CN120538877A - A device and method for sampling bedrock and rock cuttings samples - Google Patents

Abstract

The invention is applicable to the technical field of bedrock sampling, and relates to a sampling device and a sampling method for bedrock and rock debris samples, comprising a sampling base, a gantry type guide rail frame, a power sliding table driven by a servo motor and a ball screw, a drilling motor and a hollow coring bit, and an integrated sensing and cognition assembly, wherein an axial force sensor is used for measuring the axial pressure of the bit, a high-frequency vibration sensor is used for capturing drilling vibration signals, a macro camera is used for shooting the rock debris form of a chip removal area, and mechanical sensing data representing rock breaking response and visual sensing data representing the rock debris form are synchronously acquired in drilling; the method comprises the steps of carrying out validity verification on visual data to generate a visual data pollution state, if the visual data is not polluted, fusing and analyzing mechanical and visual data to judge the rock physical characteristics of the current horizon, if the visual data is polluted, taking the mechanical data as the main judging characteristic and triggering an obstacle clearance instruction, and based on the judged rock characteristics, adaptively optimizing the feeding speed of a servo motor and the rotating speed of a drilling motor to realize the adaptive regulation and control of the drilling process.

Description

Sampling device and method for bedrock and rock debris samples

Technical Field

The invention belongs to the technical field of bedrock sampling, and particularly relates to a sampling device and a sampling method for bedrock and rock debris samples.

Background

The existing rock sampling operation generally depends on experience of operators in a control mode, adopts preset and relatively fixed drilling parameters (such as drilling speed and feeding speed), and during the whole drilling process, operators can manually fine-tune the parameters according to sound or vibration somatosensory change of equipment, and in terms of data recording, traditional site logs generally only contain basic information such as sample numbers, sampling depth, operation time and the like, and although some advanced equipment can be provided with basic sensors such as torque or pressure, a comprehensive sensing and decision-making system capable of sensing rock-tool interaction in an online, real-time and multi-dimensional mode is generally lacking.

The sampling method in the prior art mainly has the defects that the physical and mechanical properties of rock are continuously changed in vertical depth, fixed drilling parameters are difficult to adapt to the requirements of different lithologies, when the rock with high hardness and high brittleness is encountered, improper parameters can cause core breakage to influence the integrity of a sample, in high toughness rock, drilling efficiency is low, equipment lacks effective real-time sensing and avoiding capability for geological conditions (such as sudden holes or large cracks) unknown in the front in the operation process, idle impact of drilling tools is easy to cause damage to the equipment and the hole wall, in addition, in a water-containing or high-viscosity stratum, mud is extremely easy to pollute an observation sensor (such as a camera), the traditional equipment cannot automatically identify the 'sensing pollution' and perform obstacle clearing, so that a vision-dependent monitoring function is invalid, finally, the finally obtained physical core sample and mechanical response data in the formation process are disjointed, and subsequent analysts cannot know detailed process information experienced by the sample in the sampling process, so that the possibility of comprehensively judging the characteristics is limited.

Disclosure of Invention

The invention provides a device and a method for sampling bedrock and rock debris samples, and aims to solve the problem of improper parameter adjustment.

The invention is realized in that a sampling device for bedrock and rock debris samples comprises:

The device comprises a sampling base, a gantry type guide rail frame, a power sliding table, a power feeding assembly, a micro-distance camera, a drilling motor, a hollow coring bit and a set of sensing cognitive assembly, wherein the gantry type guide rail frame is vertically fixed on the sampling base, the power sliding table is slidably arranged on the gantry type guide rail frame, the power feeding assembly is used for driving the power sliding table to vertically move along the gantry type guide rail frame and comprises a servo motor fixed on the gantry type guide rail frame, a ball screw in transmission connection with the servo motor and meshed with the power sliding table, the drilling motor is arranged on the power sliding table, the hollow coring bit is connected with a spindle of the drilling motor, the set of sensing cognitive assembly comprises an axial force sensor, a high-frequency vibration sensor and a micro-distance camera, the axial force sensor is arranged between the drilling motor and the power sliding table and used for measuring axial pressure exerted by the coring bit, the high-frequency vibration sensor is fixed on a shell of the drilling motor and used for capturing vibration signals in the drilling process, the micro-distance camera is fixed at the bottom of the power sliding table, and the lens is aligned with a chip removing area of the coring bit and used for capturing the rock chip shapes.

Preferably, the gantry type guide rail frame comprises two parallel vertical linear guide rails, and the power sliding table is arranged on the two linear guide rails through sliding blocks.

Preferably, the sensing and cognition assembly further comprises an acoustic probe which is packaged in the protective sleeve and is arranged at the bottom of the power sliding table and used for collecting sounds generated when rocks are broken.

Preferably, an annular LED lamp is sleeved outside the lens of the macro camera and used for providing illumination for capturing the rock debris form.

A method for sampling bedrock and cuttings samples, comprising the steps of:

During drilling, synchronously acquiring a mechanical sensing data set representing rock breaking physical response and a visual sensing data set representing rock chip physical form through the sensing and cognition assembly;

performing validity verification on the visual sense data set to generate a visual data pollution state;

When the visual data pollution state is pollution-free, carrying out fusion analysis on the mechanical sensing data set and the visual sensing data set to judge the petrophysical characteristics of the current horizon;

when the visual data pollution state is polluted, taking the mechanical sensing data set as a main basis for judging the petrophysical characteristics, and triggering an obstacle clearance instruction;

based on the determined petrophysical characteristics, adaptively optimizing a feed rate controlled by the servo motor and a rotational speed controlled by the drilling motor, or performing a preset obstacle clearance operation in response to the obstacle clearance instruction.

Preferably, the step of verifying the validity of the visual sense data set comprises:

Continuously calculating a definition gradient index representing the image quality change trend and a rock debris refreshing rate index representing the new and old rock debris replacement speed in the visual field;

and setting the visual data pollution state as polluted when the negative gradient of the definition gradient index exceeds a first threshold value and the rock debris refreshing rate index is lower than a second threshold value.

Preferably, the step of adaptively optimizing based on petrophysical properties comprises:

setting the rotational speed and the feed speed to lower values when the petrophysical property is determined to be high hardness and high brittleness;

when the petrophysical property is judged to be high in hardness and toughness, the rotating speed is set to be a high value, and the feeding pressure is controlled in a closed loop mode based on the reading of the axial force sensor so as to increase the feeding speed.

Preferably, the obstacle clearing operation includes:

The servo motor drives the power sliding table to stop feeding and retract upwards slightly;

And the drilling motor executes pulse high-rotation-speed action to throw off the adhesion matters.

Preferably, after the obstacle clearing operation is executed, returning to execute the step of checking the validity of the visual sense data set, and if the visual data pollution state is still polluted after the obstacle clearing operation is continuously executed for a preset number of times, switching to a conservation mode, drilling at a low rotating speed and a low feeding speed by the conservation mode, and actively executing the obstacle clearing operation at a preset depth interval.

Preferably, the method further comprises the following steps:

And taking the drilling depth controlled by the servo motor as an index to generate a digital file, wherein the file at least comprises the mechanical sensing data set which corresponds to the depth accurately, rock debris characteristics extracted based on the visual sensing data set, the determined rock physical characteristics, the adopted feeding speed and the adopted rotating speed, and the visual data pollution state and the log record of obstacle clearing operation.

Compared with the prior art, the embodiment of the application has the following main beneficial effects:

The sensing and cognition assembly synchronously acquires a mechanical sensing data set representing the physical response of rock breaking and a visual sensing data set representing the physical form of rock scraps, and performs fusion analysis on the mechanical sensing data set and the visual sensing data set, so that the rock physical characteristics of the current horizon can be judged in real time and on line, the fundamental problems that the lithology, the operation efficiency and the sample quality are low in the operation process of the traditional sampling method are solved, the step of effectively checking the visual sensing data set is introduced, the visual data pollution state caused by the reasons of pasting of mud and the like can be intelligently identified by calculating indexes such as the definition gradient, the rock scraps refreshing rate and the like, and when pollution occurs, the system can automatically switch decision logic by taking the mechanical sensing data set as a main basis and triggering an obstacle clearing instruction, and the working reliability and autonomy of the device in a complex and changeable field environment are greatly enhanced.

Drawings

FIG. 1 is a schematic perspective view of the present invention;

FIG. 2 is a schematic view of a partial perspective view of the present invention;

FIG. 3 is a schematic view of a partial perspective view of the present invention;

FIG. 4 is a schematic view of a partial perspective view of the present invention;

FIG. 5 is a graph of dynamic identification of rock properties in accordance with the present invention;

100 parts of a sampling base, 200 parts of a gantry type guide rail frame, 210 parts of a linear guide rail, 300 parts of a power sliding table, 310 parts of a servo motor, 320 parts of a ball screw, 400 parts of a drilling motor, 410 parts of a coring bit, 510 parts of an axial force sensor, 520 parts of a high-frequency vibration sensor, 530 parts of an acoustic probe, 540 parts of a micro-distance camera, 541 parts of an annular LED lamp.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs, the terms used in the description of this application are for the purpose of describing particular embodiments only and are not intended to be limiting of the application, and the terms "comprising" and "having" and any variations thereof in the description of this application and the claims and the above description of the drawings are intended to cover non-exclusive inclusions. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

Referring to fig. 1 to 5, the present application shows a sampling device for bedrock and cuttings samples, comprising a sampling base 100 for supporting the device, a gantry type guide rail frame 200 vertically fixed to the sampling base 100, a power sliding table 300 slidably mounted on the gantry type guide rail frame 200, a power feeding assembly for driving the power sliding table 300 to move vertically along the gantry type guide rail frame 200, the power feeding assembly comprising a servo motor 310 fixed to the gantry type guide rail frame 200, and a ball screw 320 drivingly connected to the servo motor 310 and engaged with the power sliding table 300, a drilling motor 400 mounted on the power sliding table 300, a hollow coring bit 410 connected to a main shaft of the drilling motor 400, a set of sensing and recognizing assembly comprising an axial force sensor 510 disposed between the power sliding table 300 for measuring an axial pressure received by the coring bit 410, a high frequency vibration sensor 520 fixed to a housing of the motor 400 for capturing a chip removing signal in the housing of the gantry type guide rail frame 200, and a boring lens 540 fixed to the boring bit 300 for capturing cuttings in a form of a region where the boring lens is aligned with the boring lens 410.

The sampling base 100 of the device provides a stable ground support for the whole system, a gantry type guide rail frame 200 is vertically fixed on the sampling base, a power sliding table 300 can slide on the guide rail frame, specifically, a servo motor 310 fixed on the guide rail frame drives a ball screw 320 to rotate through a coupler, the ball screw 320 is meshed with a nut seat on the power sliding table 300, so that the rotary motion of the motor is converted into stable and controllable linear vertical motion of the sliding table, precise feeding speed control is provided for drilling, a drilling motor 400 mounted on the power sliding table 300 drives a hollow coring bit 410 to perform rotary drilling and coring, an axial force sensor 510 is mounted between the drilling motor 400 and the power sliding table 300 in an interlayer manner and used for measuring the axial pressure born by the bit in real time, the pressure is a direct basis for judging rock hardness, a high-frequency vibration sensor 520 is fastened on a casing of the drilling motor 400 and used for capturing vibration signals generated during rock fragility recognition, a lens of a micro-distance head 540 is precisely aligned with a chip removing area of the coring bit 410 and used for directly observing and capturing the physical form of newly discharged rock fragments, and the device is difficult to sense the physical characteristics of a real-time sensing and real-time sensing device in a conventional sampling platform by combining a high-precision mechanical execution system with a plurality of intelligent sensing system and a real-time sensing operation performance in a real-time sensing technology, and a real-time sensing device can not be easily sensed in a real-time sensing real-time.

Further, the gantry rail frame 200 includes two parallel vertical linear rails 210, and the power slipway 300 is mounted on the two linear rails 210 through a slider.

The gantry type guide rail frame 200 in this embodiment has a specific structure that two parallel vertical linear guide rails 210 are adopted, and the power sliding table 300 is installed on the two linear guide rails 210 through precise sliding blocks, so that signals collected by the axial force sensor 510 and the high-frequency vibration sensor 520 can truly reflect the crushing response of the rock itself.

Still further, the sensing and recognizing assembly further includes an acoustic probe 530 enclosed in a protective case and mounted at the bottom of the power slipway 300 for collecting sounds generated when rock is broken.

The sensing and cognition assembly in this embodiment further adds an acoustic probe 530 on the original basis, the probe is encapsulated in a sound-proof and dust-proof protective sleeve and is installed at the bottom of the power sliding table 300 near the position of the drill hole so as to clearly collect acoustic signals emitted when the rock is broken, the purpose of adding the acoustic probe 530 is to realize cross validation and high confidence identification of the brittle fracture event of the rock, when the hard and brittle rock (such as quartz rock) breaks, not only can severe fluctuation of high-frequency vibration and axial force be generated, but also clear and brittle high-frequency burst sound can be accompanied, and when the system detects that the three signals have synchronous peaks, the strategy of fusion of the multi-mode data can extremely confirm that the brittle fracture occurs, effectively overcomes the problem of multiple resolution possibly existing in the single sensor signal (such as high vibration can be caused by drilling tool resonance), and remarkably improves the accuracy and reliability of on-line identification of the physical characteristics of the rock.

Further, an annular LED lamp 541 is sleeved on the lens outer ring of the macro camera 540, so as to provide illumination for capturing the rock debris form.

In the macro camera 540 of this embodiment, an annular LED lamp 541 is specifically sleeved on the outer ring of the lens. The purpose of this design is to provide stable, uniform and shadowless lighting conditions for visual capture of the cuttings morphology.

The application further provides a method for sampling bedrock and rock debris samples, which comprises the steps of synchronously acquiring a mechanical sensing data set representing rock breaking physical response and a visual sensing data set representing rock debris physical form through the sensing and cognition assembly in a drilling process, checking validity of the visual sensing data set to generate a visual data pollution state, carrying out fusion analysis on the mechanical sensing data set and the visual sensing data set to judge the rock physical characteristic of a current horizon when the visual data pollution state is uncontaminated, taking the mechanical sensing data set as a main basis for judging the rock physical characteristic when the visual data pollution state is polluted, triggering an obstacle clearance instruction, adaptively optimizing the feeding speed controlled by the servo motor 310 and the rotating speed controlled by the drilling motor 400 based on the judged rock physical characteristic, or carrying out preset obstacle clearance operation in response to the obstacle clearance instruction.

In the method, during the drilling process, firstly, two types of data are synchronously acquired by utilizing a sensing and cognition assembly, wherein one type is a mechanical sensing data set consisting of axial force, vibration and sound sensors, and the mechanical sensing data set indirectly reflects the breaking response of rock; the other type is a vision sensing data set composed of macro cameras 540, which directly shows the physical form of rock debris, and does not directly use vision data, but firstly carries out validity check on the vision sensing data set to judge whether a 'vision data pollution state' caused by mud pasting and the like exists, then, the control logic enters into split flow, under the condition that the vision data is reliable (i.e. not polluted), the system carries out fusion analysis on the vision and the mechanical data, through directly observed rock debris forms (such as large particles and clear angles) to verify or correct the inference (such as high brittleness) of the mechanical data, thereby carrying out most accurate judgment on the physical characteristics of the rock, otherwise, if the vision data is judged to be polluted, the system is switched into a fault-tolerant mode, and in turn, the more reliable mechanical sensing data set is used as a main basis to judge, and simultaneously, a clearance instruction is triggered, the vision pollution problem is prepared to be solved, finally, the system carries out corresponding actions based on the obtained rock character judgment or the triggered clearance instruction, or self-adaptive optimization of the feeding parameters (i.e. the feeding speed controlled by a servo motor 310 and the rotation speed controlled by the motor 400) to control the preset rotation speed of the visual sensor layer, the vision sensor is matched with the vision sensor layer, the fault-tolerant performance is found, the vision sensor is valid, and the fault-free performance is recovered, and the vision sensor is found, greatly enhancing the reliability of the device in complex and changeable geological environments.

Further, the step of verifying the validity of the visual sensing data set comprises the steps of continuously calculating a definition gradient index representing the change trend of the image quality and a rock debris refreshing rate index representing the replacement speed of new and old rock debris in the visual field, and setting the visual data pollution state as polluted when the negative gradient of the definition gradient index exceeds a first threshold and the rock debris refreshing rate index is lower than a second threshold.

In this embodiment, the step of verifying the validity of the visual sensing dataset is implemented by two algorithm indexes based on image sequence analysis, the first index being a sharpness gradient index. The algorithm does not judge whether a single frame image is clear or not, but continuously calculates the change trend of the image quality by tracking parameters such as image contrast, edge sharpness and the like, and the inherent logic is that if a lens is polluted due to slow adhesion of slurry, the image quality inevitably shows continuous and trend degradation and shows negative gradient of a definition index. The second index is a rock debris refreshing rate index, the algorithm quantifies the replacement speed of new and old rock debris in the visual field by comparing textures or characteristic points of continuous inter-frame images, the inherent logic is that newly generated rock debris is continuously discharged and refreshed in the visual field during normal drilling, if a servo motor 310 is still in feeding and a camera picture has no significant change for a long time, the condition that the camera picture is covered by static mud before the lens is explained, finally, the system judges the visual data pollution state as a polluted condition is that when the negative gradient (namely the quality reduction rate) of a definition gradient index exceeds a preset first threshold value and the rock debris refreshing rate index is lower than a preset second threshold value, the dual condition judging mechanism can very accurately identify the polluted condition of the lens by combining whether the image is in blurring or not and whether the picture content is updated or not, and provides reliable trigger basis for subsequent decision switching.

Further, the step of adaptively optimizing based on the petrophysical property includes setting the rotational speed and the feed rate to a lower value when the petrophysical property is discriminated as high hardness and high brittleness, setting the rotational speed to a higher value when the petrophysical property is discriminated as high hardness and high toughness, and performing closed loop control of the feed pressure based on the reading of the axial force sensor 510 to increase the feed rate.

In this embodiment, the step of adaptively optimizing based on the physical characteristics of rock reflects a fine sampling strategy for different rock breaking mechanisms, when the system determines the rock to be high-hardness Gao Cuixing (such as granite and quartz rock) through fusion analysis, the controller aims at utilizing the brittleness to perform efficient volume breaking, therefore, the system strategically sets the rotating speed of the drilling motor 400 and the feeding speed of the servo motor 310 to be lower, the purpose of the system is to avoid unnecessary grinding caused by the excessively high rotating speed, the effective breaking of the rock is realized through lower energy input, thus obtaining a more complete core sample, on the contrary, when the rock is determined to be high-hardness and high-toughness (such as compact basalt), the breaking mode is mainly grinding, at this time, the controller can set the rotating speed of the drilling motor 400 to be higher, so as to improve the grinding efficiency, and more importantly, in order to prevent' low-efficiency grinding caused by insufficient pressure, the system can utilize the real-time reading of the axial force sensor 510 and the driving instruction of the servo motor 310 to form a control system, the dynamic adjustment is used for avoiding the excessively high rotating speed to generate unnecessary grinding, the effective breaking of the rock is realized, the efficient breaking of the rock is realized through the lower energy input, the efficient breaking mode is optimized for obtaining the optimal quality sample through the dynamic adjustment of the output torque, and the optimal feeding efficiency is balanced and the quality-optimized sampling mode is aimed at the quality of the sample.

Further, the obstacle clearing operation includes stopping the feeding and retracting slightly upward of the power slipway 300 by the servo motor 310, and performing a pulse high rotation speed action by the drilling motor 400 to throw off the adherent.

In the present embodiment, the servo motor 310 precisely controls the power slipway 300 to stop the downward feeding immediately and perform a small upward withdrawing action, the purpose of which is to instantaneously remove the pressing stress of the front end of the drill bit to break the structural stability of the mud cake which may have been formed and adhered around the lens or drill bit, and then, in the state that the drill remains at the withdrawing position, the controller instructs the drilling motor 400 to perform a "pulse type high rotation speed" action, which is embodied as rapidly raising the rotation speed to the peak value and then lowering in a very short time and repeating for several times, the purpose of which is to forcefully throw off the adhesive such as mud or rock debris adhered near the drill bit or chip removing passage, which causes visual shielding, by using the strong centrifugal force and the accompanying mechanical vibration, the combined action forms a non-contact type barrier removing scheme which does not need external intervention, and can be quickly repaired by itself after finding the problem, and the normal function of the sensing system is restored.

And if the visual data pollution state is still polluted after the obstacle clearing operation is continuously carried out for a preset number of times, switching to a conservation mode, drilling at a low rotating speed and a low feeding speed, and actively carrying out the obstacle clearing operation according to a preset depth interval.

In this embodiment, after performing the obstacle clearing operation, a set of logic for loop checking and policy updating is designed, after completing an obstacle clearing action, the system does not blindly resume conventional drilling, but first returns to perform a step of checking the validity of the vision sensing dataset to evaluate the obstacle clearing effect, if the vision pollution state is released, the system resumes conventional adaptive optimized drilling, however, if the checking result shows that the vision data pollution state is still polluted, the system repeatedly performs the obstacle clearing operation. If the problem remains after a preset number of consecutive barrier removal operations (e.g., 3), the system will make a more advanced determination that the current encounter is not sporadic contamination, but rather a persistent, highly muddy or highly viscous formation, at which time the system will switch to a preset conservative mode where the system will judiciously drill with a combination of low rotational speed and low feed rate in order to stabilize, avoid clogging, and more importantly, it will actively perform a barrier removal operation once at preset depth intervals (e.g., 5mm per drill), the design concept of this mode will be changed from "passive response" to "active prevention" by periodic cleanup before the problem is exacerbated to ensure that the operation is maintained under extremely severe formation conditions, despite the lower efficiency, the continuity of the task and the ultimate success rate are ensured.

Further, a digitized file is generated with the drilling depth controlled by the servo motor 310 as an index, wherein the file at least contains the mechanical sensing dataset corresponding to the depth, the rock debris characteristics extracted based on the visual sensing dataset, the determined petrophysical characteristics, the adopted feeding speed and rotation speed, and the visual data pollution status and log record of the obstacle clearing operation.

The method of this embodiment further includes a step of generating a digitized file, which constitutes a complete digital reproduction of the sampling process, the method uses the drilling depth controlled and recorded by the high-precision servo motor 310 as a unique index, ensuring that any point on the physical core can be precisely matched with the digital record, the digitized file generated after the completion of the operation is far richer than the traditional record, and at least contains the information of precisely binding with the depth, 1) a complete original set of mechanical sensing data sets (force, vibration and sound), 2) rock debris characteristics (such as size and sharpness) extracted based on the visual sensing data sets, 3) rock physical characteristics (such as high hardness Gao Cuixing) determined after the system fusion analysis, and 4) the feeding speed and rotation speed parameters actually adopted by the controller at the corresponding depth, especially, the file also contains detailed system states and decision logs, namely the visual data pollution states and logs of the clearing operation, but rather than passive records of the results, and the records of the decision and how to deal with the challenging process are accurately bound with each other, 2) the rock debris characteristics (such as size and sharpness) are recognized by the visual sensing data, and the visual pollution states are not being found by the analysis at the same time of a certain depth, and the visual pollution is not being successfully cleared by a certain type of the device. The addition of the process information provides rich data for subsequent scientific analysis, so that the judgment of the stratum characteristics is more accurate and comprehensive.

It should be noted that, for simplicity of description, the foregoing embodiments are all illustrated as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts, as some steps may be performed in other order or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and such partitioning of the above-described elements may be implemented in other manners, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or communication connection shown or discussed as being between each other may be an indirect coupling or communication connection between devices or elements via some interfaces, which may be in the form of telecommunications or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention. It will be apparent that the described embodiments are merely some, but not all, embodiments of the invention. Based on these embodiments, all other embodiments that may be obtained by one of ordinary skill in the art without inventive effort are within the scope of the invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art may still combine, add or delete features of the embodiments of the present invention or make other adjustments according to circumstances without any conflict, so as to obtain different technical solutions without substantially departing from the spirit of the present invention, which also falls within the scope of the present invention.

Claims (10)

1. A sampling device for bedrock and rock cuttings, comprising: A sampling base for supporting the device; a gantry guide frame vertically fixed on the sampling base; a power slide slidably mounted on the gantry guide frame; a power feed assembly for driving the power slide to move vertically along the gantry guide frame, the power feed assembly comprising a servo motor fixed to the gantry guide frame, and a ball screw transmission-connected to the servo motor and meshing with the power slide; a drilling motor mounted on the power slide; a hollow coring drill bit connected to the main shaft of the drilling motor; a sensor recognition assembly comprising: an axial force sensor arranged between the drilling motor and the power slide for measuring the axial pressure exerted on the coring drill bit; a high-frequency vibration sensor fixed on the housing of the drilling motor for capturing vibration signals during drilling; a macro camera fixed on the bottom of the power slide, with its lens aimed at the area where cuttings are removed by the coring drill bit, for capturing the shape of rock cuttings. 2. The bedrock and rock cuttings sampling device according to claim 1, characterized in that the gantry guide rail frame includes two parallel vertical linear guide rails, and the power slide is installed on the two linear guide rails through sliders. 3. The bedrock and rock chip sampling device according to claim 1 is characterized in that the sensing and recognition assembly further comprises: an acoustic probe, encapsulated in a protective cover and installed at the bottom of the power slide, for collecting the sound emitted when the rock is broken. 4. The bedrock and rock cuttings sampling device according to claim 1 is characterized in that a ring-shaped LED light is provided on the outer ring of the lens of the macro camera to provide lighting for capturing the rock cuttings morphology. 5. A method for sampling bedrock and rock cuttings, characterized by using the bedrock and rock cuttings sampling device according to claim 1, comprising the following steps: During the drilling process, the sensor-recognition assembly synchronously acquires a mechanical sensing data set representing the physical response of rock crushing and a visual sensing data set representing the physical morphology of rock cuttings; Performing validity verification on the visual sensing data set to generate a visual data contamination state; When the visual data pollution state is unpolluted, the mechanical sensing data set and the visual sensing data set are fused and analyzed to determine the rock physical properties of the current layer; When the visual data pollution state is polluted, the mechanical sensing data set is used as the main basis for determining the physical properties of the rock, and an obstacle clearance instruction is triggered; Based on the identified rock physical properties, the feed speed controlled by the servo motor and the rotation speed controlled by the drilling motor are adaptively optimized; or, in response to the obstacle clearance instruction, a preset obstacle clearance operation is performed. 6. The sampling method according to claim 5, wherein the step of performing validity verification on the visual sensor data set comprises: Continuously calculate the clarity gradient index that represents the trend of image quality changes, and the cuttings refresh rate index that represents the speed of replacement of new and old cuttings in the field of view; When the negative gradient of the clarity gradient index exceeds a first threshold and the rock fragment refresh rate index is lower than a second threshold, the visual data pollution state is set to polluted. 7. The sampling method according to claim 5, wherein the step of performing adaptive optimization based on rock physical properties comprises: When the rock physical properties are determined to be high hardness and high brittleness, the rotation speed and the feed speed are set to lower values; When the rock physical properties are determined to be high hardness and high toughness, the rotational speed is set to a higher value, and the feed pressure is closed-loop controlled based on the reading of the axial force sensor to increase the feed speed. 8. The sampling method according to claim 5, wherein the obstacle removal operation comprises: The servo motor drives the power slide to stop feeding and withdraw slightly upward; The drilling motor performs a pulsed high-speed motion to shake off the adhered matter. 9. The sampling method according to claim 8 is characterized in that after performing the obstacle clearance operation, the step of returning to perform the validity verification of the visual sensor data set is performed; if the visual data contamination status is still contaminated after the obstacle clearance operation is performed continuously for a preset number of times, a conservative mode is switched to, which drills at a low rotation speed and low feed speed, and actively performs the obstacle clearance operation at preset depth intervals. 10. The sampling method according to claim 5, further comprising the following steps: A digital archive is generated using the drilling depth controlled by the servo motor as an index, the archive including at least the mechanical sensing dataset accurately corresponding to the depth, rock cuttings characteristics extracted based on the visual sensing dataset, the identified rock physical properties, the feed speed and rotation speed used, and a log record of the visual data contamination status and obstacle clearance operation.