A three-dimensional monitoring system for slope deformation based on fused laser ranging

Abstract

The present invention belongs to the field of slope monitoring technology and specifically discloses a three-dimensional slope deformation monitoring system based on fused laser ranging. The system includes: a deformation law analysis module, a monitoring switching determination module, an environmental monitoring module, a slope deformation analysis terminal, and a deformation risk processing terminal. By identifying abnormal characteristics such as excessive slope changes, the present invention automatically captures potential high-risk areas such as acceleration mutation zones and triggers dynamic updates of monitoring settings. This effectively solves the coverage blind spot problem of fixed monitoring areas and enables adaptive tracking and monitoring of high-risk points on slopes. At the same time, by fusing past environmental tracking logs with three-dimensional coordinate sequences and setting deformation risk compensation weights, a multi-dimensional slope deformation risk assessment mechanism is constructed, breaking through the limitations of traditional single-point monitoring. Furthermore, by real-time acquisition of slope area humidity and selecting laser wavelengths, the interference of environmental noise on three-dimensional coordinate data acquisition is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of slope monitoring, and in particular relates to a three-dimensional monitoring system for slope deformation based on fused laser ranging. Background Art

[0002] Slopes are susceptible to disasters such as landslides and collapses, which can destroy buildings, block traffic, damage water conservancy facilities, and even trigger secondary disasters. Therefore, slope deformation monitoring has become a key component of geological disaster prevention and engineering safety assurance.

[0003] Existing technologies, such as a Chinese invention patent application with application number 202311251073.3, disclose a method for monitoring deformation of a high slope. The method installs a laser reflection target with multi-color concentric rings at the slope monitoring point, uses a total station to observe the center of the target at a fixed observation point with a locked initial angle, and directly determines the deformation level by the color ring where the center of the cross deviates from the center of the target. This allows remote monitoring of multiple monitoring points and the rapid determination of the degree of deformation without the need for personnel to enter the high slope site, and the monitoring is not affected by weather.

[0004] Another example of existing technology is a highway slope deformation monitoring system and method disclosed in the Chinese invention patent application with application number 202510143607.3. It solves the problems of large blind spots covered by a single monitoring method and high false alarm rate of manual warnings by constructing an air-ground collaborative monitoring system that combines a ground sensor network with a drone-mounted lidar cruise, and combines an AI model to integrate multi-source data for real-time analysis.

[0005] Regarding the first existing technical solution, it is a fixed target and cannot dynamically adjust the monitoring focus. Regarding the second existing technical solution, although the use of drones is more flexible and has air-ground coordination, the monitoring object is also fixed. Obviously, there are still the following deficiencies in slope deformation monitoring: 1. Fixed monitoring areas can easily lead to high-risk points such as acceleration mutation areas being missed due to lack of key deformation data due to lack of key monitoring, resulting in certain deficiencies in the coverage and effectiveness of deformation monitoring.

[0006] 2. The ability to capture key information such as the internal stress distribution of the slope and the evolution of the slip surface is limited. Relying on single-point monitoring such as borehole displacement meters, it is difficult to fully reveal the disaster mechanism.

[0007] 3. Technologies such as LiDAR and InSAR are easily affected by atmospheric interference and extreme weather interference. They fail to effectively compensate for environmental interference, resulting in insufficient adaptability to complex environments and the inability to guarantee the accuracy of monitoring data. Summary of the Invention

[0008] In view of this, in order to solve the above problems, a three-dimensional monitoring system for slope deformation based on fused laser ranging is proposed.

[0009] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a three-dimensional monitoring system for slope deformation based on fused laser ranging, which includes: a deformation law analysis module, which analyzes the slope change characteristics based on the three-dimensional coordinate sequence of each monitoring point in the past monitoring period, and the characteristics are the overall degree of change and the degree of change exceeding the limit.

[0010] The monitoring switching judgment module makes a monitoring setting switching judgment based on the initial monitoring setting and the slope change characteristics. If it is judged to be a switch, it confirms and updates the monitoring setting.

[0011] The environmental monitoring module collects the humidity of the slope area in real time for laser wavelength selection. Based on the updated monitoring settings and the selected laser wavelength, the corresponding laser ranging terminal is triggered to emit the corresponding wavelength laser and receive the reflected signal to obtain the three-dimensional coordinates of each monitoring point.

[0012] The slope deformation analysis terminal sets deformation risk compensation weights based on environmental tracking logs of the slope area in past monitoring periods, and calculates slope deformation risk indexes based on the three-dimensional coordinates of the monitoring points and the deformation risk compensation weights.

[0013] The deformation risk processing terminal matches the corresponding risk warning instructions based on the slope deformation risk index and issues an early warning.

[0014] Compared with the existing technology, the present invention has the following beneficial effects: (1) By identifying abnormal features such as excessive slope changes, the present invention automatically captures potential high-risk areas such as acceleration mutation areas and triggers dynamic updates of monitoring settings, accurately focusing monitoring resources on areas with active deformation. This effectively solves the coverage blind spot problem of fixed monitoring areas, realizes adaptive tracking monitoring of high-risk points on slopes, significantly improves the ability to capture key deformation data and the effectiveness of monitoring, and avoids the omission of disaster precursor information due to the solidification of monitoring focus.

[0015] (2) This invention constructs a multi-dimensional slope deformation risk assessment mechanism by fusing past environmental tracking logs with three-dimensional coordinate sequences and setting deformation risk compensation weights, thus breaking through the limitations of traditional single-point monitoring. Furthermore, it can comprehensively analyze the spatiotemporal evolution characteristics of displacement change deviation, curvature mutation point density, and other factors, and, combined with the weights of environmental factors affecting deformation, comprehensively analyze the internal stress transfer law of the slope and the development trend of the slip surface, thereby providing richer mechanical and environmental coupling data support for revealing the slope disaster mechanism and improving the refined monitoring capability of potential slope disaster processes.

[0016] (3) This invention effectively compensates for the impact of the natural environment on laser signal transmission by collecting environmental parameters such as humidity in the slope area in real time and selecting the laser wavelength. This is combined with dynamically updated monitoring settings to adjust the operating parameters of the laser ranging terminal. This reduces the interference of environmental noise on the acquisition of three-dimensional coordinate data, significantly improves the system's adaptability under complex working conditions, and ensures the high accuracy and reliability of the monitoring data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is a schematic diagram of the system module connection of the present invention.

[0019] Figure 2 It is a schematic diagram of the overall implementation process of the present invention.

[0020] Figure 3 Schematic diagram of the calculation process of the position change degree of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] See also Figure 1 and Figure 2 As shown, the present invention provides a three-dimensional monitoring system for slope deformation based on fusion laser ranging, which includes: a deformation law analysis module, a monitoring switching judgment module, an environmental monitoring module, a slope deformation analysis terminal and a deformation risk processing terminal.

[0023] In the above, the monitoring switching determination module is connected to the deformation law analysis module and the environmental monitoring module respectively, and the slope deformation analysis terminal is connected to the environmental monitoring module and the deformation risk processing terminal respectively.

[0024] The deformation law analysis module analyzes the slope change characteristics based on the three-dimensional coordinate sequence of each monitoring point in the past monitoring period, and the characteristics are the overall degree of change and the degree of change exceeding the limit.

[0025] Specifically, the specific analysis process of the overall degree of change includes: A1, traversing the three-dimensional coordinate sequence of each monitoring point, and calculating the position change degree of each monitoring point.

[0026] A2. Count the number of monitoring points whose position change exceeds the preset threshold, calculate the ratio of the number of monitoring points to the total number of monitoring points, and record it as the change-exceeding-monitoring ratio.

[0027] A3. Spatially connect the monitoring points that exceed the threshold to form a change-exceeding region. If the change exceeds the monitoring ratio or the change-exceeding region does not meet any of the following conditions, the overall degree of change is directly assigned to 0. Otherwise, an overall change is triggered: (a) The change exceeds the monitoring ratio by exceeding the preset monitoring ratio threshold.

[0028] (b) The ratio of the area of ​​the overlap between the excessive change area and the preset central monitoring area to the area of ​​the excessive change area exceeds the preset ratio threshold.

[0029] A4. If an overall change is triggered, the ratio of the overlapping area to the area of ​​the change exceeding the limit is recorded as the exceeding limit overlapping center trend ratio. The change exceeding monitoring ratio and the exceeding limit overlapping center trend ratio are weighted to obtain the overall degree of change.

[0030] Understandably, first, the deformation characteristics of single points are quantified at the micro level, and then the proportion of monitoring points exceeding the preset threshold is counted to identify statistically significant group anomalies and avoid interference from single-point noise. Secondly, the spatial connection of the exceeding monitoring points forms a change exceeding limit area, and non-systematic deformation is filtered out through double-condition verification. The former ensures that the anomaly has spatial breadth, and the latter focuses on the coordinated changes in the core dangerous area. If the overall change is triggered, the exceeding limit coincidence center trend ratio is introduced to quantify the concentration of deformation to the core area, and is weighted with the change exceeding monitoring ratio to comprehensively evaluate the severity of the overall change from the perspective of range and core correlation. When the conditions are not met, the value is assigned to 0 to exclude low-risk disturbances, thereby finally achieving a logical closed loop from single-point characteristics to overall risk, accurately reflecting the systematic characteristics and potential instability risks of slope deformation.

[0031] Further, see Figure 3 As shown, the specific calculation process of the position change degree of each monitoring point includes: A11. For the same monitoring point, calculate its displacement vector and horizontal component and vertical component in the adjacent past monitoring days, combine the three to obtain the segmented displacement, and calculate the directional change rate through the direction cosines of the adjacent segmented displacement vectors.

[0032] Understandably, segmented displacement is used to observe local changes at a monitoring point during each daily or monitoring interval. For example, a sudden, large movement on a single day could indicate localized slope instability. Combined with cumulative displacement, analysis can determine whether the displacement is changing slowly or suddenly at an accelerated rate. Direction cosines use existing formulas and are not further explained.

[0033] A12. Calculate the cumulative displacement from the initial past monitoring day to the final past monitoring day, and calculate the displacement change deviation based on the segmented displacement, directional change rate, and cumulative displacement.

[0034] It can be understood that the displacement vector is a directed line segment pointing from the position of one monitoring day to the position of the adjacent monitoring day, which can be obtained by subtracting the spatial coordinates. For example, assuming that the three-dimensional spatial position coordinates of adjacent monitoring days are and , then the displacement vector is decomposed into horizontal and vertical components, where the horizontal component is and The resultant vector of the direction, the vertical component is The direction and segment displacement are calculated using the vector modulus formula. The rate of change of direction is calculated using the direction cosines of adjacent segment displacement vectors. Direction cosines are the cosine of the angle between the displacement vector and the coordinate axis, reflecting the direction of the vector in space. By comparing the changes in the direction cosines of adjacent segment displacement vectors, the degree of directional change can be quantified.

[0035] It can be understood that the cumulative displacement is the total amount of displacement from the initial past monitoring day to the end of the past monitoring day, and the modulus of the composite vector is calculated by sequentially accumulating the displacement vectors of each segment.

[0036] A13. Use the spline interpolation algorithm to fit the three-dimensional coordinate sequence of past monitoring days to generate a continuously changing path curve. Calculate the curvature of each point on the curve and identify curvature mutation points where the curvature change exceeds a preset threshold. The ratio of the number of curvature mutation points to the total number of monitoring days is used as the curvature mutation point density.

[0037] Understandably, by fitting the three-dimensional coordinate sequence of past monitoring days through the spline interpolation algorithm, the spline interpolation algorithm can generate a smooth continuously changing path curve based on discrete coordinate points. This curve reflects the changing trajectory of the monitoring point position over time. Then calculate the curvature of each point on the curve, and the curvature is used to measure the degree of curvature of the curve. Points where the curvature change exceeds the preset threshold are identified as curvature mutation points. These points mean that the trend of the monitoring point position change has changed significantly. The ratio of the number of curvature mutation points to the total number of monitoring days is used as the curvature mutation point density. The density value reflects the frequency of mutations during the change of the monitoring point position. The spline interpolation algorithm is a relatively mature algorithm currently available, and its specific execution process will not be repeated here.

[0038] A14. Based on the changing path curve, calculate the ratio of the actual length of the path to the straight-line distance between the starting and ending points as the path tortuosity.

[0039] A15. Normalize the density of curvature mutation points and the path tortuosity, and use the preset weight coefficient to perform weighted calculation on the comprehensive normalization results and the displacement change deviation to obtain the change degree of each monitoring point.

[0040] Understandably, the density of curvature mutation points and path tortuosity are normalized, mapping their values ​​to the same range (e.g., [0, 1]) for comparison and comprehensive calculation. This normalization can be performed using the extreme value normalization method. Preset weight coefficients are set based on actual needs and the importance of each factor. A weighted calculation ultimately yields the degree of position change for each monitoring point. This value comprehensively considers multiple aspects of the monitoring point's position change and accurately describes the degree of position change.

[0041] It should be noted that the actual length of the path is calculated by integrating the curve, and the straight-line distance between the starting and ending points is calculated using the distance formula between two points in space. The path tortuosity reflects the complexity of the path changes of the monitoring point location. A larger value indicates a more tortuous path and a more complex change process.

[0042] In one specific embodiment, a single displacement or directional change metric cannot fully reflect the complexity of monitoring point changes. By comprehensively considering multiple factors, including segmented displacement, directional change rate, cumulative displacement, density of curvature mutation points, and path tortuosity, it is possible to capture multiple aspects of the monitoring point's position change process, including local fluctuations, overall trends, directional stability, and the complexity of the change path. This multi-dimensional analysis method helps to gain a deeper understanding of the changing patterns of monitoring points, avoid misjudgments caused by incomplete information, and facilitate a comprehensive and accurate understanding of the changes in the spatial position of monitoring points.

[0043] Preferably, the specific calculation process of the displacement change deviation in step A12 includes: R1, calculating the ratio of the number of past monitoring days in which the segmented displacement is continuously greater than the set reference displacement to the total number of past monitoring days, which is recorded as the continuous displacement deviation ratio.

[0044] R2. Calculate the standard deviation of the corresponding segment displacement and the corresponding directional change rate for each adjacent past monitoring day as the displacement fluctuation and directional fluctuation, respectively. Record the ratio of the displacement fluctuation to the cumulative displacement as the displacement deviation. At the same time, take the maximum directional change rate as the target directional change rate.

[0045] R3. Direction fluctuation and target direction change rate are used as direction change indicators, and after normalization, the direction change index is obtained by weighted summation.

[0046] R4. Use the continuous displacement deviation ratio, displacement fluctuation, and displacement deviation as position change indicators, and obtain the position change index in the same way as the direction change index.

[0047] R5. Import the weighted sum of the direction change index and the position change index into the Sigmoid function and output the displacement change deviation.

[0048] It should be noted that the calculation of displacement change deviation is based on the segmented displacement, directional change rate, and cumulative displacement. The segmented displacement reflects the degree of local change, the directional change rate reflects the stability of the displacement direction, and the cumulative displacement shows the overall change trend. Taking these three factors into consideration can more comprehensively describe the characteristics of the displacement change at the monitoring point.

[0049] Understandably, the persistence of displacement exceeding the threshold is measured by the continuous displacement deviation ratio, the stability of the displacement amplitude and the degree of deviation relative to the cumulative trend are characterized by the displacement fluctuation and deviation, the regularity and extreme mutation of the direction change are captured by the direction fluctuation and the target direction change rate. After standardization to eliminate the dimensional difference, the direction and position change indexes are weighted and synthesized respectively. Finally, the nonlinear mapping characteristics of the Sigmoid function are used to convert the comprehensive information of multiple indicators into a deviation probability value in the range of 0-1, so as to better quantify the specific deviation degree of the displacement change.

[0050] It should be added that the weights involved in the calculation of displacement change deviation can be determined by subjective weighting methods, such as the hierarchical analysis method, objective weighting methods such as the entropy weight method, the coefficient of variation method, etc. Taking the analysis of the weights of the directional fluctuation degree and the target directional change rate by the hierarchical analysis method as an example, a judgment matrix is ​​constructed by pairwise comparison. For example, the importance of the directional change rate to the directional consistency of the segmented displacement vector is 3 times, recorded as 3, and the importance of the directional fluctuation degree to the directional change rate is 1 / 2, recorded as 0.5. The eigenvector is calculated and a consistency test is performed, and the weights of the target directional change rate and the directional fluctuation degree are obtained as 0.75 and 0.25, respectively.

[0051] The weights of indicators within the direction / position change index and between indicators, such as the direction and position change index, can be determined through pairwise comparison, information entropy calculation, and principal component analysis. These can be selected based on actual conditions and are not limited here. For further understanding, a principal component analysis (PCA) was performed on 200 sets of slope data, taking the weights of the principal component analysis indicators, such as the direction and position change index, as an example. The first two components contributed 85% of the cumulative variance, with the following loads: the direction change index and position change index of the principal component 1 load were 0.75 and 0.6, respectively, and the direction change index and position change index of the principal component 2 load were -0.6 and 0.8, respectively. The weights of the direction change index and position change index were calculated by the squared sum of loads to be 0.45 and 0.55, respectively. The squared sum of loads refers to the ratio of the sum of the squared loads of each indicator on all principal components to the total squared loads of all indicators.

[0052] Specifically, the specific analysis process of the excessive change includes: B1, dividing the past monitoring period into time windows, traversing the historical three-dimensional coordinate sequence of the corresponding monitoring point in each time window, and calculating the single-axis change value, comprehensive displacement change value and change rate of the three-dimensional coordinates of each monitoring point in adjacent time windows.

[0053] It can be understood that the single-axis change value can be specifically such as the difference between the current period coordinate of the X-axis and the previous period coordinate. The comprehensive displacement change value is the straight-line distance of the three-dimensional coordinate change, which can be calculated by the distance formula. It is an existing common calculation formula and will not be displayed again. The change rate is obtained by dividing the comprehensive displacement change value by the number of monitoring interval days of a single time window.

[0054] B2. If any of the single-axis change value, comprehensive displacement change value, and change rate of the three-dimensional coordinates of a monitoring point in the adjacent time window exceeds the corresponding limit, it is recorded as an out-of-limit monitoring point, and the ratio of its number to the total number of monitoring points is the out-of-limit ratio.

[0055] B3. For each over-limit monitoring point, count the single-axis change value of its three-dimensional coordinates, the comprehensive displacement change value, and the number of parameter items in the change rate that exceed the corresponding limit value, and divide it by the total number of parameter items to obtain the over-limit parameter ratio.

[0056] B4. If the value of a parameter item is lower than the corresponding limit, its deviation is recorded as 0. Otherwise, the parameter item is normalized with its limit to obtain the deviation, and the maximum value of the deviation of each parameter item is taken as the parameter deviation of the over-limit monitoring point.

[0057] B5. Record the over-limit parameter ratio, parameter deviation and over-limit ratio of each over-limit monitoring point as and as well as , calculate the change over limit , , 、 and They are respectively expressed as the excess parameter ratio, parameter deviation and the weight corresponding to the excess ratio, Indicates the number of the over-limit monitoring point. .

[0058] In a specific embodiment, the single-axis change limit, comprehensive displacement change limit and displacement change rate limit can be set for the three-dimensional coordinates of the monitoring point according to the safety design specifications of the slope project, historical disaster data or real-time environmental conditions. For example, the single-axis change value is such as the X-axis single-day displacement exceeding 8 mm, the comprehensive displacement change limit is such as the cumulative displacement exceeding 50 mm within 30 days, and the displacement change rate limit is such as 3 mm / day.

[0059] It should be noted that the limits can be adjusted dynamically according to the monitoring stage. For example, the values ​​during the construction period are higher than those during the operation period, and the vertical displacement limits during the rainy season are reduced.

[0060] It should also be added that the over-limit ratio reflects the breadth of spatial distribution of abnormal monitoring points, is the basis for judging the overall stability of the slope, and is of the highest importance. The parameter deviation reflects the severity of the single-point anomaly, is directly related to the risk of local instability, and is second in importance. The over-limit parameter ratio describes the degree of coordinated anomaly of multiple parameters at a single point, and is relatively less important. Therefore, for example, the judgment matrix is ​​constructed using the 1-9 scaling method. For example, the importance of the over-limit ratio relative to the over-limit parameter ratio is 5, the importance of the over-limit ratio relative to the parameter deviation is 2, and the importance of the parameter deviation relative to the over-limit parameter ratio is 3. After eigenvector calculation and consistency test, we get 、 and The values ​​can be 0.12, 0.28 and 0.6 respectively.

[0061] By identifying abnormal characteristics such as excessive slope changes, the present invention automatically captures potential high-risk areas such as areas of sudden acceleration changes, triggering dynamic updates to monitoring settings, and precisely focusing monitoring resources on areas of active deformation. This effectively addresses coverage blind spots within fixed monitoring areas, enabling adaptive tracking and monitoring of high-risk slope points. This significantly improves the ability to capture key deformation data and enhances monitoring effectiveness, avoiding the omission of disaster precursor information due to rigid monitoring priorities.

[0062] The monitoring switching determination module makes a monitoring setting switching determination based on the current monitoring setting and the slope change characteristics, and if it is determined to be a switch, confirms to update the monitoring setting.

[0063] Specifically, the determination of switching the monitoring setting includes: if the overall degree of change or the degree of change exceeding a limit exceeds a corresponding preset threshold, determining to switch the monitoring setting.

[0064] If neither the overall degree of change nor the degree of change exceeding the limit exceeds the corresponding preset threshold and both are within the critical interval of the corresponding preset threshold, it is determined to switch the monitoring setting.

[0065] Furthermore, the specific confirmation process of confirming the update of the monitoring setting includes: C1. If the overall degree of change exceeds the corresponding preset threshold, the monitoring range is used as the update category, otherwise the monitoring density is used as the update category.

[0066] C2. When the update category is the monitoring range, the overall degree of change and its preset threshold are recorded as and ,Will As the monitoring area compensation ratio, the initial monitoring area is adjusted upward according to this ratio to obtain the updated monitoring area.

[0067] C3. When the update category is monitoring density, if the change exceeds the preset threshold, the updated monitoring point density is obtained in the same way as the updated monitoring area.

[0068] C4. When both the overall degree of change and the degree of change exceeding the limit do not exceed the corresponding preset thresholds, the monitoring density compensation ratio is obtained by calculating the absolute difference between the two and the upper limit value of the critical interval, and then inputting the weighted sum into the Sigmoid function to update the initial monitoring point density.

[0069] It should be added that the overall degree of change and the degree of excess of change are used as the core judgment basis. When the overall degree exceeds the threshold, it indicates that the slope deformation has shown regional characteristics and the monitoring scope needs to be expanded in priority. That is, the ratio of the overall degree to the threshold is used as the area compensation ratio to ensure that the systemic risk area can be fully covered. When the excess exceeds the threshold or both do not exceed the threshold, the focus is on adjusting the monitoring density. The former aims at the situation of local abnormal point concentration, and quantitatively improves the monitoring point density by analogy with the compensation logic of the overall degree, accurately capturing the co-evolution signal of single-point anomalies. The latter designs a nonlinear compensation mechanism for the critical state, that is, the absolute difference weighting combined with the Sigmoid function, which can not only avoid invalid adjustments triggered by slight fluctuations, but also amplify the potential risk signals close to the threshold through the function characteristics, realizing multi-dimensional adaptation of slope deformation from point to surface and from obvious to hidden, and ultimately avoiding excessive resource consumption while ensuring the effectiveness of monitoring.

[0070] It should also be noted that the overall degree of change reflects the macroscopic deformation trend of the monitored area and embodies the spatial distribution characteristics of systemic risk, while the excess degree of change focuses on the degree of anomalies at local monitoring points, indicating the potential for concentrated release of local risk. The contribution of these two factors to risk warning needs to be differentiated according to the project context. That is, if the monitored object is more sensitive to local anomalies, such as cracks in a steep slope, a higher weight can be given to the excess degree of change. If the focus is more on overall deformation trends, such as regional surface settlement monitoring, the overall degree of change can be given more weight. In other words, the weight setting can be determined according to the specific project type, which is flexible and does not limit the value.

[0071] The environmental monitoring module collects the humidity of the slope area in real time to select the laser wavelength. Based on the updated monitoring settings and the selected laser wavelength, the corresponding laser ranging terminal is triggered to emit the corresponding wavelength laser and receive the reflected signal to obtain the three-dimensional coordinates of each current monitoring point.

[0072] Specifically, the specific selection process for selecting the laser wavelength includes: when the humidity in the slope area exceeds a preset humidity threshold and the duration exceeds a preset humidity duration, generating a first wavelength range selection instruction.

[0073] When the first wavelength range selection instruction is not triggered, the normalized deviation value between the average humidity and the corresponding preset threshold is calculated as the environmental impact factor, the environmental impact factor is mapped to the preset wavelength range set, and the second wavelength selection range instruction is output.

[0074] In a specific embodiment, the humidity threshold can be 70%RH, and the first wavelength range corresponds to the band where the water molecule absorption rate is less than 0.1dB / km. For example, the instruction selects a 1550nm wavelength. When the environmental impact factor value range is between 0 and 0.1, the instruction selects a 1064nm wavelength. When the environmental impact factor value range is between 0.1 and 0.3, the instruction selects a 1310nm wavelength. When the environmental impact factor value is greater than 0.3, the instruction selects a 1550nm wavelength, and the preset wavelength range set is implemented by a lookup table, which stores the nonlinear mapping relationship between the compensation weight and the wavelength.

[0075] This embodiment of the present invention effectively compensates for the natural environment's impact on laser signal transmission by collecting environmental parameters such as slope humidity in real time, selecting laser wavelengths, and adjusting the operating parameters of the laser ranging terminal based on dynamically updated monitoring settings. This reduces the interference of environmental noise on 3D coordinate data acquisition, significantly improving the system's adaptability in complex operating conditions and ensuring high-precision and reliable monitoring data.

[0076] The slope deformation analysis terminal sets deformation risk compensation weights based on environmental tracking logs of the slope area in past monitoring periods, and calculates slope deformation risk indexes based on the three-dimensional coordinates of the monitoring points and the deformation risk compensation weights.

[0077] Specifically, setting the deformation risk compensation weight includes: extracting the average humidity of each monitoring day from the environmental tracking log, and calculating the ratio of the number of monitoring days with the average humidity exceeding a preset humidity threshold to the total number of monitoring days to obtain a humidity continuous interference ratio.

[0078] The temperature gradient and maximum temperature of each monitoring day were extracted from the environmental tracking log. The proportion of monitoring days with temperature gradient exceeding the preset gradient and maximum temperature exceeding the preset temperature threshold in the total number of monitoring days were counted respectively. The maximum proportion was selected as the temperature continuous interference ratio.

[0079] Based on the preset temperature and humidity influence weights, the deformation risk compensation weight is obtained by weighted summing the humidity continuous interference ratio and the temperature continuous interference ratio.

[0080] Understandably, persistent humidity exceeding a threshold can cause the rock mass to remain saturated for extended periods, accelerating the expansion and softening of clay minerals. For example, montmorillonite can expand threefold in volume under high humidity, leading to a continuous reduction in shear strength. Statistical analysis of the humidity persistence interference ratio captures this cumulative damage effect. Exceeding the temperature gradient limit can trigger thermal stress concentration within the rock mass, leading to the propagation of microcracks. For example, in granite, crack growth rates can reach 0.01 mm / cycle under temperature cycling. Exceeding the maximum temperature limit can cause dehydration and shrinkage of the rock mass, resulting in tensile cracks. Taking the maximum ratio of the two as the temperature persistence interference ratio can highlight the persistent effects of the most adverse environmental conditions on the slope.

[0081] In summary, the humidity continuous interference ratio reflects the cumulative effect of pore water pressure, and the temperature continuous interference ratio reflects the thermal stress cyclic damage. By using statistical ratios rather than instantaneous values, accidental factors such as short-term sensor failures can be filtered out, focusing on the continuous environmental disturbances that truly threaten slope stability.

[0082] By integrating historical environmental tracking logs with three-dimensional coordinate sequences and assigning deformation risk compensation weights, this embodiment of the present invention establishes a multidimensional slope deformation risk assessment mechanism, overcoming the limitations of traditional single-point monitoring. This allows for a comprehensive analysis of spatiotemporal evolutionary characteristics such as displacement deviation and curvature mutation point density. By combining the weights of environmental factors affecting deformation, this allows for a comprehensive analysis of the internal stress transfer patterns and slip surface development trends within the slope. This provides richer data support for the coupling of mechanics and the environment to reveal slope catastrophic mechanisms, enhancing the ability to more precisely monitor potential slope catastrophic processes.

[0083] In another specific embodiment, the statistical slope deformation risk index includes: D1, based on the three-dimensional position coordinates of each monitoring point, the displacement values ​​of the x-axis, y-axis and z-axis between the three-dimensional position coordinates of the current monitoring point and the three-dimensional position coordinates of the last monitoring point are calculated, and recorded as 、 and , Indicates the current monitoring point number, .

[0084] D2, based on 、 and Calculate the deformation energy of each current monitoring point , , Indicates the slope height.

[0085] D3: Construct a Delaunay triangulation network to connect the monitoring points, calculate the displacement vector angle of adjacent monitoring points based on cosine similarity, and calculate the displacement coordination index of each monitoring point and its adjacent monitoring points based on the angle. .

[0086] D4. The deformation risk compensation weight is recorded as , calculate the slope deformation risk index , ,in, Indicates the standard deviation of the deformation energy corresponding to each monitoring point, Indicates monitoring point The position corresponds to the preset risk weight, To set the reference deformation energy standard deviation value, To set the reference deformation energy value.

[0087] Understandably, , ,in, Representation and monitoring points The number of directly connected adjacent monitoring points, that is, the number of points that share a triangle edge, Indicates monitoring point Adjacent monitoring points The displacement vector angle between is the angle response function, which is based on the physical mechanism of slope displacement and statistics of a large number of landslide cases. By distinguishing divergent displacement areas from convergent displacement areas, the angle response function accurately quantifies the impact of different displacement patterns on slope stability.

[0088] It should be added that divergent displacements such as crack opening and rock separation will accelerate the formation of sliding surfaces, which are risk-enhancing behaviors, while convergent displacements such as soil extrusion and rock mass cooperative deformation may enhance the integrity of the structure, which are risk-suppressing behaviors. The functional form is derived from the strain energy release rate in fracture mechanics. When the displacement vector angle The bigger, The closer it is to 1, the larger the corresponding displacement vector angle is, and the more intense the strain energy release is. The coefficient of 0.2 is mainly derived from the statistical setting of the landslide case. Reflecting the displacement coordination, when The smaller, The closer it is to 1, the closer f is to -0.1, which corresponds to maximum risk suppression. The setting of the coefficient -0.1 is mainly based on the difference in the contribution of compression and tension failure.

[0089] In a specific embodiment, the slope deformation risk index formula is Reflects the gain effect of deformation risk compensation weight, and The ratio of displacement synergy index , deformation energy and position risk weights , accurately depict the spatial weighted effect of deformation energy at different monitoring points, Based on the dispersion of deformation energy and reference values, the risk of local mutations is logarithmically amplified. The overall design integrates spatial heterogeneity, energy intensity, and dispersion correction to achieve precise quantification of risk and engineering interpretability, allowing the index to effectively correlate geological conditions, deformation characteristics, and instability precursors.

[0090] Understandably, localized sudden changes in slope deformation are precursors to instability, such as sudden intensification of deformation in a fracture zone. However, the impact of dispersion on risk is nonlinear: small changes have a small impact, while large changes have a sharp increase. Therefore, a logarithmic function is used to compress extreme values ​​and highlight the contribution of sudden changes.

[0091] The deformation risk processing terminal matches the corresponding risk warning instruction based on the slope deformation risk index and triggers the risk warning instruction.

[0092] In another specific embodiment, the embodiment of the present invention also includes a processor and a memory, the memory stores a monitoring switching strategy and a data compensation algorithm, and the processor is configured to: determine the initial monitoring range and the initial monitoring point density based on historical deformation data, judge whether to trigger monitoring switching based on the initial monitoring settings and slope change characteristics, and select the laser wavelength of the laser ranging terminal in combination with the humidity of the slope area collected by the environmental monitoring module, and then control the laser ranging terminal to switch the wavelength.

[0093] It is understandable that the adjustment of the monitoring range and the monitoring point density can be performed by a servo drive mechanism, which is connected to the laser ranging terminal and is used to drive it to adjust the monitoring direction to update the monitoring point density or the monitoring area.

[0094] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0095] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0096] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0097] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0098] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0099] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A three-dimensional monitoring system for slope deformation based on fusion laser ranging, characterized in that: The system includes: The deformation law analysis module analyzes the slope change characteristics based on the three-dimensional coordinate sequence of each monitoring point in the past monitoring period, and the characteristics are the overall degree of change and the degree of change exceeding the limit; The monitoring switch judgment module judges the switch of the monitoring setting based on the initial monitoring setting and the slope change characteristics. If it is judged to be a switch, it confirms the update of the monitoring setting; The environmental monitoring module collects the humidity of the slope area in real time to select the laser wavelength. Based on the updated monitoring settings and the selected laser wavelength, the corresponding laser ranging terminal is triggered to emit the corresponding wavelength laser and receive the reflected signal to obtain the three-dimensional coordinates of each monitoring point. The slope deformation analysis terminal sets a deformation risk compensation weight based on the environmental tracking log of the slope area in the past monitoring period, and calculates the slope deformation risk index based on the three-dimensional coordinates of the monitoring point and the deformation risk compensation weight; The deformation risk processing terminal matches the corresponding risk warning instructions based on the slope deformation risk index and issues an early warning.

2. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The specific analysis process of the overall degree of change includes: Traverse the three-dimensional coordinate sequence of each monitoring point and calculate the position change of each monitoring point; Count the number of monitoring points whose position change exceeds the preset threshold, calculate the ratio of the number of monitoring points to the total number of monitoring points, and record it as the change-exceeding-monitoring ratio; The monitoring points that exceed the threshold are spatially connected to form an over-limit change area. If the change exceeds the monitoring ratio or the over-limit change area does not meet any of the following conditions, the overall change degree is directly assigned to 0. Otherwise, an overall change is triggered: (a) The change exceeds the monitoring ratio beyond the preset monitoring ratio threshold; (b) The ratio of the area of ​​the overlap between the excessive change area and the preset central monitoring area to the area of ​​the excessive change area exceeds the preset ratio threshold; If an overall change is triggered, the ratio of the overlapping area to the area of ​​the change exceeding limit area is recorded as the exceeding limit overlapping center trend ratio, and the change exceeding monitoring ratio and the exceeding limit overlapping center trend ratio are weighted to obtain the overall degree of change.

3. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 2, characterized in that: The specific calculation process of the position change degree of each monitoring point includes: For the same monitoring point, calculate its displacement vector, horizontal component and vertical component on the adjacent past monitoring days, combine the three to obtain the segmented displacement, and calculate the direction change rate through the direction cosine of the adjacent segmented displacement vectors; Calculate the cumulative displacement from the initial past monitoring day to the end of the past monitoring day, and calculate the displacement change deviation based on the segmented displacement, directional change rate and cumulative displacement; The spline interpolation algorithm is used to fit the three-dimensional coordinate sequence of past monitoring days to generate a continuously changing path curve. The curvature of each point on the curve is calculated and the curvature mutation points where the curvature change exceeds the preset threshold are identified. The ratio of the number of curvature mutation points to the total number of monitoring days is used as the curvature mutation point density. Based on the changing path curve, the ratio of the actual length of the path to the straight-line distance between the starting and ending points is calculated as the path tortuosity; The density of curvature mutation points and path tortuosity are normalized, and the comprehensive normalization results and displacement change deviation are weighted by a preset weight coefficient to obtain the change degree of each monitoring point.

4. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 3, characterized in that: The specific calculation process of the displacement change deviation includes: The ratio of the number of past monitoring days on which the segmented displacement was continuously greater than the set reference displacement to the total number of past monitoring days was recorded as the sustained displacement deviation ratio; Calculate the standard deviation of the corresponding segment displacement and the corresponding directional change rate for each adjacent past monitoring day as the displacement fluctuation and directional fluctuation, respectively. The ratio of the displacement fluctuation to the cumulative displacement is recorded as the displacement deviation. At the same time, the maximum directional change rate is taken as the target directional change rate. The direction fluctuation and target direction change rate are used as direction change indicators, and the direction change index is obtained by weighted summation after normalization. The continuous displacement deviation ratio, displacement fluctuation, and displacement deviation are used as position change indicators, and the position change index is obtained in the same way as the direction change index. The weighted sum of the direction change index and the position change index is introduced into the Sigmoid function to output the displacement change deviation.

5. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The specific analysis process of the variation exceeding the limit includes: Divide the past monitoring period into time windows, traverse the historical three-dimensional coordinate sequence of the corresponding monitoring point in each time window, and calculate the single-axis change value, comprehensive displacement change value and change rate of the three-dimensional coordinate of each monitoring point in adjacent time windows; If any of the single-axis change value, comprehensive displacement change value, and change rate of the three-dimensional coordinates of a monitoring point in the adjacent time window exceeds the corresponding limit, it is recorded as an over-limit monitoring point, and the ratio of its number to the total number of monitoring points is the over-limit ratio; For each over-limit monitoring point, the number of parameter items exceeding the corresponding limit values ​​in the single-axis change value of its three-dimensional coordinates, the comprehensive displacement change value, and the change rate is counted, and the number is divided by the total number of parameter items to obtain the over-limit parameter ratio; If the value of a parameter item is lower than the corresponding limit, its deviation is recorded as 0. Otherwise, the parameter item is normalized with its limit to obtain the deviation, and the maximum value of the deviation of each parameter item is taken as the parameter deviation of the over-limit monitoring point; The over-limit parameter ratio, parameter deviation and over-limit ratio of each over-limit monitoring point are recorded as and as well as , calculate the change over limit , , 、 and They are respectively expressed as the excess parameter ratio, parameter deviation and the weight corresponding to the excess ratio, Indicates the number of the over-limit monitoring point. .

6. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The monitoring setting switching judgment includes: If the overall degree of change or the degree of change exceeds the corresponding preset threshold, it is determined to switch the monitoring setting; If neither the overall degree of change nor the degree of change exceeding the limit exceeds the corresponding preset threshold and both are within the critical interval of the corresponding preset threshold, it is determined to switch the monitoring setting.

7. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The confirmation and update monitoring settings include: If the overall degree of change exceeds the corresponding preset threshold, the monitoring range is used as the update category, otherwise the monitoring density is used as the update category; When the update category is the monitoring range, the overall degree of change and its preset threshold are recorded as and ,Will As the monitoring area compensation ratio, the initial monitoring area is adjusted upward according to the ratio to obtain the updated monitoring area; When the update category is monitoring density, if the change exceeds the preset threshold, the updated monitoring point density is obtained in the same way as the updated monitoring area acquisition method; When both the overall degree of change and the degree of change exceedance do not exceed the corresponding preset thresholds, the monitoring density compensation ratio is obtained by calculating the absolute difference between the two and the upper limit value of the critical interval, and then inputting the weighted sum into the Sigmoid function to update the initial monitoring point density.

8. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The specific selection process for selecting the laser wavelength includes: When the humidity in the slope area exceeds a preset humidity threshold and the duration exceeds a preset humidity duration, a first wavelength range selection instruction is generated; When the first wavelength range selection instruction is not triggered, the normalized deviation value between the average humidity and the corresponding preset threshold is calculated as the environmental impact factor, the environmental impact factor is mapped to the preset wavelength range set, and the second wavelength selection range instruction is output.

9. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The step of setting the deformation risk compensation weight includes: The average humidity of each monitoring day is extracted from the environmental tracking log, and the ratio of the number of monitoring days with the average humidity exceeding the preset humidity threshold to the total number of monitoring days is calculated to obtain the humidity continuous interference ratio; Extract the temperature gradient and maximum temperature of each monitoring day from the environmental tracking log, and count the proportion of monitoring days with temperature gradient exceeding the preset gradient and maximum temperature exceeding the preset temperature threshold in the total number of monitoring days, and select the largest proportion as the temperature continuous interference ratio; Based on the preset temperature and humidity influence weights, the deformation risk compensation weight is obtained by weighted summing the humidity continuous interference ratio and the temperature continuous interference ratio.

10. The three-dimensional slope deformation monitoring system based on fusion laser ranging according to claim 1, characterized in that: The statistical slope deformation risk index includes: Based on the three-dimensional position coordinates of each monitoring point at present, the displacement values ​​of the x-axis, y-axis and z-axis between the three-dimensional position coordinates at the last monitoring are calculated and recorded as 、 and , Indicates the current monitoring point number. ; based on 、 and Calculate the deformation energy of each current monitoring point ; Construct a Delaunay triangulation network to connect the monitoring points, calculate the displacement vector angle of adjacent monitoring points based on cosine similarity, and calculate the displacement coordination index of each monitoring point and its adjacent monitoring points based on the angle ; The deformation risk compensation weight is recorded as , calculate the slope deformation risk index , ,in, Indicates the standard deviation of the deformation energy corresponding to each monitoring point, Indicates monitoring point The position corresponds to the preset risk weight, To set the reference deformation energy standard deviation value, To set the reference deformation energy value.

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