A geological disaster monitoring and early warning information processing method and system

Abstract

The application discloses a geological disaster monitoring and early warning information processing method and system, which comprises the following steps: firstly, obtaining the accumulated deformation variable at a certain time A0; then, determining the displacement early warning level according to the accumulated deformation variable, and judging whether the threshold of the corresponding displacement early warning level is reached; if the threshold is reached, judging whether the corresponding early warning level has sent a short message; if the short message has been sent within a preset time period, no short message is sent, the accumulated deformation variable at the next time is obtained, and the next time is continuously judged; if the short message has not been sent within the preset time period, the early warning level is determined, and the short message is sent according to the highest early warning level; the geological disaster monitoring and early warning information processing method and system provided by the application sends short message signals respectively according to the accumulated deformation variable and the deformation rate monitoring, determines to send the geological disaster monitoring short message through the continuous change of the accumulated displacement within the preset time period, and avoids the phenomenon that a large number of short message signals cause the real useful effective information to be submerged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of disaster monitoring, in particular to a geological disaster monitoring and early warning information processing method and system. BACKGROUND

[0002] The purpose of geological disaster monitoring is to accurately and timely grasp the dynamic changes of geological disasters so as to take appropriate measures to reduce and prevent the loss caused by disasters. Geological disasters may include earthquakes, debris flows, landslides, collapses, ground subsidence, etc., which pose a serious threat to human life and property safety.

[0003] The core goal of geological disaster monitoring and early warning is to avoid the expansion of disaster, which can be monitored only after the specified area geological changes. In the field of geological disasters, in addition to landslides, there are many other types of disasters such as earthquakes, debris flows, collapses, ground subsidence, etc., which are also extremely destructive and dangerous.

[0004] Current water damage monitoring and early warning mostly rely on manual patrol and manual warning, resulting in inaccurate and timely monitoring and early warning. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a geological disaster monitoring and early warning information processing method and system, which uses classified and graded processing of monitoring information data to determine the sending of short messages, thereby improving the effectiveness of short message sending.

[0006] To achieve the above purpose, the present application provides the following technical scheme:

[0007] The geological disaster monitoring and early warning information processing method provided by the present application comprises the following steps:

[0008] S1: Obtain the cumulative deformation variable at time A0;

[0009] S2: Determine the displacement warning level according to the cumulative deformation variable, and judge whether the threshold of the corresponding displacement warning level is reached. If the threshold is reached, judge whether the corresponding warning level has sent a short message. If the short message has been sent within the preset time period, no short message will be sent, and the cumulative deformation variable at the next time will be obtained, and the next time will be judged. If the short message has not been sent within the preset time period, the warning level is determined and the highest warning level is taken to send a short message;

[0010] S3: If the threshold is not reached, no short message will be sent, and the cumulative deformation variable at the next time will be obtained, i.e. the time A0+1 will be continuously judged;

[0011] S4: When a short message occurs, the cumulative deformation variable at the next time is continuously obtained, and the monitoring process at the next time is entered.

[0012] Further, the method further comprises the following steps:

[0013] S21: determining the sub-level corresponding to the early warning level, judging whether to send a short message in the sub-level, if the corresponding sub-level has sent a short message, do not send a short message, continue to obtain the cumulative deformation variable at the next time; if the short message has not been sent, determine the early warning level and send the short message according to the highest early warning level.

[0014] Further, the sub-level is formed by dividing the corresponding early warning level into N early warning sub-levels; according to the importance of the early warning degree, it is divided into different sub-levels, including blue early warning, yellow early warning, orange early warning, and red early warning; according to the value of the cumulative deformation variable, it is divided into a, b, c, and d in turn; wherein, the number range (a, b) represents blue early warning; the number range (b, c) represents yellow early warning; the number range (c, d) represents orange early warning; and the number range (d above) represents red early warning.

[0015] Further, each sub-level can be further divided into Q quantiles, and the number of quantiles of each sub-level can be different, which is determined according to specific conditions.

[0016] The blue early warning area can be divided into Q quantiles, that is, divided into Q areas, and each area is (b-a) / Q, and the value of the nth quantile is a+n(b-a) / Q.

[0017] The yellow early warning area can be divided into Q quantiles, that is, divided into Q areas, and each area is (c-b) / Q, and the value of the nth quantile is b+n(c-b) / Q.

[0018] The orange early warning area can be divided into Q quantiles, that is, divided into Q areas, and each area is (d-c) / Q, and the value of the nth quantile is c+n(d-c) / Q.

[0019] The red early warning area can be divided into Q quantiles, that is, divided into Q areas, and each area is (d-c) / Q or 0.1d, and the value of the nth quantile is d+n(d-c) / Q or d+0.1d.

[0020] Further, the Q quantiles adopt 10 quantiles or 5 quantiles.

[0021] Further, the method further comprises the following steps:

[0022] S5: obtaining the deformation rate at a time A0;

[0023] S6: According to the deformation rate, the deformation rate warning level is determined, and whether the threshold of the corresponding deformation rate warning level is reached is judged, and the number A of times that the deformation rate reaches the threshold in a preset time range is determined; whether the number A of times that the rate continuously reaches the threshold is greater than the allowed number M is judged, and if it is greater than or equal to the allowed number, the warning level is determined and the short message is sent according to the highest warning level;

[0024] S7: If it is less than the allowed number, no short message is sent, and the cumulative deformation variable at the next time is obtained, that is, the A0+1 time is continuously judged.

[0025] S8: When the short message is sent, the cumulative deformation variable at the next time is continuously obtained, and the monitoring process at the next time is entered.

[0026] Further, the short message includes a device health state type short message; the device health state type short message is used to record device state information; the device state information is determined in the following way:

[0027] Obtain the detection information sent by the device;

[0028] According to the detection time period set by the device, it is judged whether the detection information sent by the device is complete, if not, it is judged that the device is in a offline state, and the device offline information is sent according to the set time until the detection information is complete; if yes, the detection information sent by the device is continuously obtained.

[0029] Further, the short message includes a device running state type short message;

[0030] The device running state type short message is used to obtain device time period statistical information, including all device warning state information according to weeks, months and seasons, and information in different states is obtained.

[0031] Further, the short message includes a single device monitoring and warning short message;

[0032] The single device monitoring and warning short message is used to send the detected abnormal information of each device in a time period in real time.

[0033] The present application provides a geological disaster monitoring and warning information processing system, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the program to realize the above method.

[0034] The present application has the following advantages:

[0035] This invention provides a method and system for processing geological disaster monitoring and early warning information. The method sends SMS signals for monitoring cumulative deformation and deformation rate, respectively. It determines the sending of geological disaster monitoring SMS signals by the continuous change of cumulative displacement within a preset time period, thus avoiding the phenomenon of overwhelming truly useful and effective information due to the generation of a large number of SMS signals.

[0036] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0037] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following drawings are provided for illustration.

[0038] Figure 1 Flowchart of the method for processing cumulative deformation monitoring and early warning information for geological disasters.

[0039] Figure 2 A schematic diagram illustrating the process of sending text messages to the tenth digit of the geological disaster monitoring and early warning sub-level.

[0040] Figure 3 A schematic diagram of the process of sending SMS messages at the quintile level of geological disaster monitoring and early warning.

[0041] Figure 4 This is a flowchart of the method for processing information on geological disaster deformation rate monitoring and early warning.

[0042] Figure 5 Example image for monitoring and early warning SMS sending. Detailed Implementation

[0043] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0044] Example 1

[0045] like Figure 1 As shown in the figure, the geological disaster monitoring and early warning information processing method and system provided in this embodiment includes the following steps:

[0046] S1: Obtain the cumulative deformation of A0 at a certain moment. The unit of cumulative deformation is millimeters (mm).

[0047] S2: determining the displacement warning level according to the accumulated deformation variable, judging whether the threshold of the corresponding displacement warning level is reached, if the threshold is reached, judging whether the corresponding warning level has sent a short message, if the short message has been sent within a preset time period, not sending a short message, obtaining the accumulated deformation variable at the next time, and continuing to judge the next time, if the short message has not been sent within the preset time period, determining the warning level and sending a short message according to the highest warning level; in the embodiment, the different warning levels are divided into N regions, and different thresholds are set for different regions;

[0048] The preset time in the embodiment is generally set to 0.5-1 hour; the threshold can be a multi-level fixed value, and the specific value can be taken according to the threshold value that the monitored object may damage in proportion. Assuming that the accumulated deformation variable of a monitored object near the damage is 1000 mm, taking the value as the maximum deformation variable Dmax, the threshold can be taken in proportion to Dmax, for example, 1%, 5%, 10%, 20%, etc.

[0049] S3: if the threshold is not reached, no short message is sent, and the accumulated deformation variable at the next time is continuously obtained, that is, the time A0+1 is continuously judged;

[0050] S4: after the short message is sent, the accumulated deformation variable at the next time is continuously obtained, and the monitoring process at the next time is entered;

[0051] In the embodiment, when the short message has been sent in step S2, the following steps are further included:

[0052] S21: determining the sub-level of the corresponding warning level, judging whether a short message is sent in the sub-level, if the corresponding sub-level has sent a short message, not sending a short message, and continuously obtaining the accumulated deformation variable at the next time; if the short message has not been sent, determining the warning level and sending a short message according to the highest warning level; the sub-level in the embodiment is formed by dividing the corresponding warning level into N warning sub-levels;

[0053] The sub-level in the embodiment can be set to three or four sub-levels, which are divided into different sub-levels according to the importance of the warning degree, including blue warning, yellow warning, orange warning and red warning; the accumulated deformation variable is divided into a, b, c and d in turn; wherein, the number range (a, b) represents blue warning; the number range (b, c) represents yellow warning; the number range (c, d) represents orange warning; the number range (d above) represents red warning; the importance of the degree is strengthened in turn, and red represents the largest displacement, large geological displacement and possible large disaster impact;

[0054] Each sub-level can be further divided into Q quantiles, and the number of quantiles in each sub-level can be different, which is determined according to the specific situation;

[0055] The blue warning area can be divided into Q quantiles, i.e., equally divided into Q areas, each area is (b-a) / Q, and the value of the nth quantile is a+n(b-a) / Q;

[0056] The yellow warning area can be divided into Q quantiles, i.e., equally divided into Q areas, each area is (c-b) / Q, and the value of the nth quantile is b+n(c-b) / Q;

[0057] The orange warning area can be divided into Q quantiles, i.e., equally divided into Q areas, each area is (d-c) / Q, and the value of the nth quantile is c+n(d-c) / Q;

[0058] The red warning area can be divided into Q quantiles, i.e., equally divided into Q areas, each area is (d-c) / Q or 0.1d, and the value of the nth quantile is d+n(d-c) / Q or d+0.1d;

[0059] The Q quantiles in this embodiment can be 10 quantiles or 5 quantiles, or can be determined according to actual conditions; the sub-levels of the blue warning, the yellow warning, the orange warning, and the red warning can also be divided into different numbers of quantiles.

[0060] As shown in FIG. 1, Figure 2 each sub-level can be further divided into 10 quantiles, the number of quantiles of each sub-level can be different, and is determined according to specific conditions; the blue warning area can be divided into 10 quantiles, i.e., equally divided into 10 areas, each area is (b-a) / 10, and the value of the nth quantile is a+n(b-a) / 10; the yellow warning area can be divided into 10 quantiles, i.e., equally divided into 10 areas, each area is (c-b) / 10, and the value of the nth quantile is b+n(c-b) / 10; the orange warning area can be divided into 10 quantiles, i.e., equally divided into 10 areas, each area is (d-c) / 10, and the value of the nth quantile is c+n(d-c) / 10; and the red warning area can be divided into 10 quantiles, i.e., equally divided into 10 areas, each area is (d-c) / 10 or 0.1d, and the value of the nth quantile is d+n(d-c) / 10 or d+0.1d;

[0061] As shown in FIG. 1, Figure 3As shown, each sub-level can be further divided into 5 sub-grades, the number of sub-grades of each sub-level can be different, and is determined according to specific conditions; the blue warning area can be divided into 5 sub-grades, i.e., equally divided into 5 areas, each area is (b-a) / 5, and the value of the nth sub-grade is a+n(b-a) / 5; the yellow warning area can be divided into 5 sub-grades, i.e., equally divided into 5 areas, each area is (c-b) / 5, and the value of the nth sub-grade is b+n(c-b) / 5; the orange warning area can be divided into 5 sub-grades, i.e., equally divided into 5 areas, each area is (d-c) / 5, and the value of the nth sub-grade is c+n(d-c) / 5; and the red warning area can be divided into 5 sub-grades, i.e., equally divided into 5 areas, each area is (d-c) / 5 or 0.1d, and the value of the nth sub-grade is d+n(d-c) / 5 or d+0.1d.

[0062] The sub-levels in this embodiment can be determined according to actual conditions, can be divided into 4 levels of 10 sub-grades, can be divided into 3 levels of 10 sub-grades, can be divided into 4 levels of 5 sub-grades, can be divided into 3 levels of 5 sub-grades, etc., and details are not repeated.

[0063] The sub-grade values and threshold intervals in this embodiment are determined according to the accuracy of sensor monitoring data, and the sub-grade scale value is greater than the sensor monitoring accuracy, otherwise the warning will be in disorder. The sub-grade value is related to the rate, and the rate can be directly used as the sub-grade value. The sub-grade value is obtained from the rate. Assuming that the monitoring accuracy of the Beidou monitoring device is 2 mm, then the deformation fluctuation within 2 mm is more likely to be caused by monitoring error fluctuation, if the deformation fluctuation exceeds 2 mm, then the possibility of data fluctuation caused by deformation increases, and if the fluctuation exceeds 2 times and more monitoring accuracy, the data credibility has the condition of sending a warning; if the fluctuation exceeds 3 times and more, a warning message can be sent. Assuming that the fluctuation exceeds 2 times to send a warning, then when the sub-level is divided, the data range of the sub-level exceeds 2 times the monitoring accuracy. For example, it is at least 4 mm, so that the division of the level is effective.

[0064] The monitoring signal for the accumulated deformation variable provided by the embodiment is sent, since the continuous change of the accumulated displacement can cause the generation of geological disasters, so the monitoring signal needs to be sent, but the accumulated displacement can also change, but after the change, it is stable, which can not represent the generation of geological disasters, at this time, the continuous sending of the monitoring signal can generate a large amount of garbage signal, thereby submerging the truly useful effective information, so when determining whether the accumulated deformation variable information needs to be sent, whether the displacement change is continuously performed in a certain time range needs to be considered, if the displacement change is continuously performed, it indicates that the accumulated deformation variable is increasing in this time range, and geological disasters can be caused, so the accumulated deformation variable monitoring signal needs to be sent for geological disaster warning; however, a proper displacement warning threshold needs to be set, if the threshold is too large, the monitoring signal of the possible geological disaster can be missed, if the threshold is too small, a large amount of monitoring signal can be caused, a large amount of garbage signal can be formed, and effective monitoring signal can be submerged; two parameters of the continuous monitoring time and the warning threshold need to be determined, so as to determine whether the monitoring signal needs to be sent;

[0065] The accumulated deformation variable in the embodiment is in the red warning interval, which indicates that the displacement change is large, and belongs to the serious geological disaster situation, so as long as the monitoring signal is monitored, the warning signal needs to be sent in time, that is, M is temporarily taken as 1, and M represents the allowed number of times; if the accumulated displacement is in the orange warning interval, M is temporarily taken as 2; if the accumulated displacement is in the yellow and below warning interval, M is temporarily taken as 3. In this way, the severity of the disaster can be warned in time, and the number of sent monitoring signals can be reduced;

[0066] The geological disaster monitoring and warning information processing method provided by the embodiment further includes the following steps:

[0067] S5: Obtain a deformation rate at a moment A0, and the unit of the deformation rate is mm / h or mm / d;

[0068] S6: Determine a deformation rate warning level according to the deformation rate, and determine whether a threshold of the corresponding deformation rate warning level is reached, to determine the number of times A that the deformation rate reaches the threshold in a preset time range; determine whether the number of times A that the rate continuously reaches the threshold is greater than an allowed number of times M, if greater than or equal to the allowed number of times, determine the warning level and send a message according to the highest warning level;

[0069] S7: If less than the allowed number of times, do not send a message, and continue to obtain the accumulated deformation variable at the next moment, that is, continue to judge the moment A0+1;

[0070] S8: When the message is sent, continue to obtain the accumulated deformation variable at the next moment, and enter the monitoring process of the next moment;

[0071] The determination criteria for sending short messages in this embodiment are as follows: first, whether the deformation rate reaches the threshold value; second, the warning level; and finally, the number A of times that the threshold value is reached in the x time interval range;

[0072] In this embodiment, the different warning levels are divided into N regions, and different thresholds are set for different regions.

[0073] To avoid accidental factors, the deformation rate exceeds the threshold value N times, and a short message is sent.

[0074] The warning sub-levels in this embodiment include rate sub-levels.

[0075] N is the step size, which is an integer of the sub-level, and can be infinite, 100 / 50 / 10 / 5 / 1, etc.

[0076] If N is a finite number, the accumulated data will also be warned after the step size N and the accumulated data decreases.

[0077] In this embodiment, the step size is the time of remembering the sent short message, N is infinite, and the memory is the strongest, indicating that only an increase will trigger a warning, and a decrease will not trigger a warning (a decrease will also trigger a warning), and the step size is greater than 1, indicating that after N steps, if the current cumulative displacement is not in the same sub-interval as the N steps, a warning will be issued.

[0078] In this embodiment, the cumulative displacement is pushed to the level and the allowed value M, and the current cumulative displacement is in the warning level, the relationship between the number A of times that the rate continuously reaches the threshold value and the allowed number M is determined, the highest level of the two warning levels is determined, and a short message is sent A0 times.

[0079] This embodiment provides two monitoring parameters for warning, which can be rate-based and cumulative displacement-based, or can be determined according to actual conditions.

[0080] The short messages sent in this embodiment include three types, namely device health status class short messages, device running status class short messages, and single device monitoring and warning;

[0081] The device health status class short message is used to record the device's own state information.

[0082] The device's own state information is determined in the following manner:

[0083] The detection information sent by the device is obtained.

[0084] According to the detection time period set by the device, it is judged whether the detection information sent by the device is complete. If not, it is judged that the device is in a offline state, and the device offline information is sent according to the set time until the detection information is complete; if yes, the detection information sent by the device is continuously acquired in a loop.

[0085] In this embodiment, as long as it is judged that a device is offline, a short message is sent every day; or a time threshold or a whitelist is set according to specific conditions to determine the sending mode of the detection information of the offline device.

[0086] In this embodiment, the detection of the health status of the device can be set to judge by counting the data amount of a past time period at a certain fixed time point every day. When it is judged that the device is in an offline state, a short message of offline is sent immediately, and if it is not solved, a short message is sent every day in the future; if there is no offline, it is sent regularly.

[0087] Meanwhile, the detection of the health status of the device can be classified and graded according to the importance of the monitored device, the importance of the monitored object, and the importance of the monitored index. The importance of the data sent by different devices is different, and the importance of the monitored index is determined according to the importance of the monitored object.

[0088] According to the setting of the detection device, the data amount of the information that should be sent is determined, and whether the device is in a healthy state is determined according to the received data amount.

[0089] Meanwhile, the completeness of each data is detected, and the byte amount of a single data is calculated, so as to determine whether the device is in a healthy state.

[0090] The state of the device is evaluated from the above multiple dimensions, which can be scored, and a short message of early warning of the state of the device is sent according to the score.

[0091] The device of this embodiment can be determined according to the importance, such as a device normally sending 48 data per day. If the received data accounts for 90% of the total data amount, it indicates that the state of the device is excellent; if 60-70%, it indicates that the state of the device is good.

[0092] In this embodiment, the device running state class short message can be counted in time periods, such as counting the early warning state information of all devices according to weeks, months, and seasons to obtain information in different states, such as the number of high-risk devices, the number of medium-risk devices, and the number of low-risk devices.

[0093] As shown in Figure 5 , the device running state class short message examples are as follows: Figure 5

[0094] Among them, the weekly short message example is as follows:

[0095] Dear [relevant personnel]:​

[0096] This week's equipment status statistics are as follows:

[0097] High-risk equipment: [X] sets. These devices have serious deviations from normal ranges in monitoring indicators such as importance, rate, cumulative displacement, etc., which may have a great impact on threatened objects and require immediate measures for inspection and repair.

[0098] Medium-risk equipment: [Y] sets. Some monitoring indicators of the equipment, such as [specific indicators], show a certain degree of abnormality, and are in a medium-risk state, suggesting that inspection and maintenance work should be arranged in the near future.

[0099] Low-risk equipment: [Z] sets. The overall operation is relatively stable, but still needs continuous attention.

[0100] Through classification and grading of equipment operation status, more targeted and differentiated thresholds are set, enabling more accurate judgment of equipment risk status.

[0101] For example, the monthly short message is as follows:

[0102] Dear [relevant personnel]:

[0103] This month's equipment operation status report:

[0104] For example, high-risk equipment is as follows:

[0105] Number: [A] sets. These devices are judged to be high-risk based on the importance of threatened objects and the comprehensive evaluation of monitoring indicators such as importance, rate, cumulative displacement, etc. For example, [list specific circumstances of certain high-risk equipment, such as a certain key production link device with abnormally high rate and cumulative displacement exceeding the safe range, causing serious threat to important production tasks].

[0106] For example, medium-risk equipment is as follows:

[0107] Number: [B] sets. Some of these devices are in a medium-risk state due to fluctuations in certain important monitoring indicators, such as [specific indicator fluctuation conditions]. Maintenance and adjustment should be performed in a timely manner according to production arrangements.

[0108] For example, low-risk equipment is as follows:

[0109] Number: [C] sets. Although the overall risk is low, we are still continuously monitoring to ensure the long-term stable operation of the equipment.

[0110] Through this classification and grading method, we accurately judge the risk of equipment based on different thresholds, providing more effective decision-making basis for equipment management.

[0111] For example, the quarterly short message is as follows:

[0112] Dear [relevant personnel],

[0113] This quarter's equipment running status summary:

[0114] High-risk equipment: [M] sets. After a quarter of monitoring, these devices show high-risk characteristics in terms of the importance of threatened objects and the assessment of important monitoring indicators (importance, rate, cumulative displacement, etc.). For example, [give examples of high-risk equipment, such as the cumulative displacement of some core equipment continues to increase, the rate is unstable, and it seriously affects the stable operation of the entire system].

[0115] Medium-risk equipment: [N] sets. These devices have some intermittent indicator abnormalities, which may be related to device aging or external environmental factors. For example [specifically explain the problems of medium-risk equipment], regular attention and corresponding maintenance plans need to be developed.

[0116] Low-risk equipment: [P] sets. Although in a low-risk state, we still conduct regular monitoring according to the set targeted threshold to ensure the reliability of equipment operation.

[0117] This classification and grading of equipment risk assessment helps to more targeted management and maintenance of equipment, ensuring the smooth progress of production or operation.

[0118] In this embodiment, the monitoring and early warning of individual equipment can be achieved by sending real-time SMS.

[0119] Assuming that the data is checked every hour, then it is determined whether to send an SMS. If there is an anomaly, an SMS is sent immediately.

[0120] If multiple sets of equipment simultaneously reach the threshold, the SMS is sent in combination.

[0121] As shown in Figure 5 , the following explains the SMS sending example according to the specific address disaster detection system, and XX is used instead of the system detection site name in the embodiment:

[0122]

Pumped storage disaster equipment status

[0123]

Pumped storage disaster equipment status

[0124] Sending frequency: once any device is offline, send every day; all online, send every Monday at 9 am.

[0125]

Pumped storage disaster monitoring weekly report

[0126] Sending frequency: every Monday at 9 am.

[0127]

Pumped storage disaster monitoring and warning

[0128]

Pumped storage disaster warning

[0129]

Pumped storage disaster warning

[0130]

Pumped storage disaster warning

[0131]

Pumped storage disaster monitoring weekly report

[0132]

XX pumped storage disaster monitoring deformation results

[0133] The above-described embodiments are merely preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Any equivalent substitutions or transformations made by those skilled in the art based on the present application are within the protection scope of the present application. The protection scope of the present application is subject to the claims.

Claims

1. A method for processing geological disaster monitoring and early warning information, characterized in that: Includes the following steps: The geological disaster monitoring and early warning information processing method provided by this invention includes the following steps: S1: Obtain the cumulative deformation of A0 at a certain moment; S2: Determine the displacement warning level based on the cumulative deformation and determine whether the threshold of the corresponding displacement warning level has been reached. If the threshold has been reached, determine whether the corresponding warning level has been sent via SMS. If SMS has been sent within the preset time period, do not send SMS, obtain the cumulative deformation at the next moment, and continue to determine the next moment. If SMS has not been sent within the preset time period, determine the warning level and send SMS based on the highest warning level. S3: If the threshold is not reached, no text message is sent, and the cumulative deformation of the next time step is obtained, that is, the judgment of time step A0+1 is continued; S4: After an SMS message is sent, continue to acquire the cumulative deformation of the next moment and enter the monitoring process to determine the next moment; It also includes the following steps: S5: Obtain the deformation rate of A0 at a certain moment; S6: Determine the deformation rate warning level based on the deformation rate, and determine whether the threshold of the corresponding deformation rate warning level has been reached. Determine the number of times A the deformation rate reaches the threshold within the preset time range; determine whether the number of times A the rate continuously reaches the threshold is greater than the allowed number M. If it is greater than or equal to the allowed number, determine the warning level and send an SMS according to the highest warning level. S7: If the number of attempts is less than the allowed number, do not send a text message, and continue to obtain the cumulative deformation of the next time step, that is, continue to judge the time step A0+1; S8: After an SMS message is sent, continue to acquire the cumulative deformation of the next moment and enter the monitoring process to determine the next moment.

2. The geological disaster monitoring and early warning information processing method as described in claim 1, characterized in that: It also includes the following steps: S21: Determine the sub-level of the corresponding warning level, and determine whether to send a text message within that sub-level. If a text message has already been sent to the corresponding sub-level, do not send a text message and continue to obtain the cumulative deformation of the next moment. If no text message is sent, determine the alert level and send a text message based on the highest alert level.

3. The geological disaster monitoring and early warning information processing method as described in claim 2, characterized in that: The sub-levels are formed by dividing the corresponding warning level into N warning sub-levels; they are divided into different sub-levels according to the importance of the warning degree, including blue warning, yellow warning, orange warning, and red warning; and they are divided into a, b, c, and d according to the value of the cumulative deformation. Among them, the numerical range (a, b) represents blue warning; the numerical range (b, c) represents yellow warning; the numerical range (c, d) represents orange warning; and the numerical range (d and above) represents red warning.

4. The geological disaster monitoring and early warning information processing method as described in claim 3, characterized in that: Each sub-level can be further divided into Q quantiles, and the number of quantiles for each sub-level is different and is determined according to the specific circumstances. The blue warning area can be divided into Q quantiles, that is, it is divided into Q equal regions, each region is (ba) / Q, and the value of the nth quantile is a+n(ba) / Q; The yellow warning area can be divided into Q quantiles, that is, it is divided into Q equal regions, each region is (cb) / Q, and the value of the nth quantile is b+n(cb) / Q; The orange alert area can be divided into Q quantiles, that is, it is divided into Q equal regions, each region is (dc) / Q, and the value of the nth quantile is c+n(dc) / Q; The red alert area can be divided into Q quantiles, that is, divided into Q equal regions, each region being (dc) / Q or 0.1d, and the value of the nth quantile is d+n(dc) / Q or d+0.1d.

5. The geological disaster monitoring and early warning information processing method as described in claim 4, characterized in that: The Q quantile is either a 10-quartile or a 5-quartile.

6. The geological disaster monitoring and early warning information processing method according to any one of claims 1 to 5, characterized in that: The text messages include device health status messages; these messages record the device's own status information; the device's own status information is determined in the following way: Obtain the detection information sent by the device; The system determines whether the detection information sent by the device is complete based on the detection time period set by the device. If not, it determines that the device is offline and sends device offline information according to the set time until the detection information is complete. If yes, it continues to obtain the detection information sent by the device in a loop.

7. The geological disaster monitoring and early warning information processing method as described in claim 1, characterized in that: The text messages include those related to device operating status. The device operation status SMS messages are used to obtain statistical information about the devices in different time periods, including weekly, monthly, and quarterly statistics of the warning status information of all devices, to obtain information on the different statuses.

8. The geological disaster monitoring and early warning information processing method as described in claim 1, characterized in that: The text messages include monitoring and early warning messages for individual devices; The monitoring and early warning SMS messages for individual devices are used to send abnormal information detected by each device in real time at different time periods.

9. A geological disaster monitoring and early warning information processing system, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1 to 8.

Images