Artificial intelligence-based rock high slope excavation anchoring deformation prediction method

Abstract

The present application relates to the technical field of deformation prediction, in particular to a rock high slope excavation anchoring deformation prediction method based on artificial intelligence, comprising the following steps: obtaining multi-source image data to analyze rock mass volume and gravity center transfer, extracting abnormal stress and displacement corresponding relationship, constructing structure offset path, screening continuous abnormal features, extracting key deformation rate interval, and obtaining anchoring deformation trend prediction result. In the present application, by constructing the gravity center transfer trajectory and the mass difference space sequence, combining the coupling relationship between the stress abnormal point and the displacement response direction, the position of the uneven section is determined, the collaborative evolution section of the structure offset path and the stress boundary is extracted, the continuous abnormal zone is screened according to the crack change and joint fluctuation trend, the key change interval is extracted combined with the time characteristics of shear deformation rate, the dynamic judgment of the structure deformation path and the extension direction is completed, and the spatial continuity recognition ability and the time response resolution are enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of deformation prediction, in particular to a rock high slope excavation anchoring deformation prediction method based on artificial intelligence. BACKGROUND

[0002] The technical field of deformation prediction relates to the estimation and determination of the physical form changes such as displacement, crack, settlement of engineering structures or rock-soil bodies under the action of external force or environmental influence. This technical field includes core matters such as data acquisition, deformation identification, mechanical parameter analysis, mathematical model establishment, and prediction result verification. Common methods include trend analysis based on historical monitoring data, analytical method based on geophysical parameters, finite element numerical analysis method based on continuum mechanics theory and its iterative optimization method, etc. Generally, by setting initial boundary conditions and material constitutive relations, displacement or stress field is solved in combination with field monitoring data, and then the deformation state of future specific space-time nodes is derived. Among them, the traditional rock high slope excavation anchoring deformation prediction refers to predicting the tensile, shear slip or displacement variation of rock mass structure caused by stress change, hydrological condition disturbance, etc. during the blasting, excavation and anchoring construction of rock high and steep slope, using methods such as empirical formula fitting, elastoplastic constitutive model calculation, difference method and finite element discrete modeling method. The content usually includes rock mass classification, structure surface trend angle, anchor length and spacing, load boundary condition, blasting vibration velocity measurement, etc. in the deformation prediction report, and regression fitting or model iteration are combined with the measured deformation monitoring data to complete the prediction analysis.

[0003] The existing technology focuses on model parameter setting and monitoring quantity regression analysis in the process of structural deformation response identification, lacks deep extraction of spatial trajectory evolution and structure gravity migration process among multiple layers of information, and shows response delay and insufficient positioning accuracy when dealing with stress field non-uniform distribution and structure displacement path identification. It is difficult to construct an abnormal distribution framework with spatial extension at the initial stage of deformation anomaly, especially in the face of unstable continuous profile deformation trend, crack closure and joint angle dramatic fluctuation, etc. The prediction result cannot timely reflect the dynamic evolution characteristics of the key area, causing the accumulation of anchoring response path identification deviation, and it is difficult to support the stability dynamic evaluation in the process of partition regulation and continuous construction. SUMMARY

[0004] In order to solve the technical problems existing in the prior art, the embodiments of the present application provide a rock high slope excavation anchoring deformation prediction method based on artificial intelligence, which comprises the following steps:

[0005] In order to achieve the above purpose, the present application adopts the following technical scheme: a rock high slope excavation anchoring deformation prediction method based on artificial intelligence, comprising the following steps:

[0006] S1: Obtain a profile density map, a lithology division map and a construction progress map, analyze rock mass volume change, extract quality difference, coordinate structure position, track gravity center shift, and obtain slope structure migration path change characteristics;

[0007] S2: Based on the slope structure migration path change characteristics, extract an anchor layout map and a stress monitoring map, analyze anchor rod axial force change trend, search for abnormal points, judge uneven area position according to displacement response direction, and obtain stress abnormal distribution area position corresponding relationship;

[0008] S3: Based on the stress abnormal distribution area position corresponding relationship, extract cross graph line, judge direction consistency, connect continuous track points, analyze angle and distance change, and obtain offset path and stress boundary associated paragraph;

[0009] S4: Based on the offset path and stress boundary associated paragraph, read shear deformation, joint inclination and crack characteristics, compare response direction, screen change area, extract layer position, and obtain continuous abnormal trend distribution content;

[0010] S5: Based on the continuous abnormal trend distribution content, extract deformation rate change area, analyze direction continuity, judge the relationship with construction time, and obtain rock slope anchoring deformation trend prediction result.

[0011] As a further scheme of the present application, the slope structure migration path change characteristics include rock mass volume change trend, rock mass quality space difference, and slope gravity center shift trajectory, the stress abnormal distribution area position corresponding relationship includes non-uniform section position, layer number corresponding area, stress abnormal point and displacement direction response relationship, the offset path and stress boundary associated paragraph includes trajectory space direction continuous consistent point, layer space angle change trend, and boundary trend overlapping paragraph, the continuous abnormal trend distribution content includes shear deformation abnormal profile, joint inclination change area, and crack opening and closing fluctuation concentrated area, and the rock slope anchoring deformation trend prediction result includes shear deformation rate change concentrated section, construction time sequence and response change order, and space direction extension trend position.

[0012] As a further scheme of the present application, the gravity center shift refers to the space migration of the overall mass center position of the rock mass structure caused by the change of rock mass volume and density during high slope excavation construction;

[0013] The anchor rod axial force change trend refers to the change of the axial force data recorded by the differential anchor rod along the time axis during the anchor layout process.

[0014] As a further scheme of the present application, the abnormal point refers to a point that is different from surrounding monitoring values in the monitoring process, which is manifested as a change in displacement direction, a stress mutation, and an abnormal rate, representing early signs of potential risks and structural instability.

[0015] The uneven region refers to a position region in the anchoring area where the stress of the structure and the displacement response direction change suddenly, indicating that the stress distribution in the region is uneven and there is a potential risk of structural stability.

[0016] As a further scheme of the present application, the specific steps of S1 are:

[0017] S101: Obtain the profile density map, lithology division map and construction progress map, extract the rock volume and density value of the stage profile coordinate range, configure the quality data frame of the corresponding region, compare the quality distribution change of the stage, extract the regional quality state over time, and obtain the rock mass stage quality evolution sequence;

[0018] S102: Based on the rock mass stage quality evolution sequence, extract the stage boundary coordinate point, compare the spatial position of the same numbered point, judge the direction change, extract the trajectory data of the position continuous offset, divide the path according to the direction change trend, and obtain the structure position direction migration path set;

[0019] S103: Call the structure position direction migration path set, retrieve the position of the center of gravity point in the path, compare whether the transfer direction and the path trend are continuous, arrange the transfer segments with consistent direction in coordinate order as continuous paths, and obtain the slope structure migration path change characteristics.

[0020] As a further scheme of the present application, the specific steps of S2 are:

[0021] S201: Based on the slope structure migration path change characteristics, extract the layout position and axial force time sequence change information corresponding to each group of anchor rods in the anchoring layout map and stress monitoring data map, extract the change trend according to the layout number in turn, select the number section that continuously presents a linear trend turning point, and obtain the axial force change trend annotation sequence;

[0022] S202: Based on the axial force change trend annotation sequence, extract the coordinate position of the numbered point, compare the displacement response direction with the adjacent region, judge whether the direction is consistent, select the layout point whose direction deviates, extract the spatial distribution information, and obtain the direction response offset coordinate set;

[0023] S203: Based on the direction response offset coordinate set, locate the numbered index position in the layout map layer, extract the coordinate range of the adjacent numbered region in the same layer, merge the continuous regions in order into the same response region, output the region position corresponding layer coordinates, and obtain the stress abnormal distribution region corresponding relationship.

[0024] As a further scheme of the present application, the specific steps of S3 are:

[0025] S301: Based on the stress anomaly distribution area position corresponding relationship, the intersection area of the slope structure track and the stress boundary line segment in the layer is extracted, the structure deflection direction and the boundary extension direction vector at the intersection point are compared, whether the direction consistency is judged, the intersection line segment with consistent direction is extracted, and the direction consistent intersection paragraph set is obtained;

[0026] S302: Based on the direction consistent intersection paragraph set, the continuous track point on the layer is extracted according to the coordinates, the track node which continuously keeps consistent in the spatial distribution direction is screened, the point before and after the deflection of the track line segment is compared, the line segment which does not occur direction deflection is identified, and the spatial direction continuous track set is obtained;

[0027] S303: The spatial angle change and distance distribution range of the line segment presented in the layer are intercepted by calling the spatial direction continuous track set, the segment consistent with the structure deflection direction and the stress boundary trend continuation is screened, the track number and layer coordinate range are output, and the offset path and stress boundary associated paragraph are obtained.

[0028] As a further scheme of the present application, the specific steps of S4 are:

[0029] S401: Based on the offset path and stress boundary associated paragraph, the shear deformation sequence of the monitoring point, the joint inclination range and the crack opening and closing state are extracted along the path direction, the direction scalar of adjacent monitoring points in the parameter sequence is analyzed, the continuous response segment with consistent direction is screened, and the direction unified deformation segment set is obtained;

[0030] S402: Based on the direction unified deformation segment set, the layer coordinate section where the segment is located is identified, the monitoring curve fluctuation form of the adjacent area is extracted, the response path offset position point is extracted at the continuous trend change node, the spatial connection relationship between the offset points is analyzed, and the continuous response segment positioning index is obtained.

[0031] S403: Based on the continuous response segment positioning index, the number and coordinate area in the layer are matched, the path response sequence with continuous change form under the same number is screened, the point which does not form a periodic segment is eliminated, the corresponding index position and response direction information in the path sequence are aggregated, and the continuous abnormal trend distribution content is obtained.

[0032] As a further scheme of the present application, the process of screening the path response sequence with continuously changing forms under the same number is specifically: extracting the layer number and corresponding coordinate area included in the continuous response segment positioning index, sequentially comparing the response directions of the monitoring points in the path with the same number point by point, identifying the continuity characteristics of the response direction change between adjacent points, and judging whether it constitutes a continuous path segment according to the trend of direction keeping and gradual change.

[0033] The process of removing the point positions that do not form a periodic segment is specifically: identifying the response path segment, repeatedly comparing the direction response change of each point position in the path sequence, judging whether there is a regular direction change, and removing the corresponding point position from the sequence when the path lacks the continuity of the direction between adjacent points and there is a random jump.

[0034] The process of aggregating the corresponding index position and response direction information in the path sequence is specifically: according to the continuous point positions retained in the path, corresponding to extract the spatial index and response direction in order, compare the change state of the response direction, analyze the response paragraph with consistent direction, and corresponding spatial position sequence and direction information.

[0035] As a further scheme of the present application, the specific steps of S5 are:

[0036] S501: Based on the continuous abnormal trend distribution content, extract the section with concentrated change amplitude in the shear deformation rate sequence, call the monitoring time sequence corresponding index, analyze the continuity of adjacent data points in the time axis direction, screen the segment with direction keeping state, and get the shear rate continuous section index;

[0037] S502: Based on the shear rate continuous section index, match the start and end time points of the section with the construction time sequence node position in the layer, analyze the response delay distribution position point, screen the segment with time difference structure with the previous section, and get the construction response time delay path set;

[0038] S503: Call the construction response time delay path set, aggregate the path corresponding spatial coordinate point position sequence, extract the path segment with consistent direction according to coordinate sorting, exclude the segment with direction jump, and get the rock slope anchoring deformation trend prediction result according to the trajectory continuity and position trend keeping relationship.

[0039] Compared with the prior art, the present application has the following advantages and positive effects:

[0040] In the present application, the position of the unbalanced section is determined by constructing the gravity center transfer trajectory and the mass difference space sequence, combining the coupling relationship between the stress anomaly point and the displacement response direction, extracting the co-evolution section of the structural offset path and the stress boundary, screening the continuous anomaly zone according to the crack change and joint fluctuation trend, extracting the key change interval combined with the time characteristics of the shear deformation rate, and completing the dynamic judgment of the structural deformation path and the extension direction, thereby enhancing the spatial continuity recognition ability and the time response resolution. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0042] Figure 1 The step flowchart of the present application is shown in the figure.

[0043] Figure 2 The S1 refinement schematic diagram of the present application is shown in the figure.

[0044] Figure 3 The S2 refinement schematic diagram of the present application is shown in the figure.

[0045] Figure 4 The S3 refinement schematic diagram of the present application is shown in the figure.

[0046] Figure 5 The S4 refinement schematic diagram of the present application is shown in the figure.

[0047] Figure 6 The S5 refinement schematic diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0048] The technical solutions in the present application will be described below in combination with the drawings.

[0049] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0050] In the embodiments of the present application, "image" and "picture" can be used interchangeably, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0051] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0052] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0053] Please refer to Figure 1 The embodiments of the present application provide a rock high slope excavation anchoring deformation prediction method based on artificial intelligence, comprising the following steps:

[0054] S1: Obtain the profile density graph, lithology area division graph and stage construction progress distribution graph of the rock slope in the excavation process, judge the rock block volume change trend between profiles according to the construction time sequence, extract the mass difference of the rock layer in the spatial direction, compare the position change according to the coordinate sequence, track the transfer track of the gravity center of the slope with the stripping stage, and obtain the change characteristics of the slope structure migration path;

[0055] S2: Based on the change characteristics of the slope structure migration path, call the anchoring area layout graph and stress monitoring data graph, screen the linear inclination of the axial force change of the differential position anchor rod, sequentially search the abnormal distribution points according to the layout direction, judge whether there is a non-equilibrium section corresponding to the position and the displacement response direction of the adjacent area, and obtain the stress abnormal distribution area position corresponding relationship according to the area position corresponding to the layer number;

[0056] S3: Based on the stress abnormal distribution area position corresponding relationship, extract the cross graph area, judge whether the slope structure offset direction and the stress change area boundary direction remain consistent in the extension process, connect the track points with continuous spatial direction, analyze the spatial angle change and distance trend on the graph layer in sections, extract the track paragraphs that continuously coincide with the offset direction and the boundary trend, and obtain the offset path and stress boundary associated paragraphs;

[0057] S4: Based on the offset path and stress boundary associated paragraphs, read the shear deformation change trend, joint inclination change amplitude and fracture opening and closing change characteristics of the surrounding monitoring points along the path direction, compare whether the fluctuation directions of adjacent areas are consistent, screen the profile area where continuous abnormal changes occur, and obtain the continuous abnormal trend distribution content according to the layer index corresponding number and position area.

[0058] S5: Based on the continuous abnormal trend distribution content, the shear deformation rate change amplitude concentrated section in the monitoring parameter time sequence is extracted, the direction continuation characteristics in the adjacent time window are analyzed, the corresponding construction time sequence node and the response change appearance sequence are obtained, the trend line change amplitude analysis time distribution situation is obtained, the position content maintaining the extension trend in the space direction is extracted, and the rock slope anchoring deformation trend prediction result is obtained.

[0059] The slope structure migration path change characteristics include the rock mass volume change trend, the rock layer quality space difference, and the gravity center transfer trajectory of the slope, the stress abnormal distribution area position corresponding relationship includes the non-equilibrium section position, the layer number corresponding area, the stress abnormal point and the displacement direction response relationship, the offset path and the stress boundary associated paragraph include the trajectory space direction continuous consistent point, the space angle change trend on the layer, and the boundary trend coincident paragraph, the continuous abnormal trend distribution content includes the shear deformation abnormal profile, the joint inclination dramatic change area, and the fracture opening and closing fluctuation concentrated area, and the rock slope anchoring deformation trend prediction result includes the shear deformation rate change concentrated section, the construction time sequence and the response change sequence, and the space direction extension trend position.

[0060] Please refer to Figure 2 , the specific steps of S1 are as follows:

[0061] S101: Obtain the profile density map, the lithology division map and the construction progress map, extract the rock mass volume and the density value of the stage profile coordinate range, configure the quality data frame corresponding to the area, compare the quality distribution change of the stage, extract the regional quality state with the time elapse, and obtain the rock mass stage quality evolution sequence;

[0062] The layer content in the profile density map, the lithology division map and the construction progress map is obtained by sequentially reading the coordinate boundary information, the layer number and the legend mark corresponding to each profile position in the sheet, converting the sheet frame of each stage profile map in the drawing into a spatial coordinate range, and combining the actual coordinate value range calibrated according to the scale in the drawing to extract the graphic element area within the coordinate boundary corresponding to each profile. For the color scale legend in the density map, the relationship between the color shown in different regions and the corresponding density value is indicated. Based on the color distribution in the density map, the rock block unit density value covered by each coordinate region is divided, and the pixels within the same coordinate range are aggregated into a unit region. The area of the unit region is converted into an area value according to the scale of the drawing, and the height is determined according to the profile depth information, and then the three-dimensional volume is derived. The rock block volume is estimated by multiplying the area value of the divided region by the vertical extension height. If the area of a region is 15x10 proportional grid units, the height is 6 grids, then the converted volume is 900 volume units, and the density value of the corresponding region is 2.65 units of mass, then the mass data of the region is 2385 units of mass. The area and matching density of all profile maps are read in this way, and the mass value is calculated item by item to form the mass data frame under the profile stage. When processing the construction progress map of each stage, the stage identifier and boundary range marked in the sheet are retrieved, the mass data frames of the same coordinate region in each stage are compared, the mass values of the region in different stages are compared horizontally, the change difference and change direction are extracted, and it is judged whether the difference is an increment or a decrement. If the mass of a region is 2500 in stage one and 2150 in stage two, the difference is -350, which represents a decrease in mass in the later stage. The change trend of each stage region is sorted in order according to the sheet annotation sequence to obtain the mass change state sequence of multiple regions with the progress of the stage. The mass change state set is formed by rearranging the stage sequence, and the mass change state corresponding to all regions is connected in order according to the coordinate index, so that the mass change path of the region in the progress of each stage is extracted, and the stage mass evolution sequence of the rock mass is obtained.

[0063] S102: Based on the stage mass evolution sequence of the rock mass, the stage boundary coordinate points are extracted, the spatial positions of the same numbered points are compared, the direction change is judged, the trajectory data of the position continuous offset is extracted, the path is divided according to the direction change trend, and the structure position direction migration path set is obtained.

[0064] First, the coordinate points corresponding to the profile boundary positions in each stage are extracted and indexed in a numbered manner. For each numbered point, the coordinate position changes in different stages are read segment by segment. By reading the horizontal and vertical displacement values of the coordinate points, the offset direction of the point is identified and judged. For example, the coordinates of numbered point P1 in three stages are (128, 95), (130, 98), and (132, 102). It is judged that there is a shift in the longitudinal and horizontal coordinates, and it can be concluded that it is shifted to the right and up. Then, the coordinate points of the same number in multiple stages are connected in order to form a trajectory path. Next, the above coordinate comparison and direction judgment operations are performed on all numbered points. Points with continuous shift characteristics are grouped into the same trajectory group. If multiple points move in the same direction during stage advancement, it indicates that they have consistent direction. Record the trajectory set number and spatial position coordinates. These trajectories are divided into different path clusters based on direction changes. If the angle changes in multiple trajectories are within 5 degrees, they can be grouped into a consistent direction path. For example, points numbered P3, P4, and P5 change direction to the east and north in three stages, and the direction angle fluctuation is not more than 5 degrees. They can be grouped into the same trajectory direction path set. In this process, the starting point and end point coordinates of each trajectory need to be identified. The trend of each path is compared, and the direction of each sub-path in the path set is classified. Finally, the paths are divided by number, the content of each path cluster is aggregated to form a unified set, and the number, extension direction, and corresponding coordinate point set of each path are output to obtain the structure position direction migration path set.

[0065] S103: Call the structure position direction migration path set, retrieve the center point position in the path, compare the transfer direction and path trend, arrange the direction consistent transfer segment in coordinate order as a continuous path, and obtain the slope structure migration path change characteristics;

[0066] First, read all the coordinate points of each path in the path set, and extract the centroid position of the area enclosed by the path. The centroid coordinates are taken as the spatial barycenter of the path. The extraction process is performed on each path in turn. For example, the path with path number T01 has coordinate points (118, 92), (121, 94), and (125, 98). The center point is calculated as (121.3, 94.6). After recording the barycenter coordinates, the direction of the path from the starting point to the ending point is annotated. The relative position change direction of the barycenter is confirmed. It is judged whether the change direction is consistent with the original direction of the path. If the directions are consistent, the transfer segment information is retained, and the path number and trend identification are recorded. Further, the transfer segments with consistent directions are sorted according to the order of the barycenter coordinates on the coordinate axis. The continuous sorting results from the starting path to the ending path are obtained. If path numbers T05, T06, and T07 show a monotonic increasing trend in the barycenter coordinates, it indicates that the spatial arrangement has continuity. The connection relationship of the paths in this direction is further expanded. If there is a reverse path direction in the middle, the path sequence expansion is interrupted. This operation is performed on each initial path for multiple rounds of direction consistency comparison and connectivity judgment. The coordinate range covered by each continuous path and the connection order number are annotated in the final output. The slope structure migration path change characteristics are finally obtained.

[0067] Please refer to Figure 3 The specific steps of S2 are as follows:

[0068] S201: Based on the slope structure migration path change characteristics, extract the layout position and axial force time sequence change information corresponding to each group of anchor rods in the anchor layout diagram and stress monitoring data diagram. According to the layout number, extract the change trend in turn. Select the number section that continuously presents a linear trend turning point to obtain the axial force change trend annotation sequence.

[0069] First, locate the layer number corresponding to each path, extract all anchor layout number information covering the layer in the anchor layout map, and record the three-dimensional coordinate layout point for each number. Match the corresponding number position with the number axial force time series curve in the axial force monitoring data map. Segment the axial force change trend sequence under each anchor number, and use the numerical difference sequence in each time period as the basis for judging the change trend. Then, perform directional consistency judgment on each segment of the axial force sequence. If the axial force growth direction changes from positive to negative, or from negative to positive in three or more consecutive monitoring points, record the start and end numbers of the change position and mark them as a trend turning section in the order of the layout number. If there are multiple monotonic increasing segments in a certain number interval, such as A15 to A23, that turn into decreasing segments, record it as a linear turning segment. Perform this screening operation on all layout number sequences, extract and label the number sections that meet the turning conditions, and associate the three-dimensional layout position corresponding to the number based on the layout map coordinates. Finally, construct a number and change state comparison sequence table, and distinguish the number segments with different direction turning. Establish a symbol sequence to represent the turning direction, such as assigning a negative sign to a section that turns from rising to falling, and vice versa. Get the axial force change trend annotation sequence.

[0070] S202: Based on the axial force change trend annotation sequence, extract the number point coordinate position and compare it with the adjacent area displacement response direction to judge whether the direction is consistent. Screen the layout points with direction deviation, extract the spatial distribution information, and get the direction response deviation coordinate set.

[0071] Firstly, call each set of anchor rod layout number recorded therein, extract its three-dimensional coordinate information in order of number, in the process of extracting coordinates, the three-dimensional space position of all numbered points in the same layout section is aggregated to form the spatial layout point set corresponding to the layout path, and the displacement response direction information corresponding to the number is searched in the stress monitoring data graph, the direction information is compared with the response direction data of the adjacent two numbers before and after the numbered point, if the response direction change amount continuously remains in single direction change, it is determined that the direction is consistent, if the response direction change sign is different from that of the adjacent point at any numbered point, it is determined that the direction deviates, record the numbered point and its spatial coordinate information, and record its layer index number at the same time, in the specific execution, take a numbered point B12 as an example, its displacement response direction is inclined to the lower left, compared with adjacent numbered points B11 and B13, if the direction change sign changes, extract the three-dimensional coordinates of the point x=42.1, y=108.3, z=16.7, and record its layer number T07, at the same time, the point in the layout path is marked as a direction abnormal path point, after completing the direction consistency judgment of all numbered points, the spatial information aggregation operation is performed on all layout numbered points with direction deviation, the coordinate positions are classified according to the layer index, and are arranged in ascending order of number, finally the direction response deviation coordinate set is obtained.

[0072] S203: Based on the direction response deviation coordinate set, the index position in the layout graph layer is located, the coordinate range of the adjacent numbered area in the same layer is extracted, the continuous area is merged in order as a same response area, the area position corresponding layer coordinate is output, and the stress abnormal distribution area position corresponding relationship is obtained.

[0073] Firstly, read the spatial coordinates and number information of each set of offset points in turn, match each number with the index position of the anchor point in the layout graph layer, locate the specific coordinate area of each offset number in the layer grid in the layout graph, sequentially determine the number value increment or decrement direction between adjacent numbers, if there is a continuous numbering relationship between adjacent numbers, and the coordinate position belongs to the same block or exists boundary contact in the layer grid, it is determined that the point set belongs to the same numbered area, for example, the numbers P13, P14 and P15 are horizontally distributed in the layer T03, and the x-axis coordinate difference value is less than 2 meters, and the y-axis difference value is not more than 1 meter, it is determined that they are continuous numbers in the same area, and the numbered section is recorded as a set of continuous numbered areas, then the maximum x and y values and the minimum x and y values of all point coordinates in the region are extracted to establish the coordinate bounding box of the numbered region, and then the operation is continued in the adjacent layer, the regions are classified by layer number, and the region division process of all offset numbered points is completed in turn, finally, a plurality of numbered points with continuous numbering, close coordinates and consistent layers are aggregated into independent response regions, the layer number and coordinate bounding box range are output, and the stress abnormal distribution area position corresponding relationship is obtained.

[0074] Referring to Figure 4 , the specific steps of S3 are:

[0075] S301: Based on the stress anomaly distribution area position corresponding relationship, the intersection area of the slope structure trajectory and the stress boundary line segment in the layer is extracted, the structure deflection direction and the boundary extension direction vector at the intersection point are compared, it is judged whether the direction consistency is possessed, the intersection line segment with consistent direction is extracted, and the direction consistent intersection paragraph set is obtained;

[0076] Firstly, the coordinate sequence of each slope structure trajectory line segment is retrieved from the layout layer, and the annotated stress boundary line segment set in the corresponding layer is extracted synchronously. By coordinate interval comparison, the intersection area with coordinate overlap or approximate overlap between the two types of line segments is identified. The intersection point coordinates are obtained in the intersection area, and the strike vector of the trajectory segment at the intersection point and the extension vector of the boundary line segment are located. Further, the angle direction of the two vectors is judged. If the angle between the two vectors is less than the specified threshold angle and the direction cosine value is greater than the direction consistency judgment threshold, it indicates that the trajectory segment and the boundary segment at the intersection point have direction consistency. For example, the direction of the trajectory segment at a certain intersection point is north by east 10 degrees, and the direction of the stress boundary line is north by east 12 degrees, the direction angle is 2 degrees, and the direction consistency judgment threshold is set to 5 degrees. Therefore, the intersection point satisfies the direction consistency condition. The trajectory segment and the boundary segment corresponding to the intersection point are jointly regarded as the direction consistent intersection line segment, and the number index and the layer number thereof are recorded. After traversing all the intersection areas, the line segment set satisfying the direction consistency judgment is merged and numbered, and is arranged into a unified data frame output, to obtain the direction consistent intersection paragraph set.

[0077] S302: Based on the direction consistent intersection paragraph set, the continuous trajectory points on the coordinate extraction layer are extracted, the trajectory nodes continuously consistent in spatial distribution direction are screened, the points before and after the direction deflection of the trajectory line segment are compared, the line segment without direction deflection is identified, and the spatial direction continuous trajectory set is obtained;

[0078] First, the trajectory point sequence associated with each trajectory segment is extracted from the cross paragraph, and the coordinates in the layer are sequentially sorted. The sorted trajectory points are arranged in order according to the number to form an initial trajectory path set. In the set, the directional vector between any two adjacent trajectory points is calculated according to the coordinate difference. Three consecutive points form two line segments. The direction deflection is identified by calculating the included angle of the two line segments. If the included angle of the two directional vectors is less than the spatial deflection threshold, it is considered that the two trajectory segments have not deflected in the direction. The trajectory points here maintain continuity in the spatial distribution direction. For example, if the included angle of the two line segments formed by the trajectory points P1, P2 and P3 is 4 degrees and the deflection threshold is 5 degrees, P2 is retained as a direction continuous point. If the included angle is 6 degrees, the point is excluded. All adjacent points are subjected to the included angle judgment operation. The trajectory point paragraph that continuously satisfies the spatial direction consistency condition is filtered out in each trajectory. Finally, the trajectory segment set with continuous direction characteristics is output according to the trajectory number index, and the spatial direction continuous trajectory set is obtained.

[0079] S303: Call the spatial direction continuous trajectory set, intercept the spatial angle change and distance distribution range of the line segment presented in the layer, filter the segments consistent with the structure offset direction and stress boundary trend continuation, output the trajectory number and layer coordinate range, and obtain the offset path and stress boundary associated paragraph.

[0080] First, the trajectory number information in the trajectory set is used to locate the corresponding line segment in the layer one by one, and the spatial vector parameter set formed by the start and end coordinate points of each line segment is extracted. The spatial angle change of each line segment is identified separately. In the identification process, the change of the included angle between the coordinates is used as the angle determination basis. The angle interval between the start point and the end point vector is extracted. The trajectory line segment directional vector and the structure offset directional vector are compared segment by segment in combination with the structure offset directional vector parameter. When the trajectory line segment direction is within the angle offset range threshold and the direction is consistent, it is considered as a consistent segment. For example, in the scene where the structure offset direction is northeast, if the angle vector of a certain trajectory line segment is less than 15 degrees with the offset direction and points to the northeast, it is judged that the line segment is a direction consistent segment. The start and end coordinates of the direction consistent line segment in the layer are further extracted, and the distance between each segment is calculated to construct the distance distribution sequence of each trajectory. Then, the stress boundary trend directional vector is introduced. If the trajectory line segment direction and the stress boundary trend vector are consistent within the included angle range, the trajectory line segment is considered as a line segment that satisfies the dual consistency conditions of the structure offset direction and the stress boundary trend. Finally, the trajectory number, layer coordinate range and direction attribute corresponding to the line segment are output, and the offset path and stress boundary associated paragraph are obtained.

[0081] Please refer to Figure 5The specific steps of S4 are:

[0082] S401: Based on the association of the offset path and the stress boundary section, the shear deformation sequence of the monitoring points, the joint inclination range and the crack opening and closing state are extracted along the path direction, the direction scalar of the adjacent monitoring points in the parameter sequence is analyzed, the continuous response segments with consistent direction are screened, and the direction unified deformation segment set is obtained;

[0083] First, index extraction is performed on each monitoring point in the path range, and the shear deformation sequence data, joint inclination range information and crack opening and closing state content of the corresponding monitoring point are called in the layer database. The displacement direction value of the shear deformation sequence is extracted in sequence, the joint inclination is formed into a change interval according to the angle difference between adjacent points, and the crack state is positively or negatively identified according to the change direction of the gap width between adjacent nodes. The numbering sections consistent with the coordinate arrangement order are extracted from the above three parameter data, and the direction uniformity judgment operation is performed on the direction vectors of the continuous monitoring points in each path segment. In the judgment process, the direction vector pair between each adjacent two points is called to perform angle comparison operation. If the included angle is within the set threshold range, for example, less than 20 degrees, and the scalar is positive in the coordinate arrangement direction, it is determined that the directions are consistent. According to this standard, the monitoring point paragraphs that meet the direction continuity state in the whole path are screened, and the shear deformation value, joint inclination value and crack state change trend in the paragraph are recorded with position point and number information. In the example, the shear deformation in a numbered segment (such as P101-P108) is southeast displacement, the joint inclination continuously increases from 25 degrees to 32 degrees, and the crack opening increases from 3.5 mm to 4.2 mm. The directions are consistent. Such segments can be classified into unified response sequences. This screening process is performed in all path segments to extract segments with consistent directions, and finally the direction unified deformation segment set is obtained.

[0084] S402: Based on the direction unified deformation segment set, the layer coordinate section where the segment is located is identified, the monitoring curve fluctuation pattern of the adjacent area is extracted, the offset position points of the response path are extracted at the continuous trend change nodes, the spatial connection relationship between the offset points is analyzed, and the continuous response segment positioning index is obtained.

[0085] First, the coordinate analysis operation is performed on each segment corresponding to the layer number, the minimum rectangular area range covered by the segment in the layer file is extracted, and all monitoring point numbers in the range are listed as a candidate set, then the displacement response curve of the adjacent numbered points in the candidate set is called, the data points are extracted from the curve graph segment by segment, the trend nodes in the fluctuation form are identified by judging the number of positive and negative switching times of adjacent points in the value change direction, wherein if a numbered point has the same curve direction as the previous numbered point and the opposite curve direction as the next numbered point, it is a trend change node, further, the offset position points in the path direction are extracted at these nodes, the offset points should satisfy the condition that the coordinate increment direction changes or the adjacent coordinate increment is negative, then the coordinates between all offset points are combined, the adjacent offset points are connected in ascending order of number, the distance distribution of adjacent two points in horizontal and vertical directions is analyzed, if one of the horizontal direction difference and the vertical direction difference between the two points is zero, or the ratio of the two is an integer multiple of 1, it is considered that the two points have a spatial connection relationship, for example, in the example, if the offset points M105 and M106 are spaced 2.0 meters apart in the X direction and 0.0 meters apart in the Y direction, they are identified as continuous connection points, the connectivity of all offset points is judged in this way, and each offset path sequence with continuous connectivity is recorded in turn, the point position number in the path sequence is output as an index to form the unique positioning sequence of each deformation trend segment in the layer, and finally the continuous response segment positioning index is obtained.

[0086] S403: Based on the continuous response segment positioning index, the numbered and coordinate areas in the layer are matched, the path response sequence with continuous change form under the same number is screened, the points that do not form periodic segments are eliminated, the index position and response direction information corresponding to the path sequence are aggregated, and the continuous abnormal trend distribution content is obtained;

[0087] First, retrieve the layer file one by one according to the order of the index set, extract the coordinate point range corresponding to each number, and determine its spatial position in the monitoring area and the response path number group to which the number belongs. Multiple coordinate segments belonging to the same path number are classified as a trajectory response sequence. Then, according to the time sequence, extract the displacement or shear deformation monitoring value in the response sequence. For each sequence, apply the continuity judgment process, that is, take three consecutive points as the judgment unit. If the change trend of the middle point in the unit and the adjacent two points show the same direction of monotonic change, it is recorded as a continuous trend segment. For example, the value corresponding to number P304 is 1.2, 1.5, and 1.8. It can be judged that the trend is increasing and belongs to the continuous change form path. If the trend direction switches repeatedly within three points, it is considered as a non-continuous segment, and the point number in the judgment sequence is removed. Further, in the continuous trend path obtained, identify whether it has periodic characteristics between adjacent segments. The judgment logic is: calculate the response amplitude difference between trend segments and the number of continuous segments. If the amplitude difference fluctuation between different segments does not exceed the set threshold and the point number error in the trend period does not exceed the allowed range, it is considered that the path has periodic form. Otherwise, the segment number point is also removed. After removing all points without periodic characteristics, merge the remaining effective points by path number. Through the coordinate backtracking of the number position, the spatial position of the layer is obtained, and the response trend direction of each point is counted. If more than 70% of the points in a path segment have consistent trend direction vectors, that is, they are all rising or falling, the segment is assigned the "consistent direction" attribute. Finally, the number index of each path segment and its direction trend value are combined to form a number and response direction pairing sequence, and the continuous abnormal trend distribution content is obtained.

[0088] Please refer to Figure 6 The specific steps of S5 are:

[0089] S501: Based on the continuous abnormal trend distribution content, extract the section with concentrated change amplitude in the shear deformation rate sequence, call the index corresponding to the monitoring time sequence, analyze the continuity of adjacent data points in the time axis direction, and filter the segments with direction maintaining state to obtain the shear rate continuous section index.

[0090] First, relying on the path paragraph and coordinate sequence labeled in the previous stage, the corresponding shear deformation rate sequence is retrieved from each paragraph, the monitoring point number in each paragraph is corresponded to the rate value point recorded in the rate curve, the value segment with obvious change amplitude jump is extracted by point-by-point traversal, in the execution process, the monitoring point number is arranged in ascending order, the amplitude difference operation is performed with a sliding window of five consecutive points, the change value of the current point and the previous period is calculated, if the continuous three difference values are greater than the preset change threshold, such as 0.08 mm / h, it is marked as the area with obvious change, in actual application, the shear rate of numbers P211~P215 is 0.10, 0.21, 0.34, 0.43, 0.51 respectively, which can be judged as the area with obvious rate increasing trend, then the monitoring time axis index where the data segment is located is located, the index numbers of adjacent points are extracted in chronological order, the time stamps are read in turn and whether the adjacent time intervals are equal is calculated, the continuity is judged by the following method: if the time difference remains fixed within the allowable error range, such as the time interval is set to 3 hours, the error is allowed ±0.2 hours, the current paragraph is continuous in time, otherwise the part of the data segment is excluded from the sequence, after the continuity is passed, the rate change direction of adjacent monitoring points is further checked, the difference between the two adjacent points is used as the basis for judgment, if the three consecutive difference values are all positive or all negative, it is recorded as the direction maintaining state, otherwise it is marked as direction reversal and not included in the subsequent sequence, for the numbered point paragraph which meets the three conditions of amplitude significant jump, time continuity and direction consistency at the same time, the index number set corresponding to it in the original data set is generated as the labeling output, and finally the shear rate continuous segment index is obtained.

[0091] S502: Based on the shear rate continuous segment index, the start and end time points of the segment are matched with the construction time sequence node position in the layer, the response delay distribution position points are analyzed, the segments with time difference structure existing in the previous sequence are screened, and the construction response time delay path set is obtained.

[0092] First, the start and end indexes of each numbered paragraph are extracted from the obtained continuation section, and the monitoring time corresponding to the indexes is retrieved. The start and end time points of each continuation segment are read in sequence index. Taking numbered P110 as an example, if the start index is 215 and the end index is 228, the corresponding times are the 45th period and the 51st period, respectively. The duration of the continuation segment is 6 unit periods. Then, the time period is compared with the construction time sequence node list recorded in the layer. The comparison content is segmented and positioned according to the corresponding relationship between the construction stage number and the spatial coordinates of the monitoring point. The coordinate range covered by each construction number in the layer is extracted by table lookup, and the corresponding coordinates of the continuation segment are matched with the coordinate interval of the construction drawing. The matching method is to judge whether the monitoring point belongs to the coordinate boundary range corresponding to the specified construction number. If there is a position falling into but the time does not coincide, it is marked as a response delay area. Continue to extract the start time of the segment and the start time of the construction number to which it belongs to calculate the difference. If the difference exceeds the preset response delay threshold, such as 2 unit periods, the current segment number is recorded as a response delay segment. This operation is performed for each detection point segment to obtain a set of segments with time offset phenomena. Then, all monitoring points marked as delay segments are summarized and intersected with the original path segment to extract the numbered chain that still maintains trajectory continuity as the subsequent analysis object to obtain the construction response time delay path set.

[0093] S503: Call the construction response time delay path set, aggregate the path corresponding spatial coordinate point sequence, extract the path segment with consistent direction according to coordinate sorting, exclude the segment with direction jump, get the rock slope anchoring deformation trend prediction result according to the trajectory continuity and position trend maintaining relationship;

[0094] First, all path segments on the coordinate point set are extracted from the delay path set according to the number, the spatial position coordinates of the monitoring points in each segment are listed according to the path number, and these point sequence is sorted according to the longitudinal coordinate priority, horizontal coordinate sequence, so that the arrangement order is consistent with the actual space trend. After sorting, the direction extension consistency judgment process is entered, for every two vectors composed of three consecutive points in each path segment, the included angle of the two vectors in two-dimensional space is calculated, if the included angle value is not greater than 15 degrees, it is judged as direction continuation, otherwise it is judged as jump. Taking path P503 as an example, the point sequence is A (102.1, 208.3), B (103.5, 209.2), C (105.4, 212.7), the angle of AB vector and BC vector is compared, if the angle is 9 degrees, the three points can be regarded as direction continuation, if the angle is 24 degrees, it is regarded as direction jump. The angle judgment standard 15 degrees is a preset angle threshold, which is selected based on the conventional amplitude change of displacement change in structure construction process. The selection method refers to the angle change characteristics in the relatively stable section of continuous shear rate change in historical data. The jump section is excluded from the path used for trend fitting. Then the trajectory continuity of each direction continuation path segment selected is judged, the judgment standard is that the distance between any two adjacent points is not more than the set coordinate interval threshold, for example, set to 3 meters. If there is a point distance in the path that exceeds this value, it is determined that the trajectory is discontinuous, and this section does not participate in trend extraction. Then the trend extension analysis is carried out on all coordinates in the continuous direction maintaining paragraph, the linear fitting is carried out on the same direction segment to extract the direction trend of the whole path. Taking number P703 as an example, the fitting result slope is 0.75, indicating that the overall displacement trend develops in the direction of approximately 45 degrees. Combined with the segment information with trajectory continuity and direction stability, the prediction trend line is constructed, and the rock slope anchoring deformation trend prediction result is obtained.

[0095] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A rock high slope excavation anchoring deformation prediction method based on artificial intelligence, characterized in that, The method comprises the following steps: S1: Obtain a profile density map, a lithology division map and a construction progress map, analyze rock mass volume changes, extract quality differences, align structure positions according to coordinates, track gravity center shifts, and obtain slope structure migration path change characteristics; S2: Based on the slope structure migration path change characteristics, extract an anchoring layout map and a stress monitoring map, analyze anchoring rod axial force change trends, search for abnormal points, judge uneven area positions according to displacement response directions, and obtain stress abnormal distribution area position corresponding relationships; S3: Based on the stress abnormal distribution area position corresponding relationships, extract cross graph lines, judge direction consistency, connect continuous track points, analyze angle and distance changes, and obtain offset path and stress boundary associated paragraphs; S4: Based on the offset path and stress boundary associated paragraphs, read shear deformation, joint inclination and crack characteristics, compare response directions, screen change areas, extract layer positions, and obtain continuous abnormal trend distribution content; S5: Based on the continuous abnormal trend distribution content, extract deformation rate change areas, analyze direction continuity, judge relationships with construction times, and obtain rock slope anchoring deformation trend prediction results.

2. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The slope structure migration path change characteristics include rock mass volume change trends, rock mass quality spatial differences and slope gravity center shift trajectories. The stress abnormal distribution area position corresponding relationships include non-uniform section positions, layer number corresponding areas, stress abnormal points and displacement direction response relationships. The offset path and stress boundary associated paragraphs include trajectory spatial direction continuous consistent points, layer spatial angle change trends and boundary trend overlapping paragraphs. The continuous abnormal trend distribution content includes shear deformation abnormal profiles, joint inclination dramatic change areas and fracture opening and closing fluctuation concentrated areas. The rock slope anchoring deformation trend prediction results include shear deformation rate change concentrated sections, construction time sequence and response change order of precedence, and spatial direction extension trend positions.

3. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The gravity center shift refers to the spatial migration of the overall mass center position of the rock mass structure caused by changes in rock mass volume and density during high slope excavation construction. The anchoring rod axial force change trend refers to the changes in the axial force data recorded by the differential anchoring rod along the time axis during the anchoring layout process.

4. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The abnormal point refers to a point that appears different from the surrounding monitoring values during monitoring, which is manifested as a change in displacement direction, a stress mutation, an abnormal rate, and represents early signs of potential risks and structural instability. The uneven area position refers to a position area in the anchoring area where the structure stress and displacement response direction change suddenly, indicating that the stress distribution in the area is uneven and there is a potential structural stability hazard.

5. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain a profile density map, a lithology division map and a construction progress map, extract rock mass volume and density values in the stage profile coordinate range, configure mass data frames in the corresponding areas, compare quality distribution changes in different stages, extract regional quality states over time, and obtain rock mass stage quality evolution sequences. S102: Based on the stage quality evolution sequence of the rock mass, the stage boundary coordinate points are extracted, the spatial positions of the same numbered points are compared, the direction changes are judged, the trajectory data of the position continuous offset are extracted, the paths are divided according to the direction change trend, and a set of structure position direction migration paths are obtained; S103: The set of structure position direction migration paths is called, the position of the center of gravity point in the path is searched, whether the transfer direction and the path trend are continuous is compared, the transfer segments with consistent direction are arranged in the order of coordinates as continuous paths, and the change characteristics of the slope structure migration path are obtained.

6. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The specific steps of S2 are: S201: Based on the change characteristics of the slope structure migration path, the layout position and the axial force time sequence change information corresponding to each group of anchor rods in the anchor layout graph and the stress monitoring data graph are extracted, the change trend is extracted according to the layout number in turn, the number section continuously presenting linear trend turning is screened, and an axial force change trend marking sequence is obtained; S202: Based on the axial force change trend marking sequence, the coordinate position of the numbered point is extracted, and the displacement response direction is compared with the adjacent region, whether the direction is consistent is judged, the layout point with direction deviation is screened, the spatial distribution information is extracted, and a direction response offset coordinate set is obtained; S203: Based on the direction response offset coordinate set, the index position in the layout graph layer is located, the coordinate range of the adjacent numbered region in the same layer is extracted, the continuous regions are merged into the same response region in order, the layer coordinates corresponding to the region position are output, and a stress abnormal distribution area corresponding relationship is obtained.

7. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The specific steps of S3 are: S301: Based on the stress abnormal distribution area corresponding relationship, the intersection region of the slope structure trajectory and the stress boundary line segment in the layer is extracted, the structure offset direction and the boundary extension direction vector at the intersection point are compared, whether the direction consistency is judged, the intersection segment with consistent direction is extracted, and a direction consistent intersection paragraph set is obtained; S302: Based on the direction consistent intersection paragraph set, the continuous trajectory points on the layer are extracted according to the coordinates, the trajectory nodes continuously keeping consistent in the spatial distribution direction are screened, the point positions before and after the direction deflection of the trajectory line segment are compared, the line segment without direction deflection is identified, and a spatial direction continuous trajectory set is obtained; S303: The spatial angle change and distance distribution range of the line segment presented in the layer are intercepted by calling the spatial direction continuous trajectory set, the segment consistent with the structure offset direction and the stress boundary trend is screened, the trajectory number and the layer coordinate range are output, and an offset path and stress boundary associated paragraph is obtained.

8. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The specific steps of S4 are: S401: Based on the offset path and stress boundary associated paragraph, the shear deformation sequence of the monitoring point, the joint inclination change range and the crack opening and closing state are extracted along the path direction, the direction scalar of the adjacent monitoring point in the parameter sequence is analyzed, the continuous response segment with consistent direction is screened, and a direction unified deformation segment set is obtained; S402: Based on the direction uniform deformation segment set, identify the segment where the layer coordinate section is located, extract the monitoring curve fluctuation pattern of the adjacent area, extract the response path offset position point at the continuous trend change node, analyze the spatial connection relationship between the offset points, and obtain the continuous response segment positioning index; S403: Based on the continuous response segment positioning index, match the number and coordinate area in the layer, filter the path response sequence with continuous change pattern under the same number, eliminate points that do not form periodic segments, aggregate the corresponding index position and response direction information in the path sequence, and obtain the continuous abnormal trend distribution content.

9. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 8, characterized in that, The process of filtering the path response sequence with continuous change pattern under the same number is: extracting the layer number and corresponding coordinate area included in the continuous response segment positioning index, comparing the response direction of the monitoring points in the path with the same number point by point in order, identifying the continuity feature of the response direction change between adjacent points, and judging whether it constitutes a continuous path segment according to the trend of direction retention and gradual change; The process of eliminating points that do not form periodic segments is: identifying the response path segment, repeatedly comparing the direction response change of each point in the path sequence, judging whether there is regular direction transformation, and eliminating the corresponding point from the sequence when the path lacks the continuity of the direction between adjacent points and there is random jump; The process of aggregating the corresponding index position and response direction information in the path sequence is: according to the continuous points retained in the path, corresponding to the spatial index and response direction extracted in order according to the number, comparing the change state of the response direction, analyzing the response paragraph with consistent direction, and corresponding to the spatial position sequence and direction information.

10. The artificial intelligence-based rock high slope excavation anchoring deformation prediction method according to claim 1, characterized in that, The specific steps of S5 are: S501: Based on the continuous abnormal trend distribution content, extract the segment with change amplitude set in the shear deformation rate sequence, call the corresponding index of the monitoring time sequence, analyze the continuity of adjacent data points in the time axis direction, filter the segments with direction retention state, and obtain the shear rate continuous segment index; S502: Based on the shear rate continuous segment index, match the start and end time points of the segment with the construction time sequence node position in the layer, analyze the response delay distribution position point, filter the segments with time difference structure from the previous segment, and obtain the construction response time delay path set; S503: Call the construction response time delay path set, aggregate the path corresponding spatial coordinate point sequence, extract the path segment with consistent direction according to coordinate sorting, exclude the segments with direction jump, and obtain the rock slope anchoring deformation trend prediction result according to the trajectory continuity and position trend retention relationship.

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