Side slope displacement monitoring device and method based on geological drilling flexible connection
Through a slope displacement monitoring device based on flexible connection of geological drilling, combined with a dual MEMS accelerometer and inclination sensor, Kalman filtering and LSTM neural network correction data are used to solve the problem of high cost and large error in slope monitoring, and high-precision, low-cost, and long-term stable monitoring effect is achieved.
Patent Information
- Application Number
- CN202510503499.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-22
- Publication Date
- 2025-08-01
AI Technical Summary
The existing slope monitoring technology has high cost, complex installation, large measurement errors and poor environmental adaptability, making it difficult to achieve high-precision, low-cost, long-term and stable monitoring.
A slope displacement monitoring device based on flexible connection of geological drilling is adopted, and a dual MEMS accelerometer and inclination sensor are combined, and data processing and correction are performed through flexible connectors and universal deformation conduction mechanisms, combined with Kalman filtering and LSTM neural networks, achieving high-precision slope displacement monitoring.
It reduces hardware costs, improves environmental adaptability and measurement accuracy, ensures data integrity and accuracy, can achieve long-term stable monitoring of millimeter-level displacement resolution, and promptly warns of the risk of slope instability.
Smart Images
Figure CN120403520A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of underground mid - shallow slope deformation monitoring, and particularly relates to a slope displacement monitoring device and method based on flexible connection of geological boreholes. Background Art
[0002] In various mine engineering constructions, underground infrastructure construction, and natural environment monitoring, slope stability monitoring is of crucial importance. There are many deficiencies in existing slope monitoring technologies. For example, although the Global Navigation Satellite System (GNSS) and total station have high precision, their equipment costs are high, the installation and operation processes are complex, and they require professional technical personnel for maintenance and calibration, which are not suitable for large - scale and long - term slope monitoring scenarios; the traditional accelerometer integration method will cause long - term drift in measurement results due to the accumulation of noise during long - term monitoring, seriously affecting the accuracy of monitoring data; although the fiber - based displacement sensor has high precision, its anti - mechanical shock ability is weak, and it is easily damaged by external factors and the monitoring work is interrupted in complex environments such as mountainous areas and mines.
[0003] Therefore, it is of great practical significance to develop a slope displacement monitoring device and method with low cost, strong environmental adaptability, and high measurement accuracy. Summary of the Invention
[0004] The present invention aims to provide a slope displacement monitoring device and method based on flexible connection of geological boreholes to solve the problems of high cost, complex installation, large measurement error, and poor environmental adaptability existing in the existing underground mid - shallow slope monitoring technologies, and to achieve high - precision, low - cost, and long - term stable monitoring of slope displacement.
[0005] To achieve the above object, the present application provides a slope displacement monitoring device based on flexible connection of geological boreholes, which is characterized by comprising:
[0006] A main probe and multiple slave probes, the main probe and the slave probes have the same structure, and both include a flexible connecting piece, a waterproof fixing head, a tube housing, a universal deformation conduction mechanism, and a main control board arranged in the tube housing;
[0007] The flexible connecting piece is composed of multiple segments of flexible steel wire leads and is used to connect the main probe and the slave probes;
[0008] The main control board is installed in the tube housing and sealed by the waterproof fixing head, and a dual - MEMS sensor module, an inclination sensor, an MCU acquisition control and transmission module, a communication module, and a power module are arranged on the main control board;
[0009] The inclination sensor is used to measure the inclination angle information of the probe;
[0010] The MCU acquisition control and transmission module is electrically connected to the dual MEMS sensor module, the inclination sensor, the memory, and the communication module respectively, and is used to control sensor data acquisition, process the acquired data, and transmit the data.
[0011] The main probe also includes a memory for storing the acquired data and the intermediate data during the processing.
[0012] The power supply module provides power for each module inside the probe.
[0013] The universal deformation conduction mechanism is arranged outside the probe and is used to sense the slope displacement and transmit it to the internal sensors.
[0014] Further, the universal deformation conduction mechanism includes an upper universal deformation conduction mechanism and a lower universal deformation conduction mechanism, which are respectively arranged at the upper end and the lower end of the probe. In this way, multi-angle deformation conduction can be achieved, and the deformation in different directions can be accurately conducted to the main control board. When the device is subjected to external forces from horizontal, vertical or multi-angle directions and generates deformation in a complex stress environment, the upper and lower universal deformation conduction mechanisms can respectively sense the deformation information in the corresponding directions. The two universal deformation conduction mechanisms collect deformation information from different positions above and below, which can reduce the detection blind spots that may exist in a single conduction mechanism and improve the accuracy and comprehensiveness of the overall deformation detection of the device.
[0015] Further, the communication module in the main probe is divided into a host computer communication module and a slave communication module, and the slave communication module is connected to the communication module in the slave probe.
[0016] Further, the dual MEMS sensor module includes an upper MEMS accelerometer and a lower MEMS accelerometer for measuring acceleration information.
[0017] On the other hand, the present invention also provides a method for slope displacement monitoring using the above device, which is characterized by including the following steps:
[0018] S1. Start the working process of the main probe, read the data of the upper MEMS accelerometer, and detect whether a single acquisition is completed; if not, loop to read until it is completed; if completed, read the data of the lower MEMS accelerometer, and detect whether a single acquisition is completed; if not, loop to read until it is completed; if completed, read the data of the inclination sensor, and detect whether a single acquisition is completed; if not, loop to read until it is completed; if completed, read the data of multiple slave probes in sequence according to the numbers.
[0019] S2. Integrate and process all the sensor and slave probe data collected in step S1.
[0020] S3. Detect whether the data upload timer is triggered. If triggered, actively upload the processed data to the remote terminal. If not triggered, repeat steps S1 - S3 until triggered.
[0021] S4. Detect whether the data sending is completed. If not completed, repeat the upload operation until completed.
[0022] S5. Calculate the horizontal displacement component by detecting the change in the slope inclination angle measured by the inclination sensor in the data. Obtain the vertical displacement component by double - integrating the acceleration data collected by the dual MEMS accelerometers in the data. Calculate the slope displacement based on the horizontal displacement component and the vertical displacement component. When the monitored displacement exceeds the preset threshold, trigger an early warning signal and upload it to the remote terminal through the communication module.
[0023] Further, in step S1, reading the data of multiple slave probes in sequence according to the number. Specifically, detect whether the single - acquisition of the slave probe times out. If it times out, skip this probe and read the data of the next probe. If it does not time out, detect whether the single - acquisition is completed. If completed, skip this probe and read the data of the next probe.
[0024] Further, the single - acquisition process of the slave probe includes: reading the data of the upper MEMS accelerometer and detecting whether the single - acquisition of the upper MEMS accelerometer is completed. If not completed, loop - read until the single - acquisition of the upper MEMS accelerometer is completed. If completed, read the data of the lower MEMS accelerometer and detect whether the single - acquisition of the lower MEMS accelerometer is completed. If not completed, loop - read until the single - acquisition of the lower MEMS accelerometer is completed. If completed, read the data of the inclination sensor and detect whether the single - acquisition of the inclination sensor data is completed. If not completed, loop - read until the single - acquisition of the inclination sensor data is completed. If completed, perform data processing and judge whether there is a master - probe acquisition instruction. If not, continue to read data and perform data processing. If there is a master - probe acquisition instruction, send the data back to the master probe and detect whether the data sending is completed. If not completed, repeat the upload operation until the data sending is completed.
[0025] Further, in step S5, the Kalman filtering algorithm is used to perform weighted fusion on the horizontal displacement and the vertical displacement to dynamically correct the displacement calculation result.
[0026] Further, in step S5, an LSTM neural network is used for error correction to correct the displacement data in real - time. Specifically, the LSTM network is trained with historical displacement data to predict the drift error during the integration process of the accelerometer.
[0027] Beneficial effects
[0028] (1) The combination of dual MEMS accelerometers and inclination sensors significantly reduces hardware costs compared to GNSS, total stations, and other equipment. Furthermore, the device has a relatively simple structure, and installation and maintenance costs are also low. The flexible connectors can effectively buffer vibration interference, and the tube housing protects the internal modules, making the device suitable for complex and harsh environments such as mountainous areas and mines, and having strong resistance to mechanical shock.
[0029] (2) Modular layered design, with clear division of labor among the three modules of sensor reading, data processing and data uploading, reduces coupling and facilitates phased debugging and maintenance. In the data acquisition link, a sequential reading strategy is adopted to avoid signal interference or resource competition problems that may be caused by parallel acquisition of multiple sensors, ensuring data integrity. A completion judgment and timeout judgment mechanism are set for each sensor and single acquisition from the probe, effectively avoiding omissions or acquisition failures due to abnormalities during the data acquisition process, ensuring the integrity and accuracy of the collected data. Through the multi-sensor fusion algorithm, combined with dynamic segmented measurement, signal noise reduction and LSTM error correction technology, the measurement error is reduced, and millimeter-level displacement resolution can be achieved, accurately monitoring the displacement changes of the slope.
[0030] (3) All probe data acquisition starts with reading the MEMS accelerometer data, followed by the inclination sensor data. This allows for more timely and accurate judgment of whether the slope is in a critical state of instability. The accelerometer first captures the trend of accelerated slope decline, and the inclination sensor further determines the change in tilt angle. Comprehensive analysis can provide more accurate early warnings, buying time for disaster prevention and mitigation.
[0031] (4) The collected data is processed and stored in the memory, and the data is uploaded by triggering the timer, which realizes the orderly management of data from collection, processing to storage and uploading, facilitates the overall data processing and analysis of the system, and is also conducive to data interaction with other systems. The main probe can collect and upload the displacement information of the entire device in real time, facilitates remote monitoring and management, and improves the efficiency of monitoring work. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 This is the installation diagram of the monitoring device.
[0033] Figure 2 Schematic diagram of the probe structure of the monitoring device.
[0034] Figure 3 This is a schematic diagram of the main probe and slave probe principles of the monitoring device.
[0035] Figure 4 Flowchart of the main probe working algorithm.
[0036] Figure 5 Flowchart of the slave probe working algorithm. Detailed implementation manners
[0037] The following will further describe in detail the specific implementation manners of the present invention in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.
[0038] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groups.
[0039] For the sake of simplicity of the drawings, only the parts related to the present invention are schematically shown in each drawing, and they do not represent their actual structures as products. In addition, in order to make the drawings simple and easy to understand, for components with the same structure or function in some drawings, only one of them is schematically shown, or only one of them is marked. In this article, "one" not only means "only this one", but also means "more than one" situation.
[0040] It should also be further understood that the term "and / or" used in the description of this application and the appended claims refers to any combination and all possible combinations of one or more of the related listed items, and includes these combinations.
[0041] In the embodiments shown in the drawings, the indication of directions (such as up, down, left, right, front, and back) is used to explain that the structures and movements of various components of the present invention are not absolute but relative. When these components are in the positions shown in the drawings, these descriptions are appropriate. If the descriptions of the positions of these components change, then the indication of these directions also changes accordingly.
[0042] In addition, in the description of this application, the terms "first", "second", etc. are only used for differential description and cannot be understood as indicating or implying relative importance.
[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation manners of the present invention will be described below with reference to the accompanying drawings.
[0044] Embodiment 1
[0045] As Figure 1 、 Figure 2 and Figure 3 shown, the present invention provides a slope displacement monitoring device based on flexible connection of geological boreholes, including:
[0046] Figure 1This is the installation schematic diagram of the slope displacement monitoring device. The diagram shows the installation of the monitoring device in the monitoring well of the slope. The monitoring well has a monitoring well casing, and a cable waterproof fixing head is provided at the wellhead to protect the cable and prevent water from entering. It includes a No. 1 main probe and No. 2 to No. N slave probes, which are connected in series through flexible steel wire leads. The main probe and the slave probes are arranged at a certain interval in the monitoring well to sense the displacement of the slope. The whole device is installed in the monitoring well of the slope, and through the coordinated work of each component, the monitoring of the slope displacement is realized.
[0047] Figure 2 is the schematic diagram of the probe structure of the monitoring device, including a flexible connector, a waterproof fixing head, a pipe housing, a universal deformation conduction mechanism, and a main control board arranged in the pipe housing; the flexible connector is composed of multiple segments of flexible steel wire leads and is used to connect the main probe and the slave probes; the main control board is installed in the pipe housing and is sealed through the waterproof fixing head. Figure 3 It can be seen that a dual MEMS sensor module, an inclination sensor, an MCU acquisition control and transmission module, a communication module, and a power module are arranged on the main control board; the inclination sensor is used to measure the inclination angle information of the probe; the MCU acquisition control and transmission module is electrically connected to the dual MEMS sensor module, the inclination sensor, the memory, and the communication module respectively, and is used to control sensor data acquisition, process the acquired data, and transmit the data; the main probe also includes a memory for storing the acquired data and intermediate data during the processing process; the power module provides power for each module in the probe; the universal deformation conduction mechanism is arranged outside the probe and is used to sense the slope displacement and transmit it to the internal sensor.
[0048] Furthermore, the universal deformation conduction mechanism includes an upper universal deformation conduction mechanism and a lower universal deformation conduction mechanism, which are respectively arranged at the upper end and the lower end of the probe.
[0049] Furthermore, the communication module in the main probe is divided into a host computer communication module and a slave computer communication module, and the slave computer communication module is connected to the communication module in the slave probe.
[0050] Furthermore, the dual MEMS sensor module includes an upper MEMS accelerometer and a lower MEMS accelerometer, which are used to measure acceleration information. The MEMS accelerometer is based on the Coriolis force principle. When the accelerometer has an acceleration relative to the inertial space, the internal mass block will generate a displacement, and the acceleration is measured by detecting the displacement change of the mass block. The formula for measuring acceleration is a = F / m (where a is the acceleration, F is the force received by the mass block, and m is the mass of the mass block). The velocity can be obtained by integrating the acceleration, and the displacement can be obtained by integrating the velocity again. The displacement calculation formula is s = ∫∫a dt 2(where s is displacement and t is time). However, due to the accumulation of noise during the integration process, there are errors in measuring displacement using only a MEMS accelerometer. Therefore, a filtering algorithm is used to denoise the collected sensor signals, remove noise interference, and improve signal quality. Common filtering algorithms such as Kalman filtering can effectively suppress noise and improve data stability by predicting the system state and fusing measurement values.
[0051] Meanwhile, during the monitoring process, according to the speed and amplitude of the slope displacement change, the monitoring time is divided into different time periods. Within each time period, data from the dual MEMS sensor module and the inclinometer are collected respectively to adapt to different displacement change situations and improve the measurement accuracy.
[0052] Embodiment 2
[0053] This embodiment also provides a method for slope displacement monitoring using the above device, including the following steps:
[0054] Step 1, start the main probe work process, refer to Figure 4 , read the data of the upper MEMS accelerometer and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of the lower MEMS accelerometer and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of the inclinometer and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of multiple slave probes in sequence according to the number;
[0055] Step 2, integrate and process all the sensor and slave probe data collected in Step 1;
[0056] Step 3, detect whether the data upload timer is triggered; if triggered, actively upload the processed data to the remote terminal; if not, repeat the above steps until triggered;
[0057] Step 4, detect whether the data is sent completely; if not, repeat the upload operation until completed
[0058] Step 5, calculate the horizontal displacement component by detecting the change in the slope inclination angle measured by the inclinometer in the data; obtain the vertical displacement component through secondary integration of the acceleration data collected by the dual MEMS accelerometer in the data, calculate the slope displacement amount based on the horizontal displacement component and the vertical displacement component, and when the monitored displacement exceeds the preset threshold, trigger an early warning signal and upload it to the remote terminal through the communication module.
[0059] In step 1, multiple slave probe data are read sequentially in numerical order. Specifically, it is detected whether the single acquisition of the slave probe times out. If it times out, the probe is skipped and the data of the next probe is read. If it does not time out, it is detected whether the single acquisition is completed. If it is completed, the probe is skipped and the data of the next probe is read. If it is not completed, the reading is looped until it is completed. In slope displacement monitoring, first judge whether the single data acquisition of the slave probe times out. If it times out, the data acquisition of the next probe is performed. This can ensure the continuity of data acquisition, prevent a single probe from occupying the acquisition resources for a long time due to abnormal conditions such as faults and signal interference, resulting in the stagnation of the overall data acquisition. Once the acquisition of a certain slave probe times out, it is skipped in time and the acquisition of the next probe is performed, which can maintain the continuous progress of the data acquisition work, ensure that the data of each probe can be obtained continuously for analyzing the slope displacement situation. At the same time, the abnormal probe can be quickly skipped, reducing the ineffective waiting time and accelerating the overall data acquisition speed. In a large-scale slope monitoring scenario, multiple slave probes work together. If the timeout judgment is not set, the problem of one probe may drag down the entire data acquisition process, while the timeout judgment mechanism can significantly improve the data acquisition efficiency and provide data support for subsequent analysis in a timely manner. The monitoring system can flexibly respond to various emergencies. Whether the acquisition times out due to bad weather or equipment failure itself, the system can automatically adjust the acquisition strategy, reduce the impact on the monitoring work, and ensure the smooth progress of the monitoring task. This can also help to detect the abnormal situation of the probe in time, facilitate the maintenance personnel to quickly locate the faulty equipment, and take maintenance measures in time. Reduce the risk of long-term data loss or error caused by the failure of the probe not being detected in time, resulting in misjudgment and missed judgment of the slope displacement, and ensure the safety and effectiveness of slope monitoring, and gain more time for disaster warning and prevention.
[0060] See Figure 5 , the single acquisition process of the slave probe includes reading the data of the upper MEMS accelerometer and detecting whether the single acquisition of the upper MEMS accelerometer is completed. If it is not completed, the reading is looped until the single acquisition of the upper MEMS accelerometer is completed. If it is completed, the data of the lower MEMS accelerometer is read and it is detected whether the single acquisition of the lower MEMS accelerometer is completed. If it is not completed, the reading is looped until the single acquisition of the lower MEMS accelerometer is completed. If it is completed, the data of the inclinometer sensor is read and it is detected whether the single acquisition of the inclinometer sensor data is completed. If it is not completed, the reading is looped until the single acquisition of the inclinometer sensor data is completed. If it is completed, data processing is performed and it is judged whether there is a master probe acquisition instruction. If not, continue to read the data and perform data processing. If there is a master probe acquisition instruction, the data is transmitted back to the master probe and it is detected whether the data is sent successfully. If it is not completed, the upload operation is repeated until the data is sent successfully.
[0061] Whether it is the main probe or the slave probe, the data acquisition process is to first read the MEMS accelerometer data and then read the data of the inclination sensor. This is because the MEMS accelerometer can sensitively capture the instantaneous acceleration changes of the slope. When the slope undergoes minute displacements or vibrations due to factors such as rainfall or earthquakes, it can quickly obtain acceleration information and sense the dynamic change trend of the slope in real time, providing initial dynamic data for subsequent analysis. When monitoring the slope, the working conditions of the slope are complex and changeable. Reading the accelerometer data first can quickly respond to emergencies, and then reading the data of the inclination sensor can determine the change in the inclination state of the slope based on the acceleration change, better adapting to the complex and changeable slope environment and ensuring the integrity and effectiveness of data acquisition. The inclination sensor mainly measures the inclination angle of the slope. Reading it after obtaining the acceleration data can further clarify the attitude of the slope after dynamic changes. The combination of the two can comprehensively reflect the motion state of the slope. Obtaining the accelerometer data first and then combining the data of the inclination sensor can analyze the slope displacement from different dimensions, achieve data complementarity, and more accurately judge the direction, magnitude, and trend of the slope displacement.
[0062] In step 5, the Kalman filter algorithm is used to perform weighted fusion on the horizontal displacement and vertical displacement, dynamically correcting the displacement calculation results. In actual measurement, the measurement data of horizontal and vertical displacements inevitably have errors. The Kalman filter can effectively reduce the influence of these errors through the fusion of measurement values and predicted values. The horizontal and vertical displacement data measured by the sensor may be disturbed by factors such as environmental noise and instrument accuracy. Using the Kalman filter algorithm, the data with large measurement errors can be reasonably corrected, making the final displacement calculation result closer to the true value and improving the accuracy of monitoring. When the motion state of the monitored object is complex and the displacement changes in the horizontal and vertical directions are not simply linear, the Kalman filter can adjust the estimation of horizontal and vertical displacements in real time based on the state transition matrix and observation data. When dealing with a large amount of displacement measurement data, the Kalman filter algorithm can reduce unnecessary data storage and processing volume through an effective weighted fusion and prediction update mechanism. Compared with directly processing the original measurement data, this method greatly reduces the complexity and computational amount of data processing, improves the operating efficiency of the system, and enables efficient displacement monitoring and analysis even under limited hardware resource conditions.
[0063] In step 5, the LSTM neural network is used for error correction to correct the displacement data in real time. Specifically, the LSTM network is trained with historical displacement data to predict the drift error during the integration process of the accelerometer. The LSTM can learn the long-term dependence relationships in the data, predict the possible errors through the analysis of historical data and current measurement data, and correct the measurement results to achieve millimeter-level displacement resolution.
[0064] The above has introduced in detail the technical solution provided by this invention patent. Specific examples are used in this article to elaborate on the principle and implementation manner of this invention patent. The description of the above embodiments is only used to help understand the method and its core idea of this invention patent; at the same time, for those of ordinary skill in the art, according to the idea of this invention patent, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this invention patent.
Claims
1. A slope displacement monitoring device based on flexible connection of geological boreholes, characterized in that, Including: A main probe and multiple slave probes. The main probe and the slave probes have the same structure, and each includes a flexible connecting member, a waterproof fixing head, a tube housing, a universal deformation conduction mechanism, and a main control board disposed inside the tube housing; The flexible connecting member is composed of multiple segments of flexible steel wire leads and is used to connect the main probe and the slave probes; The main control board is installed inside the tube housing and sealed by the waterproof fixing head. The main control board is provided with a dual MEMS sensor module, an inclination sensor, an MCU acquisition control and transmission module, a communication module, and a power module; The inclination sensor is used to measure the inclination angle information of the probe; The MCU acquisition control and transmission module is electrically connected to the dual MEMS sensor module, the inclination sensor, the memory, and the communication module respectively, and is used to control sensor data acquisition, process the acquired data, and transmit the data; The main probe further includes a memory for storing the acquired data and the intermediate data during the processing; The power module provides power for each module inside the probe; The universal deformation conduction mechanism is disposed outside the probe and is used to sense the slope displacement and transmit it to the internal sensor.
2. The device according to claim 1, characterized in that, The universal deformation conduction mechanism includes an upper universal deformation conduction mechanism and a lower universal deformation conduction mechanism, which are respectively disposed at the upper end and the lower end of the probe.
3. The device according to claim 1, characterized in that The communication module in the main probe is divided into a host computer communication module and a slave communication module, and the slave communication module is connected to the communication module in the slave probe.
4. The device according to claim 1, wherein The dual MEMS sensor module includes an upper MEMS accelerometer and a lower MEMS accelerometer and is used to measure acceleration information.
5. A method for slope displacement monitoring using the device according to any one of claims 1-4, characterized in that, Including the following steps: S1. Start the main probe working process, read the data of the upper MEMS accelerometer, and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of the lower MEMS accelerometer, and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of the inclination sensor, and detect whether a single acquisition is completed; if not, loop to read until completed; if completed, read the data of multiple slave probes in sequence according to the number; S2. Integrate and process all the sensor and slave probe data collected in step S1; S3. Detect whether the data upload timer is triggered; if triggered, actively upload the processed data to the remote terminal; if not, repeat steps S1 - S3 until triggered; S4. Detect whether the data is sent successfully; if not, repeat the upload operation until completed; S5. Calculate the horizontal displacement component by detecting the change in the slope inclination angle measured by the inclination sensor in the data; obtain the vertical displacement component by performing double integration on the acceleration data collected by the dual MEMS accelerometer in the data, calculate the slope displacement amount based on the horizontal displacement component and the vertical displacement component, and when the monitored displacement exceeds the preset threshold, trigger an alarm signal and upload it to the remote terminal through the communication module.
6. The method according to claim 5, characterized in that, In step S1, multiple slave probe data are sequentially read in the order of the numbers. Specifically, it is detected whether the single acquisition of the slave probe times out. If it times out, the probe is skipped and the data of the next probe is read; if it does not time out, it is detected whether the single acquisition is completed; if it is completed, the probe is skipped and the data of the next probe is read.
7. The method according to claim 5, characterized in that, The single acquisition process of the slave probe includes reading the data of the upper MEMS accelerometer and detecting whether the single acquisition of the upper MEMS accelerometer is completed. If it is not completed, it is cyclically read until the single acquisition of the upper MEMS accelerometer is completed; If it is completed, the data of the lower MEMS accelerometer is read, and it is detected whether the single acquisition of the lower MEMS accelerometer is completed. If it is not completed, it is cyclically read until the single acquisition of the lower MEMS accelerometer is completed; If it is completed, the data of the inclination sensor is read, and it is detected whether the single acquisition of the inclination sensor data is completed; if it is not completed, it is cyclically read until the single acquisition of the inclination sensor data is completed. If it is completed, data processing is performed, and it is judged whether there is a main probe acquisition instruction. If not, data is continuously read and data processing is performed; if there is a main probe acquisition instruction, the data is transmitted back to the main probe, and it is detected whether the data transmission is completed; if it is not completed, the upload operation is repeatedly executed until the data transmission is completed.
8. The method according to claim 5, wherein In step S5, the Kalman filtering algorithm is used to perform weighted fusion on the horizontal displacement and the vertical displacement to dynamically correct the displacement calculation result.
9. The method according to claim 5, wherein In step S5, an LSTM neural network is used for error correction to correct the displacement data in real time. Specifically, the LSTM network is trained through historical displacement data to predict the drift error in the integration process of the accelerometer.