Online Monitoring Method and System for Slope Stability Based on Intelligent Sensors

Abstract

The present invention discloses an online monitoring method and system for slope stability based on intelligent sensors, which relates to the technical field of slope monitoring. The method includes the following steps: analyzing the degree of influence of stress data based on environmental influence parameters; performing primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment on stress data with a first-level degree of influence; performing data correction and secondary transmission adjustment on stress data with a second-level degree of influence; performing secondary acquisition adjustment on stress data with a third-level degree of influence, and transmitting the stress data to the receiving end through wireless transmission. By grading and adjusting the acquisition process and transmission process of stress when monitoring the stress of the slope, the present invention achieves the effect of accurately monitoring the slope stability by timely and accurately monitoring the stress of the slope, and solves the problem of low accuracy of slope stability monitoring according to sensors in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of slope monitoring, and particularly to an online slope stability monitoring method and system based on intelligent sensors. Background Art

[0002] Online slope stability monitoring is a technical means for real-time monitoring of the stability and safety of slope engineering. However, due to the complex geological environment, variable natural factors, and the influence of human activities, the stability and safety of slope engineering face severe challenges. Although traditional slope engineering monitoring methods can provide warning information to a certain extent, they have problems such as limited monitoring range, low monitoring frequency, and high maintenance costs. Therefore, an intelligent monitoring and warning method that can monitor slope changes in real time, automatically, and remotely, and give early warnings of slope disasters has emerged, that is, online slope stability monitoring through intelligent sensors.

[0003] Existing slope stability monitoring systems monitor key data such as the stress, displacement, and water content of slopes in real time through stress sensors, displacement sensors, water content sensors, etc., and combine Internet of Things technology, big data processing, and artificial intelligence to monitor and evaluate the stability of slopes.

[0004] For example, a slope zoning anisotropic stability analysis method and device disclosed in a patent application with the publication number: CN119442407A includes: obtaining geological structure information of a slope; constructing a finite element model based on the geological structure information; performing zoning anisotropic analysis on slope rock and soil masses based on the finite element model; constructing a full-process change analysis model of zoning anisotropy under dynamic load application; and performing coupling analysis and processing on the full-process change analysis model and the seepage field to obtain the slope stability analysis result.

[0005] For example, an open-pit mine slope stability safety assessment system disclosed in an invention patent announcement with the publication number: CN118132899B includes: a sensor arrangement module, a slope data acquisition module, a data preprocessing module, a rock and soil fissure monitoring module, a slope stress analysis module, a weight setting and distribution module, a stability model establishment module, a safety level assessment module, and an assessment result output module. The primary data information of the open-pit mine slope is collected by sensors, the rock and soil permeability coefficient is calculated through a rock and soil fissure monitoring mathematical model, the slope stress coefficient is calculated through a slope stress analysis mathematical model, corresponding weights are set, and a mathematical model is established to calculate the mine slope stability index, judge the stability of the mine slope, and perform safety level assessment on the mine slope.

[0006] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0007] In the prior art, during the use of sensors for slope stability monitoring of slopes, due to possible sudden changes in the slope environment, it will affect the process of data acquisition and data transmission by the sensors, resulting in inaccurate results of slope stability monitoring based on the data obtained by the sensors, and there is a problem of low accuracy of slope stability monitoring according to the sensors. Summary of the Invention

[0008] By providing an online slope stability monitoring method and system based on intelligent sensors in the embodiments of the present application, the problem of low accuracy of slope stability monitoring according to sensors in the prior art is solved, and accurate slope stability monitoring is realized according to the sensors.

[0009] The embodiments of the present application provide an online slope stability monitoring method based on intelligent sensors, including the following steps: monitoring the process of obtaining stress data of the slope to obtain the environmental influence parameters of the stress data, and analyzing the degree of influence of the stress data according to the environmental influence parameters of the stress data; performing primary acquisition adjustment, primary transmission adjustment, and standby transmission adjustment on the stress data with a primary degree of influence, and transmitting the stress data to the receiving end through wireless transmission; performing data correction and secondary transmission adjustment on the stress data with a secondary degree of influence, and transmitting the stress data to the receiving end through wireless transmission; performing secondary acquisition adjustment on the stress data with a tertiary degree of influence, and transmitting the stress data to the receiving end through wireless transmission.

[0010] Furthermore, the environmental influence parameters of the stress data include: the stress data change range, the stress data quantity, the groundwater level height of the stress sensor environment, the pore water pressure of the stress sensor environment, and the groundwater flow velocity of the stress sensor environment; the specific process of analyzing the influence degree of the stress data based on the environmental influence parameters of the stress data is as follows: consider the data range deviation between the stress data change range and the preset stress change range, and perform a weighted operation on the result of the data range deviation consideration through the data range weight ratio to obtain the data range index; consider the data quantity deviation between the stress data quantity and the preset stress data quantity, and perform a weighted operation on the result of the data quantity deviation consideration through the data quantity weight ratio to obtain the data quantity index; perform a coupling process on the data range index and the data quantity index, and perform a weighted operation on the result of the coupling process through the stress data change weight ratio to obtain the stress data change coefficient; consider the groundwater level height deviation after comparing the groundwater level height of the stress sensor environment with the preset groundwater level height of the stress sensor environment, and perform a weighted operation on the result of the groundwater level height deviation consideration through the groundwater level height weight ratio to obtain the groundwater level height index; consider the pore water pressure deviation after comparing the pore water pressure of the stress sensor environment with the preset pore water pressure of the stress sensor environment, and perform a weighted operation on the result of the pore water pressure deviation consideration through the pore water pressure weight ratio to obtain the pore water pressure index; consider the groundwater flow velocity deviation after comparing the groundwater flow velocity of the stress sensor environment with the preset groundwater flow velocity of the stress sensor environment, and perform a weighted operation on the result of the groundwater flow velocity deviation consideration through the groundwater flow velocity weight ratio to obtain the groundwater flow velocity index; perform a coupling process on the groundwater level height index, the pore water pressure index, and the groundwater flow velocity index, and perform a weighted operation on the result of the coupling process through the sensor environment change weight ratio to obtain the sensor environment change coefficient; obtain the stress data environmental influence degree index by performing a coupling process on the stress data change coefficient and the sensor environment change coefficient, and the stress data environmental influence degree index is used to quantitatively analyze the influence degree of the stress data by the environment during data acquisition; analyze the influence degree of the stress data based on the stress data environmental influence degree index.

[0011] Further, the specific analysis process for analyzing the degree of influence of stress data according to the environmental influence degree index of stress data is as follows: Compare the environmental influence degree index of stress data with the preset first threshold of environmental influence degree and the second threshold of environmental influence degree obtained from the database. When the environmental influence degree index of stress data is less than the preset first threshold of environmental influence degree obtained from the database, record the degree of influence of stress data as level three; when the environmental influence degree index of stress data is not less than the preset first threshold of environmental influence degree obtained from the database and not greater than the second threshold of environmental influence degree, record the degree of influence of stress data as level two; when the environmental influence degree index of stress data is greater than the second threshold of environmental influence degree, record the degree of influence of stress data as level one.

[0012] Further, the first-level acquisition adjustment refers to obtaining a new acquisition frequency of stress data according to the environmental influence degree index of stress data, and acquiring stress data at the new acquisition frequency of stress data; the first-level transmission adjustment refers to obtaining a new transmission frequency of stress data according to the environmental influence degree index of stress data, and wirelessly transmitting the stress data to the receiving end at the new transmission frequency of stress data; the backup transmission adjustment refers to modulating the stress data acquired at the new acquisition frequency of stress data onto an ultra-wideband signal and wirelessly transmitting it to the receiving end.

[0013] Further, the specific process of data correction is as follows: Collect backup stress data through a backup device at the acquisition frequency of stress data when the degree of influence of stress data is level two; obtain the stress data adjustment amount through the environmental influence degree index of stress data; perform assignment operations on each stress data through the stress data weight ratio to obtain the assignment results of each stress data, perform assignment operations on each backup stress data through the backup stress data weight ratio to obtain the assignment results of each backup stress data, and perform coupling processing on the assignment results of each stress data and the assignment results of each backup stress data with the stress data adjustment amount to obtain each target stress data; the specific process of the second-level transmission adjustment is as follows: Obtain the transmission environment influence parameters by monitoring the wireless transmission process of the target stress data; analyze the transmission environment influence degree index according to the transmission environment influence parameters, and the transmission environment influence degree index is used to quantitatively analyze the degree of influence of the target stress data during wireless transmission; analyze the degree of influence of the target stress data during wireless transmission according to the transmission environment influence degree index; judge whether to perform the second-level transmission adjustment according to the degree of influence of the target stress data during wireless transmission.

[0014] Further, the parameters affected by the environment during transmission include: RMS delay spread of stress data transmission, coherent bandwidth of stress data transmission, received signal strength of stress data transmission, and signal path loss value of stress data transmission; the specific process of analyzing the degree of influence of transmission affected by the environment based on the parameters affected by the environment during transmission is as follows: coupling the RMS delay spread of stress data transmission with the symbol period of stress data transmission and then comparing it with the symbol period of stress data transmission, and performing a weighted operation on the result of the comparison process through the delay spread weight ratio to obtain a delay spread index; performing a coherent bandwidth comparison process on the coherent bandwidth of stress data transmission and the signal bandwidth of stress data transmission, and performing a weighted operation on the result of the coherent bandwidth comparison process through the coherent bandwidth weight ratio to obtain a coherent bandwidth index; considering the deviation of the received signal strength of stress data transmission from the standard received signal strength of stress data transmission, and performing a weighted operation on the result of the signal strength deviation consideration through the signal strength weight ratio to obtain a signal strength index; coupling the signal path loss value of stress data transmission with the standard signal path loss value of stress data transmission and then comparing it with the standard signal path loss value of stress data transmission, and performing a weighted operation on the result of the comparison process through the path loss weight ratio to obtain a path loss index; coupling the delay spread index, coherent bandwidth index, signal strength index, and path loss index to obtain the degree of influence of transmission affected by the environment index.

[0015] Further, the specific analysis process of analyzing the degree of influence of the target stress data affected by the environment during wireless transmission based on the degree of influence of transmission affected by the environment index is as follows: comparing the degree of influence of transmission affected by the environment index with the preset threshold of the degree of influence of transmission obtained from the database. When the degree of influence of transmission affected by the environment index is less than the preset threshold of the degree of influence of transmission obtained from the database, it indicates that the degree of influence of the target stress data affected by the environment during wireless transmission is within the qualified range; when the degree of influence of transmission affected by the environment index is not less than the preset threshold of the degree of influence of transmission obtained from the database, it indicates that the degree of influence of the target stress data affected by the environment during wireless transmission is within the unqualified range; the specific process of judging whether to perform secondary transmission adjustment based on the degree of influence of the target stress data affected by the environment during wireless transmission is as follows: when the degree of influence of the target stress data affected by the environment during wireless transmission is within the qualified range, no secondary transmission adjustment is performed; when the degree of influence of the target stress data affected by the environment during wireless transmission is within the unqualified range, secondary transmission adjustment is performed.

[0016] Further, the specific process of the secondary transmission adjustment is as follows: obtain the transmission power increment according to the environmental influence degree index of the transmission, increase the signal transmission power of the target stress data according to the transmission power increment, re-transmit the target stress data after the signal transmission power is increased, and determine whether the environmental influence degree index of the transmission is less than the preset transmission influence degree threshold obtained from the database, and at the same time analyze whether the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database; when both the environmental influence degree index of the transmission is less than the preset transmission influence degree threshold obtained from the database and the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database are satisfied, the secondary transmission adjustment is ended.

[0017] Further, the specific process of the secondary acquisition adjustment is as follows: obtain the corresponding data acquisition frequency reduction range according to the environmental influence degree index of the stress data, reduce the acquisition frequency of the stress data according to the data acquisition frequency reduction range, acquire the stress data according to the reduced acquisition frequency, perform spectrum analysis on the signal of the acquired stress data to obtain the lowest signal frequency, compare the acquisition frequency of the stress data with the lowest signal frequency to obtain a ratio, compare the ratio with the preset ratio, and when the ratio is less than the preset ratio, stop the secondary acquisition adjustment and transmit the stress data to the receiving end through wireless transmission.

[0018] The embodiment of the present application provides an online slope stability monitoring system based on intelligent sensors, including: a data acquisition module, a primary influence analysis module, a secondary influence analysis module, and a tertiary influence analysis module; wherein, the data acquisition module: is used to monitor the process of acquiring the stress data of the slope to obtain the environmental influence parameters of the stress data, and analyze the influence degree of the stress data according to the environmental influence parameters of the stress data; the primary influence analysis module: is used to perform primary acquisition adjustment, primary transmission adjustment, and standby transmission adjustment on the stress data with a primary influence degree, and transmit the stress data to the receiving end through wireless transmission; the secondary influence analysis module: is used to perform data correction and secondary transmission adjustment on the stress data with a secondary influence degree, and transmit the stress data to the receiving end through wireless transmission; the tertiary influence analysis module: is used to perform secondary acquisition adjustment on the stress data with a tertiary influence degree, and transmit the stress data to the receiving end through wireless transmission.

[0019] One or more technical solutions provided in the embodiment of the present application have at least the following technical effects or advantages:

[0020] 1. By monitoring the process of obtaining the stress data of the slope, the environmental influence parameters of the stress data are obtained. The degree of influence on the stress data is analyzed based on the environmental influence parameters of the stress data, and corresponding adjustments are made according to the level of the degree of influence on the stress data. After the adjustment, the stress data is transmitted to the receiving end through wireless transmission, thereby realizing the accurate monitoring of the slope stability by the stress sensor and effectively solving the problem of low accuracy of slope stability monitoring according to sensors in the prior art.

[0021] 2. By monitoring the process of obtaining the stress data of the slope, the environmental influence parameters of the stress data are obtained. The degree of influence on the stress data is analyzed based on the environmental influence parameters of the stress data, and corresponding adjustments are made according to the degree of influence on the stress data, thereby realizing intelligent and accurate adjustment according to the environment where the stress sensor is located and the received influence.

[0022] 3. When the degree of influence on the stress data is at the first level, first-level acquisition adjustment, first-level transmission adjustment, and backup transmission adjustment are performed on the stress data with the first-level degree of influence on the stress data, and the stress data is transmitted to the receiving end through wireless transmission. Thus, when the stress data obtained by the stress sensor changes greatly or the environment where it is located changes significantly, the stress data can be quickly transmitted to the receiving end, which is beneficial for the receiving end to receive the stress data in a timely and rapid manner and perform corresponding processing.

[0023] 4. When the degree of influence on the stress data is at the second level, data correction and second-level transmission adjustment are performed on the stress data with the second-level degree of influence on the stress data, and the stress data is transmitted to the receiving end through wireless transmission. Thus, the more accurate target stress data after correction is transmitted to the receiving end more accurately, which is beneficial for the receiving end to perform subsequent related processing based on the more accurate target stress data.

[0024] 5. When the degree of influence on the stress data is at the third level, second-level acquisition adjustment is performed on the stress data with the third-level degree of influence on the stress data, and the stress data is transmitted to the receiving end through wireless transmission. Thus, on the basis of accurate data acquisition by the stress sensor, the acquisition frequency of the stress data is reduced, so that when the stress data is transmitted to the receiving end, the receiving end improves the data processing speed due to the reduction in the data volume of the stress data. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flowchart of an on-line slope stability monitoring method based on an intelligent sensor provided by an embodiment of the present application;

[0026] Figure 2 It is a schematic structural diagram of an on-line slope stability monitoring system based on an intelligent sensor provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] In an embodiment of the present application, by providing an online monitoring method and system for slope stability based on intelligent sensors, the problem of low accuracy in monitoring slope stability according to sensors in the prior art is solved. By monitoring the process of obtaining stress data of the slope, the environmental influence parameters of the stress data are obtained, and the degree of influence of the stress data is analyzed according to the environmental influence parameters of the stress data. Thus, when the degree of influence of the stress data is level one, primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment are performed on the stress data with a degree of influence of level one, and the stress data is transmitted to the receiving end through wireless transmission; when the degree of influence of the stress data is level two, data correction and secondary transmission adjustment are performed on the stress data with a degree of influence of level two, and the stress data is transmitted to the receiving end through wireless transmission; when the degree of influence of the stress data is level three, secondary acquisition adjustment is performed on the stress data with a degree of influence of level three, and the stress data is transmitted to the receiving end through wireless transmission, thereby achieving accurate monitoring of slope stability through stress sensors.

[0028] The technical solution in the embodiment of the present application for solving the problem of low accuracy in monitoring slope stability according to sensors is generally as follows:

[0029] By monitoring the process of obtaining stress data of the slope, the environmental influence parameters of the stress data are obtained, the environmental influence degree index of the stress data is obtained by processing according to the environmental influence parameters of the stress data, and the degree of influence of the stress data is analyzed according to the environmental influence degree index of the stress data; when the degree of influence of the stress data is level one, primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment are performed on the stress data with a degree of influence of level one, and the stress data is transmitted to the receiving end through wireless transmission; when the degree of influence of the stress data is level two, the stress data with a degree of influence of level two is corrected to obtain target stress data, the environmental influence parameters of the transmission are obtained by monitoring the wireless transmission process of the target stress data, the environmental influence degree index of the transmission is obtained by analysis according to the environmental influence parameters of the transmission, the degree of influence of the target stress data during wireless transmission is analyzed according to the environmental influence degree index of the transmission, it is judged whether secondary transmission adjustment is required according to the degree of influence of the target stress data during wireless transmission, and the stress data is transmitted to the receiving end through wireless transmission; when the degree of influence of the stress data is level three, secondary acquisition adjustment is performed on the stress data with a degree of influence of level three, and the stress data is transmitted to the receiving end through wireless transmission, achieving the effect of accurately monitoring slope stability through stress sensors.

[0030] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0031] As Figure 1 shown in the figure, it is a flowchart of an online slope stability monitoring method based on an intelligent sensor provided by an embodiment of the present application. The method includes the following steps: monitoring the process of obtaining stress data of the slope to obtain the environmental influence parameters of the stress data, and analyzing the influence degree of the stress data according to the environmental influence parameters of the stress data; when the influence degree of the stress data is at the first level, performing first-level acquisition adjustment, first-level transmission adjustment, and standby transmission adjustment on the stress data with the influence degree of the first level, and transmitting the stress data to the receiving end through wireless transmission; when the influence degree of the stress data is at the second level, performing data correction and second-level transmission adjustment on the stress data with the influence degree of the second level, and transmitting the stress data to the receiving end through wireless transmission; when the influence degree of the stress data is at the third level, performing second-level acquisition adjustment on the stress data with the influence degree of the third level, and transmitting the stress data to the receiving end through wireless transmission.

[0032] Further, the specific process of analyzing the degree of influence on stress data based on the environmental influence parameters of stress data is as follows: The environmental influence parameters of stress data include: the stress data change range, the stress data quantity, the groundwater level height in the stress sensor environment, the pore water pressure in the stress sensor environment, and the groundwater flow velocity in the stress sensor environment; Consider the data range deviation between the stress data change range in the environmental influence parameters of stress data and the preset stress change range, and perform a weighted operation on the result of the data range deviation consideration through the data range weight ratio to obtain the data range index; Consider the data quantity deviation between the stress data quantity and the preset stress data quantity, and perform a weighted operation on the result of the data quantity deviation consideration through the data quantity weight ratio to obtain the data quantity index; Perform a coupling process on the data range index and the data quantity index, and perform a weighted operation on the result of the coupling process through the stress data change weight ratio to obtain the stress data change coefficient; Compare the groundwater level height in the stress sensor environment with the preset groundwater level height in the stress sensor environment, then consider the groundwater level height deviation, and perform a weighted operation on the result of the groundwater level height deviation consideration through the groundwater level height weight ratio to obtain the groundwater level height index; Compare the pore water pressure in the stress sensor environment and the preset pore water pressure in the stress sensor environment, then consider the pore water pressure deviation, and perform a weighted operation on the result of the pore water pressure deviation consideration through the pore water pressure weight ratio to obtain the pore water pressure index; Compare the groundwater flow velocity in the stress sensor environment with the preset groundwater flow velocity in the stress sensor environment, then consider the groundwater flow velocity deviation, and perform a weighted operation on the result of the groundwater flow velocity deviation consideration through the groundwater flow velocity weight ratio to obtain the groundwater flow velocity index; Perform a coupling process on the groundwater level height index, the pore water pressure index, and the groundwater flow velocity index, and perform a weighted operation on the result of the coupling process through the sensor environment change weight ratio to obtain the sensor environment change coefficient; Obtain the stress data environmental influence degree index by performing a coupling process on the stress data change coefficient and the sensor environment change coefficient. The stress data environmental influence degree index is used to quantitatively analyze the degree of influence of stress data on the environment during data acquisition; Analyze the degree of influence of stress data based on the stress data environmental influence degree index.

[0033] In this embodiment, the specific calculation formula for the stress data environmental influence degree index is:

[0034] ;

[0035] In the formula, represents the stress data environmental influence degree index, represents the stress data change range, It is expressed as the preset stress change range, It is expressed as the number of stress data, It is expressed as the preset number of stress data, It is expressed as the height of the groundwater level in the environment of the stress sensor, It is expressed as the preset height of the groundwater level in the environment of the stress sensor, It is expressed as the pore water pressure in the environment of the stress sensor, It is expressed as the preset pore water pressure in the environment of the stress sensor, It is expressed as the groundwater flow velocity in the environment of the stress sensor, It is expressed as the preset groundwater flow velocity in the environment of the stress sensor, It is expressed as the weight ratio of the data range, It is expressed as the weight ratio of the data volume, It is expressed as the weight ratio of the groundwater level height, It is expressed as the weight ratio of the pore water pressure, It is expressed as the weight ratio of the groundwater flow velocity, It is expressed as the weight ratio of the stress data change, It is expressed as the weight ratio of the environmental change of the sensor.

[0036] Obtain the parameters of the stress data affected by the environment when the stress sensor obtains stress data. Obtain the stress data collected by the stress sensor (the stress sensor is installed in the soil of the slope for stability monitoring). Sort the data in the stress data by size to obtain the maximum value and the minimum value. Subtract the minimum value from the maximum value to obtain the stress data change range (the length of the interval), unit: Pascal (Pa) or megapascal (MPa). Obtain the stress sensor change range from the historical data, which is the preset stress change range, unit: Pascal (Pa) or megapascal (MPa).

[0037] Obtain the number of stress data collected by the stress sensor, which is the number of stress data, unit: piece. According to the collection frequency and collection duration of the stress data collected by the stress sensor, the result of multiplying the two is the preset number of stress data, unit: piece.

[0038] Measure the height of the groundwater level at the preset position (in the vertical direction of the position where the stress sensor is located) in the environment of the stress sensor by tools such as a water level gauge or a sounding rope, which is the height of the groundwater level in the environment of the stress sensor, unit: meter (m) or centimeter (cm). Obtain the preset height of the groundwater level in the environment of the stress sensor from the historical data, unit: meter (m) or centimeter (cm).

[0039] The pore water pressure measured by a piezometer at a preset position in the environment where the stress sensor is located (2 cm vertically from the position where the stress sensor is located) is the pore water pressure of the stress sensor environment, unit: Pascal (Pa) or kilopascal (kPa). Obtain the preset environmental pore water pressure of the stress sensor from historical data, unit: Pascal (Pa) or kilopascal (kPa).

[0040] The groundwater flow velocity at a preset position in the environment where the stress sensor is located (vertically from the position where the stress sensor is located) measured by an acoustic velocimeter is the groundwater flow velocity of the stress sensor environment, unit: meter per second (m / s) or centimeter per second (cm / s). Obtain the preset environmental groundwater flow velocity of the stress sensor from historical data.

[0041] The rise and fall of the groundwater level will change the effective stress state of the slope soil mass. When the groundwater level rises, the pore water pressure in the soil mass increases, resulting in a decrease in effective stress, which may trigger the sliding or deformation of the slope. Conversely, when the groundwater level drops, the pore water pressure in the soil mass decreases, and the effective stress increases, and the stability of the slope may be improved. This redistribution of stress will affect the measurement results of the stress sensor. The change in pore water pressure directly affects the shear strength and stability of the slope soil mass. The increase in pore water pressure will reduce the shear strength of the soil mass and increase the risk of slope sliding. The decrease in pore water pressure may increase the shear strength of the soil mass and enhance the stability of the slope. Therefore, the change in pore water pressure is one of the key factors affecting the accuracy of stress measurement. The flow velocity of groundwater in the slope soil mass will also affect the stability of the slope. Fast-flowing groundwater may scour the slope soil mass, resulting in the destruction of the soil structure and a decrease in stability. At the same time, the hydrodynamic pressure generated by groundwater flow may also have an adverse impact on the slope. These factors may all affect the accuracy of stress measurement.

[0042] Therefore, when the variation range of stress data is significantly different from the preset stress variation range and the number of stress data is significantly different from the preset number of stress data, it indicates that the data obtained by the stress sensor has changed greatly, which may be due to a huge change in the environment where the stress sensor is located. At this time, the groundwater in the environment where the stress sensor is located will change correspondingly. When the height of the groundwater level in the stress sensor environment is significantly different from the preset groundwater level height in the stress sensor environment, the pore water pressure in the stress sensor environment is significantly different from the preset pore water pressure in the stress sensor environment, and the groundwater flow velocity in the stress sensor environment is significantly different from the preset groundwater flow velocity in the stress sensor environment, it indicates that there is indeed a huge change in the environment where the stress sensor is located. Therefore, this change needs to be quickly sent to the receiving end so that the receiving end can take corresponding measures in time. Therefore, when the degree index of the influence of stress data by the environment is larger, the receiving end needs to respond more quickly. The degree index of the influence of stress data by the environment is obtained according to the environmental influence parameter of stress data. The degree of influence of stress data is analyzed according to the degree index of the influence of stress data by the environment. According to the degree of influence of stress data, it is accurately analyzed whether the stress sensor is affected by the environment during data acquisition, resulting in changes in the collected stress data and the severity of the changes, which is beneficial to taking corresponding treatment measures according to the analyzed results, enabling intelligent processing in the face of different severities and being beneficial to more careful monitoring of slope stability.

[0043] Obtain the data range weight ratio and the data quantity weight ratio from the database. The data range weight ratio and the data quantity weight ratio respectively represent the influence degrees of the stress data variation range and the number of stress data on the degree index of the influence of stress data by the environment. There is a mapping relationship between the stress data variation range and the number of stress data and the corresponding data range weight ratio and data quantity weight ratio. The value ranges of the data range weight ratio and the data quantity weight ratio are [0, 1], and at the same time, the sum of the data range weight ratio and the data quantity weight ratio is 1. For example, the corresponding data range weight ratio and data quantity weight ratio are obtained according to the mapping relationship between the real-time stress data variation range and the number of stress data and the corresponding data range weight ratio and data quantity weight ratio.

[0044] Obtain the weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity from the database. The weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity represent the influence degrees of the environmental groundwater level height, environmental pore water pressure, and environmental groundwater flow velocity of the stress sensor on the influence degree index of stress data affected by the environment, respectively. There is a mapping relationship between the environmental groundwater level height, environmental pore water pressure, and environmental groundwater flow velocity of the stress sensor and the corresponding weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity. Moreover, the value ranges of the weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity are [0, 1], and the sum of the weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity is 1. For example, obtain the corresponding weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity according to the mapping relationship between the real-time environmental groundwater level height, environmental pore water pressure, and environmental groundwater flow velocity of the stress sensor and the corresponding weight ratios of the groundwater level height, pore water pressure, and groundwater flow velocity.

[0045] Obtain the weight ratio of stress data change and the weight ratio of sensor environment change from the database. The weight ratio of stress data change and the weight ratio of sensor environment change represent the influence degrees of the stress data change coefficient and the sensor environment change coefficient on the influence degree index of stress data affected by the environment, respectively. There is a mapping relationship between the stress data change coefficient and the sensor environment change coefficient and the corresponding weight ratio of stress data change and the weight ratio of sensor environment change. Moreover, the value ranges of the weight ratio of stress data change and the weight ratio of sensor environment change are [0, 1], and the sum of the weight ratio of stress data change and the weight ratio of sensor environment change is 1. For example, obtain the corresponding weight ratio of stress data change and the weight ratio of sensor environment change according to the mapping relationship between the real-time stress data change coefficient and the sensor environment change coefficient and the corresponding weight ratio of stress data change and the weight ratio of sensor environment change.

[0046] Further, the specific analysis process for analyzing the degree of influence on stress data according to the environmental influence degree index of stress data is as follows: Compare the environmental influence degree index of stress data with the preset first threshold of environmental influence degree and the second threshold of environmental influence degree obtained from the database. When the environmental influence degree index of stress data is less than the preset first threshold of environmental influence degree obtained from the database, record the degree of influence on stress data as level three; when the environmental influence degree index of stress data is not less than the preset first threshold of environmental influence degree obtained from the database and not greater than the second threshold of environmental influence degree, record the degree of influence on stress data as level two; when the environmental influence degree index of stress data is greater than the second threshold of environmental influence degree, record the degree of influence on stress data as level one.

[0047] In this embodiment, when the environmental influence degree index of stress data is less than the preset first threshold of environmental influence degree obtained from the database, record the degree of influence on stress data as level three, indicating that the degree of influence on stress data is lighter; when the environmental influence degree index of stress data is greater than the second threshold of environmental influence degree, record the degree of influence on stress data as level one, indicating that the degree of influence on stress data is serious.

[0048] Further, the specific process of performing primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment on stress data with a degree of influence on stress data of level one and transmitting the stress data to the receiving end via wireless transmission is as follows: Primary acquisition adjustment means obtaining a new acquisition frequency of stress data according to the environmental influence degree index of stress data, and acquiring stress data at the new acquisition frequency of stress data; primary transmission adjustment means obtaining a new transmission frequency of stress data according to the environmental influence degree index of stress data, and wirelessly transmitting the stress data to the receiving end at the new transmission frequency of stress data; backup transmission adjustment means modulating the stress data acquired at the new acquisition frequency of stress data onto an ultra-wideband signal and wirelessly transmitting it to the receiving end.

[0049] Obtain the corresponding new acquisition frequency of stress data and new transmission frequency of stress data from the database according to the environmental influence degree index of stress data. There is a mapping relationship between the environmental influence degree index of stress data and the new acquisition frequency of stress data and the new transmission frequency of stress data, which may be one-to-one or many-to-one. For example, obtain the corresponding new acquisition frequency of stress data and new transmission frequency of stress data according to the mapping relationship between the real-time environmental influence degree index of stress data and the new acquisition frequency of stress data and the new transmission frequency of stress data.

[0050] Acquire stress data at the new acquisition frequency of stress data, which improves the data volume of stress data. The receiving end can analyze the stability of the slope based on more data, which is beneficial to more accurately analyze the slope stability.

[0051] The stress data collected at the new stress data acquisition frequency is transmitted at the new transmission frequency of the stress data, which improves the transmission speed of the stress data and is conducive to the receiving end quickly and timely analyzing the slope stability based on the received stress data so as to take corresponding actions in a timely manner.

[0052] By modulating the stress data onto the ultra-wideband signal and wirelessly transmitting it to the receiving end, it is ensured that the stress data is transmitted to the receiving end at an extremely fast speed, providing a two-layer guarantee for the transmission of the stress data.

[0053] In this embodiment, the specific method for obtaining the target stress data is as follows:

[0054] The backup stress data is obtained through the backup device, and each data in the stress data collected by the stress sensor is numbered. , denoted as the number of each data in the stress data, denoted as the total number of data in the stress data. The number of data in the backup stress data and the target stress data is the same as that of the stress data;

[0055] ;

[0056] In the formula, denoted as the th data in the target stress data, denoted as the th data in the stress data, denoted as the th data in the backup stress data, denoted as the stress data adjustment amount obtained according to the environmental influence degree index of the stress data, denoted as the stress data weight ratio, denoted as the backup stress data weight ratio.

[0057] Further, the specific process of data correction is as follows: collecting standby stress data through a standby device at the acquisition frequency of the stress data when the degree of influence on the stress data is at the second level; obtaining the stress data adjustment amount through the environmental influence degree index of the stress data; performing an assignment operation on each stress data through the stress data weight ratio to obtain the assignment result of each stress data, performing an assignment operation on each standby stress data through the standby stress data weight ratio to obtain the assignment result of each standby stress data, and coupling the assignment result of each stress data and the assignment result of each standby stress data with the stress data adjustment amount to obtain each target stress data; the specific process of secondary transmission adjustment is as follows: obtaining the transmission environmental influence parameter by monitoring the wireless transmission process of the target stress data; analyzing the transmission environmental influence degree index according to the transmission environmental influence parameter, and the transmission environmental influence degree index is used for quantitatively analyzing the degree of influence of the target stress data on the wireless transmission process by the environment; analyzing the degree of influence of the target stress data on the wireless transmission process by the environment according to the transmission environmental influence degree index; judging whether to perform secondary transmission adjustment according to the degree of influence of the target stress data on the wireless transmission process by the environment.

[0058] In this embodiment, the stress data weight ratio and the standby stress data weight ratio are obtained from the database. The stress data weight ratio and the standby stress data weight ratio respectively represent the influence degree of the stress data and the standby stress data on the target stress data. There is a mapping relationship between the stress data and the standby stress data and the corresponding stress data weight ratio and standby stress data weight ratio, and the value ranges of the stress data weight ratio and the standby stress data weight ratio are [0, 1], and at the same time, the sum of the stress data weight ratio and the standby stress data weight ratio is 1. For example, the corresponding stress data weight ratio and standby stress data weight ratio are obtained according to the mapping relationship between the real-time stress data and the standby stress data and the corresponding stress data weight ratio and standby stress data weight ratio.

[0059] The stress data adjustment amount is obtained from the database. The stress data adjustment amount represents the influence degree of the environmental influence degree index of the stress data on the target stress data. There is a one-to-one mapping relationship between the environmental influence degree index of the stress data and the corresponding stress data adjustment amount. For example, the corresponding stress data adjustment amount is obtained according to the mapping relationship between the real-time environmental influence degree index of the stress data and the corresponding stress data adjustment amount.

[0060] Further, the specific process of obtaining the environmental impact degree index of transmission based on the analysis of transmission environmental impact parameters is as follows: The transmission environmental impact parameters include: stress data transmission RMS (Root Mean Square) delay spread, stress data transmission coherence bandwidth, stress data transmission signal reception strength, and stress data transmission signal path loss value; After coupling the stress data transmission RMS delay spread with the stress data transmission symbol period and then comparing it with the stress data transmission symbol period, a weighting operation is performed on the result of the comparison process through the delay spread weight ratio to obtain the delay spread index; The stress data transmission coherence bandwidth is subjected to a coherence bandwidth comparison process with the stress data transmission signal bandwidth, and a weighting operation is performed on the result of the coherence bandwidth comparison process through the coherence bandwidth weight ratio to obtain the coherence bandwidth index; The stress data transmission signal reception strength is considered for the signal strength deviation from the stress data transmission signal standard reception strength, and a weighting operation is performed on the result of the signal strength deviation consideration through the signal strength weight ratio to obtain the signal strength index; After coupling the stress data transmission signal path loss value with the stress data transmission signal standard path loss value and then comparing it with the stress data transmission signal standard path loss value, a weighting operation is performed on the result of the comparison process through the path loss weight ratio to obtain the path loss index; The delay spread index, coherence bandwidth index, signal strength index, and path loss index are coupled to obtain the environmental impact degree index of transmission.

[0061] In this embodiment, the RMS delay spread is a parameter that measures the degree of delay dispersion of a wireless signal during propagation due to multipath effects. By measuring the delay power spectrum of the wireless signal of the target stress data and then calculating the average value of its square root, the stress data transmission RMS delay spread is obtained, with the unit of seconds (s) or milliseconds (ms). The RMS delay spread can analyze the real-time nature of the target stress data.

[0062] The symbol period refers to the duration of each symbol (such as a digital bit or a modulation symbol) in wireless communication. The stress data transmission symbol period is obtained by referring to the design and modulation method of the communication system, with the unit of seconds (s) or milliseconds (ms), microseconds (μs).

[0063] The coherence bandwidth is a parameter that measures the coherence of the wireless signal of the target stress data in the frequency domain. By measuring the frequency response or correlation function of the signal of the target stress data, the stress data transmission coherence bandwidth is obtained, with the unit of hertz (Hz).

[0064] The signal bandwidth refers to the width occupied by the signal in the frequency domain. By measuring the spectrum of the signal of the target stress data or performing a Fourier transform, the stress data transmission signal bandwidth is obtained, with the unit of hertz (Hz).

[0065] The signal reception strength is a parameter that measures the power of a wireless signal received at the receiving end. The stress data transmission signal reception strength is obtained by measuring the signal power or voltage at the receiving end, with the unit: watt (W) or decibel-milliwatt (dBm). In slope monitoring, the signal reception strength is an important indicator for evaluating the quality of the communication link and the reliability of data transmission. Ensuring a sufficiently high reception strength can ensure the accurate reception of data. Obtain the standard reception strength of the stress data transmission signal from the database, with the unit: watt (W) or decibel-milliwatt (dBm).

[0066] Measure the transmission power of the signal at the sending end of the stress sensor and the power of the signal received at the receiving end using a power meter or a spectrum analyzer. Obtain the stress data transmission signal path loss value through the path loss calculation formula, with the unit: decibel (dB). Obtain the standard path loss value of the stress data transmission signal from the database, with the unit: watt (W) or decibel-milliwatt (dBm).

[0067] The specific method for obtaining the index of the degree of influence of transmission by the environment is as follows:

[0068] ;

[0069] In the formula, represents the index of the degree of influence of transmission by the environment, represents the RMS delay spread of the stress data transmission, represents the symbol period of the stress data transmission, represents the coherence bandwidth of the stress data transmission, represents the signal bandwidth of the stress data transmission, represents the signal reception strength of the stress data transmission, represents the standard reception strength of the stress data transmission signal, represents the stress data transmission signal path loss value, represents the standard stress data transmission signal path loss value, represents the delay spread weight ratio, represents the coherence bandwidth weight ratio, represents the signal strength weight ratio, represents the path loss weight ratio.

[0070] Compare the RMS delay spread of the stress data transmission with the symbol period of the stress data transmission. If the RMS delay spread of the stress data transmission is greater than the symbol period of the stress data transmission, it may cause inter-symbol interference and affect the accuracy of data transmission. For example, if the RMS delay spread is close to or exceeds half of the symbol period of the stress data transmission, then the inter-symbol interference problem will become significant, affecting the accuracy of the target stress data transmission.

[0071] Compare the coherent bandwidth of stress data transmission with the signal bandwidth of stress data transmission. If the signal bandwidth of stress data transmission is greater than the coherent bandwidth of stress data transmission, frequency-selective fading will occur, affecting the stability of data transmission. For example, if the signal bandwidth of stress data transmission is twice or more than the coherent bandwidth of stress data transmission, the problem of frequency-selective fading will become significant.

[0072] Compare the received strength of the stress data transmission signal with the standard received strength of the stress data transmission signal. If the deviation between the two is large, the signal strength fluctuates greatly, which may lead to unstable data transmission.

[0073] By comparing and processing the path loss value of the stress data transmission signal with the standard path loss value of the stress data transmission signal, the change in the attenuation degree of the wireless signal can be clarified. The greater the attenuation degree, the worse the signal quality.

[0074] The mutual restriction between RMS delay spread and coherent bandwidth: It is known that RMS delay spread and coherent bandwidth show an inverse relationship in wireless channel characteristics. This means that when the RMS delay spread increases, the coherent bandwidth decreases, and vice versa. This mutual restriction relationship is crucial for understanding the time-frequency characteristics of the channel.

[0075] The direct correlation between signal received strength and signal path loss value: The signal received strength is not only affected by factors such as transmit power and antenna gain, but also directly affected by the signal path loss value. The larger the path loss value, the lower the signal strength received at the receiving end. This direct correlation makes path loss one of the key factors affecting data transmission quality.

[0076] Analyze the index of the degree of environmental influence on transmission through the RMS delay spread of stress data transmission, the coherent bandwidth of stress data transmission, the received strength of the stress data transmission signal, and the path loss value of the stress data transmission signal. According to the index of the degree of environmental influence on transmission, analyze the degree of environmental influence on the target stress data during wireless transmission, so as to more comprehensively and accurately analyze the degree of environmental influence on the target stress data during wireless transmission, which is beneficial to making corresponding adjustments more accurately and improving the accuracy of slope stability monitoring.

[0077] Obtain the delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio from the database. The delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio respectively represent the influence degrees of the RMS delay spread of stress data transmission, the coherent bandwidth of stress data transmission, the signal reception strength of stress data transmission, and the signal path loss value of stress data transmission on the transmission environmental influence degree index. There is a mapping relationship between the RMS delay spread of stress data transmission, the coherent bandwidth of stress data transmission, the signal reception strength of stress data transmission, the signal path loss value of stress data transmission and the corresponding delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio, and the sum of the delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio is 1. For example, according to the mapping relationship between the real-time RMS delay spread of stress data transmission, the coherent bandwidth of stress data transmission, the signal reception strength of stress data transmission, the signal path loss value of stress data transmission and the corresponding delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio, obtain the corresponding delay spread weight ratio, coherent bandwidth weight ratio, signal strength weight ratio, and path loss weight ratio.

[0078] Furthermore, the specific analysis process for analyzing the environmental influence degree of the target stress data during wireless transmission according to the transmission environmental influence degree index is as follows: Compare the transmission environmental influence degree index with the preset transmission influence degree threshold obtained from the database. When the transmission environmental influence degree index is less than the preset transmission influence degree threshold obtained from the database, it indicates that the environmental influence degree of the target stress data during wireless transmission is within the qualified range; when the transmission environmental influence degree index is not less than the preset transmission influence degree threshold obtained from the database, it indicates that the environmental influence degree of the target stress data during wireless transmission is within the unqualified range; The specific process for judging whether to perform secondary transmission adjustment according to the environmental influence degree of the target stress data during wireless transmission is as follows: When the environmental influence degree of the target stress data during wireless transmission is within the qualified range, no secondary transmission adjustment is performed; when the environmental influence degree of the target stress data during wireless transmission is within the unqualified range, secondary transmission adjustment is performed.

[0079] In this embodiment, when the index of the degree of influence of transmission on the environment is less than the preset threshold of the degree of influence of transmission on the environment obtained from the database, the smaller the index of the degree of influence of transmission on the environment, the smaller the degree of influence of the target stress data on the environment during wireless transmission, and the less secondary adjustment is required; when the index of the degree of influence of transmission on the environment is not less than the preset threshold of the degree of influence of transmission on the environment obtained from the database, the larger the index of the degree of influence of transmission on the environment, the greater the degree of influence of the target stress data on the environment during wireless transmission, and the more secondary adjustment is required.

[0080] Further, the specific process of secondary transmission adjustment is as follows: obtain the transmission power increment according to the index of the degree of influence of transmission on the environment, increase the signal transmission power of the target stress data according to the transmission power increment, transmit the target stress data again after the signal transmission power is increased, and determine whether the index of the degree of influence of transmission on the environment is less than the preset threshold of the degree of influence of transmission on the environment obtained from the database, and at the same time analyze whether the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database; when both the index of the degree of influence of transmission on the environment is less than the preset threshold of the degree of influence of transmission on the environment obtained from the database and the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database are satisfied, end the secondary transmission adjustment; when in other situations, repeat the above process, and when the set number of repetitions is reached and the index of the degree of influence of transmission on the environment is less than the preset threshold of the degree of influence of transmission on the environment obtained from the database and the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database do not hold simultaneously, give a warning reminder for secondary transmission adjustment.

[0081] In this embodiment, obtain the corresponding transmission power increment from the database according to the index of the degree of influence of transmission on the environment, and there is a one-to-one mapping relationship between the index of the degree of influence of transmission on the environment and the transmission power increment. For example, establish the corresponding mapping relationship between the index of the degree of influence of transmission on the environment and the transmission power increment according to the historical data, and obtain the corresponding transmission power increment according to the mapping relationship between the real-time index of the degree of influence of transmission on the environment and the transmission power increment.

[0082] After obtaining the transmission power increment, the computer increases the transmission power increment on the basis of the signal transmission power to obtain a new signal transmission power, and transmits the target stress data again with the new signal transmission power.

[0083] By increasing the signal transmission power at the transmitting end, the intensity of the signal of the target stress data during transmission is increased, thereby resisting the influence of path loss. When the degree index of transmission affected by the environment is still not less than the preset threshold of the degree of transmission affected by the environment obtained from the database and the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database after the repeated setting times, a secondary transmission adjustment warning reminder is sent to the preset personnel.

[0084] Further, the specific process of the secondary acquisition adjustment is as follows: obtaining the corresponding data acquisition frequency reduction range according to the degree index of stress data affected by the environment, reducing the acquisition frequency of stress data according to the data acquisition frequency reduction range, acquiring stress data according to the reduced acquisition frequency, performing spectrum analysis on the signal of the acquired stress data to obtain the lowest signal frequency, comparing and processing the acquisition frequency of stress data with the lowest signal frequency to obtain a ratio, comparing the ratio with a preset ratio, when the ratio is less than the preset ratio, stopping the secondary acquisition adjustment, and transmitting the stress data to the receiving end through wireless transmission; when in other situations, repeating the above process, when the ratio is not less than the preset ratio after the repeated setting times, a secondary acquisition adjustment warning reminder is performed.

[0085] In this embodiment, the corresponding data acquisition frequency reduction range is obtained from the database according to the degree index of transmission affected by the environment, and there is a one-to-one or many-to-one mapping relationship between the degree index of transmission affected by the environment and the data acquisition frequency reduction range. For example, the corresponding data acquisition frequency reduction range is obtained according to the mapping relationship between the real-time degree index of transmission affected by the environment and the data acquisition frequency reduction range. When the ratio is not less than the preset ratio after the repeated setting times, a secondary acquisition adjustment warning reminder is given to the preset personnel.

[0086] When the data change range of the sensor is small and the corresponding environmental change degree is low, the energy-saving effect can be achieved by reducing the data acquisition frequency. After reducing the data acquisition frequency, the amount of data processed by the receiving end correspondingly decreases, and the speed of the receiving end processing data is correspondingly increased.

[0087] The specific process of analyzing whether to stop the secondary acquisition adjustment is as follows: using a spectrum analysis tool to analyze the frequency distribution of the signal, identifying the lowest frequency component of the signal, calculating the ratio between the current acquisition frequency and twice the lowest signal frequency. If the ratio is large enough (for example, greater than 2), further reducing the acquisition frequency is considered. If the ratio is less than or equal to 2, the acquisition frequency should not be further reduced to avoid aliasing.

[0088] Such as Figure 2As shown, it is a schematic structural diagram of the slope stability online monitoring system based on intelligent sensors provided by the embodiments of the present application. The slope stability online monitoring system based on intelligent sensors provided by the embodiments of the present application includes: a data acquisition module, a primary impact analysis module, a secondary impact analysis module, and a tertiary impact analysis module; among them, the data acquisition module: used to monitor the process of acquiring the stress data of the slope to obtain the environmental impact parameters of the stress data, and analyze the degree of influence of the stress data according to the environmental impact parameters of the stress data; the primary impact analysis module: used to perform primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment on the stress data with a primary degree of influence when the degree of influence of the stress data is primary, and transmit the stress data to the receiving end through wireless transmission; the secondary impact analysis module: used to perform data correction and secondary transmission adjustment on the stress data with a secondary degree of influence when the degree of influence of the stress data is secondary, and transmit the stress data to the receiving end through wireless transmission; the tertiary impact analysis module: used to perform secondary acquisition adjustment on the stress data with a tertiary degree of influence when the degree of influence of the stress data is tertiary, and transmit the stress data to the receiving end through wireless transmission.

[0089] In the technical solution of the above embodiments of the present application, by monitoring the process of acquiring the stress data of the slope to obtain the environmental impact parameters of the stress data, and analyzing the degree of influence of the stress data according to the environmental impact parameters of the stress data, so that when the degree of influence of the stress data is primary, perform primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment on the stress data with a primary degree of influence, and transmit the stress data to the receiving end through wireless transmission; when the degree of influence of the stress data is secondary, perform data correction and secondary transmission adjustment on the stress data with a secondary degree of influence, and transmit the stress data to the receiving end through wireless transmission; when the degree of influence of the stress data is tertiary, perform secondary acquisition adjustment on the stress data with a tertiary degree of influence, and transmit the stress data to the receiving end through wireless transmission, thereby realizing the accurate monitoring of slope stability through stress sensors, and effectively solving the problem of low accuracy of slope stability monitoring according to sensors in the prior art.

[0090] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0091] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one flow Figure 1 or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0092] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the functions specified in one flow Figure 1 or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0094] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present invention.

[0095] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An online monitoring method for slope stability based on intelligent sensors, characterized in that, It includes the following steps: Monitor the process of obtaining the stress data of the slope to obtain the environmental influence parameters of the stress data, and analyze the degree of influence on the stress data according to the environmental influence parameters of the stress data; Perform primary acquisition adjustment, primary transmission adjustment, and backup transmission adjustment on the stress data with a first-level degree of influence, and transmit the stress data to the receiving end through wireless transmission; Perform data correction and secondary transmission adjustment on the stress data with a second-level degree of influence, and transmit the stress data to the receiving end through wireless transmission; Perform secondary acquisition adjustment on the stress data with a third-level degree of influence, and transmit the stress data to the receiving end through wireless transmission; The specific process of the secondary transmission adjustment is as follows: Obtain the environmental influence parameters of the transmission by monitoring the wireless transmission process of the target stress data; Analyze the environmental influence degree index of the transmission according to the environmental influence parameters of the transmission, and the environmental influence degree index of the transmission is used to quantitatively analyze the degree of influence of the target stress data on the environment during the wireless transmission process; Analyze the degree of influence of the target stress data on the environment during the wireless transmission process according to the environmental influence degree index of the transmission; Judge whether to perform secondary transmission adjustment according to the degree of influence of the target stress data on the environment during the wireless transmission process; The specific process of analyzing the degree of influence of the stress data according to the environmental influence parameters of the stress data is as follows: Perform coupling processing on the data range index and the data volume index, and perform weighted operation on the result of the coupling processing through the stress data change weight ratio to obtain the stress data change coefficient; Perform coupling processing on the groundwater level height index, the pore water pressure index, and the groundwater flow velocity index, and perform weighted operation on the result of the coupling processing through the sensor environment change weight ratio to obtain the sensor environment change coefficient; Obtain the environmental influence degree index of the stress data by performing coupling processing on the stress data change coefficient and the sensor environment change coefficient; The specific process of analyzing the environmental influence degree index of the transmission according to the environmental influence parameters of the transmission is as follows: Perform coupling processing on the RMS delay spread of the stress data transmission and the symbol period of the stress data transmission, and then compare the result with the symbol period of the stress data transmission. Perform weighted operation on the result of the comparison processing through the delay spread weight ratio to obtain the delay spread index; Perform coherent broadband comparison processing on the coherent bandwidth of the stress data transmission and the signal bandwidth of the stress data transmission, and perform weighted operation on the result of the coherent broadband comparison processing through the coherent broadband weight ratio to obtain the coherent broadband index; Consider the signal strength deviation between the received strength of the stress data transmission signal and the standard received strength of the stress data transmission signal, and perform weighted operation on the result of the signal strength deviation consideration through the signal strength weight ratio to obtain the signal strength index; Perform coupling processing on the signal path loss value of the stress data transmission and the standard signal path loss value of the stress data transmission, and then compare the result with the standard signal path loss value of the stress data transmission. Perform weighted operation on the result of the comparison processing through the path loss weight ratio to obtain the path loss index; Couple the delay spread index, coherent bandwidth index, signal strength index, and path loss index to obtain an index of the degree of influence of the transmission by the environment.

2. The online monitoring method for slope stability based on intelligent sensors according to claim 1, characterized in that, The parameters of the stress data affected by the environment include: the variation range of the stress data, the quantity of the stress data, the height of the groundwater level in the environment of the stress sensor, the pore water pressure in the environment of the stress sensor, and the groundwater flow velocity in the environment of the stress sensor; The analysis of the degree of influence of the stress data according to the parameters of the stress data affected by the environment further includes: Consider the data range deviation between the variation range of the stress data and the preset stress variation range, and perform a weighted operation on the result of the data range deviation consideration through the data range weight ratio to obtain a data range index; Consider the data quantity deviation between the quantity of the stress data and the preset quantity of the stress data, and perform a weighted operation on the result of the data quantity deviation consideration through the data quantity weight ratio to obtain a data quantity index; Perform a comparison process on the height of the groundwater level in the environment of the stress sensor and the preset height of the groundwater level in the environment of the stress sensor, then consider the deviation of the groundwater level height, and perform a weighted operation on the result of the deviation consideration of the groundwater level height through the groundwater level height weight ratio to obtain a groundwater level height index; Perform a comparison process on the pore water pressure in the environment of the stress sensor and the preset pore water pressure in the environment of the stress sensor, then consider the deviation of the pore water pressure, and perform a weighted operation on the result of the deviation consideration of the pore water pressure through the pore water pressure weight ratio to obtain a pore water pressure index; Perform a comparison process on the groundwater flow velocity in the environment of the stress sensor and the preset groundwater flow velocity in the environment of the stress sensor, then consider the deviation of the groundwater flow velocity, and perform a weighted operation on the result of the deviation consideration of the groundwater flow velocity through the groundwater flow velocity weight ratio to obtain a groundwater flow velocity index; The index of the degree of influence of the stress data affected by the environment is used to quantitatively analyze the degree of influence of the stress data during data acquisition; Analyze the degree of influence of the stress data according to the index of the degree of influence of the stress data affected by the environment.

3. The online monitoring method for slope stability based on intelligent sensors according to claim 2, wherein, The specific analysis process of analyzing the degree of influence of the stress data according to the index of the degree of influence of the stress data affected by the environment is: Compare the index of the degree of influence of the stress data affected by the environment with the preset first threshold of the degree of environmental influence and the second threshold of the degree of environmental influence obtained from the database. When the index of the degree of influence of the stress data affected by the environment is less than the preset first threshold of the degree of environmental influence obtained from the database, record the degree of influence of the stress data as level three; When the index of the degree of influence of the stress data affected by the environment is not less than the preset first threshold of the degree of environmental influence obtained from the database and not greater than the second threshold of the degree of environmental influence, record the degree of influence of the stress data as level two; When the index of the degree of influence of the stress data affected by the environment is greater than the second threshold of the degree of environmental influence, record the degree of influence of the stress data as level one.

4. The online monitoring method for slope stability based on intelligent sensors according to claim 3, characterized in that, The first-level acquisition adjustment refers to obtaining a new acquisition frequency of the stress data according to the index of the degree of influence of the stress data affected by the environment, and performing data acquisition at the new acquisition frequency of the stress data to obtain the stress data; The first-level transmission adjustment refers to obtaining a new transmission frequency of the stress data according to the index of the degree of influence of the stress data affected by the environment, and wirelessly transmitting the stress data to the receiving end at the new transmission frequency of the stress data; The spare transmission adjustment refers to modulating the stress data obtained by data acquisition at the new acquisition frequency of stress data onto an ultra-wideband signal for wireless transmission to the receiving end.

5. The online monitoring method for slope stability based on intelligent sensors according to claim 3, wherein The specific process of the data correction is as follows: Collect spare stress data through the spare device at the acquisition frequency of the stress data when the degree of influence on the stress data is at the secondary level; Obtain the stress data adjustment amount through the environmental influence degree index of the stress data; Perform assignment operations on each stress data through the stress data weight ratio to obtain the assignment results of each stress data, perform assignment operations on each spare stress data through the spare stress data weight ratio to obtain the assignment results of each spare stress data, and perform coupling processing on the assignment results of each stress data and the assignment results of each spare stress data with the stress data adjustment amount to obtain each target stress data.

6. The online monitoring method for slope stability based on intelligent sensors as claimed in claim 5, wherein, The parameters affected by the environment during transmission include: the RMS delay spread of stress data transmission, the coherent bandwidth of stress data transmission, the received signal strength of stress data transmission, and the signal path loss value of stress data transmission.

7. The online monitoring method for slope stability based on intelligent sensors according to claim 6, characterized in that The specific analysis process of analyzing the degree of influence of the target stress data by the environment during wireless transmission according to the environmental influence degree index during transmission is as follows: Compare the environmental influence degree index during transmission with the preset environmental influence degree threshold obtained from the database. When the environmental influence degree index during transmission is less than the preset environmental influence degree threshold obtained from the database, it indicates that the degree of influence of the target stress data by the environment during wireless transmission is within the qualified range; When the environmental influence degree index during transmission is not less than the preset environmental influence degree threshold obtained from the database, it indicates that the degree of influence of the target stress data by the environment during wireless transmission is within the unqualified range; The specific process of judging whether to perform secondary transmission adjustment according to the degree of influence of the target stress data by the environment during wireless transmission is as follows: When the degree of influence of the target stress data by the environment during wireless transmission is within the qualified range, no secondary transmission adjustment is performed; When the degree of influence of the target stress data by the environment during wireless transmission is within the unqualified range, secondary transmission adjustment is performed.

8. The online monitoring method for slope stability based on intelligent sensors according to claim 7, characterized in that, The specific process of the secondary transmission adjustment is as follows: Obtain the transmission power increase value according to the environmental influence degree index during transmission, increase the signal transmission power of the target stress data according to the transmission power increase value, transmit the target stress data again after the signal transmission power is increased, and judge whether the environmental influence degree index during transmission is less than the preset environmental influence degree threshold obtained from the database, and at the same time analyze whether the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database; When both the environmental influence degree index during transmission is less than the preset environmental influence degree threshold obtained from the database and the signal-to-noise ratio of the target stress data is greater than the preset target signal-to-noise ratio obtained from the database are satisfied, the secondary transmission adjustment is ended.

9. The online monitoring method for slope stability based on intelligent sensors according to claim 2, characterized in that The specific process of the secondary acquisition adjustment is as follows: Obtain the corresponding range of reduction in data acquisition frequency according to the environmental influence degree index of stress data, reduce the acquisition frequency of stress data according to the range of reduction in data acquisition frequency, acquire stress data according to the reduced acquisition frequency, perform spectral analysis on the signal of the acquired stress data to obtain the lowest signal frequency, compare and process the acquisition frequency of stress data with the lowest signal frequency to obtain a ratio, compare the ratio with a preset ratio, and when the ratio is less than the preset ratio, stop the secondary acquisition adjustment and transmit the stress data to the receiving end through wireless transmission.

10. An on-line slope stability monitoring system based on intelligent sensors, which applies the on-line slope stability monitoring method based on intelligent sensors as described in any one of claims 1-9, characterized in that, Including: A data acquisition module, a primary influence analysis module, a secondary influence analysis module, and a tertiary influence analysis module; Among them, the data acquisition module: is used to monitor the process of acquiring stress data of the slope to obtain the environmental influence parameters of stress data, and analyze the influence degree of stress data according to the environmental influence parameters of stress data; The primary influence analysis module: is used to perform primary acquisition adjustment, primary transmission adjustment, and standby transmission adjustment on stress data with a primary influence degree, and transmit the stress data to the receiving end through wireless transmission; The secondary influence analysis module: is used to perform data correction and secondary transmission adjustment on stress data with a secondary influence degree, and transmit the stress data to the receiving end through wireless transmission; The tertiary influence analysis module: is used to perform secondary acquisition adjustment on stress data with a tertiary influence degree, and transmit the stress data to the receiving end through wireless transmission.

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