An automatic monitoring and alarm system for high slope deformation based on the Internet of Things

Abstract

This invention discloses an automatic monitoring and alarm system for high slope deformation based on the Internet of Things, belonging to the field of slope monitoring technology. The system discloses a surface monitoring module, a cross-section detection module, and a deep monitoring module. The monitoring and alarm system of this invention can automatically collect data without stopping work during monitoring, thus not affecting the normal construction progress at the construction site, shortening the construction period. During normal monitoring, no large amount of labor costs are required, solving the problems of delay and one-sidedness of existing conventional personnel patrols. It can monitor in real time and issue automatic alarms, greatly improving the effectiveness of slope safety monitoring, significantly reducing the safety risks for surveyors working on high slopes, and ensuring personal safety.

Description

Technical Field

[0001] The present invention relates to the technical field of slope monitoring, and more specifically, to an automatic monitoring and alarm system for high slope deformation based on the Internet of Things. Background Art

[0002] Monitoring of high slope projects has always been a difficult and important point in the construction process. After the project starts, a special person conducts high slope inspections every day, and arranges surface displacement monitoring points on characteristic sections. Surveyors regularly measure the monitoring points, record and compare data. This monitoring method has the following disadvantages: Disadvantage 1. Frequent climbing of high slopes increases the safety risk of personnel and poses a major safety hazard. Disadvantage 2. Manual inspections are highly subjective and can only determine risks at the locations seen, which is highly one-sided. Disadvantage 3. The measurement is discontinuous and cannot reflect the deformation of high slopes in a timely manner, with a certain delay. Disadvantage 4. For projects with many high slopes, a large number of personnel are required to conduct slope inspections, which greatly increases labor costs. Disadvantage 5. When personnel inspect and surveyors measure data, work must be stopped and waited. Construction can only continue after completion, which affects on-site construction and delays construction progress.

[0003] In addition, during the construction process, construction workers need to vertically drive inclined side pipes into the locations prone to landslides, and then regularly use mobile inclinometers to manually suspend gyroscopes from top to bottom along the inclined side pipes to collect three-dimensional data, and determine the deep deformation by comparing the before and after data. This monitoring method has the following disadvantages: Disadvantage 1. The locations where deep displacement monitoring is arranged are mostly prone to landslides, and there is a high safety risk when manually collecting data. Disadvantage 2. The measurement is discontinuous, and deep geological deformation cannot be discovered in time, and there is a certain delay. Disadvantage 3. When personnel patrol and surveyors measure data, work must be stopped and waited, and construction can only continue after completion, which affects on-site construction and delays construction progress. Summary of the invention

[0004] In view of the deficiencies in the prior art, the object of the present invention is to provide an automatic monitoring and alarm system for high slope deformation based on the Internet of Things.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] An automatic monitoring and alarm system for high slope deformation based on the Internet of Things, including a surface monitoring module, a cross-section detection module, and a deep layer monitoring module;

[0007] The surface monitoring module monitors the characteristic section of the slope platform through the surface monitoring equipment, and sends out an alarm signal when the monitoring data is abnormal;

[0008] The section detection module quickly determines the re-measurement sequence of the section according to the alarm signal of the surface monitoring module, and re-measures the section according to the re-measurement sequence;

[0009] The deep monitoring module monitors the potential sliding surface position of the slope platform through deep monitoring equipment, and sends out an alarm signal when the monitoring data suddenly changes.

[0010] Furthermore, the surface monitoring equipment includes multiple displacement piles, a wire splitter, a displacement sensor, and multiple steel wires. The multiple displacement piles are distributed at the characteristic section of each slope platform along the normal direction of the slope line. The displacement sensor leads out multiple steel wires through the wire splitter. The multiple steel wires correspond one-to-one to the multiple displacement piles, and the steel wires connect the displacement piles.

[0011] Furthermore, an alarm signal is issued when the monitoring data is abnormal. Specifically, when the data of the displacement sensor changes, the displacement sensor issues an alarm signal.

[0012] Furthermore, the section detection module quickly determines the re-survey order of the section according to the alarm signal of the surface monitoring module. Specifically, when the displacement sensor sends an alarm signal, the section ranking value of each characteristic section is obtained, and the characteristic sections are sorted in sequence according to the numerical values ​​of the section ranking values, and the characteristic sections are re-surveyed in sequence according to the order.

[0013] Furthermore, the section ranking value of the characteristic section is obtained by the following steps: the surface of the characteristic section is divided by multiple equidistant horizontal lines and multiple vertical lines, and n sampling matrices are generated on the surface of the characteristic section. Based on t cycles, at each cycle node, the soil in each sampling matrix is ​​sampled to obtain a matrix sampling record, and the soil detection value of the sampling matrix is ​​obtained through the matrix sampling record, and the matrix detection value of each sampling matrix is ​​obtained. The matrix detection values ​​of all sampling matrices are summed and averaged to obtain the total matrix detection value, which is marked as YBS, and the matrix influence quantity of the characteristic section at each cycle node is obtained. The matrix influence quantity of h cycle nodes before the current time of the system is summed and averaged to obtain the matrix influence mean, which is marked as PUH. The formula is used The section ranking value PXZ of the characteristic section is obtained, where c1 is the matrix total inspection value coefficient and c2 is the matrix influence mean coefficient.

[0014] Furthermore, the matrix sampling records include soil density, soil moisture, sampling time, and soil heterogeneity coefficient.

[0015] Furthermore, the soil test value is obtained by the following steps: the soil density recorded by matrix sampling is marked as TRM, the soil moisture recorded by matrix sampling is marked as SFT, the soil heterogeneity coefficient recorded by matrix sampling is marked as BJJ, and the formula is used The soil detection value JCZ is obtained, where a1 is the soil density coefficient and a2 is the soil moisture coefficient.

[0016] Further, the matrix detection value of the sampling matrix is ​​obtained by the following steps: obtaining m soil detection values ​​of the same sampling matrix before the current time of the system, summing up all the soil detection values ​​and taking the average value to obtain the soil detection average value, and marking it as RJJ, sorting the soil detection values ​​in the order of sampling time, performing difference calculation between the next adjacent soil detection value after sorting and the previous soil detection value to obtain the soil detection variable value, when the soil detection variable value is greater than or equal to 0, marking the soil detection variable value as a soil detection appreciation value, when the soil detection variable value is less than 0, marking the soil detection variable value as a soil detection decrement value, summing up all the soil detection appreciation values ​​to obtain the total soil detection appreciation value and marking it as JSZ, obtaining the soil detection variable value marked as the total number of soil detection appreciation values ​​and marking it as SCS, summing up all the soil detection decrements and taking the absolute value to obtain the total soil detection decrement value and marking it as MZP, obtaining the soil detection variable value marked as the total number of soil detection decrements and marking it as DQZ, and using the formula The matrix inspection value ZRi of the sampling matrix is ​​obtained, where b1 is the soil detection mean coefficient, i is the number of the sampling matrix, i=1, 2, ..., n.

[0017] Furthermore, the matrix influence number of the periodic node is obtained through the following steps: when the number of difference matrices of the characteristic section at the periodic node is less than 2, no corresponding processing is performed; when the number of difference matrices is greater than or equal to 2, the difference matrices are compared pairwise, the minimum path between the two difference matrices is calculated by the minimum path algorithm, a minimum path threshold is set, and when the minimum path is less than the minimum path threshold, the matrix influence number is increased by one; after all the difference matrices in the characteristic section are compared, the matrix influence number of the periodic node is obtained.

[0018] Furthermore, the deep monitoring equipment includes a plurality of inclined side tubes, which are vertically installed at the potential sliding surface position of the slope platform. A fixed inclinometer is arranged in the inclined side tube. The fixed inclinometer is composed of a plurality of gyroscopes connected in series. Each gyroscope collects its own three-dimensional coordinate data in real time. When the three-dimensional coordinate data of the gyroscope changes suddenly, the gyroscope sends an alarm signal.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The monitoring and alarm system of the present invention can automatically collect data, and there is no need to stop work during monitoring, which does not affect the normal construction progress of the construction site, shortens the construction period, and does not require a large amount of labor cost investment during normal monitoring. It solves the problems of delay and one-sidedness of existing conventional personnel inspections, and can monitor in real time and automatically alarm, which greatly improves the safety monitoring of slopes, greatly reduces the safety risks of surveyors when working on high slopes, and ensures personal safety;

[0021] 2. Set up a surface monitoring module and surface monitoring equipment, improve the surface displacement monitoring method from conventional point monitoring to line monitoring, connect the displacement piles in parallel into a whole to avoid mutual interference between the displacement piles, and be able to more comprehensively monitor the surface stability of the slope. In addition, the improvement from point monitoring to line monitoring saves cost investment and meets the requirements of green environmental protection. Set up a section detection module, which can quickly analyze the section ranking value of each characteristic section after the surface monitoring module alarms, and sort the detection order of the characteristic sections according to the section ranking value, optimize the detection path of the surveying personnel for the characteristic sections on the slope, and reduce the re-survey scope of the surveying personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a principle block diagram of the cross-section detection module of the present invention;

[0023] Figure 2 It is a schematic diagram of the installation of the surface monitoring equipment of the present invention;

[0024] Figure 3 For the present invention Figure 2 A top view of

[0025] Figure 4 It is a schematic diagram of the installation of the deep layer monitoring equipment of the present invention. DETAILED DESCRIPTION

[0026] Example 1

[0027] Reference Figures 1 to 3 , an automatic monitoring and alarm system for high slope deformation based on the Internet of Things, including a surface monitoring module and a section detection module.

[0028] The surface monitoring module monitors the characteristic sections of the slope platform through surface monitoring equipment and sends out an alarm signal when the monitoring data is abnormal.

[0029] The surface monitoring equipment includes a collection box, a displacement sensor, a splitter, a displacement pile, a steel wire, a data collection storage transmitter, and a solar panel. The solar panel provides power for the equipment, and the data collection storage transmitter can upload the monitoring data to the cloud in a timely manner. The collection box is located at the top of the slope, and the displacement sensor and the data collection storage transmitter are installed in the collection box.

[0030] The displacement piles are made of steel pipe piles and are distributed on each level of the slope platform along the normal direction of the route at the characteristic sections (such as geological fracture zones, geological fault zones, peaks, valleys, etc.). The displacement piles are driven into a depth of not less than 1 meter. The piles should be backfilled densely around and fixed with concrete. First, a steel wire is drawn from the displacement sensor, and then connected to the displacement piles one by one through the steel wire from the splitter. The steel wires of each displacement pile are in parallel.

[0031] No matter which displacement pile is displaced, it can cause the displacement sensor data to change. When receiving an abnormal data alarm, it means that the displacement pile at the characteristic section is displaced. The surveyor can re-measure the displacement piles one by one. Observe the situation around the abnormal position and preliminarily determine the cause of the abnormal data. If it is caused by manual or mechanical collision, restore the displacement pile and re-measure the initial value to continue monitoring. If it is caused by slope deformation, it should be reported to the supervision unit, the owner unit, and the survey and design unit, and the design unit shall issue a treatment plan. After the treatment is completed, continue monitoring.

[0032] Each set of surface monitoring equipment is arranged at 5-10 points of the slope opening line. The surface monitoring equipment is applicable to all levels of slopes and can conduct comprehensive monitoring of the slopes. The monitoring method is optimized from conventional point monitoring to line monitoring, and the monitoring capacity has been greatly improved.

[0033] In addition, conventional manual monitoring is optimized to intelligent system monitoring. This intelligent slope monitoring system automatically collects and calculates the displacement increment of the displacement sensor in real time 24 hours a day. Once the data exceeds the set allowable range, it can immediately and automatically send an alarm message to the construction unit, supervision unit, owner unit, design unit and other relevant persons in charge. Relevant personnel can quickly activate the emergency plan, deal with abnormal situations in time, shorten the response time and reduce losses.

[0034] Conventional inspections can only discover potential safety hazards when they are inspected at the corresponding locations, and have a strong lag. In addition, they are highly subjective. If they are not discovered or misjudged, the time for discovering abnormal situations will continue to be delayed. The present invention can achieve 24-hour real-time monitoring. If an abnormal situation occurs, the equipment can automatically send an alarm to the monitoring equipment or mobile phone software. Relevant management personnel can receive the alarm and take emergency measures to deal with the abnormality as soon as it occurs on site, thereby reducing loss of personnel and property. In addition, during the intelligent data monitoring process, there is no need for personnel to frequently climb the mountain, and there is no need to stop work on site to wait for monitoring. Operations can be carried out normally, which greatly saves the cost of slope construction, speeds up the construction progress, reduces potential safety hazards, and ensures the safety of people and property.

[0035] The surface monitoring module and surface monitoring equipment are set up to improve the surface displacement monitoring mode from conventional point monitoring to line monitoring, and the displacement piles are connected in parallel to form a whole to avoid mutual interference between the displacement piles, so as to more comprehensively monitor the surface stability of the slope. In addition, the improvement from point monitoring to line monitoring greatly reduces the number of collection boxes, displacement sensors, data collection storage transmitters, and solar panels used, saving cost investment and meeting the requirements of green environmental protection.

[0036] The section detection module quickly determines the re-survey order of the section according to the alarm signal of the surface monitoring module. Specifically, when the displacement sensor sends an alarm signal, the section ranking value of each characteristic section is obtained, and the characteristic sections are sorted in sequence according to the numerical value of the section ranking value, and the characteristic sections are re-surveyed in sequence according to the order.

[0037] The section ranking value of the characteristic section is obtained through the following steps: the surface of the characteristic section is divided by multiple equidistant horizontal lines and multiple vertical lines, and n sampling matrices are generated on the surface of the characteristic section. Based on t cycles, at each cycle node, the soil in each sampling matrix is ​​sampled to obtain a matrix sampling record, and the soil detection value of the sampling matrix is ​​obtained through the matrix sampling record. The matrix inspection value of each sampling matrix is ​​obtained, and the matrix inspection values ​​of all sampling matrices are summed and averaged to obtain the total matrix inspection value, which is marked as YBS, and the matrix influence quantity of the characteristic section at each cycle node is obtained. The matrix influence quantity of h cycle nodes before the current time of the system is summed and averaged to obtain the matrix influence mean, which is marked as PUH. The formula is used The section ranking value PXZ of the characteristic section is obtained, where c1 is the matrix total inspection value coefficient, c2 is the matrix influence mean coefficient, the value of c1 is 0.58, and the value of c2 is 0.69.

[0038] If there are 4 characteristic sections in the slope, which are marked as characteristic section a, characteristic section b, characteristic section c, and characteristic section d respectively, and the section ranking value of characteristic section a > the section ranking value of characteristic section c > the section ranking value of characteristic section d > the section ranking value of characteristic section b, then the characteristic sections are sorted in the order of characteristic section a, characteristic section c, characteristic section d, and characteristic section b, and the characteristic sections are remeasured in the sorting order. When the displacement pile of characteristic section a is detected to be displaced, it is no longer necessary to detect the remaining characteristic sections.

[0039] Matrix sampling records include soil density, soil moisture, sampling time, and soil heterogeneity coefficient.

[0040] The soil inhomogeneity coefficient is obtained through the following steps: determine the mass and particle size distribution of the sampled soil, sort each soil sample according to the particle size, and calculate the cumulative mass ratio at different particle sizes; draw a cumulative curve based on the data of the cumulative mass ratio; and obtain the soil inhomogeneity coefficient by observing and analyzing the shape of the cumulative curve.

[0041] The soil test value is obtained by the following steps: mark the soil density recorded by matrix sampling as TRM, mark the soil moisture recorded by matrix sampling as SFT, mark the soil heterogeneity coefficient recorded by matrix sampling as BJJ, and use the formula The soil detection value JCZ is obtained, where a1 is the soil density coefficient, a2 is the soil moisture coefficient, the value of a1 is 0.92, and the value of a2 is 1.02.

[0042] The matrix detection value of the sampling matrix is ​​obtained by the following steps: obtaining m soil detection values ​​of the same sampling matrix before the current time of the system, summing up all the soil detection values ​​and taking the average value to obtain the soil detection average value, and marking it as RJJ, sorting the soil detection values ​​in the order of sampling time, and performing difference calculation between the next adjacent soil detection value after sorting and the previous soil detection value to obtain the soil detection variable value, when the soil detection variable value is greater than or equal to 0, marking the soil detection variable value as a soil detection appreciation value, when the soil detection variable value is less than 0, marking the soil detection variable value as a soil detection decrement value, summing up all the soil detection appreciation values ​​to obtain the total soil detection appreciation value and marking it as JSZ, obtaining the soil detection variable value marked as the total number of soil detection appreciation values ​​and marking it as SCS, summing up all the soil detection decrements and taking the absolute value to obtain the total soil detection decrement value and marking it as MZP, obtaining the soil detection variable value marked as the total number of soil detection decrements and marking it as DQZ, and using the formula The matrix detection value ZR i of the sampling matrix is ​​obtained, where b1 is the soil detection mean coefficient, the value of b1 is 0.82, and i is the number of the sampling matrix, i=1, 2, ..., n.

[0043] The matrix influence quantity of the periodic node is obtained through the following steps: when the number of difference matrices of the characteristic section at the periodic node is less than 2, no corresponding processing is performed; when the number of difference matrices is greater than or equal to 2, the difference matrices are compared pairwise, the minimum path between the two difference matrices is calculated by the minimum path algorithm, and the minimum path threshold is set; when the minimum path is less than the minimum path threshold, the matrix influence quantity is increased by one; after all the difference matrices in the characteristic section are compared, the matrix influence quantity of the periodic node is obtained.

[0044] For example: the number of difference matrices of the current periodic node is 3, marked as difference matrix 1, difference matrix 2, and difference matrix 3 respectively. Then, it is necessary to compare them two by two 3 times, namely, the comparison between difference matrix 1 and difference matrix 2, the comparison between difference matrix 1 and difference matrix 3, and the comparison between difference matrix 2 and difference matrix 3. The minimum path between difference matrix 1 and difference matrix 2, the minimum path between difference matrix 1 and difference matrix 3, and the minimum path between difference matrix 2 and difference matrix 3 are calculated in turn. If the minimum path between difference matrix 1 and difference matrix 2 is less than the minimum path threshold, the minimum path between difference matrix 1 and difference matrix 3 is greater than the minimum path threshold, and the minimum path between difference matrix 2 and difference matrix 3 is greater than the minimum path threshold, then the number of matrix influences of this periodic node is 1.

[0045] By setting up a section detection module, the section ranking value of each characteristic section can be quickly analyzed after the surface monitoring module alarms, and the detection order of the characteristic sections can be sorted according to the section ranking value, thereby optimizing the detection path of the characteristic sections on the slope by the surveying personnel and reducing the re-survey scope of the surveying personnel.

[0046] Example 2

[0047] Reference Figure 4 On the basis of Example 1, it also includes a deep monitoring module, which monitors the potential sliding surface position of the slope platform through deep monitoring equipment and sends out an alarm signal when the monitoring data changes suddenly.

[0048] The deep monitoring equipment includes a collection box, an inclined side pipe, a fixed inclinometer, a data collection storage transmitter, and a solar panel. The solar panel provides power for the equipment. The inclined side pipe is installed vertically underground. The fixed inclinometer is placed in the inclined side pipe and connected to the data collection storage transmitter. It can collect monitoring data in real time and upload the monitoring data to the cloud.

[0049] Vertical holes are drilled at the location where there is potential slip, and then the inclined side pipe is installed. The inclined side pipe is a PVC pipe with a diameter of 40mm (slightly larger than the diameter of the gyroscope), and the depth exceeds the potential slip surface. The fixed inclinometer is composed of multiple gyroscopes in series. Starting from 50cm below the top of the inclined side pipe, a gyroscope is installed every 1m downward. Each gyroscope collects its own three-dimensional coordinate data in real time and uploads the monitoring data to the cloud through a data acquisition storage transmitter. If a large mutation occurs in the three-dimensional coordinate data of a gyroscope, the intelligent monitoring system will automatically issue an alarm message to the relevant persons in charge such as the construction unit, the supervision unit, the owner unit, and the design unit. The person in charge on site will immediately organize to observe the stability of the slope at the location where the data is abnormal, and preliminarily determine the cause of the abnormal data. If it is caused by manual or mechanical excavation collision, the alarm will be lifted and monitoring will continue; if it is caused by slope deformation, it should be reported to the supervision unit, the owner unit, and the survey and design unit, and the design unit will issue a treatment plan. After the treatment is completed, monitoring will continue.

[0050] Each set of deep monitoring equipment is arranged at the potential sliding surface. The deep monitoring equipment is applicable to all levels of slopes and can monitor possible landslides and other disasters in real time. The monitoring method is optimized from manual manual monitoring to fixed intelligent monitoring, and the monitoring capability has been greatly improved.

[0051] The current deep slope monitoring requires personnel to climb to the inclined side pipe, manually lower the gyroscope, collect the gyroscope's three-dimensional data, and then perform data comparison and processing. This has the disadvantages of monitoring lag and monitoring personnel being in an unsafe environment for a long time.

[0052] The fixed inclinometer is composed of multiple gyroscopes connected in series at a fixed interval. Once placed in the inclined side tube, there is no need to take it out again, and monitoring personnel do not have to climb the mountain frequently.

[0053] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0054] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0055] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0056] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0057] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0058] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0059] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0060] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An automatic monitoring and alarm system for high slope deformation based on the Internet of Things, characterized in that: Including surface monitoring module, cross-section detection module, and deep layer monitoring module; The surface monitoring module monitors the characteristic section of the slope platform through the surface monitoring equipment, and sends out an alarm signal when the monitoring data is abnormal; The section detection module quickly determines the re-measurement sequence of the section according to the alarm signal of the surface monitoring module, and re-measures the section according to the re-measurement sequence; The deep monitoring module monitors the potential sliding surface position of the slope platform through deep monitoring equipment, and sends out an alarm signal when the monitoring data suddenly changes; The section detection module quickly determines the re-measurement order of the section according to the alarm signal of the surface monitoring module. Specifically, when the displacement sensor sends an alarm signal, the section ranking value of each characteristic section is obtained, and the characteristic sections are sorted in order according to the numerical value of the section ranking value, and the characteristic sections are re-measured in order according to the order; The section ranking value of the characteristic section is obtained through the following steps: the surface of the characteristic section is divided by multiple equidistant horizontal lines and multiple vertical lines, and n sampling matrices are generated on the surface of the characteristic section. Based on t cycles, at each cycle node, the soil in each sampling matrix is ​​sampled to obtain a matrix sampling record, and the soil detection value of the sampling matrix is ​​obtained through the matrix sampling record. The matrix inspection value of each sampling matrix is ​​obtained, and the matrix inspection values ​​of all sampling matrices are summed and averaged to obtain the total matrix inspection value, which is marked as YBS, and the matrix influence quantity of the characteristic section at each cycle node is obtained. The matrix influence quantity of h cycle nodes before the current time of the system is summed and averaged to obtain the matrix influence mean, which is marked as PUH. The formula is used The section ranking value PXZ of the characteristic section is obtained, where c1 is the matrix total inspection value coefficient and c2 is the matrix influence mean coefficient; Matrix sampling records include soil density, soil moisture, sampling time, and soil heterogeneity coefficient; The soil test value is obtained by the following steps: mark the soil density recorded by matrix sampling as TRM, mark the soil moisture recorded by matrix sampling as SFT, mark the soil heterogeneity coefficient recorded by matrix sampling as BJJ, and use the formula The soil test value JCZ is obtained, where a1 is the soil density coefficient and a2 is the soil moisture coefficient; The matrix detection value of the sampling matrix is ​​obtained by the following steps: obtaining m soil detection values ​​of the same sampling matrix before the current time of the system, summing up all the soil detection values ​​and taking the average value to obtain the soil detection average value, and marking it as RJJ, sorting the soil detection values ​​in the order of sampling time, and performing difference calculation between the next adjacent soil detection value and the previous soil detection value after sorting to obtain the soil detection variable value, when the soil detection variable value is greater than or equal to 0, marking the soil detection variable value as a soil detection appreciation value, when the soil detection variable value is less than 0, marking the soil detection variable value as a soil detection depreciation value, summing up all the soil detection appreciation values ​​to obtain the total soil detection appreciation value and marking it as JSZ, obtaining the soil detection variable value marked as the total number of soil detection appreciation values ​​and marking it as SCS, summing up all the soil detection depreciation values ​​and taking the absolute value to obtain the total soil detection depreciation value and marking it as MZP, obtaining the soil detection variable value marked as the total number of soil detection depreciation values ​​and marking it as DQZ, and using the formula The matrix detection value ZRi of the sampling matrix is ​​obtained, wherein b1 is the soil detection mean coefficient, i is the number of the sampling matrix, i=1, 2, ..., n; The matrix influence quantity of the periodic node is obtained through the following steps: when the number of difference matrices of the characteristic section at the periodic node is less than 2, no corresponding processing is performed; when the number of difference matrices is greater than or equal to 2, the difference matrices are compared pairwise, the minimum path between the two difference matrices is calculated by the minimum path algorithm, and the minimum path threshold is set; when the minimum path is less than the minimum path threshold, the matrix influence quantity is increased by one; after all the difference matrices in the characteristic section are compared, the matrix influence quantity of the periodic node is obtained.

2. According to the Internet of Things-based high slope deformation automatic monitoring and alarm system of claim 1, it is characterized in that: The surface monitoring equipment includes multiple displacement piles, a wire splitter, a displacement sensor, and multiple steel wires. The multiple displacement piles are distributed at the characteristic section of each slope platform along the normal direction of the slope line. The displacement sensor leads to multiple steel wires through the wire splitter. The multiple steel wires correspond to the multiple displacement piles one by one, and the steel wires connect the displacement piles.

3. The high slope deformation automatic monitoring and alarm system based on the Internet of Things according to claim 2 is characterized in that: When the monitoring data is abnormal, an alarm signal is issued. Specifically, when the data of the displacement sensor changes, the displacement sensor issues an alarm signal.

4. The high slope deformation automatic monitoring and alarm system based on the Internet of Things according to claim 1 is characterized in that: The deep monitoring equipment includes a plurality of inclined side tubes, which are vertically installed at the potential sliding surface position of the slope platform. A fixed inclinometer is arranged in the inclined side tube. The fixed inclinometer is composed of a plurality of gyroscopes connected in series. Each gyroscope collects its own three-dimensional coordinate data in real time. When the three-dimensional coordinate data of the gyroscope changes suddenly, the gyroscope sends out an alarm signal.

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