Method for correcting GNSS monitoring threshold value of surface mine slope by introducing rebound value

Abstract

The invention provides a method for correcting a GNSS monitoring threshold value of a surface mine slope by introducing a rebound value, and relates to the technical field of surface mine slope monitoring. The method comprises the steps that springback values of different partitions of a slope are obtained through rock mass in-situ testing; establishing a mapping model of a rebound value and rock mass compressive strength, and determining a compressive strength mean value of the measured area; establishing a correction coefficient model based on the compressive strength collected in real time; dynamically correcting a displacement early warning threshold interval of the surface mine slope based on the correction coefficient model; through coupling analysis of a displacement measured value monitored by a GNSS monitoring point and a correction coefficient, a more accurate threshold interval is formed. The rock mass rebound value and the compressive strength are combined to serve as a threshold value correction factor, and real-time collaborative analysis with GNSS displacement data is achieved; a dynamic threshold function model is constructed, and spatial adaptive matching of rock mechanical properties-monitoring threshold values is realized; and a more reasonable and standardized threshold setting process is realized.

Description

Technical Field

[0001] This invention belongs to the field of slope monitoring technology, and specifically relates to a method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values. Background Technology

[0002] The stability of open-pit mine slopes is crucial for safe production. Currently, the most economical and effective method for monitoring open-pit mine slopes is GNSS monitoring, which acquires slope displacement data by deploying monitoring stations and reference stations. However, existing monitoring methods lack correlation with rock strength, and threshold classification is relatively coarse, often relying on experience to determine warning values. This leads to frequent false alarms and missed alarms, failing to provide more accurate guidance for safe production in open-pit mines.

[0003] Currently, GNSS monitoring of open-pit mine slopes primarily uses four warning levels—red, orange, yellow, and blue—to differentiate the degree of slope hazard. Traditional slope monitoring warning value classification mainly relies on past experience, previous slope instability data, and historical monitoring data. However, this approach faces challenges due to insufficient representativeness of the monitoring data or the lack of experience with extreme conditions such as slope instability. Experience-based judgments are subjective and susceptible to human interference. Furthermore, slopes in different regions, with different lithologies, structures, and hydrogeological conditions exhibit significant differences in deformation mechanisms, instability modes, and critical displacements. A uniform warning value range cannot accurately reflect the true risk status of a specific slope. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for evaluating the threshold range of GNSS monitoring for open-pit mine slopes by incorporating rebound value correction, thereby solving the problem that the correlation between GNSS monitoring data and rock mass strength is insufficient in existing open-pit coal mine slope monitoring methods, leading to inaccurate threshold division.

[0005] The technical solution adopted in this invention is: a method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values, the key technical points of which include the following steps:

[0006] (1) Within the GNSS monitoring area of ​​the open-pit coal mine slope, select a smooth area as the test area and divide the test area into a division area;

[0007] (2) Test each divided region, remove the maximum and minimum values ​​and obtain the average rebound value of the corresponding divided region; use the average rebound value of each divided region to calculate the average rebound value of the rock mass in the test area;

[0008] (3) The calculated average rock mass rebound value is converted into uniaxial compressive strength using the power function relationship;

[0009] (4) Using the threshold adjustment coefficient formula, the uniaxial compressive strength of the rock mass is converted into the deformation tolerance, and the deformation tolerance is used to dynamically correct the set four-level early warning threshold range.

[0010] (5) Repeat steps (1)-(5) to calculate the revised warning threshold range for different test areas; verify the false alarm rate. If it is not satisfied, repeat step (5) until a warning threshold range that meets the false alarm rate verification requirements is obtained.

[0011] Furthermore, the divided area includes five regions: the upper right, upper left, lower right, lower left, and middle of the test area.

[0012] Furthermore, the power function relationship described in step (3) is:

[0013]

[0014] Where: UCS is the uniaxial compressive strength (MPa). denoted as the average rebound value of the rock mass, and k and m as the regression coefficients of the rock mass, which are determined by fitting test data of different slope rock mass types.

[0015] Furthermore, the formula for the threshold adjustment coefficient in step (4) is:

[0016]

[0017] Among them, the empirical coefficient 'a' is the slope coefficient, which controls the influence of uniaxial compressive strength on the threshold. The larger 'a' is, the more sensitive the threshold adjustment caused by changes in uniaxial compressive strength is. To ensure sensitivity to the impact of strength changes on the threshold, the value of α ranges from 0.2 to 0.8. For slopes with significant lithological variations and where strength plays a dominant role in stability, a higher value of α (0.6-0.8) is used. For slopes with homogeneous lithology or where deformation is mainly controlled by structural planes, a lower value of α (0.2-0.4) is used. b is the baseline offset, the minimum adjustment coefficient when the uniaxial compressive strength approaches 0, preventing the threshold from returning to zero and causing the warning to fail. The value of b ranges from 0.3 to 0.6. When the rock mass is loose and the uniaxial compressive strength is less than 15 MPa, the value of b ranges from 0.5 to 0.6. When the rock mass is intact and the uniaxial compressive strength is greater than 15 MPa, the value of b ranges from 0.3 to 0.5. β is the nonlinear exponent, representing the shape of the curve between uniaxial compressive strength and the adjustment coefficient α, and its value ranges from 0.5 to 2. When β = 1, the relationship is linear. When β < 1, it indicates that the low-strength rock mass is more sensitive and is suitable for soft rocks with plastic deformation as the main process. When β > 1, it indicates that the high-strength rock mass is more sensitive and is suitable for hard rocks with brittle failure as the main process. UCSref is the reference strength, which is the typical uniaxial compressive strength (MPa) of the engineering area. UCS is the uniaxial compressive strength (MPa), and α is the threshold adjustment coefficient of the rock mass.

[0018] Furthermore, the method for dynamically correcting the set four-level early warning threshold range using deformation tolerance in step (4) is as follows: calculate the product of the threshold adjustment coefficient and the initial four-level early warning threshold range respectively.

[0019] The beneficial effects of this invention are as follows: This method for evaluating the threshold interval of GNSS monitoring for open-pit mine slopes by introducing rebound value correction, combined with rock mass mechanical properties and real-time displacement monitoring, has the core advantage of significantly improving the accuracy, reliability of early warning, and engineering practicality of slope stability monitoring and evaluation. It features simple operation, reliable intervals, and strong adaptability. It can be flexibly adjusted according to the specific conditions and monitoring needs of the mine slope, providing a new solution for threshold interval decision-making in slope stability monitoring. It combines rock mass rebound value and compressive strength as threshold correction factors, and performs real-time collaborative analysis with GNSS displacement data; it constructs a dynamic threshold function model to achieve spatial adaptive matching of "rock mechanical properties - monitoring threshold"; it solves the problem that early warning threshold intervals in on-site GNSS monitoring are generally judged based on experience, using rapid on-site measured rock mass data combined with daily GNSS monitoring data to form a zonal setting of monitoring and early warning thresholds, achieving a more reasonable and standardized threshold setting process. This invention can significantly solve the pain point that fixed thresholds cannot adapt to the inconsistency of slope rock mass deformation, providing highly reliable technical support for early warning of open-pit mine slope instability and reliable technical support for geological disaster prevention. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the rebound value measurement area and measurement points of the present invention;

[0022] Figure 2 This is a flowchart illustrating the working mode of the rebound hammer of the present invention;

[0023] The numbers in the diagram are explained as follows: 1. Slope surface near the GNSS monitoring equipment deployment range; 2. GNSS monitoring equipment; 3. Rebound value measurement area; 4. Rebound value measurement point in each measurement area; 5. Rebound hammer plunger; 6. Rebound hammer body; 7. Rebound hammer digital display screen; 8. Rebound test rock surface. Detailed Implementation

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the following description is provided in conjunction with the accompanying drawings. Figure 1, Figure 2 The present invention will be further described in detail below with reference to specific embodiments.

[0025] This embodiment provides a method for evaluating the threshold range of GNSS monitoring for open-pit mine slopes by introducing a rebound value correction.

[0026] (1) Based on the overall design scheme for open-pit mine slope monitoring, five areas with smooth surfaces (i.e., without cracks, protrusions, or obvious spalling materials with a width greater than 1 cm) are selected as test areas within a horizontal 50m range where GNSS monitoring points need to be deployed. The spatial location of the test areas should be divided according to the distribution pattern of upper right, upper left, lower right, lower left, and center. The purpose of this division is to ensure the typicality and representativeness of the average rebound value within the test area. In this embodiment, the test area is a square area with a side length of about 1.5m.

[0027] (2) The greater the impact kinetic energy of the rock rebound hammer, the greater its rebound value. This law is also reflected in indoor and outdoor tests. Therefore, this embodiment uses RS8000 Schmidt N-type rock rebound hammer. Before use, it must be calibrated with steel felt. After calibration, the rebound hammer performs rebound operation on the rock mass in the vertical direction of the impact surface of the test area.

[0028] (3) Sixteen rock rebound tests were conducted on each of the five regions within the test area, including the upper right, upper left, lower right, lower left, and middle regions. The calculated values ​​for each region were averaged after removing the three maximum and three minimum values. The average value of the rock rebound within the test area was then calculated by taking the average value of the five regions. The formula is as follows:

[0029]

[0030] in: Let be the average rebound value of the rock mass, n be the number of measuring points, and RXI be the rebound value of the rock at the i-th measuring point.

[0031] (4) There is a correlation between the obtained rock mass rebound value and the uniaxial compressive strength of the slope in the test area, as shown in the formula:

[0032]

[0033] Where: UCS is the uniaxial compressive strength (MPa). denoted as the average rebound value of the rock mass, and k and m as the regression coefficients of the rock mass, which are determined by fitting test data of different slope rock mass types.

[0034] Although in the laboratory, a large number of experiments can be conducted to test the uniaxial compressive strength of representative rock cores collected from rock strata, and the rebound value can be measured at their end faces to establish a statistical regression relationship between uniaxial compressive strength and average rebound value, thereby obtaining the regression coefficients k and m of a specific rock mass, the lithology of the strata involved in mine slopes is complex and there is no condition to calibrate the uniaxial compressive strength of the rock strata in the deployment area of ​​each GNSS monitoring point in the laboratory. Therefore, this embodiment uses the power function formula (2) for rapid on-site estimation.

[0035] In this embodiment, sandstone is the main typical stratum in the open-pit mine. Its regression coefficient k is the baseline strength factor, which is mainly controlled by the type of cement. Generally, for siliceous cement, k≈0.08-0.12, and for argillaceous cement, k≈0.03-0.07. The regression coefficient m is the strength growth sensitivity, which is mainly controlled by the homogeneity of the minerals. Generally, for quartz sandstone, m≈1.3-1.5, and for lithic sandstone, m≈1.6-1.8. Combining the above parameters k and m, the uniaxial compressive strength UCS can be calculated using formula (2).

[0036] (5) Based on the analysis of the initial month's GNSS observation data of the slope in the open-pit mine survey area, using the daily cumulative displacement as the unit, and combining the initial four-level early warning threshold range in the existing overall slope monitoring design scheme of the mining enterprise, the rock mass strength property is converted into deformation tolerance, and the magnitude of deformation tolerance is represented by the threshold adjustment coefficient α. The calculation formula is as follows:

[0037]

[0038] Among them, the empirical coefficient 'a' is the slope coefficient, which controls the influence of uniaxial compressive strength on the threshold. The larger 'a' is, the more sensitive the threshold adjustment caused by changes in uniaxial compressive strength is. To ensure sensitivity to the impact of strength changes on the threshold, the value of α ranges from 0.2 to 0.8. For slopes with significant lithological variations and where strength plays a dominant role in stability, a higher value of α (0.6-0.8) is used. For slopes with homogeneous lithology or where deformation is mainly controlled by structural planes, a lower value of α (0.2-0.4) is used. b is the baseline offset, the minimum adjustment coefficient when the uniaxial compressive strength approaches 0, preventing the threshold from returning to zero and causing the warning to fail. The value of b ranges from 0.3 to 0.6. When the rock mass is loose and the uniaxial compressive strength is less than 15 MPa, the value of b ranges from 0.5 to 0.6. When the rock mass is intact and the uniaxial compressive strength is greater than 15 MPa, the value of b ranges from 0.3 to 0.5. β is the nonlinear exponent, representing the shape of the curve between uniaxial compressive strength and the adjustment coefficient α, and its value ranges from 0.5 to 2. When β = 1, the relationship is linear. When β < 1, it indicates that low-strength rock masses are more sensitive, and this is suitable for soft rocks where plastic deformation is dominant. When β > 1, it indicates that high-strength rock masses are more sensitive, and this is suitable for hard rocks where brittle failure is dominant. (UCS)ref The reference strength is the typical uniaxial compressive strength (MPa) of the engineering area, UCS is the uniaxial compressive strength (MPa), α is the threshold adjustment coefficient of the rock mass, and a, β, and b are empirical parameters that need to be calibrated based on field test data.

[0039] (6) The calculated threshold adjustment coefficient α is substituted into the initial 4-level warning threshold range to dynamically adjust the warning threshold: When α = 1, no correction is made; when α < 1, the threshold range is tightened, i.e., the adjusted warning threshold is obtained by calculating the product of α and the initial 4-level warning threshold range. When α > 1, the threshold range is widened, i.e., the adjusted warning threshold is obtained by calculating the product of α and the initial 4-level warning threshold range. The formula is:

[0040] The revised warning threshold = the initial warning threshold × α.

[0041] (7) Calculate the warning threshold for different lithological regions according to the methods (1)-(6), observe the degree of matching between the warning and actual deformation in the corrected threshold interval, and if the false alarm rate decreases, the model calculation is effective; otherwise, readjust the values ​​of coefficients a, β, and b.

[0042] Since sandstone is the main typical stratum in open-pit mines, this embodiment will use sandstone as an example for illustration.

[0043] (1) The test site consisted mainly of medium-strength sandstone. Laboratory test data was obtained using an N-type hammer on the end face of a standard specimen. Regression analysis yielded the following power function relationship:

[0044]

[0045] (2) On-site testing of the target sandstone slope, select a relatively homogeneous area with a flat surface. Measure 5 sets of rebound values ​​in the upper right, upper left, lower right, lower left, and middle of this area. Each set contains 16 rebound values. Remove the 3 largest deviations and 3 smallest deviations. The specific data and calculated averages are as follows:

[0046] ① 28, 42, 47, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 68, 75, average 52.4

[0047] ② 38, 40, 43, 45, 46, 47, 48, 48, 51, 51, 52, 53, 67, 71, 74, 79, average 48.7

[0048] ③ 35, 48, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 72, 73, 75, 85, average 55.3

[0049] ④ 25, 36, 40, 42, 43, 44, 45, 46, 47, 48, 49, 50, 62, 65, 70, 78, average 46.2

[0050] ⑤ 39, 50, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 73, 77, 82, 88, average 57.8

[0051] The overall average is (52.4 + 48.7 + 55.3 + 46.2 + 57.8) / 5 = 52.08

[0052] (3) Substitute the total average into the power function formula (2) for uniaxial compressive strength. The rock mass in the test area is relatively strong and belongs to argillaceous cementation, so k is taken as 0.065; the mineral composition is between quartz sandstone and lithic sandstone, so m is taken as 1.45. The average uniaxial compressive strength of the sandstone in the vicinity of the GNSS monitoring point is obtained as follows:

[0053] UCS = 0.065 * 52.08 1.45 =20.05Mpa

[0054] (4) The reference strength of the sandstone on the mine slope is 16 MPa. The strength at this location plays a dominant role in stability, so the value of a is 0.6. The rock mass is intact and the uniaxial compressive strength is greater than 15 MPa, so the value of b is 0.4. The rock mass on the open-pit mine slope is mainly subjected to plastic failure, so the value of β is 0.5. Substituting the obtained uniaxial compressive strength into the formula, the correction coefficient α is calculated to be 1.07.

[0055]

[0056] (5) After one month of GNSS monitoring data analysis, the monitoring warning values ​​for this point were determined as follows: original blue warning < 20 mm / d, original yellow warning 20-25 mm / d, original orange warning 25-30 mm / d, and original red warning > 30 mm / d. Each warning interval was corrected using a correction factor of 1.07. The corrected warning value intervals are shown in Table 1 below. The corrected warning values ​​are more consistent with the actual engineering conditions on site. Furthermore, based on the different locations of the slope, different threshold monitoring intervals can be defined, thereby improving the effectiveness of slope monitoring.

[0057] Table 1 Summary of Threshold Ranges and Correction Ranges for Each Warning Level

[0058]

[0059] Correcting the GNSS early warning threshold using the compressive strength calculated by a rock rebound hammer essentially transforms the rock mass strength attribute into a quantitative expression of deformation tolerance. This method significantly improves early warning accuracy, and is particularly suitable for large mine slopes with complex lithology. The core of this embodiment lies in the on-site calibration of the correction model, continuously calculating the deformation tolerance parameters for different on-site areas. Furthermore, the computational mathematical model can be subsequently embedded into GNSS monitoring software to achieve real-time dynamic threshold adjustment.

[0060] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values, characterized in that, Includes the following steps: (1) Within the GNSS monitoring area of ​​the open-pit coal mine slope, select a smooth area as the test area and divide the test area into a division area; (2) Test each divided region, remove the maximum and minimum values ​​and obtain the average rebound value of the corresponding divided region; use the average rebound value of each divided region to calculate the average rebound value of the rock mass in the test area; (3) The calculated average rock mass rebound value is converted into uniaxial compressive strength using the power function relationship; (4) Using the threshold adjustment coefficient formula, the uniaxial compressive strength of the rock mass is converted into the deformation tolerance, and the deformation tolerance is used to dynamically correct the set four-level early warning threshold range. (5) Repeat steps (1)-(5) to calculate the revised warning threshold range for different test areas; verify the false alarm rate. If it is not satisfied, repeat step (5) until a warning threshold range that meets the false alarm rate verification requirements is obtained.

2. The method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values ​​according to claim 1, characterized in that: The divided areas include five regions: the upper right, upper left, lower right, lower left, and middle of the test area.

3. The method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values ​​according to claim 1, characterized in that: The power function relationship mentioned in step (3) is: Where: UCS is the uniaxial compressive strength (MPa). denoted as the average rebound value of the rock mass, and k and m as the regression coefficients of the rock mass, which are determined by fitting test data of different slope rock mass types.

4. The method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values ​​according to claim 1, characterized in that: The formula for the threshold adjustment coefficient in step (4) is: Among them, the empirical coefficient 'a' is the slope coefficient, which controls the influence of uniaxial compressive strength on the threshold. The larger 'a' is, the more sensitive the threshold adjustment caused by changes in uniaxial compressive strength is. To ensure sensitivity to the impact of strength changes on the threshold, the value of α ranges from 0.2 to 0.

8. For slopes with significant lithological variations and where strength plays a dominant role in stability, a higher value of α (0.6-0.8) is used. For slopes with homogeneous lithology or where deformation is mainly controlled by structural planes, a lower value of α (0.2-0.4) is used. b is the baseline offset, the minimum adjustment coefficient when the uniaxial compressive strength approaches 0, preventing the threshold from returning to zero and causing the warning to fail. The value of b ranges from 0.3 to 0.

6. When the rock mass is loose and the uniaxial compressive strength is less than 15 MPa, the value of b ranges from 0.5 to 0.

6. When the rock mass is intact and the uniaxial compressive strength is greater than 15 MPa, the value of b ranges from 0.3 to 0.

5. β is the nonlinear exponent, representing the shape of the curve between uniaxial compressive strength and the adjustment coefficient α, and its value ranges from 0.5 to 2. When β = 1, the relationship is linear. When β < 1, it indicates that the low-strength rock mass is more sensitive and is suitable for soft rocks with plastic deformation as the main process. When β > 1, it indicates that the high-strength rock mass is more sensitive and is suitable for hard rocks with brittle failure as the main process. UCSref is the reference strength, which is the typical uniaxial compressive strength (MPa) of the engineering area. UCS is the uniaxial compressive strength (MPa), and α is the threshold adjustment coefficient of the rock mass.

5. The method for correcting the GNSS monitoring threshold of open-pit mine slopes by introducing rebound values ​​according to claim 4, characterized in that: The method for dynamically correcting the set four-level early warning threshold range using deformation tolerance in step (4) is as follows: calculate the product of the threshold adjustment coefficient and the initial four-level early warning threshold range.

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