A mine drilling intelligent monitoring system and method

Abstract

The present application provides a kind of mine drilling intelligent monitoring system and method, belong to mine drilling monitoring field, the system includes: multi-modal sensor group, be set on drilling equipment, for real-time acquisition multiple drilling parameters, the multiple drilling parameters include the depth data of drilling, attitude measurement data of drilling equipment, pressure data of drilling hole wall, crack image data of drilling hole wall, vibration data in drilling process, any multiple in radial offset of drilling hole wall;Data transmission module is connected with the multi-modal sensor group, for the drilling parameter transmission to processing module;Processing module is used to generate drilling state monitoring result according to the drilling parameter, and the drilling state monitoring result includes any multiple in drilling depth, drilling direction, drilling hole wall stability, drilling shape.The synchronous acquisition and fusion analysis of the present application by multi-source heterogeneous sensing data have improved the comprehensiveness and reliability of drilling state monitoring.

Description

Technical Field

[0001] This invention relates to the field of mine borehole monitoring, and more particularly to an intelligent monitoring system and method for mine boreholes. Background Technology

[0002] In mining engineering and underground space development operations, mine drilling is a crucial foundational task for exploration, support, and gas extraction. As mining depths increase, the geological conditions in mines become increasingly complex. Harsh environments such as high temperatures, high pressures, high stresses, and fractured rock strata pose significant challenges to the safety and accuracy of drilling operations. Problems such as borehole path deviations and borehole instability not only affect project progress and quality but can also lead to safety accidents, seriously threatening the lives of underground workers and the stable operation of the mine. Therefore, effective monitoring methods are urgently needed to ensure the smooth progress of drilling operations.

[0003] Currently, monitoring of mine boreholes primarily employs traditional, decentralized technical solutions. For depth monitoring, mechanical counters or simple pulse sensors are often used to record drill pipe advance. Borehole attitude monitoring acquires localized data using inertial devices such as gyroscopes, but this is prone to significant errors in complex geomagnetic environments. For borehole wall condition monitoring, manual inspection at the borehole opening using simple imaging equipment is typically required, making it difficult to obtain real-time information about the depths of the borehole. These monitoring methods operate independently, lacking systematic integration, and have limited data acquisition range and accuracy, failing to meet the monitoring needs of borehole operations under complex conditions.

[0004] Existing borehole monitoring technologies have significant limitations. First, monitoring equipment is scattered, failing to achieve comprehensive, end-to-end coverage of drilling operations. Many crucial information points are difficult to obtain, such as the mechanical state at different depths of the borehole wall and changes in the overall borehole shape. Second, the monitoring data are isolated, lacking effective correlation analysis and collaborative processing mechanisms, making it impossible to comprehensively assess and accurately predict borehole conditions. When borehole anomalies occur, operators struggle to quickly pinpoint the root cause and take effective countermeasures, leading to low drilling efficiency, increased engineering costs, and a failure to provide timely warnings of potential safety hazards, severely hindering the intelligent development of mine drilling operations. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide an intelligent monitoring system and method for mine boreholes to solve at least one of the above-mentioned technical problems.

[0006] To achieve the above objectives, in a first aspect, the present invention provides an intelligent monitoring system for mine boreholes, comprising:

[0007] A multimodal sensor array is installed on the drilling equipment to collect multiple drilling parameters in real time. These multiple drilling parameters include any multiple of the following: drilling depth data, drilling equipment attitude measurement data, drilling wall pressure data, drilling wall crack image data, drilling process vibration data, and drilling wall radial offset data.

[0008] A data transmission module, connected to the multimodal sensor group, is used to transmit the drilling parameters to the processing module;

[0009] The processing module is used to generate drilling status monitoring results based on the drilling parameters. The drilling status monitoring results include any multiple parameters such as drilling depth, drilling direction, drilling wall stability, and drilling shape.

[0010] Secondly, a method for intelligent monitoring of mine boreholes is provided, the method being based on the aforementioned intelligent monitoring system for mine boreholes, the method comprising the following steps:

[0011] Multiple drilling parameters are collected in real time by a multi-modal sensor group installed on the drilling equipment. These multiple drilling parameters include any multiple of the following: drilling depth data, drilling equipment attitude measurement data, drilling hole wall pressure data, drilling hole wall crack image data, drilling process vibration data, and drilling hole wall radial offset data.

[0012] The drilling parameters are transmitted to the processing module via the data transmission module.

[0013] The processing module generates borehole status monitoring results based on the borehole parameters. The borehole status monitoring results include any number of parameters such as borehole depth, borehole direction, borehole wall stability, and borehole shape.

[0014] The above technical solution has the following beneficial effects:

[0015] The technical solution of this invention improves the comprehensiveness and reliability of borehole status monitoring through the synchronous acquisition and fusion analysis of multi-source heterogeneous sensor data. First, it avoids the limitations of traditional single-parameter sensing modes, enabling real-time acquisition of multi-dimensional dynamic information such as borehole depth, equipment attitude, and borehole wall deformation, effectively eliminating monitoring blind spots. Second, based on multi-dimensional parameter correlation modeling and intelligent analysis, it can accurately identify precursors to borehole wall instability, abnormal trajectory deviations, and the trend of rock fracture expansion, improving the timeliness of risk warnings under complex geological conditions. Simultaneously, by optimizing the data transmission architecture, it ensures the continuity and integrity of monitoring data in harsh downhole environments. Furthermore, the integrated design of the system enables automated assessment of the entire borehole operation status, providing technical support for optimizing drilling parameters, preventing borehole accidents, and reducing resource consumption. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a functional block diagram of a mine borehole intelligent monitoring system according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram illustrating the classification of borehole condition monitoring results according to an embodiment of the present invention;

[0019] Figure 3 This is a flowchart illustrating the analysis process of the hole wall stability prediction results in an embodiment of the present invention.

[0020] Figure 4 This is a flowchart illustrating the process of determining the borehole shape according to an embodiment of the present invention;

[0021] Figure 5 This is a flowchart of an intelligent monitoring method for mine boreholes according to an embodiment of the present invention;

[0022] Figure 6 This is a functional block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example 1

[0025] like Figure 1 As shown, this embodiment provides an intelligent monitoring system for mine boreholes, which includes:

[0026] A multimodal sensor array is installed on the drilling equipment to collect multiple drilling parameters in real time. These multiple drilling parameters include any multiple of the following: drilling depth data, drilling equipment attitude measurement data, drilling wall pressure data, drilling wall crack image data, drilling process vibration data, and drilling wall radial offset data.

[0027] A data transmission module, connected to the multimodal sensor group, is used to transmit the drilling parameters to the processing module;

[0028] The processing module is used to generate drilling status monitoring results based on the drilling parameters. The drilling status monitoring results include any multiple parameters such as drilling depth, drilling direction, drilling wall stability, and drilling shape.

[0029] In this embodiment, the multimodal sensor group may include a depth sensor, a triaxial accelerometer and gyroscope combined attitude sensor, a miniature pressure sensor array, a miniature camera, a vibration sensor, and a laser rangefinder. The depth sensor, employing an optical encoder, is mounted on the drill rod drive mechanism of the drilling equipment to accurately measure the drilling depth by recording the number of rotations and pitch of the drill rod. The triaxial accelerometer and gyroscope combined attitude sensor is fixed near the drill bit to collect real-time attitude measurement data such as the tilt angle and azimuth angle of the drilling equipment. The miniature pressure sensor array is evenly arranged circumferentially along the sidewall of the drill head to collect pressure data at different locations on the borehole wall. The miniature camera is mounted on the front end of a retractable probe to capture images of cracks in the borehole wall. The vibration sensor can be fixed to the drilling equipment body to monitor vibration data during the drilling process. The laser rangefinder measures the radial offset data of the borehole wall by emitting a laser beam. These sensors work together to collect multiple drilling parameters from all directions. This embodiment organically integrates multiple sensors (depth, attitude, pressure, vision, vibration, and laser rangefinder) to form a comprehensive monitoring system.

[0030] In some embodiments, the laser rangefinder sensor can be mounted on the side of the drill bit or on the drill rod near the drill bit. This location is closest to the borehole wall, enabling direct and accurate measurement of the radial offset of the borehole wall at the current drilling position. During drilling, as the drill bit advances, the laser rangefinder sensor mounted near the drill bit can acquire real-time information about the borehole wall in the latest drilling area. This is highly beneficial for timely detection of minute changes in the borehole wall shape, allowing operators to adjust drilling equipment parameters immediately and ensure the borehole shape and orientation meet design requirements. Furthermore, a sealed protective structure is provided, employing a fully sealed housing made of high-strength, wear-resistant, and well-sealing materials, such as stainless steel or engineering plastics, to encapsulate the key components of the laser rangefinder sensor. Simultaneously, rubber sealing rings or sealant are used to seal the interfaces of the housing to prevent dust from entering the laser rangefinder sensor and affecting the normal operation of optical and electronic components. Additionally, an air purging device is provided, which equips the laser rangefinder sensor with an air purging system that uses compressed air to generate a high-speed airflow to continuously purge the laser emission and reception windows. This effectively prevents dust accumulation on the window surface, ensuring normal laser beam emission and reception, and improving measurement accuracy. The air purging device can be adjusted according to the actual dust concentration using either timed or continuous purging. Furthermore, a heat insulation layer is installed around the laser rangefinder sensor, using materials with good heat insulation properties, such as ceramic fiber or aerogel, to reduce the impact of high external temperatures on the sensor. The heat insulation layer can wrap around the sensor housing, forming a heat barrier and effectively reducing the internal temperature of the laser rangefinder sensor. Additionally, a vibration-damping mounting base is provided, employing rubber damping pads, spring dampers, and other vibration-damping elements to isolate the laser rangefinder sensor from the vibration source of the drilling equipment. The vibration-damping mounting base effectively absorbs and buffers vibration energy, reducing the impact of vibration on the sensor and ensuring the stability and reliability of the laser rangefinder sensor.

[0031] In some embodiments, the laser rangefinder sensor can be installed on the drilling equipment body near the borehole inlet, with the laser emission direction facing the borehole wall. This relatively fixed location facilitates installation and maintenance. The radial offset data of the borehole wall is measured using the following principle: When the drilling equipment rotates, the laser rangefinder sensor rotates synchronously with the equipment, emitting laser beams towards the borehole wall at fixed angular intervals (e.g., every 1° or 5°). The laser beams are reflected by the borehole wall and received by the sensor. The real-time distance from the sensor to the borehole wall is calculated by measuring the laser's flight time or phase difference. Since the ideal shape of a borehole is a cylinder, with its central axis as the design reference, the multiple angular distance data collected by the sensor during rotation reflect the actual radius of the borehole wall in different orientations. The data processing module fits the multi-angular distance data at the same depth, calculates the actual distance between each measurement point and the borehole's central axis, and compares it with the design radius; the difference is the radial offset in that orientation. If the borehole has ellipticity deviation, local protrusions or depressions, the radial offset will show regular or abnormal fluctuations. The system uses this to determine whether the borehole shape meets the predetermined standard, providing data support for borehole trajectory adjustment.

[0032] In an alternative embodiment, the depth sensor can be a magnetostrictive displacement sensor. In borehole depth measurement, a permanent magnet can be mounted at a specific position on the drill string, and an electronic detection device is fixed to the drilling equipment. As the drill string advances, the position of the permanent magnet changes, and the borehole depth can be obtained by measuring the change in distance between the permanent magnet and the electronic detection device.

[0033] The data transmission module can employ a combination of wired and wireless transmission methods. Drilling parameters collected by the multimodal sensor array are first transmitted via high-temperature resistant, interference-resistant shielded cables to a data transfer box installed near the drilling equipment. Inside the data transfer box, the signal undergoes preprocessing such as filtering and amplification before being transmitted to the underground monitoring base station via industrial Ethernet. The monitoring base station then uses a mining-grade wireless transmission module to send the data to the ground control center, ensuring that drilling parameters are transmitted stably and quickly to the processing module, avoiding data loss or transmission delays caused by the complex underground environment.

[0034] The processing module, located in the ground control center, includes a server and data analysis software. After receiving drilling parameters from the data transmission module, the server first normalizes various data types to eliminate dimensional differences between parameters. Then, a data association model is established using deep learning algorithms. The drilling direction is calculated using depth and attitude measurement data; borehole wall stability is determined based on borehole pressure data, crack image data, and radial offset; and the borehole shape is determined by combining radial offset data from multiple locations. Finally, the calculated borehole depth, drilling direction, borehole wall stability, and borehole shape monitoring results are presented to operators in the form of visual charts or reports, allowing them to promptly grasp the borehole status and adjust drilling operation parameters.

[0035] Specifically, in one embodiment, the process of determining the borehole shape by combining multi-position radial offset is as follows: A laser rangefinder performs a 360° rotational scan along the borehole axis at equal intervals (e.g., every 0.5 meters of drilling) to obtain a dataset of radial offsets at each depth section; After converting the polar coordinate measurements of each section into three-dimensional point cloud data in the Cartesian coordinate system, a B-spline surface fitting algorithm is used to spatially interpolate the point cloud of the continuous sections to generate a three-dimensional geometric model of the borehole; Based on preset borehole design parameters (e.g., target diameter, axis straightness), the spatial deviation value between the actual model and the theoretical model is calculated, and the shape compliance is evaluated through quantitative indicators of ellipticity, taper, and curvature. Finally, a visual report containing a three-dimensional heat map (showing local expansion or contraction areas) and a deviation parameter table is generated to guide operators to correct the drilling trajectory or adjust the drill bit pressure.

[0036] The multimodal sensor group may include any number of the following:

[0037] A depth measurement sensor installed on drilling equipment is used to detect the depth data of the borehole.

[0038] An attitude measurement sensor installed on the drilling equipment is used to detect attitude measurement data of the drilling equipment, including tilt angle, pitch angle and deviation angle.

[0039] A pressure sensor installed on the drilling equipment is used to detect pressure data on the borehole wall, and the pressure data is related to the stability of the borehole wall.

[0040] An optical camera assembly installed inside the drilling equipment, the optical camera assembly including an optical camera, is used to acquire image data of cracks in the borehole wall, the crack image data being correlated with the stability of the borehole wall;

[0041] A temperature sensor installed on the drilling equipment is used to detect the temperature data of the borehole wall, and the temperature data of the borehole wall is related to the stability of the borehole wall.

[0042] A vibration sensor installed on the drilling equipment is used to detect vibration data during the drilling process. The vibration data is related to the stability of the borehole wall. The vibration data during the drilling process includes vibration data of the borehole wall and vibration data of the drilling equipment.

[0043] A laser rangefinder sensor installed on the drilling equipment is used to detect radial offset data of the borehole wall, which is related to the shape of the borehole.

[0044] In some embodiments, a high-precision magnetostrictive displacement sensor can be selected as the depth measurement sensor, which is axially fixed to the side of the drill rod guide frame of the drilling equipment. The telescopic measuring rod of the magnetostrictive displacement sensor is rigidly connected to the end of the drill rod, and extends synchronously as the drill rod penetrates deeper underground during drilling operations. Based on the magnetostrictive effect, the magnetostrictive displacement sensor accurately calculates the travel distance of the drill rod by detecting changes in the position of the magnetic ring on the telescopic measuring rod, thereby obtaining the borehole depth data. This magnetostrictive displacement sensor features strong anti-interference capability and high accuracy, and can adapt to the complex environment of dampness and vibration in underground mines, providing the system with real-time and accurate borehole depth information.

[0045] Specifically, the drill rod guide frame is a mechanical structure in drilling equipment used to support, position, and guide the axial movement of the drill rod. It is located at the front of the machine body or above the drilling platform. Its function is to ensure that the drill rod's axis remains aligned with the drilling direction during rotational feeding, avoiding deviations in the drilling trajectory or equipment vibration caused by skewness or swaying. The guide frame includes a rigid support, guide rollers (or sliding sleeves), and an adjustment mechanism. The rigid support is fixedly installed on the machine body or foundation, providing a stable support reference. The guide rollers or sliding sleeves are arranged around the outer circumference of the drill rod, constraining the radial displacement of the drill rod through rolling friction (rollers) or sliding fit (sleeves), allowing it to feed freely along the axial direction. The adjustment mechanism can finely adjust the tilt angle or horizontal position of the guide frame to adapt to the construction requirements of different drilling angles (e.g., vertical holes, inclined holes). In the installation scheme of the magnetostrictive displacement sensor, the side of the guide frame provides a fixed installation reference for the sensor, ensuring that the sensor's retractable measuring rod is parallel to the drill rod axis, thereby accurately capturing the axial displacement of the drill rod.

[0046] Specifically, the drill rod end refers to the front connection point of the drill rod during drilling operations, that is, the end of the drill rod that is directly assembled with the drill bit. When a single drill rod operates independently, the end refers to its front connection interface (e.g., the male threaded end), used to directly install end-effectors such as drill bits, reamers, or core tubes. When multiple drill rods are connected in series to form a drill string, the end refers to the front interface of the drill rod at the very front of the entire drill string. This interface is rigidly connected to the drill bit, and its rear end is sequentially assembled with the male threaded connectors of subsequent drill rods via female threads, forming a long-distance power transmission chain. In depth measurement scenarios, the axial displacement of the drill rod end is strongly correlated with the drilling depth of the drill bit's working face (the two can be considered to move synchronously under rigid connection). Therefore, by rigidly connecting the measuring rod of the magnetostrictive displacement sensor to the drill rod end, the real-time displacement of the end can be directly captured to accurately reflect the drill bit's travel distance. This design avoids displacement transmission errors that may be caused by the gap between the threaded interfaces when multiple drill pipes are connected in series, ensuring that the measured value directly corresponds to the actual drilling depth of the drill bit, and providing a high-precision data benchmark for borehole depth monitoring.

[0047] Specifically, the ranging principle of the magnetostrictive displacement sensor is based on the magnetostrictive effect. When a current pulse propagates along the measuring rod (waveguide wire), it generates a circular magnetic field, which interacts with the magnetic field of the magnetic ring outside the measuring rod (which moves with the drill rod), inducing a torsional wave (stress wave) to propagate to both ends. By measuring the time difference between the return of the current pulse and the torsional wave, the position of the magnetic ring can be calculated, as shown in the following formula: L = v ×2 t Where L is the drilling depth (i.e., the displacement of the magnetic ring, in mm); v is the propagation speed of the torsional wave in the measuring rod (a known constant, determined by the material properties, in mm / μs); and t is the time difference between the current pulse emission and the reception of the torsional wave signal (in μs).

[0048] In some embodiments, the attitude measurement sensor can be a nine-axis inertial measurement unit integrating a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer, tightly fixed at the center of the near-end face of the drill bit of the drilling equipment. The three-axis accelerometer detects the acceleration components of the drilling equipment under the gravitational field in real time, the three-axis gyroscope measures the angular velocity changes of the drilling equipment, and the three-axis magnetometer senses the direction of the geomagnetic field. Using the microprocessor inside the nine-axis inertial measurement unit, the raw data is fused using Kalman filtering, particle filtering, sliding window filtering, or gradient descent methods to accurately calculate attitude measurement data such as the tilt angle, pitch angle, and deviation angle of the drilling equipment, providing crucial information for determining whether the drilling direction and trajectory have deviated.

[0049] In the drill bit structure of drilling equipment, the near-end face center position refers to the geometric center region of the transverse end face of the drill bit near its working end (i.e., the tip side that directly participates in drilling operations). The near-end face refers to the transverse cross-section (circular or regular-shaped plane) at the front end of the drill bit that supports functional components. This end face is perpendicular to the drilling direction and close to the drill tip; the center position refers to the geometric center of symmetry of this end face (e.g., the center of a circular end face). Installing an attitude measurement sensor (e.g., a nine-axis inertial measurement unit) at this location ensures that the sensor coordinate system is naturally aligned with the geometric axis of the drill bit (drilling direction), avoiding centrifugal acceleration interference and mechanical vibration errors caused by eccentric installation. This enables high-precision measurement of the drill bit's attitude (pitch, roll, yaw), providing a reliable data foundation for drilling trajectory control and attitude adjustment.

[0050] Specifically, the gradient descent method (Madgwick algorithm) is an attitude fusion algorithm based on gradient descent optimization, used to process data from nine-axis inertial measurement units (such as three-axis accelerometers, gyroscopes, and magnetometers). By iteratively optimizing quaternion attitude parameters, it minimizes the error between sensor measurements and theoretical values ​​(such as gravity and geomagnetic field direction), thereby estimating the attitude of the device in real time (such as tilt angle, pitch angle, and yaw angle).

[0051] In some embodiments, multiple thin-film pressure sensors can be selected as the pressure sensors. Multiple grooves are evenly formed along the circumferential direction on the outer wall of the drill bit in the drilling equipment. The thin-film pressure sensors are tightly embedded in these grooves, ensuring that their surfaces are flush with the outer wall of the drill bit. During drilling, the borehole wall contacts and is compressed by the drill bit, causing deformation of the sensitive diaphragm of the thin-film pressure sensor. This deformation alters the internal resistance of the sensor, which is converted into a voltage signal output via a Wheatstone bridge circuit. After amplification and filtering by a signal conditioning circuit, pressure data at different locations on the borehole wall can be obtained, allowing for the assessment of borehole wall stability and the timely detection of areas at risk of collapse. This scheme, during the dynamic contact process of drilling, uses a thin-film pressure sensor array to acquire the pressure distribution along the circumferential direction of the borehole wall in real time, providing multi-dimensional data support for borehole wall stability analysis.

[0052] In some embodiments, the optical camera in the optical imaging assembly can be a miniature high-definition industrial camera, paired with an autofocus wide-angle lens, and mounted at the front end of a retractable robotic arm inside the drilling equipment. The supplementary lighting device uses a ring-shaped LED light-emitting diode array, arranged around the lens of the optical camera. By adjusting the brightness and color temperature of the LED array, uniform and sufficient illumination is ensured for the borehole wall. When it is necessary to acquire image data of cracks in the borehole wall, the robotic arm extends to the target position, and the optical camera captures high-definition images at set time intervals or according to instructions. The image data is transmitted to the data processing module via an internal data cable for subsequent crack identification and analysis to determine the integrity and stability of the borehole wall. The aforementioned target position refers to a specific borehole wall area that needs to be detected during the drilling process, which may include: the depth corresponding to the fracture zone marked by geological exploration, the radial orientation of abnormal fluctuations detected by pressure sensors, the borehole segment with abrupt changes in radial offset as shown by laser ranging, the axial position of abnormal vibration spectrum characteristics, crack areas, and borehole walls at different depths.

[0053] In other embodiments, without using a robotic arm, the optical camera can be fixedly mounted at a location on the drilling equipment, for example, around the drill bit. Specifically, a miniature high-definition industrial camera with a wide-angle lens and autofocus can be used, automatically focusing at different distances to capture clear images without a robotic arm. In other embodiments, multiple optical cameras can be mounted at different locations on the drilling equipment (e.g., at different depths or angles) to form a comprehensive image acquisition network. The multiple cameras can work alternately to ensure that crack image data is acquired at every angle and location.

[0054] In some embodiments, the temperature sensor can be a small or lightweight armored thermocouple temperature sensor, installed on the outer surface of the drill bit or the inner surface of the drilling equipment. One or more blind holes are axially opened on the outer surface of the drill bit or the inner surface of the drill rod. The measuring end of the armored thermocouple temperature sensor is embedded in the bottom of the blind hole, and high-temperature resistant thermally conductive adhesive is used to fix the measuring end of the armored thermocouple temperature sensor to the blind hole on the surface of the drill bit or drilling equipment, ensuring good contact between the armored thermocouple temperature sensor and the surface of the drill bit or drilling equipment, thereby achieving accurate measurement of the borehole wall temperature. The blind hole should not be too deep or too close to the working surface of the drill bit. The top (open end) of the blind hole is closed or sealed. After sealing, the inside of the blind hole is filled with a solid material such as thermally conductive adhesive, forming a continuous heat conduction path with the base material, ensuring that the measuring end quickly and accurately receives the temperature change of the base surface. This design utilizes the solid thermal conductivity of the drill bit or drill rod, allowing the temperature sensing end to detect borehole wall temperature changes indirectly through the drill bit or drill rod substrate. This avoids measurement errors caused by direct sensor exposure to the complex drilling environment, and ensures efficient heat conduction through blind hole positioning and thermally conductive adhesive fixation, thus achieving accurate and reliable measurement of borehole wall temperature. During drilling, heat is generated by friction between the borehole wall and the drill bit. The armored thermocouple, based on the Seebeck effect, converts temperature changes into thermoelectric potential signals, which are transmitted to the processing module via compensating wires. After linearization and / or temperature calibration, the processing module obtains accurate borehole wall temperature data. Since temperature changes are related to drilling stability, analyzing the trend of borehole wall temperature data can help determine whether there is abnormal friction or stress concentration in the borehole wall during drilling, providing early warning of risks. Linearization converts the nonlinear thermoelectric potential signal of the thermocouple into a linear temperature output; temperature calibration eliminates sensor system errors, ensuring the accuracy and reliability of the measured values, including zero-point calibration, full-scale calibration, and error correction. The specific methods of linearization processing include: using hardware circuits (such as linearization compensation circuits) or software algorithms (such as polynomial fitting, lookup table method, neural network algorithm) built into the processing module to perform nonlinear correction on the thermoelectric potential signal, so that its output has an approximately linear relationship with the temperature, which facilitates subsequent temperature calculation and analysis.

[0055] In some embodiments, biaxial piezoelectric accelerometers are used as vibration sensors, installed in the middle of the drilling equipment's body and at the drill bit connection point, respectively. The piezoelectric accelerometer installed in the middle of the body detects the overall vibration data of the drilling equipment and monitors abnormal vibrations during operation. The piezoelectric accelerometer installed at the drill bit connection point primarily collects vibration data of the borehole wall, judging its stability by sensing minute vibration changes. Based on the piezoelectric effect, when subjected to vibration, the piezoelectric crystal inside the sensor generates an electric charge, which is converted into a voltage signal by a charge amplifier before being output. Spectral and time-domain analyses are performed on the collected vibration data to extract vibration characteristic parameters, providing a reference for evaluating the drilling operation status and borehole wall stability.

[0056] Specifically, the drill bit connection area refers to the region where the drill bit is directly assembled with the drill rod, drilling rig body, or power transmission components, achieving a mechanical or power connection. This area is located at the tail end (non-working end) of the drill bit, and its specific form depends on the design of the drilling equipment, manifesting as a threaded interface, flange-type connection surface, or quick-change slot structure. Its function is to transmit the rotational torque and propulsion force of the drilling rig host to the drill bit, and to ensure the coaxiality and connection rigidity of the drill bit during high-speed rotation or axial feed. The drilling rig body refers to the main supporting frame of the drilling equipment, integrating the power system and transmission mechanism.

[0057] The biaxial piezoelectric accelerometer is installed here because this part is in direct contact with or adjacent to the borehole wall (especially during deep hole drilling when the gap between the drill bit and the borehole wall is small), and its vibration characteristics are highly coupled with the borehole wall condition. When minor collapses, crack propagation, or localized stress concentrations occur in the borehole wall, high-frequency vibration signals are transmitted through the contact interface between the drill bit and the borehole wall. These signals are then transmitted through the drill bit body to the connection point and captured by the sensor. Compared to global vibration monitoring in the middle of the machine body, the sensor installed at the drill bit connection point can more directly and sensitively reflect the local vibration characteristics of the borehole wall (such as abnormal amplitudes in specific frequency ranges), thus providing more accurate local data support for borehole wall stability assessment. This differentiated sensor layout, combining the mechanical connection characteristics and vibration transmission path of the drilling equipment, achieves dual monitoring of the global operating status and the local borehole wall condition.

[0058] In some embodiments, the laser rangefinder can be a phase-type laser rangefinder, which is fixedly mounted on the side wall of the drilling equipment, specifically the cylindrical outer wall of the drill bit or drill rod, so that the laser emission direction is perpendicular to the borehole wall. The laser emitter inside the laser rangefinder emits a modulated laser beam towards the borehole wall. After being reflected by the borehole wall, the modulated laser beam is received by the laser receiver inside the laser rangefinder. In phase-type ranging, the emitter and receiver are arranged coaxially or in close parallel configuration to ensure effective reception of the reflected light. By measuring the phase difference between the emitted and received laser beams, and combining this with the wavelength of the modulated laser beam, the distance from the laser rangefinder to the borehole wall is calculated. During the rotation of the drilling equipment, the laser rangefinder performs multiple distance measurements at set angular intervals to acquire distance data at different locations on the borehole wall, thereby calculating the radial offset data of the borehole wall. Based on the radial offset data from multiple locations, the shape profile of the borehole can be reconstructed, providing a basis for evaluating drilling quality and adjusting the drilling process. Specifically, by performing three-dimensional fitting on the radial offset data at multiple depth positions along the borehole axis, the cross-sectional profile of the borehole (e.g., ellipticity, irregular protrusions) and axial curvature (e.g., whether the borehole is skewed) can be reconstructed. The principle of phase-based ranging is to calculate the target distance by measuring the phase change of the laser beam during its round trip. Assuming the angular frequency of the modulated laser beam is ω (unit: rad / s), the modulation frequency is f (unit: Hz), the wavelength is λ (unit: m, and λ=c / f, where λ is the speed of light), and the target distance is d, then the time for the laser to travel to and from the target is t=2d / c. Since the phase change of the modulated light over time is... Therefore, the phase difference generated during the laser's round trip This can be expressed as the following formula: This phase difference was measured with high precision. The target distance can then be calculated using the following formula. This enables distance measurement based on phase difference.

[0059] Specifically, fixing the laser rangefinder sensor to the sidewall refers to mounting a phase-type laser rangefinder on the cylindrical outer surface of the drill bit or drill rod. Areas with good rigidity and easy radial scanning, such as the middle or near-end face of the drill bit (the cylindrical section close to the working end), can be selected. During installation, the laser emission window of the sensor must be flush with the outer cylindrical surface of the drill bit or drill rod, and the laser beam emission direction must be strictly perpendicular to the equipment axis (i.e., radially pointing towards the borehole wall), forming a radial scanning path centered on the equipment axis. Multiple sensors evenly distributed circumferentially (or a single sensor rotating with the equipment) can perform radial distance measurement on the borehole wall at set angular intervals during the rotation of the drilling equipment, thereby obtaining distance distribution data in the circumferential direction of the borehole wall. This installation location avoids mechanical interference from drill bit cutting teeth, chip flutes, and other structures, and utilizes the rotational motion of the equipment itself to achieve dynamic scanning of the borehole wall, providing a data acquisition benchmark for subsequent reconstruction of the borehole cross-sectional profile (e.g., ellipticity, irregular deformation) and assessment of axial curvature.

[0060] The processing module includes a data preprocessing unit and an analysis unit; the data preprocessing unit is used to preprocess the drilling parameters to obtain preprocessed drilling parameters; the analysis unit is used to obtain drilling status monitoring results based on the preprocessed drilling parameters.

[0061] In some embodiments, the data preprocessing unit may include hardware circuitry and software algorithms. On the hardware side, a Field-Programmable Gate Array (FPGA) is used as the processing chip, which possesses high-speed parallel processing capabilities and can quickly process a large number of drilling parameters transmitted by the multimodal sensor array. On the data transmission line, signal conditioning circuits such as low-pass filters and amplifiers are set up to perform preliminary processing on the raw data, eliminating high-frequency noise interference and improving signal quality. On the software side, the data preprocessing unit employs a preprocessing program. Upon receiving drilling parameters such as depth data, attitude measurement data, and pressure data, missing value processing is first performed. For a small number of missing data points, Lagrange interpolation is used to fill them. Next, outlier detection is performed, using the 3σ principle to identify and remove obviously abnormal data points. Finally, data of different types and dimensions are normalized and mapped to the [0, 1] interval for subsequent analysis. After the above processing, the preprocessed drilling parameters are obtained.

[0062] In some embodiments, the analysis unit is built on a high-performance server and runs data analysis software. The server adopts a multi-core CPU and GPU collaborative computing architecture to meet the computing resource requirements of complex data analysis. At the software algorithm level, multiple analysis methods are used for different drilling parameters and monitoring targets. For determining the drilling depth and direction, preprocessed depth data and attitude measurement data are used, and a Geographic Information System (GIS) spatial coordinate transformation algorithm is used to convert the attitude data of the drilling equipment into geospatial coordinates. Combined with the depth data, the actual depth and direction of the borehole are calculated. When evaluating the borehole wall stability, preprocessed pressure data, crack image data, temperature data, and vibration data are input into a hybrid deep learning model based on Convolutional Neural Network (CNN) and Long Short-Term Memory network (LSTM). The model learns from a large amount of historical data, extracts data features, and then predicts the borehole wall stability. When determining the borehole shape, a three-dimensional shape model of the borehole is constructed based on the radial offset data of the borehole wall collected by the preprocessed laser rangefinder sensor and a three-dimensional modeling algorithm. Finally, the analysis unit outputs the drilling status monitoring results, such as drilling depth, drilling direction, drilling wall stability, and drilling shape, in the form of visual charts or reports, providing operators with intuitive and accurate drilling status information.

[0063] In a specific embodiment, when determining the borehole shape, based on the pre-processed radial offset data of the borehole wall collected by the laser rangefinder, the following three-dimensional modeling algorithms can be used to construct the three-dimensional shape model of the borehole:

[0064] Moving Least Squares (MLS) is a method that uses locally weighted fitting of the radial offset data points of the borehole wall to construct a local coordinate system centered on the data points. It calculates the local surface at each point and then merges these local surfaces to generate a continuous and smooth 3D borehole surface model. This algorithm is robust to noisy data and can handle irregularly distributed data points well, making it suitable for situations where the borehole shape contains local abrupt changes or complex shapes.

[0065] Triangulation algorithms (such as Delaunay triangulation) treat the borehole wall radial offset data points as discrete points in 3D space. Using the Delaunay triangulation algorithm, non-overlapping triangular facets are constructed between these points, forming a continuous triangular mesh. Each triangular facet represents a portion of the borehole surface, and numerous facets combine to form the 3D shape of the borehole. This method visually represents the geometric contour of the borehole and facilitates subsequent model rendering and analysis.

[0066] The voxelization algorithm divides the spatial region containing the borehole into many small cubic units (voxels). Based on the radial offset data of the borehole wall, it determines whether each voxel belongs to the interior, surface, or exterior of the borehole. By filling or marking the voxels, a three-dimensional voxel model of the borehole is generated. This algorithm is simple, intuitive, easy to implement, and computationally efficient when processing large-scale data, making it suitable for rapid modeling and preliminary analysis of borehole shapes.

[0067] Implicit surface reconstruction algorithms (such as the stepping cube algorithm) first construct an implicit function based on the radial offset data of the borehole wall. This implicit function has a value of zero on the borehole surface and different positive and negative values ​​inside and outside the borehole. Then, the stepping cube algorithm is used to discretize the implicit function and extract the isosurface (i.e., the borehole surface), thereby generating a 3D model. The model surface generated by this algorithm is relatively smooth and can better reflect the true shape of the borehole, making it suitable for scenarios with high model accuracy requirements.

[0068] like Figure 2 As shown, the borehole status monitoring results include: borehole depth analysis results, used to determine whether the borehole depth data has reached the predetermined target depth; borehole direction analysis results, used to determine the borehole direction based on the attitude measurement data of the drilling equipment; borehole wall stability analysis results, used to determine the stability of the borehole wall based on the borehole wall pressure, borehole wall crack image data, borehole wall temperature data, and vibration data during the drilling process, wherein the stability of the borehole wall is related to borehole wall rupture or borehole wall collapse; and borehole shape analysis results, used to determine whether the borehole shape conforms to a predetermined standard based on the radial offset of the borehole wall.

[0069] In some embodiments, the borehole depth data collected by the depth measurement sensor is transmitted to the data preprocessing unit of the processing module via the data transmission module. The data preprocessing unit performs noise reduction, filtering, and missing value completion on the depth data before transmitting it to the analysis unit. The analysis unit pre-stores predetermined target depth data for the borehole operation. By comparing the real-time acquired preprocessed borehole depth data with the predetermined target depth, if the difference is less than a set error threshold (e.g., ±5 cm), it is determined that the borehole depth has reached the predetermined target depth, generating an analysis result indicating that the borehole depth has met the target. If the difference exceeds the error threshold, based on the gap between the current depth data and the target depth, an analysis result indicating that the borehole depth has not met the target and that a remaining drilling depth is required is generated. Simultaneously, suggested drilling speed and other optimization parameters are provided to provide a basis for operators to adjust the borehole operation.

[0070] In some embodiments, attitude measurement data, including tilt angle, pitch angle, and deviation angle, collected by the attitude measurement sensor, is transmitted to the processing module via the data transmission module. After the data preprocessing unit normalizes and removes outliers from the attitude measurement data, the analysis unit converts the processed attitude measurement data into direction parameters in a geographic coordinate system using a geospatial coordinate transformation algorithm. By comparing these direction parameters with the theoretical direction of the drilling design, if the deviation angle between the actual and theoretical directions is within the allowable range (e.g., ±1.5°), an analysis result indicating that the drilling direction meets the requirements is generated. If the deviation angle exceeds the allowable range, the analysis unit calculates the angle compensation value required to adjust the attitude of the drilling equipment based on the deviation, generating an analysis result indicating a drilling direction deviation with correction suggestions. This helps operators correct the drilling direction in a timely manner, ensuring that the drilling trajectory meets the design requirements.

[0071] like Figure 3As shown, in some embodiments, borehole wall pressure data, crack image data, temperature data, and vibration data collected by pressure sensors, optical camera components, temperature sensors, and vibration sensors are transmitted to the processing module via the data transmission module. The data preprocessing unit then sequentially performs format unification and noise reduction on these multi-source data to obtain preprocessed multi-source data. For example, this includes noise-removed pressure data, temperature data, vibration data, and crack image data. The analysis unit constructs a deep learning-based borehole wall stability assessment model. This model uses a convolutional neural network to extract features from the crack image data, extracting features such as crack length, width, and orientation. It also uses a long short-term memory network to perform time-series analysis on the pressure, temperature, and vibration data, extracting time-series features and capturing the trends of data changes over time, such as pressure variation patterns, temperature fluctuations, and vibration periodicity. The extracted feature data are then fused and input into the classifier of the deep learning-based borehole wall stability assessment model, which outputs a prediction of the stability state. If a deep learning-based borehole wall stability assessment model determines that there is a risk of borehole wall rupture or collapse, the analysis results will mark the risk areas in detail and provide targeted suggestions such as reducing drilling speed and increasing wall protection measures.

[0072] Specifically, during the model training and validation phase, the prediction accuracy is evaluated by comparing the classifier output with the actual labels (stability status annotated in historical borehole validation data), and the model parameters are optimized. In the practical application phase, when the model determines that a risk exists, a borehole wall stability analysis report is generated based on the prediction results. This report includes the location of the risk area or targeted suggestions (such as reducing drilling speed, injecting wall protection materials, etc.).

[0073] Specifically, the aforementioned feature data refers to key features extracted from raw data collected from multiple sensors. For example, features of crack image data include crack length, width, orientation, and depth; features of pressure data include pressure variation curves, peak pressure, and average pressure; features of temperature data include temperature variation range and stable temperature interval; and features of vibration data include vibration frequency, amplitude, and period. After processing, this feature data provides multi-dimensional information support for borehole wall stability assessment.

[0074] Specifically, these various feature data can be combined through multimodal data fusion. Fusion methods include weighted averaging, which assigns weights to each data source based on their importance and then synthesizes the features from each source using weighted averages; feature-level fusion, which directly concatenates all feature data into a large feature vector and then inputs it into a classifier for learning; and decision-level fusion, where each data source is analyzed using an independent model, and then the prediction results are fused to arrive at the final decision. These fusion methods can fully utilize the advantages of multiple sensor data, improving the accuracy and robustness of borehole wall stability assessment.

[0075] Specifically, the output of the classifier is a category label representing the stability state of the hole wall, such as "stable", "risk of cracking", "risk of collapse", etc.

[0076] Specifically, increasing borehole wall protection measures refers to reducing the risk of borehole wall collapse or rupture by strengthening the support and protection of the borehole wall. Specific methods may include: reinforcing the structure around the borehole, using specialized wall protection materials, or enhancing borehole wall stability by injecting stabilizing fluids during the drilling process.

[0077] Specifically, risk area location refers to determining the specific location (e.g., depth range, azimuth angle) and its influence range (e.g., crack extension length, stress concentration area radius) in the borehole wall that may fracture or collapse, based on multimodal sensor data (e.g., crack image features, pressure / temperature fluctuation trends, vibration spectrum, etc.) and prediction results of deep learning models, by using coordinate mapping algorithms to associate the abnormal signals identified by the model with the three-dimensional spatial coordinates of the borehole, thereby determining the specific location (e.g., depth range, azimuth angle) of the borehole wall that may fracture or collapse, and the range of influence (e.g., crack extension length, stress concentration area radius), and finally marking it in the borehole structure model in the form of a visualized heat map or coordinate parameters.

[0078] like Figure 4 As shown, in some embodiments, after the radial offset data of the borehole wall collected by the laser rangefinder is transmitted to the processing module, the data preprocessing unit first smooths the data to remove measurement noise, and then transmits the processed data to the analysis unit. The analysis unit stores predetermined standards for the borehole shape, including the allowable radial offset range, shape regularity parameters, etc. By comparing the radial offset data of each measurement point with the predetermined standards one by one, the difference between the actual borehole shape and the predetermined standard shape is calculated. If the difference is within an acceptable range, an analysis result is generated indicating that the borehole shape conforms to the predetermined standards; if the difference exceeds the standards, the analysis unit will generate an analysis result indicating that the borehole shape does not conform to the standards based on the offset of each measurement point, and draw a schematic diagram of the borehole shape deviation. At the same time, it will provide optimization suggestions such as adjusting the rotation parameters and propulsion parameters of the drilling equipment to assist operators in correcting the borehole shape to meet engineering requirements.

[0079] Specifically, the process of generating the borehole shape deviation diagram is as follows: Based on the preprocessed radial offset dataset, the polar coordinate measurements (angle θ, radius r) are first converted into three-dimensional points in a Cartesian coordinate system (x=r·cosθ, y=r·sinθ, z=current section depth), constructing a full-hole three-dimensional point cloud model; the discrete points between adjacent sections are fitted with a spatial surface using a B-spline curve interpolation algorithm to generate the actual borehole three-dimensional geometric model. The actual model is then spatially superimposed with a predetermined standard model (theoretical cylinder or design surface), and a deviation diagram is generated using a corresponding visualization method.

[0080] The processing module also includes an alarm unit, which is used to trigger an alarm signal when the borehole status monitoring result indicates an abnormality.

[0081] In some embodiments, the alarm unit includes hardware and software. The hardware may employ a microcontroller as the processing unit, connected to an audible and visual alarm device, a wireless communication module, and a power management module. The audible and visual alarm device includes a high-brightness red warning light and a high-decibel buzzer, installed in prominent locations in the drilling equipment operating area and the ground monitoring center for easy detection by operators. The wireless communication module uses an industrial-grade 4G or 5G communication module to ensure stable and rapid transmission of alarm signals to the remote monitoring terminal.

[0082] In terms of software, the microcontroller of the alarm unit is pre-configured with alarm thresholds and rule bases for various borehole status monitoring results. When the analysis unit generates borehole depth analysis results, borehole direction analysis results, borehole wall stability analysis results, or borehole shape analysis results, the data is synchronously transmitted to the alarm unit. The alarm unit first analyzes these results. For example, if the borehole depth analysis result shows that the difference between the current depth and the predetermined target depth exceeds the preset error range and the duration exceeds the specified time; or if the deviation angle between the actual direction and the theoretical direction in the borehole direction analysis result is greater than the allowable deviation threshold; or if the borehole wall stability analysis result determines that there is a risk of borehole wall rupture or collapse; or if the borehole shape analysis result shows that the difference between the borehole shape and the predetermined standard exceeds the acceptable range, as long as any of these abnormal conditions are met, the microcontroller of the alarm unit will immediately trigger an alarm signal according to the preset rules.

[0083] Upon triggering the alarm signal, a bright red warning light begins to flash, and a high-decibel buzzer emits a continuous alarm. Simultaneously, the wireless communication module sends alarm data containing detailed information such as the anomaly type, location, and severity to the management system at the ground monitoring center and the mobile terminals of relevant personnel. The management system at the ground monitoring center marks the location of the abnormal borehole on an electronic map in real time and displays a detailed alarm prompt, allowing management personnel to promptly grasp the situation and take appropriate emergency measures. Upon receiving the alarm information from their mobile terminals, personnel can quickly proceed to the site to troubleshoot and resolve the problem, effectively ensuring the safe operation of mine drilling.

[0084] The processing module is connected to a remote monitoring platform to transmit the borehole status monitoring results to the platform in real time. The remote monitoring platform displays the borehole status monitoring results in real time, graphically showing borehole depth, borehole direction, borehole wall stability, and borehole shape. The remote monitoring platform provides real-time alerts based on preset thresholds for the graphically displayed data. When the monitoring data for borehole depth, borehole direction, borehole wall stability, or borehole shape exceeds the normal range, the graphical interface will issue an alarm by flashing, changing color, or displaying a pop-up notification box.

[0085] In some embodiments, the processing module is deployed on a server cluster in the mine surface control center, and its connection with the remote monitoring platform is achieved through an industrial-grade network communication architecture. The network communication part adopts a dual-redundant link design combining wired and wireless links. The wired link uses fiber optic Ethernet, with a dedicated single-mode fiber laid between the mine surface control center and the remote monitoring platform. A stable high-speed data transmission channel is established using the TCP / IP protocol to ensure low latency and high reliability of data transmission. The wireless link uses 5G communication technology and is equipped with an intrinsically safe 5G base station for mining. When the wired link fails, it automatically switches to the wireless link for data transmission, ensuring the continuity of data transmission.

[0086] The processing module includes a data interface adaptation unit responsible for format conversion and encapsulation of borehole status monitoring results. These results include borehole depth analysis, borehole direction analysis, borehole wall stability analysis, and borehole shape analysis. The data interface adaptation unit first encodes this structured data in JSON format, adds metadata such as timestamps and data source identifiers, and then packages the encapsulated data into data packets conforming to the transmission protocol requirements, according to the application programming interface (API) specifications of the remote monitoring platform.

[0087] Once the processing module generates the borehole status monitoring results, the data interface adaptation unit immediately sends the data packets to the network transmission module. Based on the link status, the network transmission module prioritizes the fiber optic Ethernet link and transmits the data packets to the server hosting the remote monitoring platform via network devices such as switches and routers. If the fiber optic link malfunctions, the network transmission module automatically switches to a 5G wireless link, utilizing a 5G base station to transmit the data packets to the remote monitoring platform.

[0088] The remote monitoring platform is built on a cloud computing architecture, possessing distributed storage and parallel computing capabilities. Upon receiving data packets, the platform first decapsulates and verifies their format using a data parsing module, extracting the borehole status monitoring results. This data is then stored in a distributed database and displayed in real-time on a visual interface, intuitively presenting information such as borehole depth, borehole direction, borehole wall stability, and borehole shape through dynamic charts and 3D models. Simultaneously, the platform also provides data query, historical data tracing, and data analysis functions, facilitating remote monitoring of borehole operation status by management personnel and enabling timely decision-making and adjustments.

[0089] The drilling equipment includes a control system; the multimodal sensor group exchanges data with the control system of the drilling equipment wirelessly to trigger the control system of the drilling equipment to realize real-time adjustment of the drilling process.

[0090] Specifically, the control system of the drilling equipment is used for:

[0091] Based on the drilling depth data and the attitude measurement data, adjust the feed speed and feed direction of the drilling equipment;

[0092] Adjust the drill bit pressure and drill bit rotation speed based on the borehole wall temperature data, borehole wall pressure data, vibration data during drilling, and borehole wall crack data.

[0093] Based on the radial offset data of the borehole wall, adjust the spatial position or angle of the drilling equipment to ensure that the borehole maintains a stable shape.

[0094] Based on vibration data during the drilling process, the operating parameters of the drilling equipment are adjusted, including at least one of feed rate, drill bit rotation speed, and drill bit load.

[0095] Based on the borehole wall temperature data, the drilling fluid flow rate and velocity output by the drilling fluid supply system connected to the drilling equipment are adjusted.

[0096] Specifically, feed rate refers to the speed at which the drill bit advances along the borehole axis (axial direction), measured in millimeters per minute. It reflects how quickly the drill bit cuts into the borehole wall material, directly affecting the cumulative rate of borehole depth and material removal efficiency. Its adjustment requires combining borehole depth data (e.g., the deviation between real-time depth and design depth) and attitude measurement data (e.g., borehole skew trend) to control the axial feed rhythm and correct directional deviations. Drill bit rotation speed refers to the rate at which the drill bit rotates around its own axis, measured in revolutions per minute. It reflects the frequency of the drill bit's cutting edge's circumferential motion, determining the contact frequency between the cutting edge and the borehole wall material and the distribution of cutting force. Its adjustment requires reference to borehole vibration data (e.g., high-frequency vibration indicating a mismatch between rotational speed and material hardness) to optimize cutting performance, reduce drill bit wear, and lower vibration risks.

[0097] Specifically, drill bit load refers to the comprehensive mechanical load borne by the drill bit during drilling, mainly including axial pressure (thrust in the feed direction) and rotational torque (resistance torque when cutting material). Its magnitude reflects the strength of the interaction between the drill bit and the hole wall material, and the unit is Newton (N) or Newton-meter. When vibration data shows abnormalities (e.g., high-frequency vibration or amplitude exceeding limits), it indicates that the drill bit load is not matched with the current material hardness and cutting state. That is, excessive load can easily lead to drill bit jamming, accelerated wear, or even breakage, while insufficient load will cause insufficient cutting or slippage. Therefore, the system will adjust the feed rate (changing the axial pressure) and drill bit rotation speed (affecting torque demand) in real time according to the vibration signal, indirectly controlling the drill bit load within a reasonable range. For example, when the vibration is too large, the feed rate will be reduced to reduce the axial pressure, or the rotation speed will be adjusted to optimize the torque distribution, thereby balancing cutting efficiency and drilling equipment stability, and avoiding drilling failures caused by abnormal load.

[0098] In this embodiment, the control system of the drilling equipment employs an industrial-grade programmable logic controller (PLC) paired with an embedded microprocessor to form the control hub. The multimodal sensor array incorporates a low-power Bluetooth communication module and a Wi-Fi module, supporting dual-mode wireless data transmission. After the sensors collect parameters such as drilling depth and attitude measurement data, the data is initially encoded by the sensor's built-in data processing unit and then transmitted to the wireless receiving module of the drilling equipment control system via Bluetooth or Wi-Fi. Upon receiving the data, the control system uses a cyclic redundancy check (CRC) algorithm to verify its integrity, ensuring data accuracy. This enables stable wireless data exchange between the multimodal sensor array and the control system, providing a data foundation for real-time adjustments during the drilling process.

[0099] In this embodiment, after receiving the drilling depth data from the depth measurement sensor and the attitude measurement data from the attitude measurement sensor, the drilling equipment control system compares them with the preset drilling design parameters. When the depth data shows that the current drilling depth is close to the design depth, and the attitude measurement data indicates that there is a deviation in the drilling direction, the control system automatically reduces the feed speed of the drilling equipment through the PID (Proportional-Integral-Derivative) control algorithm, and simultaneously drives the servo motor to adjust the feed direction of the drilling equipment, so that the drilling trajectory gradually returns to the design path. If the drilling depth does not reach the design depth, but the attitude measurement data shows that the drilling is significantly tilted, the control system will immediately stop the feed, recalibrate the attitude of the drilling equipment, and then continue drilling with an appropriate feed speed and direction to ensure that the drilling depth and direction accurately meet the design requirements.

[0100] In this embodiment, the control system receives borehole wall pressure data collected by a pressure sensor, crack data acquired by an optical camera assembly, temperature data collected by a temperature sensor, and vibration data detected by a vibration sensor in real time. When the pressure data shows an abnormally high borehole wall pressure, and the crack data indicates a risk of borehole wall rupture, the control system automatically reduces the drill bit pressure and increases the drill bit rotation speed to reduce stress on the borehole wall, enhance cutting efficiency, and reduce the risk of collapse. If the temperature data shows an excessively high borehole wall temperature, and the vibration data shows abnormal fluctuations, the control system further increases the drill bit rotation speed while appropriately reducing the drill bit pressure, coordinating with adjustments to the drilling fluid supply system to quickly remove heat and stabilize drilling operations, ensuring borehole wall stability.

[0101] In this embodiment, after the radial offset data of the borehole wall collected by the laser rangefinder is transmitted to the control system, the system compares and analyzes it with the preset borehole shape standard. If the radial offset data at a certain depth exceeds the allowable range, the control system calculates the offset direction and amount, and controls the hydraulic support device and the rotation adjustment mechanism of the drilling equipment to work together. For example, when the offset on the left side of the borehole wall is detected to be too large, the hydraulic support device increases the support force on the right side, while the rotation adjustment mechanism fine-tunes the angle of the drilling equipment, causing the drill bit to shift to the left, gradually correcting the borehole shape, and ensuring that the borehole maintains a stable designed shape throughout the entire depth range.

[0102] In another embodiment, the process of adjusting the spatial position or angle of the device based on the radial offset data of the borehole wall is as follows:

[0103] First, the radial offset at different depths of the borehole is collected in real time, which is the coordinate deviation of the center of each cross section relative to the design axis in the horizontal plane (XY plane), generating a continuous offset curve. When the offset at a certain depth exceeds a preset threshold (e.g., 5 mm / m) or a trend deviation occurs (e.g., three consecutive measurement points shift in the same direction with increasing offset), the system determines that the borehole shape is abnormal.

[0104] Secondly, analyze the types of deviations. If the offset continues to increase in a single direction (e.g., continuous offset in the positive X-axis direction), it indicates that there is a systematic deviation in the borehole, and the azimuth angle (rotation angle around the borehole axis) or inclination angle (angle between the borehole equipment axis and the design axis) of the equipment needs to be adjusted. If the offset at a certain depth suddenly increases (e.g., local deviation exceeds 10 mm), it is mostly due to local collapse of the borehole wall or sudden change in rock hardness, and the feed direction of the drill bit needs to be finely adjusted, that is, the horizontal component of the drill bit's axial advance is corrected in real time, i.e., the feed direction vector in the XY plane.

[0105] During the adjustment process, the control system inputs the current offset data into the kinematic model to calculate the parameters that need to be adjusted: for track-mounted drilling rigs, the base is moved or the turntable is rotated by a servo motor to change the drill bit entry position or initial angle; for drilling rigs with hydraulic leveling devices, the inclination and azimuth angles of the drill rod axis are directly changed by adjusting the extension and retraction of the tilting cylinder. After adjustment, the drilling equipment continues drilling in the corrected direction while continuously monitoring subsequent offset data. If the newly acquired offset shows that the deviation has decreased to the allowable range (e.g., cumulative offset per meter is less than or equal to 3 mm), the current parameters are maintained; if the deviation is not effectively improved, the system automatically enters a secondary calibration until the actual borehole shape matches the designed trajectory.

[0106] In this embodiment, the control system performs real-time spectrum analysis on the vibration data of the drilling equipment itself and the borehole wall vibration data collected by the vibration sensor. When the analysis finds that the vibration frequency is close to the natural frequency of the drilling equipment, indicating a risk of resonance, the control system immediately reduces the feed rate and drill bit rotation speed, and appropriately reduces the drill bit load to avoid damage to the drilling equipment due to resonance. If the borehole wall vibration data shows abnormally severe vibration, indicating a decrease in borehole wall stability, the control system will adjust the ratio of feed rate and drill bit rotation speed according to the vibration characteristics, while optimizing the drill bit load, so that the drilling equipment maintains borehole wall stability while ensuring drilling efficiency, thus ensuring the safe conduct of drilling operations.

[0107] In this embodiment, when the temperature sensor detects a change in the borehole wall temperature, the control system compares the temperature data with a preset temperature threshold range. If the borehole wall temperature is higher than the upper threshold, it indicates that excessive heat is generated during drilling. The control system then sends a command to the drilling fluid supply system to increase the drilling fluid flow rate and velocity, accelerating heat exchange and reducing the borehole wall temperature. If the borehole wall temperature is lower than the lower threshold, it will affect the lubrication and wall protection performance of the drilling fluid. The control system then correspondingly reduces the drilling fluid flow rate and velocity to maintain the borehole wall temperature within a suitable range, ensuring that the drilling fluid performs optimally and guaranteeing the smooth progress of drilling operations.

[0108] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0109] Example 2

[0110] like Figure 5 As shown in the figure, this embodiment provides a method for intelligent monitoring of mine boreholes, which includes the following steps:

[0111] S10: Multiple drilling parameters are collected in real time by a multi-modal sensor group installed on the drilling equipment. The multiple drilling parameters include any multiple of the following: drilling depth data, drilling equipment attitude measurement data, drilling hole wall pressure data, drilling hole wall crack image data, drilling process vibration data, and drilling hole wall radial offset data.

[0112] S20: The drilling parameters are transmitted to the processing module via the data transmission module;

[0113] S30: The processing module generates drilling status monitoring results based on the drilling parameters. The drilling status monitoring results include any multiple of the following: drilling depth, drilling direction, drilling wall stability, and drilling shape.

[0114] In some embodiments, step S10 involves real-time acquisition of drilling parameters using a multimodal sensor array, specifically including any of the following:

[0115] The depth data of the borehole is detected by a depth measurement sensor;

[0116] The tilt angle, pitch angle, and deviation angle of the drilling equipment are detected by attitude measurement sensors.

[0117] Pressure data of the borehole wall is detected by a pressure sensor;

[0118] Image data of cracks in the borehole wall are acquired by an optical camera assembly, wherein the optical camera assembly includes an optical camera;

[0119] Temperature data of the borehole wall is detected using a temperature sensor;

[0120] Vibration data during the drilling process is detected by vibration sensors, including vibration data of the borehole wall and vibration data of the drilling equipment.

[0121] The radial offset data of the borehole wall is detected by a laser rangefinder.

[0122] In some embodiments, the step of generating borehole status monitoring results in step S30 includes:

[0123] The drilling parameters are preprocessed by the data preprocessing unit to obtain the preprocessed drilling parameters;

[0124] The analysis unit generates borehole status monitoring results based on the preprocessed borehole parameters.

[0125] In some embodiments, the borehole condition monitoring results include:

[0126] Determine whether the borehole has reached the predetermined target depth based on the depth data;

[0127] The drilling direction is determined based on the attitude measurement data;

[0128] The stability of the borehole wall is determined based on the pressure data, crack image data, temperature data, and vibration data.

[0129] The radial offset data of the borehole wall is used to determine whether the borehole shape meets the predetermined standard.

[0130] In some embodiments, the intelligent monitoring method for mine boreholes further includes the step of triggering an alarm signal when the borehole status monitoring result indicates an abnormality.

[0131] In some embodiments, the intelligent monitoring method for mine boreholes further includes the step of transmitting the borehole status monitoring results to a remote monitoring platform in real time.

[0132] In some embodiments, the intelligent monitoring method for mine boreholes further includes the step of: wirelessly transmitting the data collected by the multimodal sensor group to the control system of the drilling equipment to trigger the control system to adjust the drilling process in real time.

[0133] In some embodiments, the step of adjusting the drilling process in real time includes:

[0134] Adjust the feed rate and feed direction of the drilling equipment based on the depth data and attitude measurement data;

[0135] Adjust the drill bit pressure and rotation speed based on the temperature data, pressure data, vibration data, and crack data;

[0136] Adjust the position or angle of the drilling equipment according to the radial offset data of the borehole wall;

[0137] Adjust the feed rate, drill bit rotation speed, or drill bit load of the drilling equipment based on the vibration data;

[0138] Adjust the flow rate and velocity of the drilling fluid supply system based on the temperature data.

[0139] In some embodiments, the multimodal sensor group is disposed on the drilling rig or drill bit.

[0140] Example 3

[0141] See Figure 6 This application also provides an electronic device 600, which includes:

[0142] At least one processor; and,

[0143] A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform a mine borehole intelligent monitoring method as described in the foregoing method embodiments.

[0144] This application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute a mine borehole intelligent monitoring method as described in the foregoing method embodiments.

[0145] The following is for reference. Figure 6The diagram illustrates a structural schematic of an electronic device 600 suitable for implementing embodiments of this application. The electronic device 600 in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 6 The electronic device 600 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0146] like Figure 6 As shown, electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of electronic device 600. Processing device 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0147] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keys, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although an electronic device 600 with various devices is shown in the figure, it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0148] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined in the methods of the embodiments of this application.

[0149] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof. The aforementioned computer-readable medium can be included in the aforementioned electronic device; or it can exist independently and not assembled into the electronic device.

[0150] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0151] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A mine drilling intelligent monitoring system, characterized in that, The method comprises the following steps: a multi-modal sensor group is arranged on a drilling device to collect a plurality of drilling parameters in real time, wherein the plurality of drilling parameters include any one of drilling depth data, drilling device attitude measurement data, drilling hole wall pressure data, drilling hole wall crack image data, drilling process vibration data, and drilling hole wall radial offset data; a data transmission module is connected to the multi-modal sensor group to transmit the drilling parameters to a processing module; a processing module is used to generate drilling state monitoring results according to the drilling parameters, wherein the drilling state monitoring results include any one of drilling depth, drilling direction, drilling hole wall stability, and drilling shape; the multi-modal sensor group comprises: a depth measurement sensor arranged on the drilling device to detect drilling depth data; an attitude measurement sensor arranged on the drilling device to detect drilling device attitude measurement data including inclination angle, pitch angle, and deviation angle; a pressure sensor arranged on the drilling device to detect drilling hole wall pressure data, wherein the pressure data is associated with drilling hole wall stability; an optical camera assembly arranged on the drilling device, wherein the optical camera assembly includes an optical camera to collect drilling hole wall crack image data, and the crack image data is associated with drilling hole wall stability; a temperature sensor arranged on the drilling device to detect drilling hole wall temperature data, wherein the drilling hole wall temperature data is associated with drilling hole wall stability; a vibration sensor arranged on the drilling device to detect drilling process vibration data, wherein the vibration data is associated with drilling hole wall stability, and the drilling process vibration data includes drilling hole wall vibration data and drilling device vibration data; a laser ranging sensor arranged on the drilling device to detect drilling hole wall radial offset data, wherein the drilling hole wall radial offset data is associated with drilling shape; the processing module comprises a data preprocessing unit and an analysis unit; the data preprocessing unit is used to preprocess the drilling parameters to obtain preprocessed drilling parameters; the analysis unit is used to obtain drilling state monitoring results according to the preprocessed drilling parameters; the drilling state monitoring results include: drilling depth analysis results for determining whether the drilling depth data reaches a predetermined target depth; drilling direction analysis results for determining the drilling direction according to the drilling device attitude measurement data; The drilling hole wall stability analysis result is used to determine the stability of the drilling hole wall based on pressure data of the drilling hole wall, crack image data of the drilling hole wall, temperature data of the drilling hole wall and vibration data in the drilling process, and a hole wall stability evaluation model constructed based on a convolutional neural network and a long short-term memory network, the drilling hole wall stability being associated with hole wall rupture or hole wall collapse; the hole wall stability evaluation model extracts crack feature data including length, width and strike of the crack by using the convolutional neural network to extract features from the crack image data; the long short-term memory network is used to perform time series analysis on the pressure data, the temperature data and the vibration data to extract time series feature data; the extracted various types of feature data are fused and input into a classifier of the hole wall stability evaluation model, and a prediction result of the stability state is output by the classifier; if the hole wall stability evaluation model determines that there is a risk of rupture or collapse of the hole wall, the position of the hole wall where the risk of rupture or collapse exists is located, and a suggestion of reducing the drilling speed or increasing the hole wall protection measures for the drilling hole wall is given; The drilling hole shape analysis result is used to construct a three-dimensional shape model of the drilling hole by using a plurality of three-dimensional modeling algorithms according to the radial offset data of the drilling hole wall, so as to determine whether the shape of the drilling hole conforms to a predetermined standard according to the difference between the constructed three-dimensional shape model of the drilling hole and a predetermined standard model of the drilling hole; the three-dimensional modeling algorithms include a moving least squares method, a triangular meshing algorithm, a voxelization algorithm and an implicit surface reconstruction algorithm; and a deviation diagram of the drilling hole shape is generated based on the radial offset data of the drilling hole wall when the drilling hole does not conform to the predetermined standard.

2. The mine drilling intelligent monitoring system according to claim 1, characterized in that, The processing module further includes an alarm unit configured to trigger an alarm signal when the drilling state monitoring result indicates an abnormality.

3. The mine drilling intelligent monitoring system according to claim 1, characterized in that, The processing module is connected to a remote monitoring platform and configured to transmit the drilling state monitoring result to the remote monitoring platform in real time. The processing module is deployed on a server cluster of a mine ground control center. The remote monitoring platform is configured to display the drilling state monitoring result in real time and display the drilling depth, the drilling direction, the stability of the drilling hole wall and the drilling hole shape in a graphical manner.

4. The mine drilling intelligent monitoring system according to claim 1, characterized in that, The drilling device includes a control system. The multi-modal sensor group exchanges data with the control system of the drilling device in a wireless manner to trigger the control system of the drilling device to adjust the drilling process in real time.

5. The mine drilling intelligent monitoring system according to claim 4, characterized in that, The control system of the drilling device is specifically configured to: adjust the feed speed and the feed direction of the drilling device according to the depth data of the drilling hole and the attitude measurement data; adjust the bit pressure and the bit rotation speed according to the temperature data of the drilling hole wall, the pressure data of the drilling hole wall, the vibration data in the drilling process and the crack data of the drilling hole wall; adjust the spatial position or the angle of the drilling device according to the radial offset of the drilling hole wall; adjust the operating parameters of the drilling device according to the vibration data in the drilling process, the operating parameters including at least one of the feed speed, the bit rotation speed and the bit load. Adjusting drilling fluid flow rate and flow velocity outputted by drilling fluid supply system connected with drilling equipment according to temperature data of borehole wall. 6.The mine drilling intelligent monitoring system according to claim 1, characterized in that, the depth measuring sensor is a magnetostrictive displacement sensor, an axial fixed installation of the magnetostrictive displacement sensor is on a guide frame side of a drill rod of the drilling equipment, and a telescopic measuring rod of the magnetostrictive displacement sensor is connected with an end of the drill rod; the pressure sensor is a plurality of thin film pressure sensors, a plurality of grooves are evenly arranged on an outer wall of a drill bit of the drilling equipment in a circumferential direction, and the plurality of thin film pressure sensors are closely embedded in the plurality of grooves, and a surface of the thin film pressure sensor is flush with the outer wall of the drill bit; the attitude measuring sensor is a nine-axis inertial measurement unit integrating a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and is fixed on a center of a transverse end face of the drilling equipment close to a front end of the drill bit; the optical camera is arranged at a front end of the drill bit of the drilling equipment or is installed around the drill bit of the drilling equipment; the temperature sensor is an armored thermocouple temperature sensor, at least one blind hole is arranged on an outer surface of the drill bit, a temperature measuring end of the armored thermocouple temperature sensor is embedded in a bottom of the blind hole, and the temperature measuring end of the armored thermocouple temperature sensor is fixed with the blind hole by using heat-conducting glue; the vibration sensor is a piezoelectric acceleration sensor, and is respectively installed at a middle part of a machine body and a drill bit connecting part of the drilling equipment; the piezoelectric acceleration sensor installed at the middle part of the machine body is used for detecting vibration data of the whole drilling equipment; and the piezoelectric acceleration sensor installed at the drill bit connecting part is used for collecting vibration data of the borehole wall; the laser ranging sensor is a phase laser range finder, and the phase laser range finder is fixedly installed on an outer wall of the drill bit or the drill rod, so that a laser emission direction is perpendicular to the borehole wall.

7. A method for intelligent monitoring of a mine borehole, characterized by, The method is based on the mine drilling intelligent monitoring system according to any one of claims 1-6, and the method comprises the following steps: collecting a plurality of drilling parameters in real time through a plurality of multi-modal sensors arranged on the drilling equipment, the plurality of drilling parameters comprising any one or more of depth data of the drilling, attitude measuring data of the drilling equipment, pressure data of the borehole wall, crack image data of the borehole wall, vibration data in the drilling process, and radial offset data of the borehole wall; transmitting the drilling parameters to a processing module through a data transmission module; generating drilling state monitoring results according to the drilling parameters through the processing module, the drilling state monitoring results comprising any one or more of drilling depth, drilling direction, borehole wall stability and drilling shape.

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