. 2, specifically: assuming that monitoring devices with incidence relations in a first association group are respectively arranged at H, I, J, K and five L point locations, wherein monitoring devices arranged at an H point location are professional monitoring devices for monitoring a first type of geological disasters, monitoring devices arranged at I, J, K and an L point location are common monitoring devices, the common monitoring devices are environment monitoring devices, a server acquires environment monitoring data and state data of the environment monitoring devices, when the monitoring devices arranged at the H, I, J, K point locations are all in a line-drop state, and the environment monitoring devices arranged at the L point location are in an online state, if the server analyzes that professional geological monitoring data reported by the professional monitoring devices arranged at the H point location before the line-drop do not exceed an early warning value, the occurrence type of the disasters is preliminarily judged to be the first type of geological disasters, and further, the real-time environment monitoring data acquired by the environment monitoring devices arranged at the L point location and the environment monitoring devices of the L point location environment monitoring devices under the first type of geological disasters And matching the monitoring data, and if the matching degree exceeds a preset matching value by 99%, conforming to the first-class geological disaster early warning condition, wherein the preset matching value by 99% is only used for illustration and is not used for limiting the invention.

The method includes that whether the server receives data reported by professional monitoring equipment corresponding to the first type of geological disaster or not is judged, and when the state data of the monitoring equipment in the first association group shows that at least one monitoring equipment is in an online state, the method specifically includes the following steps: and if the data reported by the professional monitoring equipment corresponding to the first type of geological disaster is received, and the server analyzes that the professional geological monitoring data reported by the professional monitoring equipment exceeds the early warning value, the early warning condition of the first type of geological disaster is met.

Case seven:

with continued reference to fig. 2, there is also an achievable scenario, specifically: each monitoring device in the second association group is contained by the first association group, it is assumed that the monitoring devices with association relations in the first association group are respectively arranged at H, I, J, K and L five point locations, the monitoring devices with association relations in the second association group are monitoring devices on J, K and L three point locations in the first association group, wherein the monitoring devices arranged at H, I, J, K and L five point locations are common monitoring devices which are environment monitoring devices, if the environment monitoring devices on the H point location and the I point location are both in an online state, and the common monitoring devices on the J, K and the L point location are both in a dropped state, the occurrence type of the disaster is preliminarily determined to be a second type of geological disaster, and further, the actual environment monitoring data reported by the environment monitoring devices on the J, K and the L point location before the dropped line and the actual environment monitoring data reported by the environment monitoring devices on the second point location under the second type of geological disaster scene are analyzed, Matching degrees between environment monitoring data of the environment monitoring equipment in the K point location and the L point location are combined with monitoring data collected by the online common monitoring equipment in the H point location and the I point location to comprehensively judge whether the environment monitoring data are matched with the monitoring data in the second type of geological disaster scene, and if the matching degrees exceed preset matching values, the second type of geological disaster early warning conditions are met.

The monitoring equipment comprises one or more of a rain gauge, a soil moisture meter, a water level meter, an osmometer, a crack meter, an earth surface displacement monitor and an inclinometer.

Compared with the prior art, the combined type geological disaster professional monitoring and early warning method provided by the invention has the following advantages: the method comprises the steps of establishing an incidence relation between monitoring devices through geographical position characteristics and historical disaster data, preliminarily judging the disaster type according to the incidence relation between the monitoring devices when professional monitoring devices are not ready to report effective early warning information to a server and then drop, matching the monitoring data reported by common monitoring devices before dropping with the monitoring data of the common monitoring devices in a disaster scene, and if the matching degree of the monitoring data and the monitoring data exceeds a preset matching value, conforming to disaster early warning conditions. In another case, some areas are not provided with professional monitoring equipment, the probability of disaster occurrence can be judged through the association relationship among the ordinary monitoring equipment, when a certain type of geological disaster occurs, the probability of the disconnection of the common monitoring equipment exceeds a preset threshold value, then preliminarily judging the disaster type according to the line drop condition of the common monitoring equipment with the incidence relation, further matching the monitoring data reported by the common monitoring equipment before the line drop with the monitoring data under the disaster scene, if the matching degree exceeds a preset matching value, the early warning condition is met, meanwhile, the server generates corresponding early warning reminding information and sends the early warning reminding information to relevant personnel, the relevant personnel send early warning reminding to the threatened object in the relevant area after receiving the early warning reminding information, the early warning reminding mode can send early warning reminding to threatened objects in relevant areas in the form of broadcast broadcasting, short message reminding or network publishing. The invention can effectively solve the problem that the professional monitoring equipment fails to be connected before the disaster happens and can not accurately warn. Meanwhile, due to the establishment of the incidence relation among the monitoring devices, the disaster early warning can be realized under the condition that no professional monitoring device is arranged, and the cost of the disaster early warning is effectively reduced.

Example 2:

professional monitoring equipment is often expensive, and a lot of regions with relatively laggard economy have limited economic capacity; under the condition, areas with relatively backward economy usually choose to purchase cheap common monitoring equipment, the monitoring dimensionality of the common monitoring equipment is usually not complete enough, so that the loss of a part of types of geological monitoring data in geological monitoring data is caused, the loss of a part of types of geological monitoring data in certain areas is caused, and in order to fully utilize various types of geological disaster monitoring equipment and obtain more comprehensive geological disaster geological monitoring data, the invention provides another composite geological disaster professional monitoring and early warning method, and the geological monitoring data which is lost in the areas with limited economic capability is compensated through the geological monitoring data of the peripheral areas; more geological monitoring data of a certain area are obtained through monitoring equipment as few as possible, and early warning is carried out on geological disasters of economic lag areas.

Aiming at the defects or the improvement requirements, the invention provides a composite geological disaster professional monitoring and early warning method, which comprises the steps of calculating missing geological monitoring data through different peripheral area combinations, giving different weights to the same type of geological monitoring data according to the different geographic positions of the peripheral areas, generating a plurality of sets of weighted values, selecting a plurality of sets of peripheral area combinations with the same weighted values so as to find reasonable geological disaster monitoring points, calculating the missing geological monitoring data through the selected geological monitoring data of the peripheral area combinations to obtain more accurate compensation data, matching the missing compensation data in an associated monitoring group and/or the geological monitoring data acquired by monitoring equipment in local area geological association with the geological monitoring data in a disaster scene, and if the matching degree exceeds a preset matching value, the corresponding geological disaster early warning conditions are met.

In order to achieve the purpose, the invention adopts the following technical scheme:

firstly, searching a surrounding geological disaster monitoring point, wherein the specific method comprises the following steps:

as shown in fig. 15, wherein B, C, D, E, F, G, H, I, J, K, L and M denote the surrounding areas of area a in the present embodiment, at least two surrounding areas are randomly picked to form a database combination, for example, database combination KLH, database combination JMD, database combination BCD, database combination GEF and database combination KLI, and among the different database combinations picked at random, target database combinations with n sets of weights all consistent are searched, so as to calculate the geological monitoring data missing from the geological monitoring data in the target database combination.

Wherein, in different database combinations picked at random, target database combinations with n sets of weight values all consistent are searched, as shown in FIG. 16,

for geological monitoring data B1, C1 and D1 of the same type in the database combination BCD, according to the difference of the geographic positions of the region B, the region C and the region D relative to the region A in the database combination BCD, such as different altitudes, different terrains and different landforms between two regions, wherein the landforms between the two regions comprise a mountain or a river and the like, different weights are given to B1, C1 and D1, so that compensation data A1' of geological monitoring data A1 of the region A is calculated to generate a set of weights n11, and the set of weights n11 specifically comprises n111, n112 and n113 corresponding to B1, C1 and D1 respectively;

similarly, B2, C2 and D2 are given different weights, so as to calculate compensation data a 2' of the geological monitoring data a2 of the area a, and generate a set of weights n12, wherein the set of weights n12 specifically comprises n121, n122 and n123 corresponding to B2, C2 and D2 respectively;

b3, C3 and D3 are given different weights, so that compensation data A3' of geological monitoring data A3 of the region A are calculated, a set of weights n13 is generated, and the set of weights n13 specifically comprises n131, n132 and n133 corresponding to B3, C3 and D3 respectively;

b4, C4 and D4 are given different weights, so that compensation data A4' of geological monitoring data A4 of the region A are calculated, a set of weights n14 is generated, and the set of weights n14 specifically comprises n141, n142 and n143 corresponding to B4, C4 and D4 respectively;

b5, C5 and D5 are given different weights, so that compensation data A5' of geological monitoring data A5 of the region A are calculated, a set of weights n15 is generated, and the set of weights n15 specifically comprises n151, n152 and n153 corresponding to B5, C5 and D5 respectively;

combining and calculating n types of geological monitoring data of the area A by a randomly picked database, and generating n sets of weighted values; in the present embodiment, a database combination BCD is taken as an example, and in the present embodiment, the database of the area a includes 5 types of geological monitoring data, but in an actual situation, the database combination is not limited to the BCD combination, and the types of geological monitoring data in the database of the area a are not limited to 5;

when 5 types of geological monitoring data of the area a are estimated by the database combination BCD, 5 sets of weight values are generated, and if all the 5 sets of weight values are consistent, that is, n111, n121, n131, and n141 are consistent with n151, n112, n122, n132, and n142 are consistent with n152, and n113, n123, n133, and n143 are consistent with n153, the database combination BCD is determined as a target database combination.

In the embodiment of the present invention, the calculating of the geological monitoring data missing from the area a from the geological monitoring data in the target database combination specifically includes:

As shown in fig. 7, the calculation of the geological monitoring data missing from the area a according to the geological monitoring data in the target database combination specifically includes:

geological monitoring data for region a includes: a1, a2, A3, a 4;

the geological monitoring data for region B includes: b1, B2, B3, B4, B5;

geological monitoring data for region C includes: c1, C2, C3, C4, C5;

geological monitoring data for region D includes: d1, D2, D3, D4, D5;

according to geological monitoring data B5, C5 and D5, calculating geological monitoring data A5 missing from the region A through a prediction algorithm to obtain compensation data A5';

according to geological monitoring data B1, C1 and D1, calculating geological monitoring data A1 of the area A through a prediction algorithm to obtain compensation data A1';

according to geological monitoring data B2, C2 and D2, calculating geological monitoring data A2 of the area A through a prediction algorithm to obtain compensation data A2';

according to geological monitoring data B3, C3 and D3, calculating geological monitoring data A3 of the area A through a prediction algorithm to obtain compensation data A3';

according to geological monitoring data B4, C4 and D4, calculating geological monitoring data A4 of the area A through a prediction algorithm to obtain compensation data A4';

the server compares geological monitoring data A1, A2, A3 and A4 with corresponding compensation data A1 ', A2', A3 'and A4' respectively to obtain similarity R1, R2, R3 and R4 of the geological monitoring data and the corresponding compensation data respectively, wherein the average value of R1, R2, R3 and R4 is the average similarity of the geological monitoring data and the corresponding compensation data.

If the similarity reaches a similarity set threshold, considering that the compensation data A5' calculated by the prediction algorithm is reliable, as shown in FIG. 10, so as to obtain geological monitoring data missing from the area A;

and if the average similarity is lower than the set similarity threshold, the compensation data is considered to have certain uncertainty, and a prediction algorithm is adjusted, including the selection of the algorithm and the adjustment of parameters, until the average similarity is higher than or equal to the set similarity threshold, so that the geological monitoring data missing in the area A is obtained.

As shown in fig. 8, wherein A, B, C, D represents different adjacent regions, 1, 2, 3, 4, 5 represent different types of geosurveillance data, for example, a1 represents the permeate water pressure of region a, a2 represents the slope inclination angle of region a, B1 represents the permeate water pressure of region B, and B2 represents the slope inclination angle of region B; as shown in fig. 9, the permeate water pressure of the region a obtained by compensation is represented by a1 ', the slope inclination angle of the region a obtained by compensation is represented by a 2', the permeate water pressure of the region B obtained by compensation is represented by B1 ', and the slope inclination angle of the region B obtained by compensation is represented by B2'; here, different regions are indicated by different letters, different types of geostationary monitoring data are indicated by different numbers, and the number of letters and numbers is not intended to limit the number of regions and the number of types of geostationary monitoring data.

The prediction algorithm comprises a simple averaging method, a moving average method, an exponential smoothing method and a linear regression method, and the server selects different prediction algorithms for statistical analysis according to different regional climate environments and different geological monitoring data types.

According to the acquired compensation data and/or geological monitoring data of the monitoring equipment in the association group, the probability of occurrence of geological disasters is judged, and early warning is timely given, and the method specifically comprises the following steps:

assuming that monitoring devices in a first association group corresponding to a first type of geological disaster in the area a are analyzed according to big data and should be respectively arranged at five point locations, but in order to reduce economic cost, the fifth point location is not provided with monitoring devices, but only four monitoring devices are arranged (assuming that the monitoring devices are all common monitoring devices), at this time, geological monitoring data of the fifth point location lacking in the area with limited economic capability needs to be compensated through geological monitoring data of the surrounding area, and the obtained compensation data is a 5', and the above contents are referred to specifically for calculation.

When the monitoring devices of the four point locations with the association relation in the first association group of the area a are all in the offline state, the occurrence type of the disaster is preliminarily determined to be a first type of geological disaster according to the fact that the monitoring devices of the four point locations in the first association group are all in the offline state, furthermore, the occurrence probability of the first type of geological disaster is analyzed, and the compensation data a5 'are obtained by calculating the geological monitoring data of the surrounding area through a prediction algorithm, so that the compensation data a 5' are real-time data. And matching the real-time compensation data A5' obtained according to the fifth point location with geological monitoring data of fifth point location monitoring equipment in the first class of geological disaster scenes, and if the matching degree exceeds a preset matching value by 99%, conforming to the first class of geological disaster early warning conditions, wherein the preset matching value of 99% is only for illustration and is not used for limiting the invention.

In the embodiment of the invention, the real-time compensation data is obtained by calculating the geological monitoring data of the point positions with the incidence relation, and the real-time compensation data is matched with the geological monitoring data under the corresponding geological disaster scene, so that whether the early warning condition is met or not is judged.

Example 3:

the invention aims to fully utilize the existing data under the condition of limited fund, acquire geological monitoring data of the area as comprehensively as possible, and comprehensively monitor and early warn geological disasters of the area. While the above example 2 mainly addresses the lack of a type of geological monitoring data in a certain region with respect to portions of other surrounding regions, the following example 3 mainly addresses the lack of all data in a portion of disaster-prone points in a certain region.

As shown in fig. 11, the present invention provides a geological disaster geological monitoring data acquisition method (i.e., a method for executing step 20), which includes:

in step 201, determining a key position and a secondary key position of a geological disaster hidden danger point of a region A according to the analysis of the geographical position data of the region A; as shown in fig. 12, arranging geological disaster monitoring equipment at the critical locations and the secondary critical locations;

in step 202, according to the geological monitoring data of the key position, as shown in fig. 13, the geological monitoring data of the secondary key position is calculated through a prediction algorithm, so as to obtain the simulation data of the key position of the area a;

in step 203, the server compares the geological monitoring data of the secondary key position with the simulated data of the corresponding secondary key position respectively to obtain the conformity of the geological monitoring data and the simulated data;

in step 204, if the conformity reaches a conformity setting threshold, as shown in fig. 14, it is determined that the simulation data of the secondary key position in the area a is reliable, so as to cancel the monitoring device arranged at the secondary key position;

in step 205, if the conformity is lower than the conformity set threshold, it is determined that the inferred data has a certain uncertainty, and the position of the monitoring device is adjusted until the conformity reaches the conformity set threshold, it is determined that the inferred data of the key position of the area a is reliable, so as to cancel the monitoring device arranged in the key position of the area a.

In the embodiment of the present invention, the server compares the geological monitoring data of the secondary key position with the simulated data of the corresponding secondary key position, respectively, to obtain the conformity between the two, and specifically includes:

the server respectively compares each item of geological monitoring data in the geological monitoring data of the secondary key position with each item of geological monitoring data in the simulated data of the corresponding secondary key position one by one, and calculates the matching degree of each item of geological monitoring data in the geological monitoring data of the secondary key position and each item of geological monitoring data in the simulated data of the corresponding secondary key position; and in different geological disaster types, different weights are given to different geological monitoring data types, and the matching degree is subjected to weighted calculation to obtain the conformity between the geological monitoring data of the secondary key position and the simulated data of the corresponding secondary key position.

And obtaining data of the secondary key position by a geological disaster geological monitoring data acquisition method, and judging the probability of disaster occurrence by combining the simulation data of the secondary key position and the data of the key position.

With continued reference to fig. 12 to 14, it is assumed that the monitoring devices in the first associated group corresponding to the first-class geological disaster in the area a are set at nine points of the critical position and the second-critical position shown in fig. 12 according to the big data analysis, but in order to reduce the economic cost, only the monitoring devices in the critical position are left in the present embodiment, and the monitoring devices in the second-critical position are cancelled, as shown in fig. 14, where all the monitoring devices in the critical position are environment monitoring devices.

When the environment monitoring devices at the key positions are all in the off-line state, the type of the disaster is preliminarily judged to be a first type of geological disaster, further, the probability of the first type of geological disaster is analyzed, because the environment monitoring devices in the first association group are only arranged at the key positions and are not enough to judge whether the first type of geological disaster occurs, the actual environment geological monitoring data reported by the environment monitoring devices arranged at the key positions before the off-line state imitate the environment geological monitoring data at the secondary key positions, the matching degree between the environment geological monitoring data of nine points with the association relationship in the first association group and the environment geological monitoring data under the first type of geological disaster scene is analyzed, and if the matching degree exceeds a preset matching value, the first type of geological disaster early warning condition is met.

Example 4:

on the basis of the composite geological disaster professional monitoring and early warning methods provided in embodiments 1 to 3, the invention further provides a composite geological disaster professional monitoring and early warning device for implementing the methods, and as shown in fig. 17, the device architecture diagram of the embodiment of the invention is shown. The composite geological disaster professional monitoring and early warning device of the embodiment comprises one or more processors 21 and a memory 22. In fig. 17, one processor 21 is taken as an example.

The processor 21 and the memory 22 may be connected by a bus or other means, and the bus connection is exemplified in fig. 17.

The memory 22 is used as a nonvolatile computer readable storage medium for a composite geological disaster professional monitoring and early warning method, and can be used to store a nonvolatile software program and a nonvolatile computer executable program, such as the composite geological disaster professional monitoring and early warning method in embodiment 1. The processor 21 executes the composite geological disaster professional monitoring and early warning method by running the nonvolatile software program and instructions stored in the memory 22.

The memory 22 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 22 may optionally include memory located remotely from the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The program instructions/modules are stored in the memory 22, and when executed by the one or more processors 21, perform the composite geological disaster professional monitoring and early warning method in the above embodiments 1 to 3, for example, perform the steps shown in fig. 1, fig. 4 to 7, fig. 11, fig. 15, and fig. 16 described above.

Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the embodiments may be implemented by associated hardware as instructed by a program, which may be stored on a computer-readable storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims

1. A composite geological disaster professional monitoring and early warning method is characterized in that a server is connected with monitoring equipment, and the method comprises the following steps:

the geological monitoring data acquired by the server comprises compensation data and/or geological monitoring data acquired by monitoring equipment with an incidence relation;

2. The composite geological disaster professional monitoring and early warning method as claimed in claim 1, wherein the server pre-establishes the association relationship between the monitoring devices, specifically comprising:

3. The composite geological disaster professional monitoring and early warning method as claimed in claim 2, wherein the determining whether the early warning condition is met according to the acquired state data and/or geological monitoring data comprises:

4. The composite geological disaster professional monitoring and early warning method as claimed in claim 3, wherein when each monitoring device in the second association group is included in the first association group, the server matches geological monitoring data reported before the disconnection of a common monitoring device in the first association group with geological monitoring data in a corresponding geological disaster scene, and specifically comprises:

5. The composite geological disaster professional monitoring and early warning method as claimed in claim 2, wherein the method for judging whether the early warning condition is met according to the acquired state data and/or geological monitoring data further comprises:

6. The composite geological disaster professional monitoring and early warning method as claimed in claim 2, wherein when each monitoring device in the second association group is included in the first association group, the method determines whether the early warning condition is met according to the acquired state data and/or geological monitoring data, and specifically further comprises:

7. The composite geological disaster professional monitoring and early warning method as claimed in claim 2, wherein the method for judging whether the server receives the data reported by the professional monitoring devices corresponding to the first type of geological disaster, and when the status data of the monitoring devices in the first association group shows that at least one monitoring device is in an online status, further comprises:

8. The composite geological disaster professional monitoring and early warning method as claimed in claim 7, wherein the determining whether the server receives the data reported by the professional monitoring devices corresponding to the first type of geological disaster, and when the status data of the monitoring devices in the first association group shows that at least one monitoring device is in an online status, further comprises:

9. The composite geological disaster professional monitoring and early warning method as claimed in claim 1, wherein the compensation data acquisition method comprises:

10. A composite geological disaster professional monitoring and early warning device is characterized by comprising at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the program of instructions being configured to perform the composite geological disaster major surveillance and early warning method of any of claims 1-9.