Complex slope three-dimensional visual modeling calculation and intelligent monitoring system and method

Abstract

The invention discloses a three-dimensional visual modeling calculation and intelligent monitoring system and method for a complex side slope. The system comprises a sensing part, a cloud server and a personal terminal. A landslide disaster risk point is obtained through a simulation analysis unit of the cloud server, a plurality of sensing pieces are embedded in a side slope in an array mode, and the sensing pieces monitor side slope geological deformation in real time; the cloud server is provided with a monitoring and analyzing unit, the monitoring and analyzing unit is connected with the sensing pieces through a first communication module and receives the side slope geological deformation information, the monitoring and analyzing unit analyzes the side slope geological deformation information and judges whether side slope landslide occurs or not, and when monitored geological deformation reaches a threshold value, the monitoring and analyzing unit sends the side slope landslide information to the cloud server. An alarm signal is sent out when the slope landslide is judged; the personal terminal is connected with the monitoring analysis unit through the second communication module, analysis information and alarm signals of the monitoring analysis unit are received in real time, the system is suitable for being used on slopes with complex stratum environments, the automation degree is high, and the monitoring accuracy and durability are improved.

Description

Technical Field

[0001] The invention relates to the field of slope engineering calculation and monitoring, and in particular to a three-dimensional visual modeling calculation and intelligent monitoring system and method for complex slopes. Background Art

[0002] Slope engineering is divided into artificial slopes and natural slopes. Among them, artificial slopes include roads, railway roadbeds, water conservancy project slopes, channel slopes, deep foundation pit slopes and open-pit mine slopes, etc. Natural slopes include naturally formed hillsides and slopes of rivers, lakes and seas. The composition of slopes is complex and varied, including soil slopes, rock slopes, rock-soil binary slopes, engineering slag and solid waste, etc. The scouring and soaking of earthquakes, rainfall and surface water, and the continuous scouring of the slope foot by the natural flow of surface water bodies such as rivers may induce slope landslides. In addition, unreasonable human engineering activities such as excavation of the slope foot, loading on the upper part of the slope, blasting, and reservoir water storage and discharge may also induce slope landslides.

[0003] Slope landslides usually occur very suddenly, and there is often no time to react, which can easily cause very serious casualties and property losses. For this reason, it is necessary to monitor landslides, predict landslide trends, and reduce the occurrence of secondary geological disasters. Effective monitoring of slope landslides is relatively difficult, mainly because the hydrogeological conditions in the area where the slopes are located are often complex and harsh, the main material composition of the slopes is complex, and the risk points inside the slopes are highly hidden. Traditional manual measurement methods have a low degree of automation, a large amount of labor, and it is difficult to achieve long-term real-time measurement; the newly emerging three-dimensional geological modeling method for predicting landslides has problems such as unclear slope stability mechanism, inadequate sensitivity analysis of different inducements, and discontinuous monitoring. For the landslide problem of complex slopes, there is currently a lack of systems and methods that combine three-dimensional modeling numerical analysis with continuous and accurate measurement of landslide trends for monitoring. Summary of the invention

[0004] Based on this, the present invention provides a complex slope three-dimensional visualization modeling calculation and intelligent monitoring system and method, which is suitable for use on slopes with complex geological environments and improves the accuracy and durability of monitoring.

[0005] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides a complex slope three-dimensional visualization modeling calculation and intelligent monitoring system, including a sensing element, a cloud server and a personal terminal; the number of the sensing elements is multiple and they are buried in the slope in an array, and each sensing element is used to monitor the geological deformation of the slope in real time; a monitoring and analysis unit is arranged in the cloud server, and the monitoring and analysis unit is interactively connected with each of the sensing elements through a first communication module and receives the geological deformation information of the slope, the monitoring and analysis unit analyzes the geological deformation information of the slope and determines whether a slope landslide occurs, and sends an alarm signal when it is determined that a slope landslide occurs; the personal terminal is interactively connected with the monitoring and analysis unit through a second communication module, and receives the analysis information and alarm signal of the monitoring and analysis unit in real time.

[0006] Optionally, the cloud server is further provided with a simulation analysis unit, which is used for fine three-dimensional geological modeling of complex slopes and obtaining landslide risk points. Fine three-dimensional geological modeling of the slope is performed by the simulation analysis unit to achieve numerical simulation analysis of the slope. Based on the landslide risk points established by the simulation analysis unit, the sensing parts are arranged at the landslide risk points for key monitoring.

[0007] The visual modeling includes: step 1) using software to establish a slope twin model, based on full-condition dynamic analysis, using complex geological model hexahedral grid division to perform fine characterization of irregular strata and multiple faults in the slope twin model; using solid-liquid coupling to perform progressive destruction numerical simulation on the lower slope of the slope twin model, and generate a preliminary complex slope three-dimensional visual twin model;

[0008] Step 2) using image recognition technology, survey point cloud data, and geological survey data to process the preliminary complex slope three-dimensional visualization twin model of step 1) into a fuzzy three-dimensional geological model; based on the refined multi-stratum model field mapping technology, the standard cube grid model in the fuzzy three-dimensional geological model is mapped into a complex geological model of multiple strata, and the fuzzy three-dimensional geological model is converted into a numerical model for numerical simulation calculation, wherein the numerical model includes three-dimensional visual real-time data;

[0009] Step 3) Write a fast slope calculation program, which first calculates each real-life slope model in the slope data set, analyzes the potential landslide hazard points under different working conditions in the real-life slope model, and establishes a virtual-reality deep learning database; secondly, based on the virtual-reality deep learning database, the three-dimensional visual real-time data in step 2) is analyzed through real-time learning and feedback to obtain risk points; finally, the various sensors are arranged according to the location of the risk points.

[0010] Optionally, the sensing element consists of three parts: a main body, an ultrasonic measurement module and a tail wing; an ultrasonic measurement module is provided at one end of the main body, and a tail wing is provided at the other end; the main body is buried in the slope, and when the main body is affected by the geological deformation of the slope, the axial length changes, and the axial length change causes the sound wave time difference and amplitude attenuation degree of the ultrasonic measurement module to change, so as to realize real-time monitoring of the slope.

[0011] Optionally, the monitoring and analysis unit is connected to the ultrasonic measurement module, and the monitoring and analysis unit analyzes the degree of geological deformation of the slope according to the received sound wave time difference and amplitude attenuation degree change information, and determines the landslide situation of the slope.

[0012] Optionally, the first communication module includes an expander and a lead wire, the expander is provided with multiple channels, and the working ports of each channel of the expander are connected to the sensing element through the lead wires. The expander is interactively connected with the cloud server through a router and a local area network to carry out field monitoring of multiple slopes in an orderly manner.

[0013] Optionally, a temperature sensor is provided on the sensing element; the expander is provided with a temperature collection component, the temperature sensor interacts with the expander through the temperature collection component, the temperature collection component collects the temperature of the slope and uploads the temperature data to a monitoring and analysis unit, and the monitoring and analysis unit determines the landslide situation of the slope based on the geological deformation degree information of the slope and the temperature data.

[0014] Optionally, the second communication module is provided with a wireless signal transmitter, and the personal terminal is provided with a wireless signal receiver corresponding to the wireless signal transmitter. The personal terminal includes but is not limited to a personal computer or a mobile phone, so that individuals can receive warning information in real time and provide warning timeliness.

[0015] In order to achieve the above-mentioned object, in a second aspect, the present invention provides a complex slope three-dimensional visualization modeling calculation and intelligent monitoring method, which is characterized by comprising:

[0016] S100. Performing refined three-dimensional geological modeling of the slope through a simulation analysis unit of a cloud server to obtain landslide disaster risk points;

[0017] S200. Construct a landslide monitoring and early warning system, bury sensors in array at the risk point of landslide disaster on the slope to monitor the geological deformation of the slope, and transmit the geological deformation information to the monitoring and analysis unit in real time through the first communication module;

[0018] S300. The geological deformation signal is analyzed in real time by the monitoring and analysis unit. When the monitored geological deformation reaches a threshold, the monitoring and analysis unit determines that the slope has collapsed and issues a warning signal;

[0019] S400. Send a warning signal of slope landslide to a personal terminal through the second communication module.

[0020] Optionally, the method for obtaining landslide hazard risk points through three-dimensional visual modeling includes:

[0021] S110. Use the irregular strata and multiple faults refinement characterization method to carry out refined 3D geological modeling of complex slopes;

[0022] S120. Use the hexahedral meshing method to divide the grid for complex geological models;

[0023] S130. Simulate the large deformation process of landslide through numerical simulation calculation;

[0024] S140. Analyze the sensitivity of different influencing factors such as weak structural layers, water level changes, rainfall, slope morphology changes, earthquakes, etc., and obtain landslide disaster risk points.

[0025] Optionally, the data processing unit controls the working port of the expander and completes data collection, analysis and calculation, including:

[0026] S310. The simulation analysis unit collects and processes ultrasonic data to obtain the sound wave time difference P, the ultrasonic amplitude attenuation degree change value A, the frequency spectrum change value f and the deformation degree judgment value B; wherein the sound wave time difference P is the difference between the standard sound wave receiving time when the sensing part is not deformed and the sound wave receiving time measured by the ultrasonic sensor after the sensing part is inserted into the slope; wherein the ultrasonic amplitude attenuation degree change value A is the difference between the standard ultrasonic amplitude attenuation value when the sensing part is not deformed and the ultrasonic amplitude attenuation value measured by the ultrasonic sensor after the sensing part is inserted into the slope; wherein the frequency spectrum change value f is the difference between the standard frequency spectrum when the sensing part is not deformed and the frequency spectrum measured after the sensing part is inserted into the slope, and the frequency spectrum is obtained by the ultrasonic signal through the Fourier transform formula.

[0027] S320. The numerical analysis unit predicts the slope landslide, and the data processing unit processes the data to obtain the deformation degree determination value B.

[0028] B=P+(KT·ΔT+Tb)·a+A·b+f·c

[0029] Wherein, a, b, c are weighted coefficients, KT is the temperature coefficient, ΔT is the temperature change value of the sensing element, and Tb is the initial temperature of the sensing element;

[0030] S330. Set a threshold value Y, and compare the deformation degree determination value B with the set threshold value Y:

[0031] When the judgment value B>Y, it is determined that the slope has landslide, and a signal is sent to the cloud server through the communication module;

[0032] When the judgment value B≤Y, the slope is judged to be normal.

[0033] The technical advantages of a complex slope three-dimensional visualization modeling calculation and intelligent monitoring system and method provided by the present invention are at least reflected in:

[0034] First, based on the design concept of early warning and high-precision real-time monitoring, through refined three-dimensional geological modeling and numerical simulation of the slope, sensitive factors and risk locations are dynamically identified to provide early warning. On this basis, an intelligent monitoring system is established to monitor the implementation of slope landslides, improve the accuracy and durability of monitoring, and is suitable for use on slopes with complex geological environments.

[0035] Secondly, based on the geological characteristics of the slope, a refined three-dimensional geological modeling is established, and numerical simulation of multi-factor sensitivity analysis is carried out on slope stability. The changing characteristics of slope stability under the influence of multiple influencing factors are considered, the predisposing risks are identified, the dangerous locations are determined, the evolution process of the landslide body is understood and mastered, and the characteristic information of landslide disasters can be captured in a timely and accurate manner, the pertinence and scientific nature of subsequent monitoring can be improved, and landslide risks can be accurately identified.

[0036] Thirdly, based on refined three-dimensional geological modeling and numerical simulation, a landslide monitoring and early warning system is constructed. By combining ultrasonic stress detection technology, data transmission technology, cloud computing and big data analysis technology, real-time and long-distance precise monitoring of slopes is carried out, basic geological disaster early warning is timely, and landslide monitoring is uninterruptedly controlled in real time, so as to issue alarms in time before landslides form secondary disasters and avoid loss of life and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. The accompanying drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention.

[0038] Figure 1 A schematic diagram of an embodiment of a complex slope three-dimensional visual modeling calculation and intelligent monitoring system is provided;

[0039] Figure 2 A block diagram of an embodiment of the complex slope three-dimensional visualization modeling calculation and intelligent monitoring system provided;

[0040] Figure 3 A schematic structural diagram of an embodiment of the provided induction element;

[0041] Figure 4 A flowchart of an embodiment of the provided complex slope three-dimensional visualization modeling calculation and intelligent monitoring method;

[0042] Figure 5 A flowchart of an embodiment of a method for obtaining landslide hazard risk points through three-dimensional visual modeling is provided;

[0043] Figure 6 A flowchart of an embodiment of data collection, analysis and calculation by a data processing unit is provided;

[0044] Description of the accompanying drawings:

[0045] In the figure, 1 is a personal terminal, 2 is a cloud server, 21 is a monitoring and analysis unit, 22 is a simulation analysis unit, 3 is a sensor, 31 is an ultrasonic measurement module, 32 is a body, 33 is a tail wing, 4 is an extender, 5 is a router, 6 is a local area network, and 7 is a temperature collection component. DETAILED DESCRIPTION

[0046] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. The description of the exemplary embodiments is merely illustrative and is in no way intended to limit the present disclosure and its application or use. The present disclosure can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to make the present disclosure thorough and complete and to fully express the scope of the present disclosure to those skilled in the art. It should be noted that unless otherwise specifically stated, the relative arrangement of the components and steps, the composition of the materials, the numerical expressions and the numerical values ​​set forth in these embodiments should be interpreted as being merely exemplary and not as limiting.

[0047] In the process of monitoring slope landslides, both the traditional manual measurement method and the currently popular three-dimensional geological modeling have some technical problems. This is mainly because the hydrogeological conditions in the area where the slope is located are often complex and harsh, the main material composition of the slope is complex, and the risk points inside the slope are highly hidden, making the monitoring of slope landslides more difficult. The traditional manual measurement method has a low degree of automation, a large amount of labor, and it is difficult to achieve long-term real-time measurement. The method of using three-dimensional geological modeling to predict landslides has problems such as unclear slope stability mechanism, inadequate sensitivity analysis of different inducements, and discontinuous monitoring.

[0048] like Figure 1 , Figure 2As shown, a complex slope three-dimensional visualization modeling calculation and intelligent monitoring system provided by the present invention includes a sensor 3, a cloud server 2 and a personal terminal 1. The landslide disaster risk point is obtained through the simulation analysis unit 22 in the cloud server 2; the sensor 3 includes a plurality of sensors and arrays buried in the slope based on the landslide disaster risk point obtained by the simulation analysis unit 22, and each sensor 3 is used to monitor the geological deformation of the slope in real time; a monitoring and analysis unit 21 is set in the cloud server 2, and the monitoring and analysis unit 21 is connected to each sensor 3 through a first communication module and receives the geological deformation information of the slope. The monitoring and analysis unit analyzes the geological deformation information of the slope and determines whether a slope landslide occurs. When the monitored geological deformation reaches a threshold, an alarm signal is issued when it is determined that the slope has landslide; the personal terminal 1 is connected to the monitoring and analysis unit 21 through a second communication module, and receives the analysis information and alarm signal of the monitoring and analysis unit 21 in real time. It is suitable for slopes with complex stratum environments, has a high degree of automation, and improves the accuracy and durability of system monitoring.

[0049] like Figure 4 As shown, in some preferred embodiments, the above-mentioned complex slope three-dimensional visualization modeling calculation and intelligent monitoring system is used to perform slope monitoring. The present invention provides a complex slope three-dimensional visualization modeling calculation and intelligent monitoring method, including:

[0050] S100. Performing refined three-dimensional geological modeling of the slope through the simulation analysis unit 22 of the cloud server 2 to obtain landslide disaster risk points;

[0051] S200. Construct a landslide monitoring and early warning system, bury the sensor element 3 in the slope array to monitor the geological deformation of the slope, and transmit the geological deformation information to the monitoring and analysis unit 21 in real time through the first communication module;

[0052] S300. The geological deformation signal is analyzed in real time by the monitoring and analysis unit 21. When the monitored geological deformation reaches the threshold, the monitoring and analysis unit 21 determines that the slope has collapsed and issues a warning signal;

[0053] S400. Send a warning signal of slope landslide to the personal terminal 1 through the second communication module.

[0054] Based on the design concept of early warning and high-precision real-time monitoring, through refined three-dimensional geological modeling and numerical simulation of the slope, sensitive factors and risk locations are dynamically identified to provide early warning. On this basis, an intelligent monitoring system is established to monitor the implementation of slope landslides, improve the accuracy and durability of monitoring, and is suitable for use on slopes with complex geological environments.

[0055] like Figure 5 As shown, in some preferred embodiments, the method for obtaining landslide hazard risk points through three-dimensional visual modeling includes:

[0056] S110. Use the irregular strata and multiple faults refinement characterization method to carry out refined 3D geological modeling of complex slopes;

[0057] S120. Use the hexahedral meshing method to divide the grid for complex geological models;

[0058] S130. Simulate the large deformation process of landslide through numerical simulation calculation;

[0059] S140. Analyze the sensitivity of different influencing factors such as weak structural layers, water level changes, rainfall, slope morphology changes, earthquakes, etc., and obtain landslide disaster risk points.

[0060] Combined with the geological characteristics of the slope, a refined three-dimensional geological modeling is established, and numerical simulation of multi-factor sensitivity analysis is carried out on slope stability. The changing characteristics of slope stability under the influence of multiple influencing factors are considered, the predisposing risks are identified, the dangerous locations are determined, the evolution process of the landslide body is understood and mastered, and the characteristic information of landslide disasters can be captured timely and accurately. It is suitable for various natural and artificial slopes. The sensitivity factors that can be analyzed include earthquakes, precipitation, water level changes, slope changes, scour, soft interlayers, etc., which improves the pertinence and scientificity of subsequent monitoring and accurately identifies landslide risks.

[0061] In a preferred embodiment, the cloud server 2 is further provided with a simulation analysis unit 22, which is used for fine three-dimensional geological modeling of complex slopes and obtaining landslide risk points. Through fine three-dimensional geological modeling and numerical simulation methods, complex geological model hexahedral meshing technology and irregular strata and multiple faults fine characterization methods are adopted, and the complex slope is completely modeled using field mapping technology and multiple dangerous interlayer judgment methods, and connected with numerical simulation calculations, and the re-meshing technology is adopted to simulate the large deformation problem of landslides, analyze the sensitivity of different influencing factors such as weak structural layers, water level changes, rainfall, slope morphology changes, earthquakes, etc., and fully reveal the risk points of landslide disasters.

[0062] Furthermore, the slope twin model can be established using general geotechnical engineering software, such as Plaxis, Abaqus, and GeoStudio. The slope twin model is more refined than ordinary grid division technology, and can achieve refined characterization of irregular strata and multiple faults. It can also be used for numerical simulation of progressive slope failure under solid-liquid coupling.

[0063] Furthermore, a fast slope calculation program can simultaneously perform calculations on more than 3,000 real-life model engineering examples in a short period of time (30 minutes), analyze potential landslide hazard points under different working conditions, and quickly establish a virtual-reality deep learning database.

[0064] Furthermore, the monitoring and analysis unit 21 is connected to the ultrasonic measurement module 31, and the monitoring and analysis module analyzes the geological deformation degree of the slope according to the received sound wave time difference and amplitude attenuation degree change information, and determines the landslide situation of the slope.

[0065] The first communication module includes an expander 4 and lead wires. The expander 4 is multi-channel, and each working port of the multi-channel of the expander 4 is connected to the induction component 3 through lead wires. The induction component 3 is provided with a temperature sensor, and the expander 4 is provided with a temperature acquisition component 7. The temperature acquisition component 7 performs temperature acquisition and uploads the temperature data to the cloud server 2 of the monitoring and analysis unit 21 through the router 5 and the local area network 6. The monitoring and analysis unit 21 determines the slope landslide situation in combination with the slope geological deformation degree information and the temperature data.

[0066] Furthermore, the second communication module is provided with a wireless signal transmitter, and the personal terminal 1 is provided with a corresponding wireless signal receiver. The personal terminal 1 includes but is not limited to a personal computer or a mobile phone.

[0067] The landslide monitoring and early warning system is constructed by using ultrasonic stress detection technology, data transmission technology, cloud computing and big data data analysis technology. Based on the purpose of high-precision real-time monitoring and early warning, a landslide monitoring and early warning system is proposed. It realizes functions such as all-weather real-time monitoring of slopes, automatic alarm positioning of risk locations, automatic analysis of early warning predictions, and risk point information query management. Among them, the cloud server 2 is the core of the system, which is used to receive the detection and judgment results of the ultrasonic stress measurement module; the communication module is used to transmit the detection results of the ultrasonic stress measurement module to the cloud server 2.

[0068] like Figure 3As shown, the sensing element 3 includes a main body 32 and a plurality of tail wings 33 arranged on the main body 32. An ultrasonic measurement module 31 is arranged at one end of the main body 32. The main body 32 is buried in the slope. When subjected to the geological deformation of the slope, the axial length changes. The axial length change causes the acoustic wave time difference and amplitude attenuation of the ultrasonic measurement module to change. In a specific implementation, the landslide is monitored based on the deformation degree of the sensing element 3 in the slope. The ultrasonic stress measurement module 31 is used to collect and process the slope deformation data of the sensing element 3, save and process it, and transmit it to the monitoring and analysis unit 21. The monitoring and analysis unit 21 is used to determine the landslide situation. When a landslide occurs on the slope, the sensing element 3 is deformed by force and its temperature changes. The ultrasonic stress measurement module 31 monitors the deformation degree of the sensing element 3 and the temperature information collected by the temperature collection component 7 in real time. When the deformation degree reaches a certain level, the monitoring and analysis unit 21 determines that a landslide has occurred on the slope and sends a landslide warning to the cloud server 2 through the first communication module. The data transmission module of the first communication module can be wireless, 4G or 5G. The cloud server 2 can push the signal to the PC or mobile phone of the personal terminal 1.

[0069] Ultrasonic stress detection technology, data transmission technology, cloud computing and big data analysis technology are used. Based on the purpose of high-precision real-time monitoring and early warning, a landslide monitoring and early warning system is proposed to achieve all-weather real-time monitoring of slopes, automatic alarm positioning of risk locations, automatic analysis of early warning predictions, and risk point information query management. Based on refined three-dimensional geological modeling and numerical simulation, an intelligent monitoring system is established. Combined with ultrasonic stress detection technology, data transmission technology, cloud computing and big data analysis technology, real-time long-distance and precise monitoring of slopes is carried out, basic geological disaster warnings are timely, and landslide monitoring is uninterrupted in real-time control, so as to issue an alarm in time before the landslide forms a secondary disaster to avoid the loss of life and property.

[0070] like Figure 6 As shown, the steps of data collection, analysis and calculation performed by the data processing unit include:

[0071] S310. The simulation analysis unit 22 collects and processes the ultrasonic data to obtain the acoustic time difference P, the ultrasonic amplitude attenuation degree change value A, the frequency spectrum change value f and the deformation degree determination value B;

[0072] S320. Perform slope landslide prediction through the numerical analysis unit, and obtain the deformation degree determination value B through data processing by the data processing unit

[0073] B=P+(KT·ΔT+Tb)·a+A·b+f·c

[0074] Wherein, a, b, c are weighted coefficients, KT is the temperature coefficient, ΔT is the temperature change value of the sensing element, and Tb is the initial temperature of the sensing element;

[0075] S330. Set a threshold value Y, and compare the deformation degree determination value B with the set threshold value Y:

[0076] S340. When the determination value B>Y, it is determined that the slope has landslided, and a signal is sent to the cloud server 2 through the communication module;

[0077] S350. When the judgment value B≤Y, the slope is judged to be normal.

[0078] Monitoring technologies include ultrasonic stress detection technology, optical fiber detection technology, data transmission technology, cloud computing and big data analysis technology;

[0079] Wherein, the sound wave time difference P is the difference between the standard sound wave receiving time when the sensing part 3 is not deformed and the sound wave receiving time measured by the ultrasonic sensor after the sensing part 3 is inserted into the slope; wherein, the ultrasonic amplitude attenuation degree change value A is the difference between the standard ultrasonic amplitude attenuation value when the sensing part 3 is not deformed and the ultrasonic amplitude attenuation value measured by the ultrasonic sensor after the sensing part 3 is inserted into the slope; wherein, the frequency spectrum change value f is the difference between the standard frequency spectrum when the sensing part 3 is not deformed and the frequency spectrum measured after the sensing part 3 is inserted into the slope, and the frequency spectrum is obtained by the ultrasonic signal through the Fourier transform formula.

[0080] The present invention provides a complex slope three-dimensional visualization modeling calculation and intelligent monitoring system and method, which is based on the design concept of early warning and high-precision real-time monitoring. Through refined three-dimensional geological modeling and numerical simulation of the slope, combined with the geological characteristics of the slope, numerical simulation of multi-factor sensitivity analysis is carried out for slope stability, and the characteristics of slope stability changes under the action of multiple influencing factors are considered to identify the risk of inducements, determine the dangerous location, understand and master the evolution process of the landslide body, and can timely and accurately capture the characteristic information of landslide disasters, and carry out early warning. On this basis, an intelligent monitoring system is established to carry out real-time monitoring of slope landslides, real-time long-distance and fine monitoring of slopes, timely basic geological disaster warning, and uninterrupted real-time control of landslide monitoring, so as to issue an alarm in time before the landslide forms a secondary disaster, improve the accuracy and durability of monitoring, and be suitable for slopes with complex stratum environments. It improves the pertinence and scientificity of subsequent monitoring, accurately identifies landslide risks, and avoids the loss of life and property.

[0081] Finally, it should be noted that although some specific embodiments of the present disclosure have been described in detail through examples, those skilled in the art should understand that the above examples are only for illustration and are not intended to limit the scope of the present disclosure. Those skilled in the art should understand that the above embodiments may be modified or some technical features may be replaced by equivalents without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A complex slope three-dimensional visualization modeling calculation and intelligent monitoring system, characterized by: It comprises a sensor (3), a cloud server (2) and a personal terminal (1); The sensing elements (3) are multiple in number and are buried in the slope in an array, and each sensing element (3) is used to monitor the geological deformation information of the slope in real time; The cloud server (2) is provided with a monitoring and analysis unit (21), the monitoring and analysis unit (21) is interactively connected with each of the sensing elements (3) through a first communication module and receives slope geological deformation information; the monitoring and analysis unit (21) analyzes the slope geological deformation information and determines whether a slope landslide occurs, and sends an alarm signal when it is determined that a slope landslide occurs; The personal terminal (1) is interactively connected to the monitoring and analysis unit (21) via the second communication module, and receives analysis information and alarm signals from the monitoring and analysis unit (21) in real time.

2. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 1 is characterized by: The cloud server (2) is also provided with a simulation analysis unit (22), and the simulation analysis unit (22) is used for visual modeling, and based on the visual modeling, a refined three-dimensional geological modeling of a complex slope is achieved and landslide disaster risk points are obtained; The visual modeling includes: step 1) using software to establish a slope twin model, based on full-condition dynamic analysis, using complex geological model hexahedral meshing to perform refined characterization of irregular strata and multiple faults in the slope twin model; using solid-liquid coupling to perform progressive destruction numerical simulation of the lower slope of the slope twin model, and generate a preliminary complex slope three-dimensional visual twin model; Step 2) Process the preliminary complex slope 3D visualization twin model of step 1) into a fuzzy 3D geological model using image recognition technology, survey point cloud data, and geological survey data; Map the standard cube grid model in the fuzzy 3D geological model into a complex geological model of multiple strata based on the refined multi-stratum model field mapping technology, and convert the fuzzy 3D geological model into a numerical model for numerical simulation calculation, the numerical model including 3D visual real-time data; Step 3) Write a fast slope calculation program. The program first calculates each real-life slope model in the slope data set, analyzes the potential landslide hazard points under different working conditions in the real-life slope model, and establishes a virtual-reality deep learning database. Secondly, based on the virtual-reality deep learning database, the three-dimensional visual real-time data in step 2) is analyzed through real-time learning and feedback to obtain risk points. Finally, various sensing components are arranged according to the location of the risk points (3).

3. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 1 is characterized by: The sensing element (3) is composed of three parts: a body (32), an ultrasonic measuring module (31) and a tail wing (33); one end of the body (32) is provided with the ultrasonic measuring module (31), and the other end is provided with the tail wing (33); the body (32) is buried in the slope, and when the body (32) is subjected to the geological deformation of the slope, the axial length changes, and the axial length change causes the sound wave time difference and amplitude attenuation degree of the ultrasonic measuring module (31) to change.

4. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 3 is characterized by: The monitoring and analysis unit (21) is connected to the ultrasonic measurement module (31), and the monitoring and analysis unit (21) analyzes the degree of geological deformation of the slope based on the received sound wave time difference and amplitude attenuation degree change information, and determines the slope landslide situation.

5. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 1 is characterized by: The first communication module comprises an expander (4) and lead wires, the expander (4) being provided with multiple channels, and the working ports of the channels of the expander (4) being connected to the sensing element (3) via lead wires. The expander (4) is interactively connected to the cloud server (2) via a router (5) and a local area network (6).

6. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 5 is characterized by: The sensing element (3) is provided with a temperature sensor, the expander (4) is provided with a temperature collection component (7), the temperature sensor interacts with the expander (4) via the temperature collection component (7), the temperature collection component (7) collects the temperature of the slope and uploads the temperature data to the monitoring and analysis unit (21), and the monitoring and analysis unit (21) determines the landslide condition of the slope in combination with the geological deformation degree information of the slope and the temperature data.

7. The complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to claim 1 is characterized by: The second communication module is provided with a wireless signal transmitter, the personal terminal (1) is provided with a wireless signal receiver corresponding to the wireless signal transmitter, and the personal terminal (1) is a personal computer or a mobile phone.

8. A method for performing intelligent monitoring using the complex slope three-dimensional visualization modeling calculation and intelligent monitoring system according to any one of claims 1 to 7, characterized in that: include: S100. Performing a refined three-dimensional geological modeling of the slope through the simulation analysis unit (22) of the cloud server (2) to obtain landslide disaster risk points; S200. Constructing a landslide monitoring and early warning system, burying sensing elements (3) in array at the landslide risk point of the slope to monitor the geological deformation of the slope, and transmitting the geological deformation information to the monitoring and analysis unit (21) in real time through the first communication module; S300. The geological deformation signal is analyzed in real time by the monitoring and analysis unit (21). When the monitored geological deformation reaches a threshold value, the monitoring and analysis unit (21) determines that the slope has collapsed and issues a warning signal; S400. Sending a warning signal of slope landslide to the personal terminal (1) through the second communication module.

9. The intelligent monitoring method according to claim 8, characterized in that: The method of obtaining landslide risk points through 3D visualization modeling includes: S110. Use the irregular strata and multiple faults refinement characterization method to carry out refined 3D geological modeling of complex slopes; S120. Use the hexahedral meshing method to divide the grid for complex geological models; S130. Simulate the large deformation process of landslide through numerical simulation calculation; S140. Analyze the sensitivity of different influencing factors such as weak structural layers, water level changes, rainfall, slope morphology changes, and earthquakes to obtain landslide disaster risk points.

10. The intelligent monitoring method according to claim 8, characterized in that: Data collection, analysis and calculation are performed by the data processing unit, and the steps include: S310. The simulation analysis unit (22) collects and processes the ultrasonic data to obtain the acoustic time difference P, the ultrasonic amplitude attenuation degree change value A, the frequency spectrum change value f and the deformation degree determination value B; wherein the acoustic wave time difference P is the difference between the standard acoustic wave receiving time when the sensing element (3) is not deformed and the acoustic wave receiving time measured by the ultrasonic sensor after the sensing element (3) is inserted into the slope; wherein the ultrasonic amplitude attenuation degree change value A is the difference between the standard ultrasonic amplitude attenuation value when the sensing element (3) is not deformed and the ultrasonic amplitude attenuation value measured by the ultrasonic sensor after the sensing element (3) is inserted into the slope; wherein the frequency spectrum change value f is the difference between the standard frequency spectrum when the sensing element (3) is not deformed and the frequency spectrum measured after the sensing element (3) is inserted into the slope, and the frequency spectrum is obtained by the ultrasonic signal through the Fourier transform formula; S320. Predicting the slope landslide by the numerical analysis unit, and obtaining the deformation degree determination value B by the data processing unit; B=P+(KT•ΔT+Tb)•a+A•b+f•c Wherein, a, b, c are weighted coefficients, KT is the temperature coefficient, ΔT is the temperature change value of the sensing element, and Tb is the initial temperature of the sensing element; S330. Set a threshold value Y, and compare the deformation degree determination value B with the set threshold value Y: S340. When the deformation degree determination value B>Y, it is determined that the slope has landslided, and a signal is sent to the cloud server (2) through the communication module; S350. When the deformation degree judgment value B≤Y, the slope is judged to be normal.

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