A slope early warning method and system, a storage medium and an electronic device

Abstract

The application provides a slope early warning method and system, a storage medium and an electronic device, and relates to the field of geological monitoring. The method comprises the following steps: obtaining historical monitoring data of a slope sensor and a first grade threshold corresponding to a standard slope early warning grade; updating the first grade threshold corresponding to the standard slope early warning grade based on the historical monitoring data of the slope sensor to obtain a second grade threshold; obtaining current monitoring data of the slope sensor; determining an actual slope early warning grade corresponding to the current monitoring data through the second grade threshold; and outputting an early warning signal corresponding to the actual slope early warning grade. The first grade threshold corresponding to the standard slope early warning grade can be adjusted through the historical monitoring data, the actual slope early warning grade is more accurate, and thus an adaptive early warning signal can be output according to the actual situation of the slope.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geological monitoring, in particular to a slope early warning method and system, a storage medium and an electronic device. BACKGROUND

[0002] Slope early warning refers to real-time or periodic monitoring of a slope, measuring the deformation, displacement and groundwater level of the slope, analyzing the trend and cause of slope deformation, and timely alarming. Slope early warning can ensure personnel safety, reduce property loss, and protect the safety and stability of infrastructure.

[0003] The related slope early warning method is usually based on the data of monitoring the slope, according to the national standard or industry standard to determine the corresponding early warning level, and then according to the early warning level to adopt different early warning measures. However, due to the large difference between different slopes, it is difficult to adapt to the actual slope situation by using national standards or industry standards, resulting in inaccurate early warning level division, thereby affecting the early warning strength. SUMMARY

[0004] The present application provides a slope early warning method, system, storage medium and electronic device, which updates the first level threshold corresponding to the standard slope early warning level through historical monitoring data, and determines the accurate actual slope early warning level according to the current monitoring data, so as to be able to early warning according to the actual slope early warning level.

[0005] In a first aspect, the present application provides a slope early warning method, the method comprising:

[0006] obtaining historical monitoring data of a slope sensor and a first level threshold corresponding to a standard slope early warning level;

[0007] updating the first level threshold corresponding to the standard slope early warning level based on the historical monitoring data of the slope sensor to obtain a second level threshold;

[0008] obtaining current monitoring data of the slope sensor;

[0009] determining the actual slope early warning level corresponding to the current monitoring data through the second level threshold;

[0010] outputting an early warning signal corresponding to the actual slope early warning level.

[0011] By adopting the technical scheme, the first grade threshold is updated to the second grade threshold by using historical monitoring data, and the actual slope warning grade of the current monitoring data is determined according to the second grade threshold. The first grade threshold corresponding to the standard slope warning grade can be adjusted by using the historical monitoring data, so that the actual slope warning grade divided is more accurate, and thus the warning signal adapted to the actual situation of the slope can be output.

[0012] Optionally, the actual slope warning grade corresponding to the current monitoring data is determined by the second grade threshold, including:

[0013] The index of the current monitoring information is marked to obtain an actual monitoring index;

[0014] A hierarchical structure corresponding to the actual monitoring index is determined based on a knowledge graph corresponding to the actual monitoring index;

[0015] A grade weight corresponding to the hierarchical structure is determined based on the second grade threshold;

[0016] A hierarchical analysis model is constructed based on the hierarchical structure corresponding to the actual monitoring index and the grade weight corresponding to the hierarchical structure;

[0017] The current monitoring data is input into the hierarchical analysis model to obtain the actual slope warning grade corresponding to the current monitoring data.

[0018] By adopting the technical scheme, the corresponding actual monitoring index of the current monitoring information can be determined, the hierarchical relationship of each actual monitoring index is sorted by using the knowledge graph, and the grade weight corresponding to the hierarchical structure is determined by using the updated second grade threshold to obtain the hierarchical analysis model. By constructing the hierarchical structure by using the hierarchical analysis method, more accurate weights are given to different hierarchical structures, and the division of the actual slope warning grade can be more accurate.

[0019] Optionally, before the hierarchical structure corresponding to the actual monitoring index is determined based on the knowledge graph corresponding to the actual monitoring index, the method further includes:

[0020] A standard knowledge graph corresponding to the standard slope warning grade is obtained;

[0021] The actual monitoring index in the standard knowledge graph is clustered to obtain the knowledge graph corresponding to the actual monitoring index.

[0022] By adopting the technical scheme, the actual monitoring indexes in the standard knowledge graph corresponding to the preset standard slope early warning level are screened out, and the knowledge graph corresponding to the actual monitoring indexes is obtained by clustering from the existing standard knowledge graph, compared with the entity relationship analysis method, the entity relationship between the actual monitoring indexes can be determined simply and quickly, and the knowledge graph corresponding to the actual monitoring indexes is obtained.

[0023] Optionally, the determining of the level weight corresponding to the hierarchical structure based on the second level threshold value comprises:

[0024] obtaining a difference value between the current monitoring data corresponding to the hierarchical structure and a threshold value;

[0025] determining the level weight corresponding to the hierarchical structure based on the proportion of each level in the second level and the difference value between the current monitoring data and the threshold value.

[0026] By adopting the technical scheme, the level weight can be determined from two dimensions of the proportion of each level in the second level of the upper level of the hierarchical structure and the difference value between the current monitoring data of the lower level and the preset threshold value, so that the accuracy of the level weight can be improved.

[0027] Optionally, the obtaining of the historical monitoring data of the slope sensor comprises:

[0028] obtaining original monitoring data of the slope sensor;

[0029] obtaining a root mean square of the original monitoring data of the slope sensor to obtain a normal monitoring range corresponding to the slope sensor; and determining monitoring data in the original monitoring data that does not exceed the normal monitoring range as the historical monitoring data.

[0030] By adopting the technical scheme, the monitoring data exceeding the normal monitoring range in the original monitoring data is eliminated, so that the reliability of the historical monitoring data can be ensured.

[0031] Optionally, the outputting of the early warning signal corresponding to the actual slope early warning level comprises:

[0032] obtaining a response time interval between a time point of outputting the early warning signal and a time point of starting to implement an emergency measure;

[0033] obtaining temporary monitoring data of the slope sensor after the early warning signal is outputted;

[0034] determining a predicted time of reaching a next actual slope early warning level based on the temporary monitoring data and the second level threshold value;

[0035] if the response time is greater than the predicted time, outputting an early warning signal corresponding to the next actual slope early warning level.

[0036] By adopting the technical scheme, when no response to the early warning signal corresponding to the actual slope early warning level is made within the expected time, the early warning signal corresponding to the next actual slope early warning level is output in time, the response degree of the relevant personnel to the early warning signal is improved, and the effectiveness of the slope early warning can be improved.

[0037] Optionally, the first grade threshold corresponding to the standard slope early warning level is updated based on the historical monitoring data of the slope sensor to obtain a second grade threshold, including:

[0038] The first slope instability index corresponding to the historical monitoring data of the slope sensor is obtained;

[0039] The second slope instability index corresponding to the standard slope early warning level is obtained;

[0040] The difference between the first slope instability index and the second slope instability index is calculated to obtain a slope correction amount;

[0041] The first grade threshold corresponding to the standard slope early warning level is updated based on the slope correction amount to obtain the second grade threshold.

[0042] By adopting the technical scheme, the difference between the slope instability indexes is taken as the slope correction amount, the first grade threshold corresponding to the standard slope early warning level is updated, the updating of the first grade threshold is realized in a quantitative manner, and the accuracy of the second grade threshold can be improved.

[0043] In a second aspect, the present application provides a slope early warning system, including:

[0044] A standard threshold obtaining module is configured to obtain the historical monitoring data of the slope sensor and the first grade threshold corresponding to the standard slope early warning level;

[0045] A standard threshold updating module is configured to update the first grade threshold corresponding to the standard slope early warning level based on the historical monitoring data of the slope sensor to obtain a second grade threshold;

[0046] A current monitoring data obtaining module is configured to obtain the current monitoring data of the slope sensor;

[0047] An early warning level determining module is configured to determine the actual slope early warning level corresponding to the current monitoring data through the second grade threshold;

[0048] An early warning signal output module is configured to output the early warning signal corresponding to the actual slope early warning level.

[0049] Thirdly, this application provides a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing any of the methods described above.

[0050] Fourthly, this application provides an electronic device including a processor, a memory, and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform any of the methods described above.

[0051] In summary, the beneficial effects of the technical solution of this application include:

[0052] Historical monitoring data is used to update the first-level threshold to the second-level threshold, and the actual slope warning level for the current monitoring data is determined based on the second-level threshold. This allows for adjustments to the first-level threshold corresponding to the standard slope warning level using historical monitoring data, resulting in more accurate classification of the actual slope warning level. Consequently, appropriate warning signals can be output based on the actual condition of the slope. Attached Figure Description

[0053] Figure 1 This is a system architecture diagram of a slope early warning system provided in an embodiment of this application;

[0054] Figure 2 This is a schematic diagram illustrating a scenario for determining slope early warning levels using relevant technologies;

[0055] Figure 3 This is a schematic diagram illustrating a scenario for determining the early warning level of a slope, as provided in this application.

[0056] Figure 4 This is a schematic flowchart of a slope early warning method provided in an embodiment of this application;

[0057] Figure 5 This is a schematic flowchart of another slope early warning method provided in the embodiments of this application;

[0058] Figure 6 This is a schematic diagram of the slope early warning system provided in the embodiments of this application;

[0059] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0060] Explanation of reference numerals in the attached diagram: 61. Standard threshold acquisition module; 62. Standard threshold update module; 63. Current monitoring data acquisition module; 64. Warning level determination module; 65. Warning signal output module; 700. Electronic device; 701. Processor; 702. Communication bus; 703. User interface; 704. Network interface; 705. Memory. Detailed Implementation

[0061] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0062] In the description of the embodiments of this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0063] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0064] To facilitate understanding, a brief explanation of the specific terms used in this application will be provided first.

[0065] Standard slope warning levels are slope warning levels set by national or industry standards. For example, slope warning levels can be divided into four levels: Attention, Warning, Alert, and Alarm. Different warning measures are taken according to different slope warning levels. Each of the four standard slope warning levels has a corresponding first-level threshold. The slope warning level is determined by whether the actual monitoring and warning index falls into the corresponding first-level threshold.

[0066] Please see Figure 1 This diagram illustrates a system architecture for slope early warning, as provided in an embodiment of this application. The diagram shows the communication connection between the slope sensor and the server. The connection method can include various types of wired or wireless communication links. For example, wired communication links include optical fiber, twisted pair, or coaxial cable, while wireless communication links include Bluetooth, 4G, Wi-Fi, or microwave communication links.

[0067] Slope sensors are used to measure and collect data such as slope displacement and deformation, groundwater level, and surface settlement, and transmit the monitored data to a server.

[0068] Servers are used for data storage, processing, and providing various data and services.

[0069] Figure 1 The number of devices shown is only illustrative; the number of slope sensors and servers can be any number as needed.

[0070] Please see Figure 2 , Figure 2 This diagram illustrates a scenario for determining slope warning levels in related technologies. In these technologies, standard slope warning levels are used to determine slope warning levels. However, due to the differences between different slopes, the types of data and monitoring values ​​from slope sensors vary. Using standard slope warning levels can lead to inaccurate determination of slope warning levels, resulting in inaccurate selection of warning modes when issuing warnings based on these levels.

[0071] Please see Figure 3 , Figure 3 This application provides a schematic diagram of a scenario for determining slope early warning levels. Addressing the aforementioned technical problems, this application uses historical monitoring data to update the first-level threshold to a second-level threshold, and then determines the actual slope early warning level based on the second-level threshold. This allows for the adjustment of the first-level threshold corresponding to the standard slope early warning level using historical monitoring data, resulting in a more accurate determination of the actual slope early warning level and enabling the output of appropriate early warning signals based on the actual slope conditions.

[0072] Please see Figure 4 This is a flowchart illustrating a slope early warning method provided in an embodiment of this application. This method can be implemented using a computer program, a microcontroller, or run on a slope early warning system based on the von Neumann architecture. The computer program can be integrated into an application or run as a standalone utility application. This embodiment uses a server as the execution entity to provide a detailed description of the specific steps of the slope early warning method.

[0073] S401, acquire historical monitoring data from slope sensors and the first-level threshold corresponding to the standard slope early warning level.

[0074] The first-level threshold is the threshold corresponding to the standard slope warning level. For example, the first-level thresholds are 50%, 70%, and 90%. The comprehensive monitoring and warning index is at the attention level when it is greater than 0% and less than or equal to 50%, at the warning level when it is greater than 50% and less than or equal to 70%, at the alert level when it is greater than 70% and less than 90%, and at the alarm level when it is greater than 90% and less than or equal to 100%.

[0075] The first-level threshold corresponding to the standard slope warning level is a fixed threshold. Different standard slope warning levels and corresponding first-level thresholds can be determined from the database through different level classifications.

[0076] S402, based on the historical monitoring data of the slope sensor, update the first-level threshold corresponding to the standard slope early warning level to obtain the second-level threshold;

[0077] Historical monitoring data includes the types of monitoring data and the average level of the monitoring data over a period of time prior to the current moment, which enables the updating of the first-level threshold to obtain the second-level threshold.

[0078] The second-level threshold is obtained by adjusting the first-level threshold, and the corresponding slope warning level is the same as the standard slope warning level. Compared with the first-level threshold, the second-level threshold has a higher adaptability to the current slope when classifying slope warning levels.

[0079] S403, acquire the current monitoring data of the slope sensor;

[0080] The slope sensor's current monitoring data is real-time, reflecting the slope's real-time monitoring status. After collecting the current monitoring data, the slope sensor transmits it back to the server in real time, allowing the server to process the data in real-time.

[0081] S404 determines the actual slope warning level corresponding to the current monitoring data by using the second-level threshold.

[0082] Based on the current monitoring data, a comprehensive monitoring and early warning index is calculated to determine the slope early warning level. Then, the specific second-level threshold to which the comprehensive monitoring and early warning index falls is determined, thereby enabling the determination of the actual slope early warning level corresponding to the current monitoring data.

[0083] Specifically, different standard slope warning levels correspond to different comprehensive monitoring and warning indices, and also to different calculation methods for the comprehensive monitoring and warning indices, so that the first-level threshold for various slope warning levels can be adjusted.

[0084] S405 outputs the warning signal corresponding to the actual slope warning level.

[0085] The actual slope warning level is a real-time slope warning level determined based on the current monitoring data of the slope. Each actual slope warning level corresponds to a specific warning signal, and different warning signals are output to achieve different warning effects.

[0086] In one embodiment, Figure 5 As shown, a flowchart of another slope early warning method is presented. This application provides a detailed explanation of the steps for determining the actual slope early warning level in its embodiments.

[0087] S501, acquire historical monitoring data from slope sensors and the first-level threshold corresponding to the standard slope early warning level.

[0088] S502, based on historical monitoring data from slope sensors, updates the first-level threshold corresponding to the standard slope early warning level to obtain the second-level threshold.

[0089] S503, acquires the current monitoring data from the slope sensor.

[0090] Steps S501 to S503 have been described in detail in steps S401 to S403 of the above embodiments, and will not be repeated here.

[0091] S504 marks the indicators of the current monitoring information to obtain the actual monitoring indicators.

[0092] The current monitoring data includes the monitored objects. For example, displacement gauge A is set at the top of the slope, and its monitored object is the displacement at the top of the slope. The current monitoring data of displacement gauge A is marked as the displacement at the top of the slope. Piezometer B is set at the bottom of the slope, and its monitored object is the seepage pressure at the bottom of the slope. The current monitoring data of piezometer B is marked as the seepage pressure at the bottom of the slope.

[0093] The actual monitoring indicators are those monitored by the existing sensors on the slope. For example, if a certain slope only has three types of sensors: a slope top displacement gauge A, a slope bottom piezometer B, and a rain gauge C, then the actual monitoring indicators are the slope top displacement, slope bottom piezometer, and rainfall.

[0094] In practice, all received current monitoring data have been marked, which allows for accurate acquisition of the corresponding actual monitoring indicators.

[0095] S505, based on the knowledge graph corresponding to the actual monitoring indicators, determines the hierarchical structure corresponding to the actual monitoring indicators.

[0096] The relationships between various actual monitoring indicators are constructed using a knowledge graph approach. For example, monitoring deep slope deformation includes deep tilt and surface displacement. The actual monitoring indicators of deep tilt and surface displacement are at the same level and belong to the same level as deep slope deformation.

[0097] In one feasible implementation, a standard knowledge graph corresponding to the standard slope early warning level is obtained; the actual monitoring indicators in the standard knowledge graph are clustered to obtain the knowledge graph corresponding to the actual monitoring indicators.

[0098] Standard slope warning levels have standard indicator items, which in turn include different monitoring indicators. For example, the standard knowledge graph of a certain standard slope warning level includes indicator items such as surface deformation, deep deformation, groundwater, and meteorology. The meteorology item includes monitoring indicators such as soil moisture, rainfall, and soil temperature. However, for a certain slope, the actual monitoring indicators under the meteorology item are only soil moisture and rainfall. Clustering the soil moisture and rainfall indicators yields a knowledge graph corresponding to the actual monitoring indicators: meteorology item-rainfall indicator and meteorology item-soil moisture indicator.

[0099] S506, determine the level weights corresponding to the hierarchical structure based on the second level threshold.

[0100] The hierarchical structure corresponds to the weight of the factors used to determine slope warning.

[0101] In one feasible implementation, the difference between the current monitoring data corresponding to the hierarchical structure and the preset threshold is obtained; based on the proportion of each level in the second-level threshold and the difference between the current monitoring data and the preset threshold, the level weight corresponding to the hierarchical structure is determined.

[0102] The hierarchical structure is defined by the difference between the current monitoring data and the preset threshold. For example, if the preset threshold for a certain monitoring indicator is 10, and the current monitoring data is 20, the difference is 10, and the first weight for this difference is 0.1. If the current monitoring data is 30, the difference is 20, and the first weight for this difference is 0.2. The first weight represents the weight corresponding to each indicator. Therefore, the larger the difference between the current monitoring data and the preset threshold corresponding to the hierarchical structure, the more severe the anomaly, and the weights can be dynamically adjusted.

[0103] Based on the proportion of each level in the second-level threshold, the second weight of the indicator item calculated by the first weight is adaptively adjusted so that the calculated monitoring and early warning index can reflect the current monitoring situation.

[0104] S507, based on the hierarchical structure corresponding to the actual monitoring indicators and the level weights corresponding to the hierarchical structure, constructs a hierarchical analysis model.

[0105] The hierarchical structure of the hierarchical analysis model (AHP) is consistent with the entity relationships in the knowledge graph. The target layer of the AHP model is the landslide level evaluation target, which includes several criterion layers. The criterion layers correspond to the indicator items in the knowledge graph, and each criterion layer includes several alternative layers, which correspond to the monitoring indicators in the knowledge graph. Based on the above hierarchical structure and the corresponding level weights, a judgment matrix is ​​established for each alternative layer relative to the target layer. The AHP model is then constructed to obtain the target layer evaluation vector, which can be converted into an index for evaluating the early warning level of the slope.

[0106] S508: Input the current monitoring data into the hierarchical analysis model to obtain the actual slope warning level corresponding to the current monitoring data.

[0107] By adding a second-level threshold determination after the target layer of the hierarchical analysis model, the actual slope warning level corresponding to the current monitoring data can be obtained.

[0108] S509 outputs the warning signal corresponding to the actual slope warning level.

[0109] Optionally, the slope early warning system is equipped with an alarm system connected to the server. The alarm system includes, but is not limited to, audible and visual alarm devices, remote alarm terminals, and other equipment. After responding to the early warning signal, the alarm system can provide audible and visual alarms on the actual slope, or transmit the early warning information to the remote alarm terminal, enabling staff to conduct remote monitoring.

[0110] In this embodiment of the application, compared with directly determining the actual slope warning level based on each current monitoring parameter, constructing a hierarchical model can classify the monitoring indicators under the same indicator item, thereby making the determination of the slope warning level more accurate.

[0111] The following describes the filtering of the current monitoring data in this embodiment:

[0112] Obtain the raw monitoring data from the slope sensors; calculate the root mean square of the raw monitoring data from the slope sensors to obtain the normal monitoring range corresponding to the slope sensors; and determine the monitoring data in the raw monitoring data that does not exceed the normal monitoring range as historical monitoring data.

[0113] The normal monitoring range of historical monitoring data is determined by calculating the root mean square of the original monitoring data. The normal monitoring range is the normal range of the original monitoring data. Monitoring data that are greater than or less than the normal monitoring range are considered abnormal fluctuation data from the slope sensors.

[0114] In one optional implementation, the response time between the time the early warning signal is output and the time when emergency measures are started is obtained; temporary monitoring data of the slope sensor after the early warning signal is output is obtained; based on the temporary monitoring data and the second-level threshold, the estimated time to reach the next actual slope early warning level is determined; if the response time is greater than the estimated time, the early warning signal corresponding to the next actual slope early warning level is output.

[0115] When the slope warning level shows an upward trend, the estimated time to reach the next slope warning level can be predicted using the upward curve. Within the estimated time of issuing the warning signal corresponding to the current actual slope warning level, it can be determined whether the staff has taken corresponding feedback actions within the estimated time, i.e., by obtaining their response time. If no corresponding feedback action is taken within the estimated time, the warning signal corresponding to the next actual slope warning level should be promptly issued to increase the staff's vigilance.

[0116] In one feasible implementation, the first slope instability index corresponding to the historical monitoring data of the slope sensor is obtained; the second slope instability index corresponding to the standard slope warning level is obtained.

[0117] The difference between the first slope instability index and the second slope instability index is calculated to obtain the slope correction amount; based on the slope correction amount, the first-level threshold corresponding to the standard slope warning level is updated to obtain the second-level threshold.

[0118] The formula for calculating the instability index of the first slope is:

[0119] In the formula, GEI is the first slope instability index, and k i Let P be the evaluation index weight of the monitoring indicator in the i-th historical monitoring data. i This refers to the monitoring data in the i-th historical monitoring data.

[0120] The second slope instability index corresponding to the standard slope warning level can be obtained directly by acquiring the standard documents.

[0121] The slope correction amount is obtained by calculating the difference, and the first-level threshold is updated to obtain the second-level threshold.

[0122] The following are system embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the system embodiments of this application, please refer to the method embodiments of the application.

[0123] Please see Figure 6This illustration shows a schematic diagram of a slope early warning system provided in an exemplary embodiment of this application. The system can be implemented as all or part of a system through software, hardware, or a combination of both. The system includes a standard threshold acquisition module 61, a standard threshold update module 62, a current monitoring data acquisition module 63, an early warning level determination module 64, and an early warning signal output module 65.

[0124] The standard threshold acquisition module 61 is used to acquire historical monitoring data of the slope sensor and the first-level threshold corresponding to the standard slope early warning level.

[0125] The standard threshold update module 62 is used to update the first-level threshold corresponding to the standard slope warning level based on the historical monitoring data of the slope sensor to obtain the second-level threshold.

[0126] The current monitoring data acquisition module 63 is used to acquire the current monitoring data of the slope sensor;

[0127] The early warning level determination module 64 is used to determine the actual slope early warning level corresponding to the current monitoring data through the second level threshold.

[0128] The early warning signal output module 65 is used to output the early warning signal corresponding to the actual slope early warning level.

[0129] Optionally, the standard threshold acquisition module 61 also includes a historical monitoring data filtering unit.

[0130] The historical monitoring data filtering unit is used to obtain the raw monitoring data of the slope sensor; calculate the root mean square of the raw monitoring data of the slope sensor to obtain the normal monitoring range of the slope sensor; and determine the monitoring data in the raw monitoring data that does not exceed the normal monitoring range as historical monitoring data.

[0131] Optionally, the standard threshold update module 62 also includes a graded threshold correction unit.

[0132] The grade threshold correction unit is used to obtain the first slope instability index corresponding to the historical monitoring data of the slope sensor; obtain the second slope instability index corresponding to the standard slope warning level; calculate the difference between the first slope instability index and the second slope instability index to obtain the slope correction amount; and update the first grade threshold corresponding to the standard slope warning level based on the slope correction amount to obtain the second grade threshold.

[0133] Optionally, the warning level determination module 64 also includes a hierarchical analysis model construction unit.

[0134] The hierarchical analysis model construction unit is used to label the indicators of the current monitoring information to obtain the actual monitoring indicators; based on the knowledge graph corresponding to the actual monitoring indicators, the hierarchical structure corresponding to the actual monitoring indicators is determined; the level weights corresponding to the hierarchical structure are determined based on the second level threshold; the hierarchical analysis model is constructed based on the hierarchical structure corresponding to the actual monitoring indicators and the level weights corresponding to the hierarchical structure; the current monitoring data is input into the hierarchical analysis model to obtain the actual slope warning level corresponding to the current monitoring data.

[0135] Optionally, the hierarchical analysis model building unit also includes a clustering subunit for actual monitoring indicators and a subunit for determining level weights.

[0136] The actual monitoring index clustering subunit is used to obtain the standard knowledge graph corresponding to the standard slope warning level; the actual monitoring index in the standard knowledge graph is clustered to obtain the knowledge graph corresponding to the actual monitoring index.

[0137] The grade weight is determined by the sub-unit, and the difference between the current monitoring data and the preset threshold corresponding to the hierarchical structure is obtained; based on the proportion of each grade in the second grade threshold and the difference between the current monitoring data and the preset threshold, the grade weight corresponding to the hierarchical structure is determined.

[0138] Optionally, the early warning signal output module 65 also includes the response time between the time of acquiring the early warning signal output and the time of starting to implement emergency measures; acquiring temporary monitoring data of the slope sensor after the early warning signal is output; determining the estimated time to reach the next actual slope early warning level based on the temporary monitoring data and the second-level threshold; and outputting the early warning signal corresponding to the next actual slope early warning level if the response time is greater than the estimated time.

[0139] This application also provides a computer storage medium that can store multiple instructions, which are adapted to be loaded and executed by a processor as described above. Figures 1-5 The slope early warning method of the illustrated embodiment can be further explained in the following steps: Figures 1-5 The specific details of the illustrated embodiments will not be elaborated here.

[0140] Please see Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 7 As shown, the electronic device 700 may include: at least one processor 701, at least one network interface 704, a user interface 703, a memory 705, and at least one communication bus 702.

[0141] The communication bus 702 is used to enable communication between these components.

[0142] The user interface 703 may include a display screen and a camera. Optionally, the user interface 703 may also include a standard wired interface and a wireless interface.

[0143] The network interface 704 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0144] The processor 701 may include one or more processing cores. The processor 701 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 705, and by calling data stored in memory 705. Optionally, the processor 701 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 701 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 701 and may be implemented as a separate chip.

[0145] The memory 705 may include random access memory (RAM) or read-only memory. Optionally, the memory 705 may include a non-transitory computer-readable storage medium. The memory 705 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 705 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 705 may also be at least one storage device located remotely from the aforementioned processor 701. Figure 7As shown, the memory 705, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a slope early warning method.

[0146] exist Figure 7 In the electronic device 700 shown, the user interface 703 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 701 can be used to call an application program of a slope early warning method stored in the memory 705. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0147] An electronic device readable storage medium stores instructions that, when executed by one or more processors, cause the electronic device to perform one or more methods as described in the above embodiments.

[0148] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0149] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0151] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0153] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0154] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for slope early warning, characterized in that, The method comprises: acquiring historical monitoring data of a slope sensor and a first level threshold corresponding to a standard slope early warning level; updating the first level threshold corresponding to the standard slope early warning level based on the historical monitoring data of the slope sensor to obtain a second level threshold; acquiring current monitoring data of the slope sensor; determining an actual slope early warning level corresponding to the current monitoring data through the second level threshold; the determining of the actual slope early warning level corresponding to the current monitoring data through the second level threshold comprises: labeling an index of the current monitoring information to obtain an actual monitoring index; determining a hierarchical structure corresponding to the actual monitoring index based on a knowledge graph corresponding to the actual monitoring index; determining a level weight corresponding to the hierarchical structure based on the second level threshold; constructing an analytic hierarchy process model based on the hierarchical structure corresponding to the actual monitoring index and the level weight corresponding to the hierarchical structure; inputting the current monitoring data into the analytic hierarchy process model to obtain the actual slope early warning level corresponding to the current monitoring data; the determining of the level weight corresponding to the hierarchical structure based on the second level threshold comprises: acquiring a difference between the current monitoring data corresponding to the hierarchical structure and a preset threshold; determining the level weight corresponding to the hierarchical structure based on a proportion of each level in the second level threshold and the difference between the current monitoring data and the preset threshold, the preset threshold being a standard early warning value corresponding to the current monitoring data; outputting an early warning signal corresponding to the actual slope early warning level.

2. The method of claim 1, wherein, Before the determining of the hierarchical structure corresponding to the actual monitoring index based on the knowledge graph corresponding to the actual monitoring index, the method further comprises: acquiring a standard knowledge graph corresponding to the standard slope early warning level; performing clustering processing on the actual monitoring index in the standard knowledge graph to obtain a knowledge graph corresponding to the actual monitoring index.

3. The method of claim 1, wherein, The acquiring of the historical monitoring data of the slope sensor comprises: acquiring original monitoring data of the slope sensor; calculating a root mean square of the original monitoring data of the slope sensor to obtain a normal monitoring range corresponding to the slope sensor; determining monitoring data in the original monitoring data that does not exceed the normal monitoring range as the historical monitoring data.

4. The method of claim 1, wherein, The outputting of the early warning signal corresponding to the actual slope early warning level comprises: acquiring a response time interval between a time of outputting the early warning signal and a time of starting to implement an emergency measure; acquiring temporary monitoring data of the slope sensor after the outputting of the early warning signal; determining a predicted time of reaching a next actual slope early warning level based on the temporary monitoring data and the second level threshold; if the response time is greater than the predicted time, outputting an early warning signal corresponding to the next actual slope early warning level.

5. The method of claim 1, wherein, The updating of the first level threshold corresponding to the standard slope early warning level based on the historical monitoring data of the slope sensor to obtain the second level threshold comprises: calculating a first slope instability index corresponding to the historical monitoring data of the slope sensor; acquiring a second slope instability index corresponding to the standard slope early warning level; a difference between the first slope instability index and the second slope instability index is calculated to obtain a slope correction amount; a first grade threshold corresponding to the standard slope warning grade is updated based on the slope correction amount to obtain a second grade threshold.

6. A slope warning system, characterized by The system comprises: a standard threshold acquisition module (61) configured to acquire historical monitoring data of a slope sensor and a first grade threshold corresponding to a standard slope warning grade; a standard threshold updating module (62) configured to update the first grade threshold corresponding to the standard slope warning grade based on the historical monitoring data of the slope sensor to obtain a second grade threshold; a current monitoring data acquisition module (63) configured to acquire current monitoring data of the slope sensor; a warning grade determination module (64) configured to determine an actual slope warning grade corresponding to the current monitoring data by using the second grade threshold; the determination of the actual slope warning grade corresponding to the current monitoring data by using the second grade threshold comprises: marking an index of the current monitoring information to obtain an actual monitoring index; determining a hierarchical structure corresponding to the actual monitoring index based on a knowledge graph corresponding to the actual monitoring index; determining a grade weight corresponding to the hierarchical structure based on the second grade threshold; constructing an analytic hierarchy process model based on the hierarchical structure corresponding to the actual monitoring index and the grade weight corresponding to the hierarchical structure; inputting the current monitoring data into the analytic hierarchy process model to obtain the actual slope warning grade corresponding to the current monitoring data; the determination of the grade weight corresponding to the hierarchical structure based on the second grade threshold comprises: acquiring a difference between the current monitoring data corresponding to the hierarchical structure and a preset threshold; determining the grade weight corresponding to the hierarchical structure based on a proportion of each grade in the second grade threshold and the difference between the current monitoring data and the preset threshold, the preset threshold being a standard warning value corresponding to the current monitoring data; a warning signal output module (65) configured to output a warning signal corresponding to the actual slope warning grade.

7. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, which are suitable for being loaded and executed by a processor to perform the method of any one of claims 1-5.

8. An electronic device, comprising: The electronic device comprises a processor, a memory and a transceiver, the memory is configured to store instructions, the transceiver is configured to communicate with other devices, and the processor is configured to execute the instructions stored in the memory to enable the electronic device to perform the method of any one of claims 1-5.

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