A mine roadway anchoring support member into rock structure anti-collision system based on blind area deduction and automatic mining equipment

Abstract

The application discloses a mine roadway anchoring support component into rock structure anti-collision system based on blind area deduction and automatic mining equipment, and relates to the field of mine intelligent equipment safety control. The system comprises a sensing and measuring device, an actuator and an industrial control computer. The industrial control computer is internally arranged with multiple logic modules in a data link one-way step-by-step cascade mode. The logic modules successively comprise a sensing enhancement module, a structure analysis module, a blind area deduction module and a planning control module. The sensing enhancement module is used for constructing a continuous space structure representation. The structure analysis module is used for separating a rock wall background from an exposed part of the anchoring support component and establishing a space geometric constraint relationship. The blind area deduction module is used for completing the space and constructing a probabilistic model containing a probabilistic risk envelope area. The planning control module is used for constructing a unified collision risk field and planning a collision-free motion trajectory. The application has stable safety protection capability in a limited visual distance and a diffuse medium environment.

Description

Technical Field

[0001] This invention relates to the field of safety control of intelligent mining equipment, and in particular to a rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation and automated mining equipment. Background Technology

[0002] During mine roadway excavation and support operations, the surrounding rock is typically reinforced using support components such as anchor bolts or anchor cables. These components generally exhibit a structure where one part is exposed and the other part is embedded within the rock mass. The embedded section bears the main load-bearing load, but it is difficult to directly observe in the actual working environment.

[0003] At the same time, the underground environment generally has problems such as high dust concentration, poor lighting conditions and narrow space. Laser or vision-based perception systems are easily affected by diffusion media in such environments, resulting in increased noise and degradation of structural features in point cloud data, making it difficult to stably distinguish between slender support components and background rock mass.

[0004] Existing collision avoidance technologies mainly rely on geometric modeling and distance calculation of visible obstacles, which is essentially a passive obstacle avoidance method based on current observation. For anchored support components, since their key structural parts are located inside the rock mass, traditional methods can only model the exposed sections and cannot reflect their actual spatial occupancy, thus posing a potential collision risk during equipment operation.

[0005] Furthermore, under conditions of dust obstruction or sensor performance degradation, the sensing system may become partially or even completely "blinded." In such cases, collision avoidance strategies based on real-time perception will lose effective input, further exacerbating safety hazards.

[0006] Therefore, how to achieve stable identification of anchored support components in complex mining environments and reasonably infer their rock penetration range under unobservable conditions, thereby realizing forward-looking safety protection and control, is an urgent technical problem to be solved. Summary of the Invention

[0007] The purpose of this invention is to provide a collision prevention system for the rock-entry structure of anchored support components in mine roadways based on blind zone extrapolation, as well as automated mining equipment. This addresses the problem mentioned in the background art that traditional collision prevention technologies cannot reflect the actual space occupancy range and thus pose serious collision hazards during mine roadway excavation and support operations due to strong dust interference, weak visual characteristics of support components, and the physical unobservable nature of the anchored rock-entry section.

[0008] To achieve the above objectives, this invention provides a mine roadway anchorage support component rock-entry anti-collision system based on blind zone simulation, comprising sensing and measuring equipment, an actuator, and an industrial control computer. The industrial control computer deploys multiple logic modules with unidirectional, cascaded data links. These logic modules sequentially include: The perception enhancement module is used to perform multi-source fusion and densification reconstruction on the raw environmental data acquired by the perception and measurement equipment, and to construct a continuous spatial structure representation in a dust-covered environment. The structural analysis module is used to separate the exposed parts of the rock wall background and anchor support components from the spatial structural representation based on geometric or semantic features, and to establish a deterministic geometric model between the exposed parts and the rock wall. The blind zone deduction module is used to spatially complete the invisible structure within a finite anchorage length range, starting from the anchorage intrusion point and along the axis of the component, based on spatial geometric constraints and prior information on the finite length of the anchorage support component. It also introduces an uncertainty diffusion model that varies with the penetration depth to obtain a probabilistic risk envelope region that extends axially and gradually diffuses radially, thus constructing a probabilistic model. The planning and control module is used to merge the deterministic geometric model of the exposed part with the probabilistic model of the probabilistic risk envelope region to construct a unified collision risk field, and to plan the collision-free motion trajectory of the actuator based on the collision risk field.

[0009] Preferably, the industrial control computer is further equipped with a sensor blinding detection mechanism, which specifically executes the following logic: The stability of the local structure of the point cloud is continuously evaluated. When the proportion of a region exceeding the preset threshold changes from having obvious structural features to having no principal direction distribution of the point cloud within a continuous time window, it is determined that the current sensing data lacks effective geometric constraints and the sensor is in a blind or severely occluded state. In this state, the collision avoidance decision output is suspended and a braking control signal is sent to the actuator.

[0010] Preferably, the perception enhancement module achieves cross-frame point cloud fusion through multi-frame spatial coordinate unification and motion compensation to form a locally denser point cloud. The multi-frame fusion process is as follows: Using inertial measurement units and pose estimation results, the spatial transformation relationship between consecutive time frames is calculated, and the point clouds of each historical frame are uniformly mapped to the current reference coordinate system; spatial consistency constraints are applied to the repeatedly observed areas, and weighted updates are performed; areas with point density below a preset threshold or insufficient structural continuity are identified as potential observation missing areas and structural candidate points are extracted.

[0011] Preferably, the structural analysis module separates the rock wall from the anchored support components through local anisotropy analysis, and the separation judgment logic is as follows: A three-dimensional covariance description is constructed within the local neighborhood of the point cloud. If the point set expands significantly in two directions and converges in another direction, it is determined to be a planar structure and included in the rock wall point set. If the point set shows significant extension in a single direction, it is determined to be a linear structure and included in the anchor support component point set. If the point set has no significant dominant trend in any direction, it is determined to be invalid data and is removed.

[0012] Preferably, the spatial geometric constraints established by the structural analysis module include: Axis fitting is performed on the point set of anchor support components to obtain the axis direction vector; a local planar model is constructed by combining the point set of the rock wall; the spatial intersection point is solved by combining the axis equation of the components with the planar equation of the rock wall; if the intersection point exists and is located within the effective structural range of the rock wall, the intersection point is determined as the anchor intrusion point.

[0013] Preferably, the blind zone estimation module estimates the risk space range using a probability distribution, and the estimation logic includes: Based on the prior value of the total length of the anchoring component and the length of the exposed section, the internal anchoring length of the rock mass is calculated; starting from the anchoring intrusion point, it extends along the axis of the component, and a radial position variance function that varies with the penetration depth is introduced to construct a spatial credibility weight model; spatial points with weights higher than the preset safety threshold are extracted to form a three-dimensional probabilistic risk envelope region that extends along the axis and gradually diffuses radially.

[0014] Preferably, the blind zone extrapolation module introduces an uncertainty diffusion model that varies with depth. The radial position variance function of the uncertainty diffusion model is set as a quadratic or exponential function of depth to characterize the nonlinear growth of uncertainty caused by borehole offset and rock mass stress disturbance with anchoring depth.

[0015] Preferably, the risk space range deduced by the blind zone deduction module is an inverted cone-shaped probability envelope region that extends along the axis of the anchoring member and whose radial cross-section gradually increases with depth. The risk weight of each spatial point in this region decays in a Gaussian distribution along the radial direction.

[0016] Preferably, the planning and control module performs trajectory optimization based on the collision risk field, and the specific algorithm includes: A joint objective optimization function is established, which includes collision risk cost, trajectory adjustment energy consumption cost, and drilling position deviation cost. The optimal drilling trajectory parameters that minimize the joint objective optimization function are solved, and the inverse kinematics of the optimal drilling trajectory parameters are analyzed into lifting, rotating, and telescopic drive commands for the drill guide rail. During the drilling process, the rotational degree of freedom is locked to keep the drilling angle constant.

[0017] An automated mining equipment includes a chassis, a multi-degree-of-freedom operating mechanism, and a control and communication system. It is equipped with a mine roadway anchor support component rock structure anti-collision system based on blind zone simulation as described in any one of claims 1 to 9. This system is used to achieve predictive safety protection based on blind zone simulation of anchor support components under conditions of dust obstruction, limited visibility, and incomplete structural observation.

[0018] Therefore, the present invention employs the above-mentioned anti-collision system for rock-entry structures of mine roadway anchorage support components based on blind zone deduction and automated mining equipment, which has the following beneficial effects: (1) This invention achieves efficient physical stripping and targeted target extraction of high-concentration dispersed media in mines at the mathematical principle level through the anisotropy analysis of the three-dimensional spatial covariance tensor, solving the problem of component feature extraction under limited line of sight.

[0019] (2) This invention is the first to combine the finite length prior of the anchoring component with precise linear and surface geometric constraints (anchoring intrusion point and axial direction), and introduces an uncertainty diffusion model that increases with depth to perform probabilistic extrapolation on the invisible rock section, forming an inverted cone-shaped risk envelope region. This model breaks through the fundamental limitation of traditional passive obstacle avoidance in handling blind spots.

[0020] (3) This invention optimizes collision protection from the bottom-level reactive braking to the pre-emptive global prediction and planning level by optimizing the joint integral cost of global deterministic structure and probabilistic risk space. While ensuring the absolute safety of continuous operation of multiple rigid bodies, it achieves the best overall balance between spatial execution efficiency and energy consumption cost.

[0021] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0022] Figure 1 This is a system module connection and data flow diagram of an embodiment of a mine roadway anchoring support component rock-entry structure anti-collision system and automated mining equipment based on blind zone simulation of the present invention. Figure 2 This is a schematic diagram of the spatial morphology of the probability risk envelope region in the blind zone simulation of a mine roadway anchorage support component rock-entry structure anti-collision system and automated mining equipment embodiment of the present invention. Detailed Implementation

[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] Example Please see Figures 1-2 The present invention provides a rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation, including sensing and measuring equipment, actuators and industrial control computer.

[0026] Sensing and measurement equipment includes multiple full-view non-repeating scanning LiDARs and a high-frequency inertial measurement unit (IMU). The LiDARs are mounted on a vibration-damping bracket on the drill bit box of the drilling rig to acquire 3D point clouds of the tunnel environment; the IMU is mounted at the end of the guide rail to measure the angular velocity and acceleration of the guide rail. The LiDARs are connected to the industrial control computer via a gigabit Ethernet interface, and the IMU data is connected to the drilling rig PLC via an SPI interface before being transmitted to the industrial control computer.

[0027] The actuator is a three-degree-of-freedom drill bit guide, comprising a lifting hydraulic cylinder, a rotary servo motor, and a telescopic feed cylinder. The lifting hydraulic cylinder controls the vertical lifting of the drill bit, the rotary servo motor adjusts the drilling azimuth angle, and the telescopic feed cylinder controls the depth of feed into the drill bit. All three are connected to an industrial control computer via a CAN bus. During drilling, the three degrees of freedom are locked to ensure the drilling angle remains constant.

[0028] Industrial control computer: Built on a multi-core heterogeneous processor, deployed in the explosion-proof control compartment of mining equipment, running a real-time operating system. The industrial control computer contains four sequentially cascaded logical modules: a perception enhancement module, a structure analysis module, a blind zone deduction module, and a planning and control module.

[0029] The perception enhancement module is used to achieve dense reconstruction through multi-frame point cloud fusion. In this embodiment, the lidar outputs the original point cloud frames at a preset frequency, and the IMU outputs pose data at a higher frequency. After receiving this data, the perception enhancement module first uses the IMU data for motion compensation, uniformly mapping the point clouds of each historical frame to the current reference coordinate system. Let the first... Any point in the frame point cloud is , In a three-dimensional real space, the rotation matrix of this frame relative to the current reference coordinate system is: The translation vector is The mapped coordinates are: ; The perception enhancement module maps all point clouds from a predetermined number of historical frames to the current reference coordinate system and then performs cumulative overlay. For repeatedly observed spatial regions (divided according to a predetermined voxel side length), a weighted update is used: assuming that the accumulated data within a certain voxel... There are points, and their average coordinates are [number] points. The newly observed point is The updated mean is: ; The perception enhancement module outputs a locally dense point cloud and transmits it to the structure analysis module.

[0030] The structural analysis module is used to receive locally densed point clouds, separate the rock wall from the anchoring components, and establish spatial geometric constraints.

[0031] The structural analysis module first separates the rock face from the structural components: for any point in the point cloud, it searches for a set of neighboring points within a preset radius. Construct the three-dimensional covariance matrix: ; in, The total number of points within the searched neighborhood. This is an index variable used to iterate through each point in the neighborhood point set. This is a transpose.

[0032] right Perform eigenvalue decomposition to obtain eigenvalues ​​arranged in descending order. Calculate the dispersion Flatness linearity The classification rules are as follows: If If the dust concentration exceeds the preset dust threshold, it is identified as a dust point and removed; otherwise, if... and If the value is greater than a preset plane threshold, it is determined to be a rock wall point and added to the rock wall point set. Otherwise, if and If the value is greater than the preset linear threshold, it is determined to be an anchor support component point and added to the component point set. .

[0033] The structural analysis module then performs spatial geometric constraint establishment: for the component point set A three-dimensional straight line is fitted using a random sampling consensus algorithm to obtain the unit vector of the axis direction. and a point on the axis Point set for the rock face The plane is fitted using the least squares method to obtain the plane normal vector. (Unit vector) and a point on the plane Find the intersection point between the axis of the structural member and the plane of the rock wall. Let the intersection point be... Substitute into the plane equation , obtain parameters : ; If the denominator If the value is less than the preset minimum, the component is deemed invalid and processing is terminated. Otherwise, the anchoring intrusion point is... Validity check: intersection point It should be located at the rock wall point set Inside the convex hull, and penetrating the angle It should meet the preset angle range. After verification, determine the axis direction. Point inwards from the rock mass and calculate the length of the exposed section. (From the anchoring intrusion point) (Euclidean distance to the exposed end of the component). Also, based on the length of the exposed section. and the preset component radius Construct a cylindrical deterministic geometric model of the exposed anchoring component: the axis is... The starting point is The destination is , radius is The structure parsing module will , , The exposed cylindrical component model is transmitted to the blind zone simulation module and the planning control module.

[0034] The blind zone deduction module is the core module of this invention, used to perform probabilistic deduction of invisible anchorage sections. The blind zone deduction module receives... , , And the system's preset total length of anchoring components prior. .

[0035] The blind zone simulation module first calculates the anchorage length: ; like If the length is less than or equal to the preset minimum length, no further deduction is required.

[0036] The blind zone deduction module then performs axis parameterization: using the anchorage intrusion point Starting from the axis, along the direction of the axis Extending into the rock mass, establish a parametric straight line: , ; in, The depth is along the axis.

[0037] The blind zone deduction module introduces an uncertainty diffusion model: defining the radial position variance function: ; in, This is the initial positioning error. This is the diffusion coefficient (preset based on rock mass type). (Note: The last part is a typographical notation and doesn't need a direct translation.) .

[0038] The blind zone inference module constructs a spatial credibility weighting function: for any spatial point inside the rock mass Calculate the projection depth: ; Radial distance: ; Weight: .

[0039] The blind spot simulation module constructs a probabilistic risk envelope region and sets a safety threshold. All satisfied The spatial points constitute the probabilistic risk envelope region. This region has a depth... The radial radius at that location is ,because Follow As the area increases, it becomes inverted cone-shaped. The blind zone extrapolation module discretizes the internal region of the rock mass into an octagonal voxel map. Each voxel... With preset side length ,volume voxel center point weight Only retain The voxels. The blind spot deduction module transmits the octree weight map to the planning and control module.

[0040] The planning and control module is used to receive the geometric model of the deterministic entity and the probabilistic risk envelope region output by the blind zone inference module, generate the collision-free optimal drilling trajectory, and convert it into actuator drive commands.

[0041] The planning and control module first constructs a three-dimensional weighted topological field: the voxels occupied by deterministic entities (including exposed anchoring components, guide rail bodies, and modeled rock walls) are forcibly weighted. The voxels within the probability risk envelope region are weighted according to the values ​​calculated by the blind zone inference module. The remaining free space voxel weights are set to... .

[0042] The planning and control module samples candidate drilling trajectories: Input target hole coordinates Ideal drilling direction unit vector Drilling depth Within the allowable deviation range, random sampling or grid search methods are used to generate [the data]. Candidate trajectories ( Each trajectory includes entry points. Drilling direction unit vector feed depth .

[0043] The planning and control module establishes the physical motion envelope: for the trajectory The motion envelope is simplified to a cylinder, and the radius of the drill rod is denoted as . Then the envelope of a cylinder is defined as: ; The planning and control module calculates the collision risk cost: in the octree voxel map, it identifies all objects that overlap with the cylinder envelope. The set of intersecting voxels is denoted as . ,but .

[0044] The planning and control module calculates the energy consumption cost of trajectory adjustment: Let the current actuator pose be (lifting height). Rotation angle telescopic length ), trajectory The corresponding target pose is The increment is: , , ; The energy cost is: ; in, This is the preset unit energy consumption coefficient.

[0045] The planning and control module calculates the cost of the drilling position deviation as follows: ; in, These are preset weighting coefficients.

[0046] The planning and control module performs joint optimization: Constructing a joint cost function: ; in, The preset weighting coefficients are used, with safety as the highest priority. The optimization objective is... To reduce computational load, the cost of collision risk can be eliminated first. For trajectories exceeding a preset safety threshold, a complete calculation is then performed on the remaining trajectories. And take the minimum value.

[0047] The planning and control module performs inverse kinematics analysis and issues commands: determining the entry point of the optimal trajectory. and drilling direction Inverse kinematics analysis yields the target value of the actuator: lifting height. Rotation angle Telescopic length It is sent to the actuator controller via the CAN bus.

[0048] The working principle of this embodiment is as follows: During the work preparation phase, the operator inputs the coordinates of the target drilling area through a human-machine interface. Ideal drilling direction Priority of total length of anchorage components .

[0049] After the system starts up, the lidar and IMU continuously scan at a preset frequency. The perception enhancement module fuses the most recent multi-frame point clouds to generate a locally denser point cloud, which is then transmitted to the structure analysis module.

[0050] The structural analysis module separates the rock face from the anchoring components and calculates the anchoring intrusion point. axial direction Length of exposed section The exposed component cylindrical model is constructed and transmitted to the blind zone simulation module and the planning control module.

[0051] Blind spot simulation module based on and calculate Construct an inverted cone-shaped probability risk envelope region, generate an octree weight map, and transmit it to the planning and control module.

[0052] The planning and control module samples candidate trajectories and calculates the joint cost. It outputs the optimal trajectory parameters and converts the inverse kinematics into actuator commands.

[0053] The actuator moves to the drilling point according to the instruction, locks the rotational degree of freedom, and completes the drilling by telescopic feed.

[0054] The above steps of perception, analysis, deduction, planning, and execution are continuously cycled during the operation.

[0055] The present invention also provides an automated mining equipment, including a chassis, a multi-degree-of-freedom operating mechanism and a control and communication system, and is equipped with a mine roadway anchor support component rock structure anti-collision system based on blind zone simulation, which is used to achieve predictive safety protection based on blind zone simulation of anchor support components under conditions of dust obstruction, limited visibility and incomplete structural observation.

[0056] Therefore, this invention employs a mine roadway anchorage support component rock-entry anti-collision system and automated mining equipment based on blind zone extrapolation. Stable separation of the rock wall and anchorage components is achieved through point cloud densification and spatial structural feature discrimination. Based on this, the component axis and anchorage intrusion location are determined by combining the rock wall constraint relationship. Furthermore, based on the prior anchorage length and the spatial uncertainty diffusion law, a restricted extrapolation is performed on the invisible rock-entry section to form a probabilistic risk envelope region. Finally, by integrating the deterministic structure and probabilistic risk space, a unified risk field is constructed, and predictive anti-collision control based on risk evolution is achieved, maintaining stable safety protection capabilities even in environments with limited visibility and diffuse media.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A mine roadway anchorage support component rock-entry anti-collision system based on blind zone simulation, comprising sensing and measuring equipment, an actuator, and an industrial control computer, characterized in that, The industrial control computer has multiple logical modules deployed within it, connected in a unidirectional, cascaded manner via data links. These logical modules sequentially include: The perception enhancement module is used to perform multi-source fusion and densification reconstruction on the raw environmental data acquired by the perception and measurement equipment, and to construct a continuous spatial structure representation in a dust-covered environment. The structural analysis module is used to separate the exposed parts of the rock wall background and anchor support components from the spatial structural representation based on geometric or semantic features, and to establish a deterministic geometric model between the exposed parts and the rock wall. The blind zone deduction module is used to spatially complete the invisible structure within a finite anchorage length range, starting from the anchorage intrusion point and along the axis of the component, based on spatial geometric constraints and prior information on the finite length of the anchorage support component. It also introduces an uncertainty diffusion model that varies with the penetration depth to obtain a probabilistic risk envelope region that extends axially and gradually diffuses radially, thus constructing a probabilistic model. The planning and control module is used to merge the deterministic geometric model of the exposed part with the probabilistic model of the probabilistic risk envelope region to construct a unified collision risk field, and to plan the collision-free motion trajectory of the actuator based on the collision risk field.

2. The anti-collision system for rock-entry structures of mine roadway anchorage support components based on blind zone extrapolation as described in claim 1, characterized in that, The industrial control computer is also equipped with a sensor blinding detection mechanism, which specifically executes the following logic: The stability of the local structure of the point cloud is continuously evaluated. When the proportion of a region exceeding the preset threshold changes from having obvious structural features to having no principal direction distribution of the point cloud within a continuous time window, it is determined that the current sensing data lacks effective geometric constraints and the sensor is in a blind or severely occluded state. In this state, the collision avoidance decision output is suspended and a braking control signal is sent to the actuator.

3. The anti-collision system for rock-entry structures of mine roadway anchorage support components based on blind zone extrapolation as described in claim 1, characterized in that, The perception enhancement module achieves cross-frame point cloud fusion through multi-frame spatial coordinate unification and motion compensation to form a locally denser point cloud. The multi-frame fusion process is as follows: Using inertial measurement units and pose estimation results, the spatial transformation relationship between consecutive time frames is calculated, and the point clouds of each historical frame are uniformly mapped to the current reference coordinate system; spatial consistency constraints are applied to the repeatedly observed areas, and weighted updates are performed; areas with point density below a preset threshold or insufficient structural continuity are identified as potential observation missing areas and structural candidate points are extracted.

4. The anti-collision system for rock-entry structures of mine roadway anchorage support components based on blind zone extrapolation as described in claim 1, characterized in that, The structural analysis module separates the rock wall from the anchored support components through local anisotropy analysis. The separation judgment logic is as follows: A three-dimensional covariance description is constructed within the local neighborhood of the point cloud. If the point set expands significantly in two directions and converges in another direction, it is determined to be a planar structure and is included in the rock wall point set; if the point set shows significant extension in a single direction, it is determined to be a linear structure and is included in the anchor support component point set. If the point set does not show a significant dominant trend in any direction, it is considered invalid data and is removed.

5. A rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation as described in claim 1, characterized in that, The spatial geometric constraints established by the structural analysis module include: Axis fitting is performed on the point set of anchor support components to obtain the axis direction vector; a local planar model is constructed by combining the point set of the rock wall; the spatial intersection point is solved by combining the axis equation of the components with the planar equation of the rock wall; if the intersection point exists and is located within the effective structural range of the rock wall, the intersection point is determined as the anchor intrusion point.

6. A rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation according to claim 1, characterized in that, The blind zone simulation module simulates the risk space range using a probability distribution method. The simulation logic includes: Based on the prior value of the total length of the anchoring component and the length of the exposed section, the internal anchoring length of the rock mass is calculated; starting from the anchoring intrusion point, it extends along the axis of the component, and a radial position variance function that varies with the penetration depth is introduced to construct a spatial credibility weight model; spatial points with weights higher than the preset safety threshold are extracted to form a three-dimensional probabilistic risk envelope region that extends along the axis and gradually diffuses radially.

7. A rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation according to claim 1, characterized in that: The blind zone simulation module introduces an uncertainty diffusion model that varies with depth. The radial position variance function of the uncertainty diffusion model is set as a quadratic or exponential function of depth to characterize the nonlinear growth of uncertainty caused by borehole offset and rock mass stress disturbance with anchoring depth.

8. A rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation as described in claim 6, characterized in that, The risk space range derived by the blind zone deduction module is an inverted cone-shaped probability envelope region that extends along the axis of the anchoring member and whose radial cross section gradually increases with depth. The risk weight of each spatial point in this region decays in a Gaussian distribution along the radial direction.

9. A rock-entry anti-collision system for mine roadway anchorage support components based on blind zone simulation according to claim 1, characterized in that, The planning and control module performs trajectory optimization based on the collision risk field, and the specific algorithm includes: A joint objective optimization function is established, which includes collision risk cost, trajectory adjustment energy consumption cost, and drilling position deviation cost. The optimal drilling trajectory parameters that minimize the joint objective optimization function are solved, and the inverse kinematics of the optimal drilling trajectory parameters are analyzed into lifting, rotating, and telescopic drive commands for the drill guide rail. During the drilling process, the rotational degree of freedom is locked to keep the drilling angle constant.

10. An automated mining equipment, characterized in that, It includes a chassis, a multi-degree-of-freedom working mechanism and a control and communication system, and is equipped with a mine roadway anchor support component rock structure anti-collision system based on blind zone simulation as described in any one of claims 1 to 9, which is used to achieve predictive safety protection based on blind zone simulation of anchor support components under conditions of dust obstruction, limited visibility and incomplete structural observation.

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