A kind of early warning method and device

Abstract

The present invention relates to the field of geological monitoring technology, and in particular to an early warning method and device. The method comprises: preprocessing an acquired original displacement data sequence to obtain a displacement data sequence, the original displacement data sequence comprising a plurality of original displacement data of target objects associated with respective monitoring times, dividing each displacement data in the displacement data sequence into a corresponding deformation stage, determining a first tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a previous deformation stage adjacent to the target deformation stage, the target deformation stage being a deformation stage to which the displacement data associated with the current monitoring time belongs, determining a second tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a deformation stage to which the previous monitoring time adjacent to the current monitoring time belongs, determining a target tangent angle according to the first tangent angle and / or the second tangent angle, and determining early warning information according to the target tangent angle.

Description

Technical Field

[0001] The present invention relates to the field of geological monitoring technology and geotechnical engineering monitoring technology, and in particular to an early warning method, an early warning device, an electronic device, a computer storage medium and a computer program product. Background Art

[0002] A geological disaster refers to a geological action or phenomenon caused by natural or man-made factors that causes loss of human life and property and damage to the environment.

[0003] Landslide is a major geological disaster. Existing technologies monitor slopes by sensing the dynamic changes of parameters and indicators that reflect landslide stability, and issue early warnings by comparing critical values ​​with monitoring data. This method relies heavily on engineering experience and has low real-time performance, and is subject to defects such as false alarms and missed alarms.

[0004] Therefore, an accurate and efficient early warning method for landslide disasters is urgently needed. Summary of the invention

[0005] The present application provides an early warning method, an early warning device, an electronic device, a computer storage medium, and a computer program product.

[0006] In a first aspect, the present application relates to an early warning method, comprising: preprocessing an acquired original displacement data sequence to obtain a displacement data sequence; wherein the original displacement data sequence includes original displacement data of a plurality of target objects associated with respective monitoring times; dividing each displacement data in the displacement data sequence into a corresponding deformation stage; determining a first tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a previous deformation stage adjacent to the target deformation stage; the target deformation stage is a deformation stage to which the displacement data associated with the current monitoring time belongs; determining a second tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a deformation stage to which a previous monitoring time adjacent to the current monitoring time belongs; determining a target tangent angle according to the first tangent angle and / or the second tangent angle; and determining early warning information according to the target tangent angle.

[0007] In a possible example, the early warning method also includes: when the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage, no early warning information is reported; and / or when the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the deformation stage belonging to the previous monitoring time adjacent to the current monitoring time, no early warning information is reported.

[0008] In a possible example, preprocessing the acquired original displacement data sequence to obtain the displacement data sequence includes: fitting the original displacement data sequence to obtain the correlation between the displacement and the monitoring time; estimating the original displacement data according to the correlation to obtain a displacement data sequence including multiple displacement data.

[0009] In a possible example, fitting processing is performed on the original displacement data sequence to obtain the correlation relationship between the displacement and the monitoring time, including: sampling the original displacement data sequence with s different numbers of samples to obtain s candidate displacement data sequences; fitting processing is performed on each candidate displacement data sequence to obtain s candidate correlation relationships; and determining the correlation relationship based on the evaluation parameters of each candidate correlation relationship.

[0010] In a possible example, the evaluation parameters include a fitting error parameter and / or the number of samples involved in the fitting process at each deformation stage.

[0011] In a possible example, before performing fitting processing on the original displacement data sequence, the method further includes: performing data noise reduction processing on the original displacement data sequence.

[0012] In a possible example, dividing each displacement data in the displacement data sequence into a corresponding deformation stage includes: dividing each displacement data in the displacement data sequence into a corresponding deformation stage through ordered clustering processing.

[0013] In a possible example, determining warning information according to the target tangent angle includes: determining warning information according to the target tangent angle and a tangent angle range threshold, the warning information including a warning level, and each tangent angle range threshold maps a warning level.

[0014] In a possible example, the displacement rate corresponding to the deformation stage is determined according to the ratio of the displacement data difference of the deformation stage and the monitoring time difference; or, the displacement rate corresponding to the deformation stage is determined according to the average value of the derivative of the correlation relationship corresponding to the deformation stage.

[0015] In a possible example, the number of deformation stages and / or parameters of the fitting process are obtained by pre-configuration.

[0016] In a second aspect, the present application relates to an early warning device, comprising: a first module, used to preprocess the acquired original displacement data sequence to obtain a displacement data sequence; wherein the original displacement data sequence includes multiple original displacement data of target objects associated with their respective monitoring times; a second module, used to divide each displacement data in the displacement data sequence into a corresponding deformation stage; a third module, used to determine a first tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a previous deformation stage adjacent to the target deformation stage; the target deformation stage is the deformation stage to which the displacement data associated with the current monitoring time belongs; a fourth module, used to determine a second tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a deformation stage to which a previous monitoring time adjacent to the current monitoring time belongs; a fifth module, used to determine a target tangent angle according to the first tangent angle and / or the second tangent angle; a sixth module, used to determine early warning information according to the target tangent angle.

[0017] In a third aspect, the present application relates to an electronic device, comprising: a processor and an interface circuit, the interface circuit being used to receive signals from devices other than the electronic device and transmit them to the processor or to send signals from the processor to devices other than the electronic device, the processor being used to implement the above-mentioned early warning method through logic circuits or execution code instructions.

[0018] In a fourth aspect, the present application relates to a computer storage medium having a computer program stored thereon, which, when the computer instructions are executed, causes a processor to execute the above-mentioned early warning method.

[0019] In a fifth aspect, the present application relates to a computer program product, including a computer program, which implements the above-mentioned early warning method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 Schematic diagram of the displacement-time curve for slope monitoring divided into different deformation stages;

[0022] Figure 2 A schematic diagram showing an exemplary system architecture to which the early warning method according to an embodiment of the present application can be applied;

[0023] Figure 3 A flowchart of an early warning method according to an embodiment of the present disclosure is schematically shown;

[0024] Figure 4A Schematically shows an original displacement data sequence U t Schematic diagram of

[0025] Figure 4B Schematic diagram of candidate association relationship R1 after fitting processing of candidate displacement data sequence P1 with 40 samples;

[0026] Figure 4C Schematic diagram of candidate association relationship R2 after fitting processing of candidate displacement data sequence P2 with 60 samples;

[0027] Figure 4D Schematic diagram of candidate association relationship R3 after fitting processing of candidate displacement data sequence P3 with 80 samples;

[0028] Figure 5 A flowchart of an early warning method according to another embodiment of the present disclosure is schematically shown;

[0029] Figure 6 A schematic block diagram of an early warning device 600 according to an embodiment of the present disclosure is schematically shown;

[0030] Figure 7 A schematic block diagram of an electronic device 700 that can be used to implement the early warning method of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0032] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0033] The terms "first" and "second" in the description and claims of the embodiments of the present application are used to distinguish different objects rather than to describe a specific order of objects. For example, a first target object and a second target object are used to distinguish different target objects rather than to describe a specific order of target objects.

[0034] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0035] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0036] The following describes in detail the relevant technical terms and background of the early warning method in the embodiment of the present application.

[0037] A geological disaster refers to a geological action or phenomenon caused by natural or human factors that causes loss of human life and property and damage to the environment. Landslide is a major geological disaster.

[0038] In one implementation, slope monitoring is performed by sensing the dynamic changes of parameters and indicators reflecting the stability of the landslide, and early warning is issued by comparing the critical value with the monitoring data. The monitoring indicators may include: surface displacement and internal displacement, groundwater level, rainfall, internal force of the support structure, etc. Among them, surface displacement and internal displacement are the most commonly used monitoring indicators, and the monitoring instruments mainly include total stations, crack meters, Global Navigation Satellite System (Global Navigation Satellite System) receivers, Synthetic Aperture Radar (Interferometric Synthetic Aperture Radar, InSAR), borehole inclinometers, multi-point displacement meters, inclinometers, optical fibers, etc. This method relies more on engineering experience and has low real-time performance, and has defects such as false alarms and missed alarms.

[0039] In another implementation, a "process warning" method is adopted to improve the accuracy of landslide warning by judging the deformation stage of the landslide (the deformation stage here can be understood as a deformation stage).

[0040] Figure 1 The schematic diagram shows that the displacement time curve of slope monitoring is divided into different deformation stages.

[0041] like Figure 1 As shown, the displacement-time curve L of slope monitoring is divided into five stages from deformation stage 1 to deformation stage 5, which can also be understood as four stages: initial deformation, constant speed deformation, initial acceleration, uniform acceleration, and impending sliding.

[0042] The corresponding warning level for the deformation stage of isokinetic deformation is relatively low. In this stage, the rear edge, both sides and front edge gaps of the surface cracks (spaces) are formed in stages and in an orderly manner. The tangent angle is about 45°, the stability coefficient (strength) is between 1-1.05, and the acceleration oscillates within a certain amplitude range.

[0043] The corresponding warning level of the initial acceleration deformation stage is higher than that of the initial deformation stage. In this stage, the surface cracks gradually match, connect, and finally close. The tangent angle is in the range of 45°-80°, the stability coefficient (strength) is between 0.95-1.0, and the acceleration oscillates within a certain amplitude range.

[0044] The corresponding warning level of the uniform acceleration deformation stage is higher than that of the initial acceleration stage. In this stage, the surface cracks gradually match, connect, and finally close. The tangent angle is in the range of 80°-85°, the stability coefficient (strength) is between 0.95-1.0, and the acceleration oscillates within a certain amplitude range.

[0045] During the deformation stage of impending slip, the corresponding warning level is higher than that during the uniform acceleration stage. During this stage, the cracks on the trailing edge open sharply, bulges and small collapses occur on the leading edge, the tangent angle is greater than or equal to 85°, the stability coefficient is less than 0.95, and the acceleration increases suddenly.

[0046] The above-mentioned initial acceleration stage and uniform acceleration stage can also be combined into one acceleration stage.

[0047] The following formula (1) shows an example of how to calculate the tangent angle:

[0048] (1)

[0049] Among them, S(i) represents the cumulative displacement of the slope within a certain unit time period (such as one day, one week, etc.); vi is the rate at time i; and v0 is the displacement rate in the constant-speed deformation stage.

[0050] It should be noted that the calculation of the tangent angle is based on the rate of the constant-speed deformation stage, that is, only when the constant-speed deformation stage is identified and judged can the current tangent angle of the slope deformation be accurately calculated, and then the warning level of the slope can be determined. However, there is a lack of basis for dividing the deformation stage, and the division of the deformation stage is not uniform, so the warning accuracy is also low.

[0051] Figure 2 A schematic diagram of an exemplary system architecture to which the early warning method according to an embodiment of the present application can be applied is shown, that is, a schematic diagram of an exemplary system to which the early warning method according to an embodiment of the present application can be applied.

[0052] like Figure 2 As shown, an exemplary system architecture to which the early warning method of the embodiment of the present application can be applied may include: a first device 201 , a communication link 203 , and a second device 202 .

[0053] The first device 201 may be a device for monitoring the displacement of a target object. The first device 201 may obtain an original displacement data sequence by monitoring the displacement of the target object.

[0054] The first device 201 may be the above-mentioned total station, crack meter, Global Navigation Satellite System (GNSS) receiver, Synthetic Aperture Radar (InSAR), borehole inclinometer, multi-point displacement meter, inclinometer, optical fiber, etc.

[0055] The first device 201 and the second device 202 may communicate with each other via a communication link 203 , for example. The communication link 203 may be a wireless communication link.

[0056] The second device 202 may be, for example, a device for implementing the early warning method of the embodiment of the present disclosure.

[0057] The second device 202 may be, for example, a server. In the case where the second device 202 is a server, the warning information determined by the second device 202 may be sent to the terminal device. In this case, the system architecture of the embodiment of the present disclosure may further include the terminal device.

[0058] The second device 202 may also be a terminal device.

[0059] It should be noted that the number of the first device 201, the second device 202 and the communication link 203 in the above embodiment can be determined according to actual needs and is not limited here.

[0060] Figure 3 The flowchart of the early warning method according to the embodiment of the present disclosure is schematically shown.

[0061] like Figure 3 As shown, the early warning method according to the embodiment of the present application may include operations S310 to S360.

[0062] In operation S310, the acquired original displacement data sequence is preprocessed to obtain a displacement data sequence.

[0063] The original displacement data sequence includes a plurality of original displacement data of the target objects associated with respective monitoring times.

[0064] The following will take landslide warning as an example to illustrate that the original displacement data of the target object can be, for example, Figure 2 The unprocessed surface displacement or internal displacement collected by the first device.

[0065] The original displacement data sequence Ut includes y1 to y Q Take Q original displacement data as an example, that is ,y i Represents the original displacement data associated with a certain monitoring time. i represents the order of the original displacement data and takes a value from 1 to Q, where Q is an integer greater than or equal to 2. For example, the initial displacement data obtained by displacement monitoring for x monitoring periods such as x days or x hours, the order of the original displacement data represented by i corresponds to the monitoring time, for example, y i It can also represent the original displacement data of the i*xth monitoring time unit, where x is a number greater than 0.

[0066] Original displacement data sequence U t The number of displacement data included in the displacement data sequence obtained after preprocessing may be less than or equal to Q.

[0067] In operation S320, each displacement data in the displacement data sequence is divided into a corresponding deformation stage.

[0068] Combination Figure 1 For example, Figure 1 Each deformation stage from deformation stage 1 to deformation stage 5 in the figure has its own characteristics of geographical conditions, tangent angles, stability coefficients, and accelerations. Therefore, each displacement data can be divided into the corresponding deformation stage based on the characteristics of each deformation stage.

[0069] In operation S330, a first tangent angle is determined according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a previous deformation stage adjacent to the target deformation stage.

[0070] The target deformation stage is the deformation stage to which the displacement data associated with the current monitoring time belongs.

[0071] It should be noted that the current monitoring time here can be the latest monitoring time in the displacement data sequence to achieve early warning at the latest moment. For example, the last displacement data y in the displacement data sequence in the above embodiment Q The corresponding monitoring time is the current monitoring time t. Figure 1 As shown, the displacement data y associated with the current monitoring time t Q The corresponding deformation stage, that is, the target deformation stage, is deformation stage 5 (imminent slip). The previous deformation stage adjacent to the target deformation stage is deformation stage 4 (uniform acceleration).

[0072] Exemplarily, the displacement rate corresponding to any deformation stage may be determined according to the ratio of the displacement data difference and the monitoring time difference of the deformation stage. That is, the displacement rate corresponding to any deformation stage may be the average displacement rate corresponding to the deformation stage.

[0073] Except for other explanations, the above example is still used below. The displacement rate corresponding to the target deformation stage is, for example, v 5，t represents the displacement rate of the target deformation stage (the target deformation stage is the deformation stage 5 mentioned above) corresponding to the current monitoring time t. The displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage (that is, the deformation stage 4 mentioned above) is, for example, v 4，t .

[0074] Exemplarily, for example, the inverse tangent value of the ratio of the displacement rate corresponding to the target deformation stage to the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage may be determined as the first tangent angle.

[0075] The early warning method of the embodiment of the present disclosure is used to determine the early warning information at the current monitoring time based on the displacement data of the target object at the current monitoring time, thereby improving the accuracy of the early warning and reducing the safety threat of the landslide.

[0076] In the early warning method of the embodiment of the present disclosure, the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage can both reflect the displacement trend of the target object at the current monitoring time from the dimension of the deformation stage, so that the first tangent angle determined thereby has higher accuracy for early warning.

[0077] In operation S340, a second tangent angle is determined according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a deformation stage to which a previous monitoring time adjacent to the current monitoring time belongs.

[0078] Exemplarily, for example, the inverse tangent value of the ratio of the displacement rate corresponding to the target deformation stage to the displacement rate corresponding to the deformation stage belonging to the previous monitoring time adjacent to the current monitoring time can be determined as the second tangent angle.

[0079] Combination Figure 1 And using the above example, the displacement rate corresponding to the target deformation stage is, for example, v 5，t , when the deformation stage to which the previous monitoring time t-1 adjacent to the current monitoring time t belongs is deformation stage 5, the displacement rate corresponding to deformation stage 5 is, for example, v5,t-1.

[0080] Similar to operation S330, in the early warning method of the embodiment of the present disclosure, the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the deformation stage belonging to the previous monitoring time adjacent to the current monitoring time can both reflect the displacement trend of the target object at the current monitoring time from the dimension of monitoring time, so that the second tangent angle determined thereby has higher accuracy for early warning.

[0081] In operation S350, a target tangent angle is determined according to the first tangent angle and / or the second tangent angle.

[0082] Exemplarily, a larger value of the first tangent angle and the second tangent angle may be determined as the target tangent angle.

[0083] Exemplarily, the first tangent angle may be determined as the target tangent angle, or the second tangent angle may be determined as the target tangent angle.

[0084] In operation S360, warning information is determined according to the target tangent angle.

[0085] In the early warning method of the embodiment of the present invention, the first tangent angle is determined based on the deformation stage dimension, and the second tangent angle is determined based on the monitoring time dimension. Therefore, the target tangent angle determined according to the first tangent angle and the second tangent angle can take into account both the deformation stage dimension and the monitoring time dimension. The target tangent angle determined in this way is used for early warning, which can improve the accuracy of the early warning and reduce the safety threat of the landslide.

[0086] According to another embodiment of the early warning method of the present disclosure, the early warning method may further include: when the displacement rate corresponding to the target deformation stage is smaller than the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage, no early warning information is reported; and / or when the displacement rate corresponding to the target deformation stage is smaller than the displacement rate corresponding to the deformation stage belonging to the previous monitoring time adjacent to the current monitoring time, no early warning information is reported.

[0087] like Figure 1 The time displacement curve shown is a schematic diagram of the trend of landslide occurrence. According to the schematic diagram, it can be determined that in the case of landslide, the displacement rate of each deformation stage and the displacement rate based on the monitoring time are increasing in sequence. If a landslide occurs, the corresponding displacement data sequence should be consistent with Figure 1 The trend shown.

[0088] Similar to the above embodiment, when the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage, it can be considered that based on the deformation stage dimension, the displacement rate at the current monitoring time has a slowing trend and the security threat is low. Therefore, no warning information may be reported, that is, no warning is issued.

[0089] Similarly, when the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the deformation stage of the previous monitoring time adjacent to the current monitoring time, it can be considered that based on the monitoring time dimension, the displacement rate of the current monitoring time has a slowing trend and the security threat is low. Therefore, no warning information may be reported, that is, no warning is issued.

[0090] According to the early warning method of another embodiment of the present disclosure, for example, the following embodiments can be used to implement preprocessing of the acquired original displacement data sequence to obtain a specific example of the displacement data sequence: fitting the original displacement data sequence to obtain the correlation between the displacement and the monitoring time; estimating the original displacement data according to the correlation to obtain a displacement data sequence including multiple displacement data.

[0091] Since the original displacement data sequence U t Including multiple original displacement data, these original displacement data corresponding to the monitoring time can reflect the displacement change trend (the displacement change trend here can also be understood as the deformation trend). Therefore, the early warning method of the embodiment of the present disclosure can fit the preprocessing method of fitting processing to obtain, for example, Figure 1 The correlation between displacement and monitoring time shown in the figure can accurately characterize the displacement change trend. The displacement data sequence obtained by estimating the original displacement data based on the correlation is more accurate for early warning. Specifically, from the long-term monitoring data of the displacement and time curve, the change trend of the curve can be clearly observed. However, if the monitoring time is shortened to a certain local time period, it can be found that it is actually a fluctuating curve, which occurs under the combined effect of slope movement and equipment monitoring accuracy. Due to the change characteristics of the curve of monitoring time and displacement, the use of original displacement data for early warning is prone to false alarms. Therefore, the early warning method of the embodiment of the present disclosure can reduce this influence by pre-processing the original displacement data sequence through fitting processing.

[0092] According to another embodiment of the early warning method of the present disclosure, before performing fitting processing on the original displacement data sequence, the method may further include: performing data noise reduction processing on the original displacement data sequence.

[0093] Data noise reduction processing may include, for example, outlier removal processing.

[0094] It should be noted that the displacement rate corresponding to the deformation stage may also be determined by an average value derived from the correlation relationship corresponding to the deformation stage.

[0095] According to another embodiment of the early warning method of the present disclosure, for example, the following embodiments can be used to implement fitting processing on the original displacement data sequence to obtain a specific embodiment of the correlation relationship between the displacement and the monitoring time: sampling the original displacement data sequence with s different numbers of samples to obtain s candidate displacement data sequences; fitting processing is performed on each candidate displacement data sequence to obtain N candidate correlation relationships; and the correlation relationship is determined based on the evaluation parameters of each candidate correlation relationship.

[0096] Taking the U in the above example t In the above example, starting from time t, we can obtain s candidate displacement data sequences based on s different sample numbers, which are P1, P2, ..., P s-1 , P s .

[0097] Assume that the candidate displacement data sequence P s There are q displacement monitoring data in total. For example, the candidate displacement data sequence P can be s Perform polynomial fitting, the degree of the polynomial is k, and get the fitting formula The fitting formula obtained here is also the candidate displacement data sequence P s The candidate association relationship Rs is based on the candidate displacement data sequence P s The fitting value of the candidate displacement data calculated by the corresponding candidate association relationship is .

[0098] The polynomial degree k here can be understood as a parameter of a fitting process. For example, the parameters of the fitting process, the number of deformation stages, etc. can be pre-configured.

[0099] Exemplarily, the evaluation parameters of the candidate association relationship may include a fitting error parameter.

[0100] The fitting error parameter can be the mean of the residual sum of squares. The following formula (2) shows the mean of the residual sum of squares: The calculation method of .

[0101] (2)

[0102] For example, the candidate association relationship with the smallest residual square sum mean value may be selected as the association relationship from N candidate association relationships.

[0103] Exemplarily, the evaluation parameters of the candidate association relationship may also include: the number of samples involved in the fitting process in each deformation stage.

[0104] It is understandable that in order to fit an accurate correlation relationship, a certain number of samples are required. For example, two samples can only fit a linear relationship. Therefore, the evaluation parameters can also include the number of samples involved in the fitting process at each deformation stage. For example, the number of samples involved in the fitting process at each deformation stage is greater than 2.

[0105] Figure 4A Schematically shows an original displacement data sequence U t Schematic diagram of .

[0106] like Figure 4A As shown, the original displacement data sequence U t For example, including y1-y 150 A total of 150 original displacement data, then connecting each original displacement data can be obtained Figure 4A curve.

[0107] The following will take s=3 and three different sample numbers of 40, 60, and 80 as examples for explanation.

[0108] Figure 4B Schematic diagram of the candidate association relationship R1 after fitting the candidate displacement data sequence P1 with 40 samples.

[0109] Figure 4C Schematic diagram of the candidate association relationship R2 after fitting the candidate displacement data sequence P2 with 60 samples.

[0110] Figure 4D Schematic diagram of the candidate association relationship R3 after fitting the candidate displacement data sequence P3 with 80 samples.

[0111] The candidate displacement data sequence P1 with 40 samples may include, for example, y 111 -y 150 The candidate displacement data sequence P2 with 60 samples may include, for example, y 91 -y 150 The candidate displacement data sequence P3 with 80 samples may include, for example, y 71 -y 150 .

[0112] After evaluating the candidate association relationships R1, the candidate association relationship R2, and the candidate association relationship R3 according to the evaluation parameters of the candidate association relationships, for example, the candidate association relationship R1 is determined to be an association relationship.

[0113] According to the early warning method of the embodiment of the present disclosure, the original displacement data sequence is a plurality of collected unprocessed original displacement data, and the fitting process is used to establish the relationship between variables based on the plurality of data. In some cases, a certain part of the original displacement data is used to fit the displacement trend more accurately and better. Therefore, in the early warning method of the embodiment of the present disclosure, in order to accurately characterize the accurate correlation between the monitoring time and the displacement, s candidate displacement data sequences are obtained by sampling s different numbers of samples, and each candidate displacement data sequence is fitted to obtain s candidate correlation relationships. Each candidate correlation relationship can be evaluated by evaluation parameters, and a correlation relationship with better fitting effect can be selected from the s candidate correlation relationships. The subsequent displacement data determined based on the correlation relationship will also be more accurate for early warning.

[0114] According to another embodiment of the early warning method of the present disclosure, for example, the following embodiment can be used to implement a specific example of dividing each displacement data in the displacement data sequence into a corresponding deformation stage: each displacement data in the displacement data sequence is divided into a corresponding deformation stage through ordered clustering processing.

[0115] Ordered clustering can be understood as a clustering analysis method. In the early warning method of the embodiment of the present disclosure, the multiple displacement data included in the displacement data sequence have a sequential relationship based on the monitoring time. Through ordered clustering, f division points can be determined, and the multiple displacement data in the displacement data sequence can be classified into (f+1) deformation stages.

[0116] Of course, the early warning method of the embodiment of the present disclosure can also realize the automatic classification deformation stage through machine learning methods such as classification models, which is not limited here.

[0117] According to another embodiment of the early warning method of the present disclosure, for example, the following embodiment can be used to implement a specific example of determining early warning information according to the target tangent angle: determining early warning information according to the target tangent angle and the tangent angle range threshold.

[0118] The warning information includes a warning level, and each tangent angle range threshold maps a warning level.

[0119] For example, the first tangent angle , the second tangent angle , the larger value of the first tangent angle α and the second tangent angle β can be used as the target tangent angle w .

[0120] Table 1 below schematically shows an example of a mapping relationship between a warning level and a cutting angle range threshold.

[0121] Table 1

[0122]

[0123] Note: 45° <A<B<C<90°

[0124] Table 1 schematically shows the mapping relationship between the tangent angle range threshold and the warning level corresponding to the target tangent angle w.

[0125] In summary, the early warning method of the embodiment of the present disclosure can, on the one hand, determine the target tangent angle for early warning based on the dimension of deformation stage and / or monitoring time, which can improve the accuracy of early warning and reduce early warning false alarms. In addition, the original displacement data can be processed through preprocessing operations such as fitting processing to reduce early warning false alarms caused by the original displacement data itself. Furthermore, the automatic classification of deformation categories can be achieved through methods such as ordered clustering, which relies less on manual experience and can adapt to landslide early warnings in various scenarios.

[0126] Figure 5 The following schematically shows a flow chart of an early warning method according to another embodiment of the present disclosure.

[0127] Figure 5 In the example, the access data is the original displacement data collected. Figure 5 For example, the current monitoring time is t, and the deformation stage corresponding to the current monitoring time t is the nth deformation stage among the n deformation stages. The specific step flow details can refer to the detailed description of the above embodiment, which will not be repeated here.

[0128] The embodiment of the present disclosure also provides an early warning device.

[0129] Figure 6 A schematic block diagram of an early warning device 600 according to an embodiment of the present disclosure is schematically shown.

[0130] like Figure 6 As shown, the early warning device 600 includes: a first module 610, a second module 620, a third module 630, a fourth module 640, a fifth module 650 and a sixth module 660.

[0131] The first module 610 is used to preprocess the acquired original displacement data sequence to obtain a displacement data sequence; wherein the original displacement data sequence includes original displacement data of multiple target objects associated with respective monitoring times.

[0132] The second module 620 is used to divide each displacement data in the displacement data sequence into a corresponding deformation stage.

[0133] The third module 630 is used to determine the first tangent angle according to the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage; the target deformation stage is the deformation stage to which the displacement data associated with the current monitoring time belongs.

[0134] The fourth module 640 is used to determine the second tangent angle according to the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the deformation stage to which the previous monitoring time adjacent to the current monitoring time belongs.

[0135] The fifth module 650 is used to determine a target tangent angle according to the first tangent angle and / or the second tangent angle.

[0136] The sixth module 660 is used to determine the warning information according to the target tangent angle.

[0137] It should be understood that Figure 6 The embodiments of the device part of the present application shown are the same or similar to the embodiments of the method part of the present application, and the technical problems solved and the technical effects achieved are also the same or similar, which will not be repeated in this application.

[0138] The embodiments of the present disclosure also provide an electronic device, a computer storage medium, and a computer program product.

[0139] Figure 7 A schematic block diagram of an electronic device 700 that can be used to implement the early warning method of an embodiment of the present application is shown. The implementation example of the electronic device may include various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also include various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the present application described herein and / or required.

[0140] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 to a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0141] Multiple components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0142] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSP), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above, such as the early warning method. For example, in some embodiments, the aforementioned method may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the early warning method described above may be executed. Alternatively, in other embodiments, the computing unit 701 may be configured to execute the early warning method in any other appropriate manner (eg, by means of firmware).

[0143] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0144] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0145] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, flash memories, or any suitable combination of the foregoing.

[0146] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0147] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0148] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0149] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

Claims

1. An early warning method, characterized in that: The method comprises: Preprocessing the acquired original displacement data sequence to obtain a displacement data sequence; wherein the original displacement data sequence includes original displacement data of a plurality of target objects associated with respective monitoring times; Divide each displacement data in the displacement data sequence into a corresponding deformation stage; Determine the first tangent angle according to the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage; the target deformation stage is the deformation stage to which the displacement data associated with the current monitoring time belongs; Determine a second tangent angle according to a displacement rate corresponding to the target deformation stage and a displacement rate corresponding to a deformation stage to which a previous monitoring time adjacent to the current monitoring time belongs; wherein the first tangent angle is determined based on a deformation stage dimension, and the second tangent angle is determined based on a monitoring time dimension; Determining the first tangent angle or the second tangent angle as a target tangent angle specifically includes: Determine the larger value of the first tangent angle and the second tangent angle as the target tangent angle; or, determine the first tangent angle as the target tangent angle; or, determine the second tangent angle as the target tangent angle; determining warning information according to the target tangent angle; The preprocessing of the acquired original displacement data sequence to obtain the displacement data sequence includes: Performing fitting processing on the original displacement data sequence to obtain the correlation relationship between the displacement and the monitoring time; The original displacement data is estimated according to the association relationship to obtain the displacement data sequence including a plurality of the displacement data.

2. The method according to claim 1, characterized in that Also includes: When the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage, the warning information is not reported; and / or, If the displacement rate corresponding to the target deformation stage is less than or equal to the displacement rate corresponding to the deformation stage of the previous monitoring time adjacent to the current monitoring time, the warning information is not reported.

3. The method according to claim 1, characterized in that The fitting process of the original displacement data sequence to obtain the correlation relationship between the displacement and the monitoring time includes: Sampling the original displacement data sequence with s different numbers of samples to obtain s candidate displacement data sequences; Perform fitting processing on each candidate displacement data sequence to obtain s candidate association relationships; The association relationship is determined according to the evaluation parameters of each candidate association relationship.

4. The method according to claim 3, characterized in that The evaluation parameters include a fitting error parameter and / or the number of samples involved in the fitting process at each deformation stage.

5. The method according to claim 1, before performing fitting processing on the original displacement data sequence, further comprises: The original displacement data sequence is subjected to data noise reduction processing.

6. The method according to claim 1 or 2, characterized in that: The step of dividing each displacement data in the displacement data sequence into corresponding deformation stages comprises: Each displacement data in the displacement data sequence is divided into the corresponding deformation stage through ordered clustering processing.

7. The method according to claim 1 or 2, characterized in that: Determining the warning information according to the target tangent angle includes: The warning information is determined according to the target tangent angle and the tangent angle range threshold, wherein the warning information includes a warning level, and each tangent angle range threshold is mapped to a warning level.

8. The method according to claim 1, characterized in that The displacement rate corresponding to the deformation stage is determined according to the ratio of the displacement data difference and the monitoring time difference of the deformation stage; or, the displacement rate corresponding to the deformation stage is determined according to the average value of the derivative of the correlation relationship corresponding to the deformation stage.

9. The method according to claim 1, characterized in that: The number of deformation stages and / or the parameters of the fitting process are obtained by pre-configuration.

10. An early warning device, characterized in that: include: The first module is used to preprocess the acquired original displacement data sequence to obtain a displacement data sequence; wherein the original displacement data sequence includes original displacement data of multiple target objects associated with respective monitoring times; The second module is used to divide each displacement data in the displacement data sequence into a corresponding deformation stage; The third module is used to determine the first tangent angle according to the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the previous deformation stage adjacent to the target deformation stage; the target deformation stage is the deformation stage to which the displacement data associated with the current monitoring time belongs; The fourth module is used to determine the second tangent angle according to the displacement rate corresponding to the target deformation stage and the displacement rate corresponding to the deformation stage to which the previous monitoring time adjacent to the current monitoring time belongs; wherein the first tangent angle is determined based on the deformation stage dimension, and the second tangent angle is determined based on the monitoring time dimension; A fifth module, configured to determine the first tangent angle or the second tangent angle as a target tangent angle; The fifth module is further configured to determine the larger value of the first tangent angle and the second tangent angle as the target tangent angle; or determine the first tangent angle as the target tangent angle; or determine the second tangent angle as the target tangent angle; A sixth module is used to determine warning information according to the target tangent angle; The first module is also used to perform fitting processing on the original displacement data sequence to obtain the correlation relationship between the displacement and the monitoring time; The original displacement data is estimated according to the association relationship to obtain the displacement data sequence including a plurality of the displacement data.

11. An electronic device, characterized in that: include: A processor and an interface circuit, wherein the interface circuit is used to receive signals from devices other than the electronic device and transmit them to the processor or send signals from the processor to devices other than the electronic device, and the processor is used to implement the early warning method as described in any one of claims 1 to 9 through a logic circuit or execution code instructions.

12. A computer storage medium having a computer program stored thereon, characterized in that: When the computer instructions are executed, the processor is caused to execute the early warning method according to any one of claims 1-9.

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the early warning method according to any one of claims 1 to 9.

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