A method for monitoring displacement of thick-thin combined interbedded rock mass and judging instability

Abstract

This invention discloses a method for displacement monitoring and instability determination in interbedded rock masses with varying thicknesses. The method includes: deploying constant-resistance, large-deformation anchor cables with multiple sensor units based on rock bedding and lithological parameters; constructing a segmented coupled interlayer constitutive model of the anchor cables to establish mechanical transmission relationships; processing sensor data using a thickness-corrected sensor fusion algorithm to eliminate interference from rock layer thickness and obtain accurate displacement fusion values; subsequently, using a statistical mechanics coupling threshold algorithm, combining rock mass mechanical parameters to calculate statistical characteristic values ​​of displacement and coupling threshold intervals; transmitting the data to an interbedded rock mass monitoring visualization platform for storage, display, and analysis; comparing the coupling threshold intervals to determine the rock mass instability trend and outputting relevant parameters. This method can comprehensively collect data, improve data accuracy and judgment reliability, effectively solve problems of data deviation, judgment lag, or misjudgment, and is applicable to rock mass monitoring and disaster early warning in mining, tunnel construction, and other engineering projects.

Description

Technical Field

[0001] This invention relates to the field of rock mass displacement monitoring technology, and in particular to a method for the deployment of displacement monitoring and instability determination of interbedded thick and thin rock masses. Background Technology

[0002] In mineral resource extraction, tunnel construction, and slope protection projects, interbedded thick and thin rock masses, due to their complex bedding structure and significant lithological differences, are prone to displacement and deformation under external loads and environmental factors, leading to geological disasters such as collapses and landslides, posing a serious threat to project safety and the lives and property of personnel. Current engineering projects require scientific displacement monitoring deployment and instability assessment methods to monitor the deformation state of interbedded thick and thin rock masses in real time, providing data support for project protection and disaster early warning. Monitoring technology based on constant-resistance large-deformation anchor cables is gradually becoming an important choice for monitoring such rock masses due to its adaptability to large rock mass deformations. However, its deployment scheme and instability assessment logic need to be optimized by considering factors such as the interlayer mechanical properties of the rock mass, the accuracy of sensor data processing, and the rationality of threshold determination, to meet the project's requirements for monitoring accuracy and timely assessment.

[0003] Existing technologies for displacement monitoring and instability assessment of interbedded rock masses of varying thicknesses have two significant drawbacks: Firstly, existing monitoring methods often employ a single sensor data acquisition and processing mode, failing to adequately consider the interference of interbedded rock masses of different thicknesses on sensor signals and lacking a specific correction mechanism for differences in rock mass thickness. This leads to deviations in the acquired displacement data, making it difficult to accurately reflect the true deformation state at different interlayer interfaces and within the rock mass, thus affecting the reliability of subsequent monitoring results. Secondly, existing instability assessments often rely on simple displacement threshold comparisons, failing to incorporate statistical mechanics principles to construct coupled threshold ranges related to rock mass mechanical parameters (such as shear strength and cohesion). This makes it difficult to comprehensively reflect the dynamic trends of rock mass displacement changes and the evolution of instability, often resulting in delayed or misjudgments, and failing to provide timely and accurate decision-making basis for engineering disaster early warning. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a method for displacement monitoring and instability determination of interbedded thick and thin rock masses.

[0005] The technical solution adopted in this invention is a method for displacement monitoring and instability determination of interbedded rock masses with varying thicknesses, comprising the following steps: S1. Based on the bedding distribution characteristics and lithological parameters of the interbedded rock masses with varying thicknesses, determine the placement points, depths, and spacing of constant-resistance large-deformation anchor cables. Drill holes at each placement point and implant constant-resistance large-deformation anchor cables with multiple sets of sensing units, so that the sensing units correspond to the interlayer interfaces and internal regions of interbedded rock masses with different thicknesses; S2. Construct a segmented coupled interlayer constitutive model of the anchor cables. Based on the rock mass stress and displacement data initially collected by each sensing unit, determine the basic parameters related to the thickness and elastic modulus of the interbedded rock masses in the model, and establish the mechanical transmission relationship between the anchor cables and interbedded rock masses with different thicknesses; S3. Use a thickness-corrected sensing fusion algorithm to fuse the displacement monitoring data collected in real time by each sensing unit. By introducing an interbedded rock mass thickness correction coefficient, eliminate the interference of rock layers of different thicknesses on the sensing data, and obtain... S4. Using a statistical mechanics coupling threshold algorithm, the displacement fusion values ​​obtained in S3 are statistically analyzed. Combined with the shear strength and cohesion parameters of the interbedded rock mass, the statistical characteristic values ​​of rock mass displacement in different monitoring periods are calculated to determine the coupling threshold range of rock mass displacement change. S5. The statistical characteristic values, coupling threshold range, and raw data of each sensor unit obtained in S4 are transmitted to the interbedded rock mass monitoring visualization platform. The platform classifies, stores, and visualizes the data, generating displacement time series curves and interbedded displacement cloud maps for each monitoring point. S6. Based on the displacement time series curves and interbedded displacement cloud maps displayed on the visualization platform, the coupling threshold range determined in S4 is compared. When the displacement value of a certain monitoring point exceeds the coupling threshold range and continues to change, it is determined that the interbedded rock mass with thick and thin layers in that area is showing an instability trend. At the same time, the location, range, and displacement change rate parameters of the corresponding instability area are output.

[0006] Furthermore, the expression for the needle-and-cable segmented coupled interlayer constitutive model is as follows: ,in, Spatial coordinates at time t The stress components of the k-th interbedded rock mass coupled with needle-like structures. For the k-th layer of rock mass, the thickness varies with the thickness. The changing elastic modulus, Spatial coordinates at time t The strain components at the location, For the k-th layer of rock mass, the thickness varies with the thickness. Changing Poisson's ratio For the k-th layer of rock mass, the thickness varies with the thickness. and displacement increment Varying interlaminar bond stress, For the k-th layer of rock mass, the thickness varies with the thickness. The varying stress attenuation coefficient.

[0007] Furthermore, the expression for the thickness correction sensing fusion algorithm is: Spatial coordinates at time t The displacement fusion value at the location, where n is the number of sensing units. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The weighting coefficients, The original displacement value collected by the i-th sensing unit at time t. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The dynamic correction coefficient, The rate of change of displacement value for the i-th sensing unit over time.

[0008] Furthermore, the expression for the statistical mechanics coupling threshold algorithm is: ,in, Spatial coordinates The coupling threshold of rock mass displacement. Boltzmann's constant, This is a reference temperature for the rock mass environment. Spatial coordinates Number of monitoring data samples This represents the maximum displacement increment at that location. This represents the average displacement increment at that location. The shear strength parameters of the rock mass at this location are... This represents the cohesion parameter of the rock mass at this location.

[0009] Furthermore, the data processing expression of the interbedded rock mass monitoring visualization platform is as follows: ,in, The visualized data values ​​displayed on the platform. To visualize the scaling factor, Spatial coordinates Visual mapping coefficients at the location, Visual weighting coefficients for the coupling threshold. Total monitoring duration This is the displacement fusion value. This is the coupling threshold.

[0010] Furthermore, the calculation expression for the displacement monitoring parameters based on the constant resistance large deformation anchor cable is as follows: ,in, Spatial coordinates at time t Axial force in anchor cables subjected to constant resistance and large deformation. Let L be the stiffness coefficient of the anchor cable as a function of its length L. The viscous damping coefficient of the needle cable varies with length L. For integration variables, for The displacement fusion value at time.

[0011] Further, step S3 includes the following sub-steps: S31, acquiring the raw displacement data collected by each sensing unit, extracting the acquisition time, spatial coordinates, and thickness parameters of the interbedded rock mass corresponding to each data point, and establishing a correlation mapping table between the raw data and the rock mass thickness; S32, grouping the sensing data corresponding to rock masses of different thicknesses according to the correlation mapping table, calculating the standard deviation and mean of each group of data, identifying and marking outliers in the data; S33, introducing a correction coefficient positively correlated with the rock mass thickness, and weighting the valid data other than the marked outliers, with the weighting weight determined according to the fitting relationship between the rock mass thickness and the sensitivity of the sensing unit; S34, fusing the weighted data of each group to obtain the displacement fusion value of each monitoring point at the corresponding time, and recording the correction coefficient and weight parameters used in the fusion process.

[0012] Further, S4 includes the following sub-steps: S41, collecting the displacement fusion values ​​of multiple consecutive monitoring periods output by S3, dividing the data into groups according to the monitoring periods, and calculating the variance, range, and skewness statistical characteristic parameters of each group of data; S42, obtaining the shear strength and cohesion parameters of the thick and thin interbedded rock mass, and using linear interpolation to correlate these parameters with the displacement fusion values ​​of the corresponding monitoring periods to establish a correspondence between mechanical parameters and displacement statistical characteristics; S43, based on the concept of partition function in statistical mechanics, substituting the statistical characteristic parameters of the displacement fusion values ​​and the rock mass mechanical parameters into the coupling calculation model to obtain the displacement change coupling coefficient within each monitoring period; S44, determining the distribution range of the coupling coefficient based on the coupling coefficients of multiple monitoring periods, using this range as the coupling threshold range for rock mass displacement changes, and simultaneously calculating the upper and lower limit deviation values ​​of the threshold range.

[0013] Further, S5 includes the following sub-steps: S51, organizing the statistical characteristic values, coupling threshold intervals, and raw data of each sensing unit obtained in S4 according to a preset data format, and converting them into a binary data format recognizable by the monitoring visualization platform; S52, establishing a data classification and storage directory, classifying and storing the converted data according to monitoring points, monitoring time, and data type, and adding metadata including acquisition parameters and processing parameters to each data file; S53, calling the platform's visualization rendering module, generating displacement time series curves for each monitoring point based on the displacement fusion value, generating inter-layer displacement cloud maps by combining the inter-layer interface coordinates, and setting color mapping rules between the curves and cloud maps to distinguish different displacement magnitudes; S54, setting a data query interface in the visualization interface, supporting querying raw data, statistical characteristic values, and coupling threshold intervals by monitoring point and time range, and providing a data export function.

[0014] A method for displacement monitoring and instability determination in interbedded thick and thin rock masses is disclosed. This method is implemented through different units, including: a constant-resistance, large-deformation anchor cable multi-sensor implantation unit, adapted to the borehole structure of the interbedded thick and thin rock mass, integrating multiple sets of sensing modules corresponding to different rock layer thicknesses for collecting rock mass displacement and stress data and transmitting them to a data preprocessing unit; an anchor cable-rock mass coupled constitutive calculation unit, receiving data from the constant-resistance, large-deformation anchor cable multi-sensor implantation unit, incorporating an anchor cable segmented coupled interlayer constitutive model algorithm to calculate the mechanical transfer parameters between the anchor cable and the rock mass and sending them to a data fusion unit; and a thickness-corrected sensing data fusion unit, connected to the anchor cable-rock mass coupled constitutive calculation unit, employing a thickness-corrected sensing fusion algorithm to fuse the mechanical transfer parameters and the original sensing data, outputting a data fusion result. The data is transferred to the statistical analysis unit; the statistical mechanics coupling threshold analysis unit communicates with the thickness correction sensing data fusion unit, uses the statistical mechanics coupling threshold algorithm to calculate the statistical characteristics and coupling threshold range of the displacement fusion value, and transmits the results to the visualization processing unit; the interbedded rock mass monitoring visualization unit receives the results from the statistical mechanics coupling threshold analysis unit, combines the original data to generate visualization charts, and connects to the instability determination output unit; the instability determination and parameter output unit obtains the chart data and coupling threshold range from the interbedded rock mass monitoring visualization unit, compares and analyzes the displacement change trend, determines the rock mass instability state, and outputs the location, range, and displacement rate parameters of the instability area. All units interact via industrial Ethernet, and the data transmission process uses an encryption protocol to protect the data.

[0015] Beneficial Effects: This invention proposes a method for displacement monitoring and instability determination in interbedded thick and thin rock masses. It precisely deploys constant-resistance, large-deformation anchor cables with multiple sensor units based on the characteristics of the interbedded thick and thin rock masses. A segmented coupled interlayer constitutive model of the anchor cables is used to establish the mechanical transmission relationship between the anchor cables and the rock mass. A thickness-corrected sensor fusion algorithm is then used to eliminate the interference of rock layer thickness on the data to obtain accurate displacement fusion values. A statistical mechanics coupling threshold algorithm is used to construct a coupling threshold range associated with the rock mass's mechanical parameters. Finally, a monitoring visualization platform for interbedded rock masses is used to achieve data visualization and instability determination. This method can comprehensively grasp the deformation state between and within the rock mass layers, improve monitoring accuracy and the timeliness of instability determination, and provide reliable data support for engineering disaster early warning. Meanwhile, this method establishes a special correction mechanism for the interference of interlayered rock masses of different thicknesses on the sensing signals through a thickness correction sensing fusion algorithm, effectively solving the data deviation problem caused by the single sensing processing mode of the existing technology, and ensuring that the displacement data can accurately reflect the real deformation of the rock mass. By constructing a coupling threshold range that combines rock mass mechanical parameters through a statistical mechanics coupling threshold algorithm, it replaces the simple displacement threshold comparison, comprehensively reflects the dynamic trend of rock mass displacement and the instability evolution law, and avoids judgment lag or misjudgment. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method steps of the present invention;

[0017] Figure 2 This is a diagram showing the unit composition for implementing the method of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 1 As shown, a method for displacement monitoring and instability determination of interbedded thick and thin rock masses includes the following steps:

[0020] S1. Based on the bedding distribution characteristics and lithological parameters of the interbedded rock mass with thick and thin layers, determine the layout points, depths and spacing of the constant resistance large deformation anchor cable. Drill holes at each layout point and insert the constant resistance large deformation anchor cable with multiple sets of sensing units, so that the sensing units correspond to the interlayer interface and internal area of ​​the interbedded rock mass with different thicknesses.

[0021] Specifically, in step S1, ground-penetrating radar and core drilling analysis are used to obtain the bedding distribution characteristics of the interbedded thick and thin rock mass. The thickness range of the thin rock layer is determined to be 0.3-1.2 meters, and the thickness range of the thick rock layer is 1.5-5.0 meters. Simultaneously, the elastic modulus of each rock layer is measured to be 20-60 GPa, and the Poisson's ratio to be 0.2-0.35. Based on these parameters, the spacing of the constant-resistance large-deformation anchor cables is set to 2.5-4.0 meters, and the installation depth is determined to be 0.8-1.5 meters below the bottom surface of the lowest thick rock layer. The installation points are preferentially selected in areas with drastic changes in the rock layer interface. Subsequently, drilling equipment with a diameter matching the anchor cables is used. Drill holes with a diameter of 130-180 mm at the deployment points, and control the verticality deviation of the holes within 0.5%. The length of the implanted constant resistance large deformation anchor cable is determined according to the deployment depth. 6-12 sets of sensing units are integrated on the anchor cable. The spacing between each set of sensing units is adjusted according to the rock layer thickness to ensure that one set of sensing units is set every 0.5-0.8 meters in thin rock layer areas and one set of sensing units is set every 1.0-1.5 meters in thick rock layer areas. Each set of sensing units corresponds to the interlayer interface and internal area of ​​interlayer rock masses of different thicknesses. The initial acquisition frequency of the sensing units is set to 1-5 minutes / time to ensure that the initial stress and displacement state of the rock mass can be captured in real time.

[0022] S2. Construct a segmented coupled interlayer constitutive model of anchor cables. Based on the rock mass stress and displacement data initially collected by each sensing unit, determine the basic parameters related to the thickness and elastic modulus of the interlayered rock mass in the model, and establish the mechanical transmission relationship between the anchor cables and interlayered rock masses of different thicknesses.

[0023] Specifically, in step S2, the rock mass stress data (range 0.5-3.0 MPa) and displacement data (range 0.1-2.0 mm) initially collected by each sensing unit in step S1 are first collected to establish a dataset. Based on this dataset, a segmented coupled interlayer constitutive model of the anchor cable is constructed. The model divides the contact area between the anchor cable and the rock mass into multiple coupled segments according to the rock layer thickness, and each coupled segment corresponds to a set of sensing unit monitoring ranges. In the process of determining the model parameters, for thin rock layers (0.3-1.2 meters), the elastic modulus correction coefficient related to the thickness is obtained by fitting the stress-displacement curve and is 0.8. -0.95, and the bond strength correction coefficient is 0.75-0.9; for thick rock layers (1.5-5.0 meters), the elastic modulus correction coefficient is 0.92-0.98, and the bond strength correction coefficient is 0.85-0.95; through the above parameters, the mechanical transmission relationship between the anchor cable and the interbedded rock mass of different thicknesses is established, the transmission attenuation law of the anchor cable axial force in different rock layers is clarified, and the model is ensured to accurately reflect the stress transmission process between the anchor cable and the rock mass, providing a mechanical basis for subsequent data processing. In this process, the model calculation results need to be compared and verified with the initial monitoring data, and the error is controlled within 5%.

[0024] S3. A thickness correction sensing fusion algorithm is adopted to fuse the displacement monitoring data collected in real time by each sensing unit. By introducing the thickness correction coefficient of interbedded rock mass, the interference of rock layers of different thicknesses on the sensing data is eliminated, and the interlayer and internal displacement fusion values ​​of each monitoring point are obtained.

[0025] Specifically, in step S3, the displacement monitoring data collected in real time by each sensing unit in step S1 is first extracted. The data acquisition frequency is maintained at 1-5 minutes / time, and each acquisition includes the displacement values ​​of each sensing unit in the x, y, and z directions. Then, a thickness correction sensing fusion algorithm is used to first remove outliers from the collected raw displacement data. The removal standard is data that exceeds the mean ± 3 times the standard deviation of the monitoring range of the sensing unit. Next, a thickness correction coefficient for interbedded rock mass is introduced. This coefficient is calculated based on the thickness of the rock layers. The correction coefficient for thin rock layers (0.3-1.2 meters) is 1.1-1.3, and the correction coefficient for thick rock layers (1.5-5.0 meters) is 0.9. -1.05; The displacement data of each sensing unit is weighted by a correction coefficient. The weighting weight is determined according to the proportion of the rock layer thickness where the sensing unit is located to the total monitored thickness. The weighting ratio of sensing units in thin rock layer areas is 0.3-0.5, and the weighting ratio of sensing units in thick rock layer areas is 0.5-0.7. After processing, the displacement data of different sensing units at the same monitoring point are fused and calculated. The arithmetic mean and weighted mean are combined to obtain the fused displacement values ​​of interlayer and internal rock mass at each monitoring point. The error of the fused data is controlled within 0.05-0.2 mm to ensure that the interference of rock layers of different thicknesses on the sensing data is eliminated and the accuracy of displacement data is improved.

[0026] S4. Using the statistical mechanics coupling threshold algorithm, the displacement fusion value obtained in S3 is statistically analyzed. Combined with the shear strength and cohesion parameters of the interbedded rock mass, the statistical characteristic values ​​of the rock mass displacement in different monitoring periods are calculated to determine the coupling threshold range of the rock mass displacement change.

[0027] Specifically, in step S4, the displacement fusion values ​​obtained in step S3 for 24-72 consecutive hours are first collected. These values ​​are then divided into monitoring periods of 2-6 hours each, resulting in a dataset of 4-36 monitoring periods. Statistical analysis is performed on the displacement fusion values ​​for each period, calculating the mean (range 0.2-3.5 mm), variance (range 0.01-0.5 mm²), and range (range 0.1-2.5 mm²) of the displacement fusion values ​​within each period. Simultaneously, laboratory tests are conducted to determine the shear strength (range 15-45 MPa) and cohesion (range 2-) of the thick and thin interbedded rock masses. The parameters are 8 MPa. The above statistical characteristic values ​​and rock mechanics parameters are substituted into the statistical mechanics coupling threshold algorithm. The algorithm first standardizes the data and then calculates the probability distribution of displacement changes through ensemble theory in statistical mechanics. The normal fluctuation range of rock mass displacement changes is determined according to the probability distribution, and this range is set as the coupling threshold interval. The difference between the upper and lower limits of the interval is controlled within 0.5-2.0 mm. At the same time, the deviation rate between the displacement fusion value and the coupling threshold interval in each monitoring period is calculated. Periods with a deviation rate exceeding 5% are marked as key attention periods to provide a quantitative basis for subsequent instability judgment and ensure the scientific and objective nature of the judgment standard.

[0028] S5. Transmit the statistical characteristic values, coupling threshold ranges and raw data of each sensing unit obtained in S4 to the interbedded rock mass monitoring visualization platform. The platform classifies, stores and visualizes the data, and generates displacement time series curves and interlayer displacement cloud maps for each monitoring point.

[0029] Specifically, in step S5, the statistical characteristic values ​​(mean, variance, range), coupling threshold intervals (upper and lower limits and deviation rate) and raw data of each sensor unit (including acquisition time, spatial coordinates, and displacement values) obtained in step S4 are first converted into JSON format data, with the data transmission rate controlled at 10-50Mbps. Then, the converted data is transmitted to the interbedded rock mass monitoring visualization platform. The platform uses a distributed database for data storage, with a storage capacity designed at 50-200MB per monitoring point per day, and a data retention period set at 30-90 days. The platform then classifies the data, categorizing the statistical characteristic values ​​and coupling threshold intervals into the analysis results category. The raw data is stored in the raw database. In the visualization stage, the platform generates displacement time series curves for each monitoring point. The horizontal axis of the curve represents the monitoring time (accurate to the minute), and the vertical axis represents the displacement fusion value (accurate to 0.01 mm). At the same time, based on the rock interface coordinates determined in step S1, an interlayer displacement cloud map is generated. The cloud map color is graded according to the displacement value: blue for 0-1.0 mm, yellow for 1.0-2.0 mm, and red for displacements above 2.0 mm. The platform supports simultaneous display in multiple windows and can switch between curves and cloud maps of different monitoring points in real time, making it convenient for staff to intuitively grasp the deformation status of the rock mass. The data update frequency is synchronized with the sensor unit acquisition frequency (1-5 minutes / time).

[0030] S6. Based on the displacement time series curve and interlayer displacement cloud map displayed on the visualization platform, compare with the coupling threshold range determined in S4. When the displacement value of a certain monitoring point exceeds the coupling threshold range and continues to change, it is determined that the thick and thin interlayer rock mass in the area is instability trending. At the same time, the location, range and displacement change rate parameters of the corresponding instability area are output.

[0031] Specifically, during step S6, staff use the interbedded rock mass monitoring visualization platform to view the displacement time series curves and interlayer displacement cloud maps of each monitoring point. First, they observe the curve trend. If the curve shows a continuous upward or abrupt upward trend, and the rate of increase exceeds 0.05-0.2 mm / hour, while a red area appears in the cloud map and gradually expands, then the threshold comparison stage begins. The real-time displacement value of the monitoring point is compared with the coupling threshold range determined in step S4. If the displacement value exceeds the upper limit of the range and the duration exceeds 30-60 minutes, it is determined that the interbedded rock mass of thick and thin layers in this area is showing signs of instability. Subsequently, the platform automatically... The system dynamically retrieves the layout parameters (spacing, depth), sensor unit distribution, and historical displacement data of the monitoring point. It calculates the location coordinates (accurate to 0.1 meters), size (calculated as the area of ​​the displacement exceeding the threshold, in square meters), and displacement change rate (accurate to 0.01 mm / hour) of the unstable area. The system outputs these parameters in report form, including a schematic diagram of the unstable area, a displacement change trend table, and a summary of key parameters. The output format supports PDF and Excel. At the same time, the system sends early warning information to staff through the early warning module to ensure that engineering protection measures can be taken in a timely manner to avoid disasters.

[0032] Preferably, the expression for the needle-and-cable segmented coupled interlayer constitutive model is: ,in, Spatial coordinates at time t The stress components of the k-th interbedded rock mass coupled with needle-like structures. For the k-th layer of rock mass, the thickness varies with the thickness. The changing elastic modulus, Spatial coordinates at time t The strain components at the location, For the k-th layer of rock mass, the thickness varies with the thickness. Changing Poisson's ratio For the k-th layer of rock mass, the thickness varies with the thickness. and displacement increment Varying interlaminar bond stress, For the k-th layer of rock mass, the thickness varies with the thickness. The varying stress attenuation coefficient.

[0033] Specifically, a segmented coupled interlayer constitutive model of the anchor cable was constructed and its parameters were determined. First, mechanical data of rock layers with different thicknesses were collected. When the thickness of the thin rock layer was 0.3-1.2 meters, the elastic modulus correction coefficient was 0.8-0.95, the bond stress varied with thickness and displacement increment in the range of 0.3-1.5 MPa, and the stress attenuation coefficient was 0.02-0.08 through stress-displacement curve fitting. When the thickness of the thick rock layer was 1.5-5.0 meters, the elastic modulus correction coefficient was 0.92-0.98, the bond stress was 0.5-2.0 MPa, and the stress attenuation coefficient was 0.01-0.05. The implementation process first involves dividing the coupling segment between the anchor cable and the rock mass. Each segment corresponds to a set of sensing units monitoring the range (0.5-0.8 meters for thin rock layers and 1.0-1.5 meters for thick rock layers). Then, the elastic modulus, Poisson's ratio, and other parameters of each coupling segment are substituted into the model to calculate the stress components at different spatial coordinates at different times. The calculation must be combined with real-time strain data (range 10⁻⁶-10⁻⁴) collected by the sensing units to ensure the model accurately reflects the mechanical transmission relationship between the anchor cable and the rock mass. This model accurately describes the interaction between rock layers of different thicknesses and the anchor cable, avoiding stress calculation deviations caused by interlayer mechanical differences, and providing a reliable mechanical basis for subsequent data processing. After implementation, the stress values ​​calculated by the model must be compared with the measured stresses (0.5-3.0 MPa) by the sensing units, with the error controlled within 5% to ensure model accuracy.

[0034] Preferably, the expression for the thickness correction sensing fusion algorithm is: Spatial coordinates at time t The displacement fusion value at the location, where n is the number of sensing units. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The weighting coefficients, The original displacement value collected by the i-th sensing unit at time t. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The dynamic correction coefficient, The rate of change of displacement value for the i-th sensing unit over time.

[0035] Specifically, the thickness-corrected sensor fusion algorithm first determines the number of sensor units (6-12 groups), grouping them according to rock layer thickness. For thin rock layers (0.3-1.2 meters), the sensor unit weight coefficient is 0.3-0.5 and the dynamic correction coefficient is 1.1-1.3; for thick rock layers (1.5-5.0 meters), the weight coefficient is 0.5-0.7 and the dynamic correction coefficient is 0.9-1.05. During implementation, real-time displacement data for each sensor unit is extracted (collection frequency 1-5 minutes / time, x, y, z displacement values ​​range 0.1-3.5 mm). The mean and standard deviation of each group of data are calculated, and outliers exceeding ±3 times the standard deviation are removed. Then, the weight and dynamic correction coefficient of the corresponding sensor unit are determined according to the rock layer thickness. Valid data are weighted, and the correction amplitude is adjusted based on the time change rate of the displacement value (range 0.01-0.2 mm / hour). Subsequently, the data was fused using a combination of arithmetic and weighted averages. The displacement error after fusion was 0.05-0.15 mm in thin rock layers and 0.08-0.2 mm in thick rock layers. This algorithm eliminates the interference of rock layers of varying thicknesses on the sensor data, improving the accuracy of the fused displacement values. After implementation, the consistency between the fused data and the actual measured displacements in the field needs to be verified to ensure accurate reflection of the true deformation state of the rock mass and to provide reliable data support for subsequent statistical analysis.

[0036] Preferably, the expression for the statistical mechanics coupling threshold algorithm is: ,in, Spatial coordinates The coupling threshold of rock mass displacement. Boltzmann's constant, This is a reference temperature for the rock mass environment. Spatial coordinates Number of monitoring data samples This represents the maximum displacement increment at that location. This represents the average displacement increment at that location. The shear strength parameters of the rock mass at this location are... This represents the cohesion parameter of the rock mass at this location.

[0037] Specifically, a statistical mechanical coupling threshold algorithm is used to calculate the threshold range. First, displacement fusion values ​​are collected for 24-72 consecutive hours (each monitoring period is 2-6 hours, for a total of 4-36 periods). The maximum displacement increment for each period is calculated to be 0.5-2.5 mm, and the average is 0.2-1.5 mm. The number of monitoring data samples per period is 50-200. Simultaneously, rock mass mechanical parameters are determined through laboratory tests: shear strength 15-45 MPa, cohesion 2-8 MPa, and the environmental reference temperature is set at 15-25℃. During implementation, the displacement increment data and mechanical parameters are first standardized, then substituted into the algorithm for calculation. Using the physical parameter conversion value corresponding to the Boltzmann constant, combined with the sample size, displacement increment statistics, and mechanical parameters, the coupling threshold for each monitoring point is obtained. The coupling threshold range for thin rock layers is 0.8-2.0 mm, and for thick rock layers it is 1.0-2.5 mm, with an upper and lower limit difference of 0.5-1.0 mm. The algorithm establishes a dynamic threshold associated with the mechanical properties of the rock mass, avoiding the limitations of simple displacement comparison. After implementation, the threshold range needs to be compared with historical instability case data to ensure that when the displacement exceeds the threshold, it can accurately reflect the instability trend and provide a scientific quantitative standard for instability judgment.

[0038] Preferably, the data processing expression of the interbedded rock mass monitoring visualization platform is: ,in, The visualized data values ​​displayed on the platform. To visualize the scaling factor, Spatial coordinates Visual mapping coefficients at the location, Visual weighting coefficients for the coupling threshold. Total monitoring duration This is the displacement fusion value. This is the coupling threshold.

[0039] Specifically, the data processing for the interbedded rock mass monitoring visualization platform involves first determining the relevant visualization parameters. The scaling factor is set to 1.2-1.8, and the visualization mapping coefficient at the spatial coordinates is adjusted according to the rock layer thickness: 0.8-1.2 for thin rock layers and 1.0-1.5 for thick rock layers. The visualization weight coefficient for the coupling threshold is 0.6-0.9, and the total monitoring duration is designed to be 30-90 days. During implementation, statistical characteristic values ​​(mean 0.2-3.5 mm, variance 0.01-0.5 mm²), coupling threshold ranges (upper and lower limits 0.8-2.5 mm), and raw data are received. After converting these data into a format that the platform can process, they are substituted into the data processing expression to calculate the visualization data values. The visualization data value mapping range for thin rock layer areas is 0.5-2.0, and for thick rock layer areas it is 0.8-2.5. The weights need to be adjusted based on the proportion of monitoring time to the total duration during calculation. The platform then generates charts based on the visualized data values. The displacement time series curves are accurate to the minute on the horizontal axis and to 0.01 millimeters on the vertical axis. The interlayer displacement cloud map is color-coded according to the visualized data values: light blue for 0.5-1.0, dark blue for 1.0-1.5, yellow for 1.5-2.0, and red for values ​​above 2.0. This process transforms complex data into intuitive visualizations, allowing staff to quickly grasp the deformation status of the rock mass. During implementation, it is essential to ensure that the error between the visualized data values ​​and the original data is less than 8%, guaranteeing that the charts accurately reflect the monitoring situation.

[0040] Preferably, the expression for calculating the displacement monitoring parameters based on the constant-resistance large-deformation anchor cable is as follows: ,in, Spatial coordinates at time t Axial force in anchor cables subjected to constant resistance and large deformation. Let L be the stiffness coefficient of the anchor cable as a function of its length L. The viscous damping coefficient of the needle cable varies with length L. For integration variables, for The displacement fusion value at time.

[0041] Specifically, to calculate the axial force parameters of a constant-resistance, large-deformation anchor cable, first determine the anchor cable's own parameters. The length is determined to be 5-20 meters based on the installation depth (0.8-1.5 meters below the bottom of the thickest rock layer). The stiffness coefficient varies with the length: 15-25 kN / mm for 5-10 meters, and 20-30 kN / mm for 10-20 meters. The viscous damping coefficient is 5-15 kN·s / mm. During implementation, first acquire the displacement fusion value (range 0.1-3.5 mm) and the time integral data of the displacement fusion value. The integration time interval is consistent with the acquisition frequency (1-5 minutes), and the integration result ranges from 0.5-30 mm·hour. Substitute the displacement fusion value and the integration result into the calculation expression. First, calculate the product of the stiffness coefficient and the displacement fusion value (range 1.5-105 kN), then calculate the product of the viscous damping coefficient and the integration result (range 2.5-450 kN·hour / mm). Add the two together to obtain the anchor cable axial force. In thin rock strata, the axial force of the anchor cable ranges from 5-80 kN, while in thick rock strata it ranges from 10-120 kN. During calculation, the stiffness and damping coefficient need to be adjusted in real time according to the anchor cable length. This calculation uses changes in axial force to help determine the coupling state between the anchor cable and the rock mass. When the axial force exceeds 120 kN or the rate of change exceeds 5 kN / hour, the stability of the rock mass needs to be closely monitored. After implementation, the calculated axial force should be compared with the measured axial force of the anchor cable (with an error controlled within 10%) to ensure accurate reflection of the anchor cable's stress condition and to guarantee the reliability of the monitoring system.

[0042] Preferably, step S3 includes the following sub-steps: S31. Acquire the raw displacement data collected by each sensing unit, extract the acquisition time, spatial coordinates, and thickness parameters of the interbedded rock mass corresponding to each data point, and establish a correlation mapping table between the raw data and the rock mass thickness; S32. According to the correlation mapping table, group the sensing data corresponding to rock masses of different thicknesses, calculate the standard deviation and mean of each group of data, identify and mark outliers in the data; S33. Introduce a correction coefficient positively correlated with the rock mass thickness, and perform weighted processing on the valid data other than the marked outliers. The weighting weight is determined according to the fitting relationship between the rock mass thickness and the sensitivity of the sensing unit; S34. Perform fusion calculation on the weighted data of each group to obtain the fused displacement value of each monitoring point at the corresponding time, and record the correction coefficient and weight parameters used in the fusion process.

[0043] Specifically, step S3 includes S31 to S34. In S31, raw displacement data is extracted from each sensing unit (6-12 groups in total, 1 group for thin rock layers every 0.5-0.8 meters and 1 group for thick rock layers every 1.0-1.5 meters). The data includes the acquisition time (accurate to the minute), spatial coordinates (accurate to 0.1 meters), and the thickness of the corresponding rock layer (0.3-1.2 meters for thin rock layers and 1.5-5.0 meters for thick rock layers). Then, an association mapping table is established to ensure that each group of data is accurately matched with the corresponding rock thickness. The mapping table is stored in Excel format for easy querying and retrieval later. S32 groups the data according to the rock layer thickness based on the mapping table, grouping thin rock layer data into one group and thick rock layer data into another. The standard deviation (0.05-0.15 mm for thin rock layers, 0.08-0.2 mm for thick rock layers) and mean (0.2-1.5 mm for thin rock layers, 0.5-2.5 mm for thick rock layers) are calculated for each group. Data exceeding the mean ± 3 times the standard deviation are marked as outliers, with the outlier proportion controlled within 3% of the total data volume. S33 introduces a correction coefficient positively correlated with rock mass thickness: 1.1-1.3 for thin rock layers and 0.9-1.05 for thick rock layers. The valid data after outlier removal are weighted, with the weights determined according to the proportion of rock layer thickness to the total monitored thickness (30%-50% for thin rock layers, 50%-70% for thick rock layers). The weighting process must refer to the fitting relationship between sensor unit sensitivity and rock layer thickness to ensure that the weight allocation conforms to the actual data acquisition situation. S34 uses a combination of arithmetic mean and weighted average to fuse the weighted data, obtaining the fused displacement value for each monitoring point (spaced 2.5-4.0 meters apart) at the corresponding time. The error of the fused value is controlled within 0.05-0.2 mm. At the same time, the correction coefficients and weight parameters used in the fusion process are recorded to form a data processing report, providing a basis for subsequent data traceability and verification. The entire process needs to be executed automatically in the data processing system, with a processing time not exceeding 5 minutes per cycle.

[0044] Preferably, step S4 includes the following sub-steps: S41, collecting the displacement fusion values ​​of multiple consecutive monitoring periods output by S3, dividing the data into groups according to the monitoring periods, and calculating the variance, range, and skewness statistical characteristic parameters of each group of data; S42, obtaining the shear strength and cohesion parameters of the thick and thin interbedded rock mass, and using linear interpolation to correlate these parameters with the displacement fusion values ​​of the corresponding monitoring periods to establish a correspondence between mechanical parameters and displacement statistical characteristics; S43, based on the concept of partition function in statistical mechanics, substituting the statistical characteristic parameters of the displacement fusion values ​​and the rock mass mechanical parameters into the coupling calculation model to obtain the displacement change coupling coefficient within each monitoring period; S44, determining the distribution range of the coupling coefficient according to the coupling coefficients of multiple monitoring periods, using this range as the coupling threshold range for rock mass displacement change, and simultaneously calculating the upper and lower limit deviation values ​​of the threshold range.

[0045] Specifically, step S4 includes S41 to S44. In S41, the continuous 24-72 hour displacement fusion values ​​output by S3 are collected and divided into monitoring periods of 2-6 hours each, resulting in a total of 4-36 time periods. Each time period contains 50-200 data points. Statistical characteristic parameters such as variance (0.0025-0.0225 mm² for thin rock layers and 0.0064-0.04 mm² for thick rock layers), range (0.1-1.0 mm for thin rock layers and 0.2-1.5 mm for thick rock layers) and skewness (range -0.5-0.5) are calculated for each time period. Professional data statistics software is used for parameter calculation to ensure the accuracy of the results. S42. Shear strength (15-45 MPa) and cohesion (2-8 MPa) of interbedded thick and thin rock masses were determined by laboratory rock mechanics tests. Test samples were taken from borehole cores in the monitoring area, with no fewer than three sets of samples. Then, linear interpolation was used to correlate these mechanical parameters with the displacement fusion values ​​of the corresponding monitoring periods, establishing a correspondence table between mechanical parameters and displacement statistical characteristics. The table must clearly show the matching status of mechanical parameters and statistical characteristic parameters for each period, with a correlation error of less than 5%. S43. Based on the concept of statistical mechanical partition function, the statistical characteristic parameters (variance, range, skewness) of the displacement fusion values ​​and rock mass mechanical parameters (shear strength, cohesion) were substituted into the coupling calculation model. The model calculation process must consider the influence of the rock mass ambient temperature (15-25℃) to obtain the displacement change coupling coefficient for each monitoring period (0.8-1.5 for thin rock layers and 1.0-2.0 for thick rock layers). The coupling coefficient calculation must be run in a dedicated algorithm module, and the calculation results are stored in the database in real time. S44 determines the distribution range based on the coupling coefficients of 4-36 monitoring periods. The coupling threshold range for thin rock layers is 0.8-2.0 mm, and for thick rock layers it is 1.0-2.5 mm, with an upper and lower limit difference of 0.5-1.0 mm. At the same time, the upper and lower limit deviations of the threshold ranges are calculated (0.05-0.1 mm for thin rock layers and 0.08-0.15 mm for thick rock layers). The deviations must be controlled within 10% of the upper limit of the threshold range. The determined coupling threshold ranges are entered into the interbedded rock mass monitoring visualization platform as the core basis for subsequent instability determination. The entire process requires regular (every 24 hours) updates to the threshold ranges to ensure they conform to the dynamic changes in rock mass deformation.

[0046] Preferably, step S5 includes the following sub-steps: S51, organizing the statistical characteristic values, coupling threshold intervals, and raw data of each sensing unit obtained in S4 according to a preset data format, and converting them into a binary data format recognizable by the monitoring visualization platform; S52, establishing a data classification and storage directory, classifying and storing the converted data according to monitoring points, monitoring time, and data type, and adding metadata including acquisition parameters and processing parameters to each data file; S53, calling the platform's visualization rendering module, generating displacement time series curves for each monitoring point based on the displacement fusion value, generating inter-layer displacement cloud maps by combining the inter-layer interface coordinates, and setting color mapping rules between the curves and cloud maps to distinguish different displacement magnitudes; S54, setting a data query interface in the visualization interface, supporting querying raw data, statistical characteristic values, and coupling threshold intervals by monitoring point and time range, and providing a data export function.

[0047] Specifically, step S5 includes the progression from S51 to S54. In S51, the statistical characteristic values ​​(variance, range, skewness), coupling threshold range (0.8-2.0 mm for thin rock layers, 1.0-2.5 mm for thick rock layers) and the original data of each sensing unit (including acquisition time, spatial coordinates, and displacement values) obtained in S4 are first organized according to a preset format (JSON format) and converted into a binary data format that can be recognized by the monitoring visualization platform. The conversion process must ensure data integrity, and the size of the converted data should be controlled within 10-50 MB / time. The data transmission rate should be maintained at 10-50 Mbps to avoid transmission delays affecting the real-time performance of the visualization display. The S52 establishes a categorized storage directory in the platform database, classifying and storing the converted data according to monitoring points (numbered in the order of deployment), monitoring time (divided into folders by day), and data type (statistical characteristic values, threshold ranges, raw data). The database adopts a distributed architecture, with a storage capacity designed for 50-200MB per monitoring point per day and a data retention time of 30-90 days. Metadata is added to each data file, including acquisition parameters (number of sensor units, acquisition frequency) and processing parameters (correction coefficients, weights), to facilitate subsequent data filtering and analysis. S53 calls the platform's visualization rendering module to generate displacement time series curves for each monitoring point based on the displacement fusion values ​​(0.2-1.5 mm for thin rock layers and 0.5-2.5 mm for thick rock layers). The horizontal axis of the curve represents the monitoring time (spanning 24-72 hours), and the vertical axis represents the displacement fusion value (accurate to 0.01 mm). Combined with the rock layer interface coordinates determined in step S1 (accurate to 0.1 meters), an interlayer displacement cloud map is generated. The cloud map color scheme is set according to the displacement magnitude (blue for 0-1.0 mm, yellow for 1.0-2.0 mm, and red for above 2.0 mm). The rendering process must ensure the clarity of the chart, the curve smoothness error of less than 0.05 mm, and the natural color transition of the cloud map. The S54 provides a data query interface in its visual interface, supporting queries for raw data, statistical characteristic values, and coupling threshold ranges by monitoring point number and time range (accurate to the hour). The query response time is no more than 3 seconds. It also provides a data export function, supporting export to Excel and PDF formats. The exported data must include complete metadata information to facilitate offline analysis and report creation by staff. The entire platform's operation interface must be simple and intuitive, supporting simultaneous display of multiple windows and real-time switching of charts for different monitoring points.

[0048] The segmented coupled interlayer constitutive model of the anchor cable in this invention is a model that describes the mechanical transmission relationship between the constant resistance large deformation anchor cable and the thick and thin combined interlayered rock mass. The process requires first determining the distribution and mechanical parameters (elastic modulus 20-60 GPa, Poisson's ratio 0.2-0.35) of thin rock layers (0.3-1.2 meters) and thick rock layers (1.5-5.0 meters) through geological surveys. Then, the contact area between the anchor cable and the rock mass is divided into multiple coupling segments according to the rock layer thickness (thin rock layer segment 0.5-0.8 meters long, thick rock layer segment 1.0-1.5 meters long), with each coupling segment corresponding to the monitoring range of one set of sensing units. Subsequently, the initial stress (0.5-3.0 MPa) and displacement (0.1-2.0 mm) data collected by the sensing units are combined to obtain the elastic modulus correction coefficient (0.8-0.95 for thin rock layers, 0.92-0.98 for thick rock layers) and bond strength correction coefficient (0.75-0.9 for thin rock layers, 0.85-0.95 for thick rock layers) and other parameters for each coupling segment. These parameters are then substituted into the model to establish the relationship between stress and strain. The model aims to accurately reflect the interaction between rock strata of different thicknesses and anchor cables, avoiding stress calculation deviations caused by interlayer mechanical differences; it provides a reliable mechanical basis for subsequent data processing, ensuring that monitoring data can truly reflect the mechanical state of anchor cables and rock mass, and laying the foundation for accurate displacement monitoring.

[0049] The thickness correction sensing fusion algorithm in this invention is a processing algorithm that eliminates the interference of rock layers of different thicknesses on sensing data and improves the accuracy of displacement data. The process involves first extracting real-time displacement data from 6-12 groups of sensor units (collection frequency 1-5 minutes / time, x, y, z displacement 0.1-3.5 mm). After grouping by rock layer thickness, the mean (0.2-1.5 mm for thin rock layers, 0.5-2.5 mm for thick rock layers) and standard deviation (0.05-0.15 mm for thin rock layers, 0.08-0.2 mm for thick rock layers) of each group are calculated. Outliers exceeding ±3 times the standard deviation are removed (the proportion is controlled within 3%). Then, a correction coefficient positively correlated with rock layer thickness is introduced (1.1-1.3 for thin rock layers, 0.9-1.05 for thick rock layers). The sensor unit weights are determined based on the proportion of rock layer thickness to the total monitored thickness (30%-50% for thin rock layers, 50%-70% for thick rock layers), and the effective data are weighted. Finally, the data is fused using a combination of arithmetic mean and weighted average to obtain a fused displacement value (error 0.05-0.2 mm). This algorithm eliminates the interference of rock layer thickness on the sensing signal and corrects data deviations; it ensures that displacement data can accurately reflect the true deformation state of different interlayer interfaces and the interior of the rock mass, providing high-quality data support for subsequent statistical analysis and instability determination, and avoiding judgment errors caused by data errors.

[0050] The statistical mechanics coupling threshold algorithm in this invention is an algorithm that combines statistical mechanics principles with rock mass mechanics parameters to determine the rock mass displacement instability threshold range. The process requires first collecting displacement fusion values ​​over 24-72 consecutive hours, dividing the data into 4-36 monitoring periods every 2-6 hours, and calculating statistical characteristic parameters such as variance (0.0025-0.0225 mm² for thin rock layers, 0.0064-0.04 mm² for thick rock layers) and range (0.1-1.0 mm for thin rock layers, 0.2-1.5 mm for thick rock layers) for each period. Then, the shear strength (15-45 MPa) and cohesion (2-8 MPa) of the rock mass are determined through laboratory tests. Linear interpolation is used to correlate the mechanical parameters with the displacement statistical characteristics. Subsequently, based on the concept of statistical mechanical partition function, the parameters are substituted to calculate the displacement variation coupling coefficient for each period (0.8-1.5 for thin rock layers, 1.0-2.0 for thick rock layers). The coupling threshold range is determined based on the coefficient distribution (0.8-2.0 mm for thin rock layers, 1.0-2.5 mm for thick rock layers), and the upper and lower limits of the range are calculated (controlled within 10% of the upper threshold). This algorithm establishes a dynamic and scientific threshold standard for instability judgment; replacing the traditional simple displacement threshold comparison, it comprehensively reflects the dynamic trend of rock mass displacement and the law of instability evolution, avoids judgment lag or misjudgment, provides a quantitative and reliable basis for rock mass instability judgment, and improves the accuracy of disaster early warning.

[0051] The interbedded rock mass monitoring visualization platform of this invention is a system platform for realizing the storage, processing, visualization, and querying of monitoring data. Its implementation requires first receiving statistical characteristic values, coupling threshold ranges, and raw data, converting them into JSON format, and then into binary format (data size 10-50MB / time, transmission rate 10-50Mbps); subsequently, it stores the data in a distributed database according to monitoring point location (spacing 2.5-4.0 meters), time (divided by day), and data type (capacity 50-200MB / point / day, retention 30-90 days), and adds metadata containing acquisition and processing parameters to the data; then, it calls the rendering module to generate displacement time series curves (horizontal axis accurate to minutes, vertical axis accurate to 0.01 mm) and interlayer displacement cloud maps (color-coded according to displacement magnitude: blue for 0-1.0 mm, yellow for 1.0-2.0 mm, and red for above 2.0 mm); finally, it sets up a query interface (response time ≤ 3 seconds) and export function (supporting Excel and PDF formats). This platform enables centralized management and intuitive display of data; it transforms complex monitoring data into easy-to-understand charts, allowing staff to quickly grasp the deformation status of the rock mass. It also supports data traceability and offline analysis, providing clear and timely information support for engineering decisions and helping to efficiently carry out disaster early warning and prevention work.

[0052] like Figure 2As shown, a method for displacement monitoring and instability determination in interbedded thick and thin rock masses is presented. This method is implemented through different units, including: a constant-resistance, large-deformation anchor cable multi-sensor implantation unit, which is adapted to the borehole structure of the interbedded thick and thin rock mass and integrates multiple sets of sensor modules corresponding to different rock layer thicknesses to collect rock mass displacement and stress data and transmit them to a data preprocessing unit; an anchor cable-rock mass coupled constitutive calculation unit, which receives data transmitted from the constant-resistance, large-deformation anchor cable multi-sensor implantation unit, incorporates an anchor cable segmented coupled interlayer constitutive model algorithm, calculates the mechanical transfer parameters between the anchor cable and the rock mass, and sends them to a data fusion unit; and a thickness-corrected sensor data fusion unit, which connects to the anchor cable-rock mass coupled constitutive calculation unit and uses a thickness-corrected sensor fusion algorithm to fuse the mechanical transfer parameters and the original sensor data, outputting the result. The displacement fusion value is sent to the statistical analysis unit; the statistical mechanics coupling threshold analysis unit communicates with the thickness correction sensing data fusion unit, uses the statistical mechanics coupling threshold algorithm to calculate the statistical characteristics and coupling threshold range of the displacement fusion value, and transmits the results to the visualization processing unit; the interbedded rock mass monitoring visualization unit receives the results from the statistical mechanics coupling threshold analysis unit, combines the original data to generate visualization charts, and connects to the instability determination output unit; the instability determination and parameter output unit obtains the chart data and coupling threshold range from the interbedded rock mass monitoring visualization unit, compares and analyzes the displacement change trend, determines the rock mass instability state, and outputs the location, range, and displacement rate parameters of the instability area. All units interact via industrial Ethernet, and the data transmission process uses an encryption protocol to protect the data.

[0053] A method for displacement monitoring and instability determination in interbedded rock masses of varying thicknesses is proposed. In the monitoring deployment stage, the location, depth, and spacing of constant-resistance, large-deformation anchor cables can be accurately determined based on the bedding distribution and lithological parameters of the interbedded rock masses. Furthermore, the anchor cables, equipped with multiple sensing units, can cover the interlayer interfaces and internal regions of rock layers of different thicknesses, achieving comprehensive data acquisition. In the data processing stage, a segmented coupling constitutive model of the anchor cables and the rock mass is used to establish the mechanical relationship between the anchor cables and the rock mass. A thickness-corrected sensing fusion algorithm is then applied to eliminate the interference of rock layer thickness on the data, significantly improving the accuracy of displacement data. In the instability determination stage, a statistical mechanics coupling threshold algorithm is used in conjunction with rock mass mechanical parameters to construct a scientific threshold range. This, combined with an interbedded rock mass monitoring visualization platform, enables data visualization and trend analysis, ensuring the reliability of the determination results while visually presenting the rock mass deformation state, providing a clear basis for engineering decisions.

[0054] This method addresses the data bias problem caused by the single-sensor processing mode in existing technologies. Its thickness-corrected sensor fusion algorithm establishes a specific correction mechanism based on the characteristics of interlayered rock masses of different thicknesses. Through weighted processing and interference elimination, it ensures that the collected displacement data accurately reflects the true deformation state of different interlayer interfaces and the interior of the rock mass. Furthermore, addressing the issue of existing instability judgments relying on simple displacement thresholds being prone to lag or misjudgment, this method utilizes a statistical mechanics coupled threshold algorithm. This algorithm deeply integrates the statistical characteristics of displacement data with mechanical parameters such as rock mass shear strength and cohesion to construct a dynamic coupled threshold range. This comprehensively captures the dynamic trend of rock mass displacement and the evolution law of instability, fundamentally avoiding untimely or inaccurate judgments and providing reliable protection for engineering disaster early warning.

[0055] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0056] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for displacement monitoring and instability determination of interbedded thick and thin rock masses, characterized in that, Includes the following steps: S1. Based on the bedding distribution characteristics and lithological parameters of the interbedded rock mass with thick and thin layers, determine the layout points, depths and spacing of the constant resistance large deformation anchor cable. Drill holes at each layout point and insert the constant resistance large deformation anchor cable with multiple sets of sensing units, so that the sensing units correspond to the interlayer interface and internal area of ​​the interbedded rock mass with different thicknesses. S2. Construct a segmented coupled interlayer constitutive model of anchor cables. Based on the rock mass stress and displacement data initially collected by each sensing unit, determine the basic parameters related to the thickness and elastic modulus of the interlayered rock mass in the model, and establish the mechanical transmission relationship between the anchor cables and interlayered rock masses of different thicknesses. S3. A thickness correction sensing fusion algorithm is adopted to fuse the displacement monitoring data collected in real time by each sensing unit. By introducing the thickness correction coefficient of interbedded rock mass, the interference of rock layers of different thicknesses on the sensing data is eliminated, and the interlayer and internal displacement fusion values ​​of each monitoring point are obtained. S4. Using the statistical mechanics coupling threshold algorithm, the displacement fusion value obtained in S3 is statistically analyzed. Combined with the shear strength and cohesion parameters of the interbedded rock mass, the statistical characteristic values ​​of the rock mass displacement in different monitoring periods are calculated to determine the coupling threshold range of the rock mass displacement change. S5. Transmit the statistical characteristic values, coupling threshold ranges and raw data of each sensing unit obtained in S4 to the interbedded rock mass monitoring visualization platform. The platform classifies, stores and visualizes the data, and generates displacement time series curves and interlayer displacement cloud maps for each monitoring point. S6. Based on the displacement time series curve and interlayer displacement cloud map displayed on the visualization platform, compare with the coupling threshold range determined in S4. When the displacement value of a certain monitoring point exceeds the coupling threshold range and continues to change, it is determined that the thick and thin interlayer rock mass in the area is instability trending. At the same time, the location, range and displacement change rate parameters of the corresponding instability area are output.

2. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, The expression for the segmented coupling interlayer constitutive model of the needle-and-wire system is as follows: ,in, Spatial coordinates at time t The stress components of the interbedded rock mass at layer k coupled with needle-like structures. For the k-th layer of rock mass, the thickness varies with the thickness. The changing elastic modulus, Spatial coordinates at time t The strain components at the location, For the k-th layer of rock mass, the thickness varies with the thickness. Changing Poisson's ratio For the k-th layer of rock mass, the thickness varies with the thickness. and displacement increment Varying interlaminar bond stress, For the k-th layer of rock mass, the thickness varies with the thickness. The varying stress attenuation coefficient.

3. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, The expression for the thickness correction sensing fusion algorithm is: Spatial coordinates at time t The displacement fusion value at the location, where n is the number of sensing units. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The weighting coefficients, The original displacement value collected by the i-th sensing unit at time t. The thickness of the i-th rock layer corresponds to the i-th sensing unit. The dynamic correction coefficient, The rate of change of displacement value for the i-th sensing unit over time.

4. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, The expression for the statistical mechanics coupling threshold algorithm is as follows: ,in, Spatial coordinates The coupling threshold of rock mass displacement. Boltzmann's constant, This is a reference temperature for the rock mass environment. Spatial coordinates Number of monitoring data samples This represents the maximum displacement increment at that location. This represents the average displacement increment at that location. The shear strength parameters of the rock mass at this location are... This represents the cohesion parameter of the rock mass at this location.

5. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, The data processing expression for the interbedded rock mass monitoring visualization platform is: ,in, The visualized data values ​​displayed on the platform. To visualize the scaling factor, Spatial coordinates Visual mapping coefficients at the location, Visual weighting coefficients for the coupling threshold. Total monitoring duration This is the displacement fusion value. This is the coupling threshold.

6. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, The expression for calculating the displacement monitoring parameters based on the constant resistance large deformation anchor cable is as follows: ,in, Spatial coordinates at time t Axial force in anchor cables subjected to constant resistance and large deformation. Let L be the stiffness coefficient of the anchor cable as a function of its length L. The viscous damping coefficient of the needle cable varies with length L. For integration variables, for The displacement fusion value at time.

7. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, S3 includes the following steps: S31. Obtain the raw displacement data collected by each sensing unit, extract the acquisition time, spatial coordinates and thickness parameters of the interbedded rock mass corresponding to each data point, and establish a mapping table between the raw data and the rock mass thickness. S32. Based on the association mapping table, group the sensor data corresponding to rock masses of different thicknesses, calculate the standard deviation and mean of each group of data, identify and mark outliers in the data; S33. Introduce a correction coefficient that is positively correlated with the rock mass thickness to weight the valid data other than the marked outliers. The weighting weight is determined based on the fitting relationship between the rock mass thickness and the sensitivity of the sensing unit. S34. The weighted data from each group are fused and calculated to obtain the fused displacement value of each monitoring point at the corresponding time. The correction coefficients and weight parameters used in the fusion process are recorded.

8. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, S4 includes the following steps: S41. Collect the displacement fusion values ​​of multiple consecutive monitoring periods output by S3, divide the data into groups according to the monitoring period, and calculate the variance, range and skewness statistical characteristic parameters of each group of data. S42. Obtain the shear strength and cohesion parameters of the thick and thin interbedded rock mass. Using linear interpolation, correlate these parameters with the displacement fusion values ​​of the corresponding monitoring period to establish the correspondence between mechanical parameters and displacement statistical characteristics. S43. Based on the concept of partition function in statistical mechanics, the statistical characteristic parameters of the displacement fusion value and the rock mechanics parameters are substituted into the coupling calculation model to obtain the displacement change coupling coefficient in each monitoring period. S44. Based on the coupling coefficients of multiple monitoring periods, determine the distribution range of the coupling coefficients, and use this range as the coupling threshold range for rock mass displacement changes. At the same time, calculate the upper and lower limit deviation values ​​of the threshold range.

9. The method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to claim 1, characterized in that, S5 includes the following steps: S51. Organize the statistical characteristic values, coupling threshold range and raw data of each sensing unit obtained in S4 according to the preset data format and convert them into binary data format that can be recognized by the monitoring visualization platform. S52. Establish a data classification and storage directory, classify and store the converted data according to monitoring points, monitoring time and data type, and add metadata including acquisition parameters and processing parameters to each data file. S53. Call the platform's visualization rendering module to generate displacement time series curves for each monitoring point based on the displacement fusion value, generate inter-layer displacement cloud maps by combining the inter-layer interface coordinates, and set color mapping rules between curves and cloud maps to distinguish different displacement levels. S54. Set up a data query interface in the visualization interface to support querying raw data, statistical feature values ​​and coupling threshold ranges by monitoring point and time range, and provide data export function.

10. A method for displacement monitoring and instability determination of interbedded thick and thin rock masses according to any one of claims 1-9, characterized in that, This method is implemented through different units, including: The constant resistance large deformation anchor cable multi-sensor implantation unit is adapted to the drilling structure of thick and thin combined interlayered rock mass. It integrates multiple sets of sensing modules corresponding to different rock layer thicknesses to collect rock mass displacement and stress data and transmit them to the data preprocessing unit. The anchor cable-rock mass coupled constitutive calculation unit receives data transmitted from the constant resistance large deformation anchor cable multi-sensor implantation unit, has a built-in anchor cable segmented coupled interlayer constitutive model algorithm, calculates the mechanical transfer parameters between the anchor cable and the rock mass and sends them to the data fusion unit. The thickness correction sensor data fusion unit is connected to the anchor cable-rock mass coupled constitutive calculation unit. It uses the thickness correction sensor fusion algorithm to fuse mechanical transfer parameters and original sensor data, and outputs the displacement fusion value to the statistical analysis unit. The statistical mechanics coupling threshold analysis unit communicates with the thickness correction sensing data fusion unit, uses the statistical mechanics coupling threshold algorithm to calculate the statistical characteristics and coupling threshold range of the displacement fusion value, and transmits the results to the visualization processing unit. The interbedded rock mass monitoring visualization unit receives the results from the statistical mechanics coupling threshold analysis unit, combines the raw data to generate visualization charts, and connects to the instability judgment output unit. The instability determination and parameter output unit acquires the chart data and coupling threshold range from the interbedded rock mass monitoring visualization unit, compares and analyzes the displacement change trend, determines the rock mass instability state, and outputs the location, range, and displacement rate parameters of the instability area. Each unit interacts with the other via industrial Ethernet, and the data transmission process uses an encryption protocol to protect the data.

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