Drill bit temperature self-adaptive control method based on drilling sensing

Abstract

The invention discloses a drill bit temperature self-adaptive control method based on drilling sensing, and relates to the technical field of intelligent control. Acquiring multi-modal data, calculating an intensity difference value of adjacent sampling points based on the reflected wave intensity sequence, identifying a rock stratum interface position according to the intensity difference value, and calculating a thermal conductivity difference ratio of two sides of an interface and an interface position coordinate through a rock stratum attribute model; when the thermal conductivity difference ratio reaches a temperature rise prediction threshold value, calculating predicted temperature rise based on the multi-modal data, and generating a basic cooling compensation scheme; when the thermal conductivity difference ratio is increased to an inhibition response threshold value, an enhanced cooling compensation scheme is generated based on parameters after predicted temperature rise and load reduction; actual temperature rise data is monitored in real time, the error amplitude of temperature rise is compared and predicted, and the compensation coefficient of the basic cooling compensation scheme is updated; and a thermal field distribution diagram is constructed based on the multi-modal data and the interface position coordinates, a high-temperature hot spot area is marked, a corrected environment temperature value is output, and basic cooling compensation scheme parameters are updated.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a drill bit temperature adaptive control method based on drilling sensing. Background Technology

[0002] During rock drilling rig operations, excessively high drill bit temperatures significantly exacerbate drill bit wear, shorten service life, and can even lead to thermal cracking or stuck drill accidents. Existing technologies suffer from systemic flaws: temperature monitoring mechanisms are severely inadequate; traditional methods rely on single-point contact temperature measurement, failing to capture dynamic temperature changes at rock interfaces, resulting in missed detection of critical temperature jumps; cooling regulation systems are severely disconnected from the actual drill bit temperature, with cooling water or airflow control relying on fixed parameters or manual experience, lacking precise linkage with real-time operating conditions, creating a dual contradiction of insufficient cooling of hard rock layers and excessive cooling of soft rock layers; and safety protection systems have blind spots, with localized high-temperature hotspots not being promptly identified and sudden changes in rock hardness not being effectively predicted, resulting in persistently high risks of thermal cracking and stuck drills. These deficiencies collectively lead to a significant increase in the overall cost of drill bit wear, low operational efficiency, and prominent safety hazards, necessitating the reconstruction of a fully integrated collaborative mechanism for temperature monitoring, cooling control, and safety protection through intelligent technology. Summary of the Invention

[0003] This application provides a drill bit temperature adaptive control method based on drilling perception, which solves the problems of blind spots in rock interface temperature rise monitoring, disconnect between cooling control and operating conditions, and lagging safety protection in the prior art, and realizes full-link collaborative optimization of dynamic control of drill bit temperature and safety protection.

[0004] This application provides a drill bit temperature adaptive control method based on drilling sensing, including:

[0005] S1: Acquire multimodal data including reflected waves, drilling pressure and rotation speed; calculate the intensity difference between adjacent sampling points based on the reflected wave intensity sequence; identify the rock layer interface location based on the intensity difference; and calculate the thermal conductivity difference ratio on both sides of the interface and the interface location coordinates through the rock layer property model.

[0006] S2: When the thermal conductivity difference ratio reaches the temperature rise prediction threshold, the predicted temperature rise is calculated based on multimodal data to generate a basic cooling compensation scheme; when the thermal conductivity difference ratio rises to the suppression response threshold, an enhanced cooling compensation scheme is generated based on the predicted temperature rise and the parameters after load reduction.

[0007] S3: Monitor actual temperature rise data in real time, compare the error range with the predicted temperature rise, and update the compensation coefficient of the basic cooling compensation scheme based on the predicted error range; when the actual temperature rise exceeds the critical threshold, trigger the graded early warning protocol and execute shutdown protection.

[0008] S4: Construct a thermal field distribution map based on multimodal data and interface location coordinates, mark high-temperature hot spots, solve the interference from adjacent vehicles through a thermal radiation transfer model, output the corrected ambient temperature value, and update the parameters of the basic cooling compensation scheme.

[0009] Furthermore, the reflected wave intensity difference includes: collecting a sequence of reflected wave intensity values ​​{I1, I2, ..., I...} along the borehole depth direction. n} Calculate the change in reflected wave intensity between adjacent sampling points:

[0010] ΔI k =|I k -I k-1 |,

[0011] Where, ΔI k I represents the difference in intensity of the reflected waves. k Let ΔI be the intensity value of the reflected wave. k When the value is greater than 10dB, the location is determined to be a rock stratum interface.

[0012] Furthermore, the thermal conductivity difference ratio includes: converting the reflected wave intensity into rock layer density:

[0013] ρ = a·log(I / I0) + b,

[0014] Where ρ is the rock layer density, I is the reflected wave intensity value, I0 is the reference reflected intensity, a is the density sensitivity coefficient to the acoustic response, and b is the minimum reference density.

[0015] Converting rock density to rock hardness:

[0016] H=C1·ρ n +C2,

[0017] Where H is the rock layer hardness, C1 is the scale coefficient of hardness density, n is the nonlinear exponent term, and C2 is the basic hardness term.

[0018] Converting rock hardness into rock thermal conductivity:

[0019] DR = a·H B ,

[0020] Wherein, DR is the thermal conductivity of the rock strata, a is the scale coefficient, and B is the nonlinear exponent. All coefficients are calibrated through core experiments.

[0021] Calculate the difference in thermal conductivity:

[0022]

[0023] Among them, G k The thermal conductivity difference ratio, DR a For the thermal conductivity of the rock strata in front of the interface, DRb The thermal conductivity of the rock strata behind the interface reflects the degree of change in the heat conduction capacity on both sides of the interface.

[0024] Furthermore, the predicted temperature rise includes: calculating the expected temperature rise range based on the hardness difference between the preceding and following rock strata.

[0025]

[0026] Where, ΔT p To predict the temperature rise, P is the drilling rig pressure, V is the drill bit edge linear velocity, μ is the drill bit rock friction coefficient, and Δt is the heat accumulation time (m·°C). p For the heat capacity of the drill bit, λ·G k For the thermal resistance gain at the rock interface, ΔT env β represents the environmental temperature variable, and β is the environmental sensitivity coefficient.

[0027] Furthermore, the basic cooling compensation scheme includes: calculating the initial cooling flow rate based on the predicted temperature rise and cooling efficiency coefficient.

[0028] Q init =k·ΔT p ,

[0029] Among them, Q init Let Q be the initial cooling flow rate, k be the cooling efficiency coefficient, and Q be... init It is converted into a current signal to drive the intelligent cooling regulating valve to execute the basic cooling compensation scheme.

[0030] Furthermore, the enhanced cooling compensation scheme includes: setting a load reduction ratio based on the thermal conductivity difference ratio.

[0031]

[0032] Among them, P re U is the drilling pressure after deloading, P is the drilling pressure before deloading, and U is the drilling pressure before deloading. re U represents the rotational speed after unloading, and U represents the rotational speed before unloading. The coefficients 0.6 and 0.4 were calibrated through rock impact tests.

[0033] Calculate the enhancement compensation based on the initial cooling flow rate:

[0034]

[0035] Where ΔQ is the reinforcement compensation term, and η is the reinforcement coefficient. Nonlinear thermal accumulation in hard rock layers;

[0036] Calculate the total cooling flow based on the enhancement compensation term and the initial cooling flow:

[0037] Q total =Q init +ΔQ,

[0038] Among them, Q total To compensate for the total cooling flow rate, additional cooling capacity is added to the basic cooling compensation scheme to prevent the drill bit from overheating and being damaged.

[0039] Furthermore, the compensation coefficients of the updated basic cooling compensation scheme include: updating the compensation coefficients based on the predicted temperature rise error magnitude:

[0040]

[0041] Where C is the compensation coefficient, C old λ is the compensation coefficient for the previous cycle, ΔT is the update sensitivity coefficient, and ΔT is the value of ΔT. act This represents the actual temperature rise. To predict the relative error of temperature rise;

[0042] Adjust the cooling flow rate according to the compensation coefficient:

[0043] Q ad =Q init ·C,

[0044] Among them, Q ad To compensate for the cooling flow rate.

[0045] Furthermore, the graded early warning protocol includes: triggering a three-level response mechanism when the actual temperature rise data exceeds a preset safety threshold; in the first-level early warning state, audible and visual alarm devices are activated and high-temperature risk points at the borehole location are marked, and potential danger areas are marked in real time on the thermal field distribution map; in the second-level early warning state, an enhanced cooling compensation scheme is forcibly activated and the load reduction ratio is increased, environmental parameters are corrected through a thermal radiation model, and a real-time adjustment panel pops up on the drilling rig control interface; in the third-level early warning state, the power supply is immediately cut off and the hydraulic lock is released, a borehole risk analysis report is generated based on the rock stratum interface location, and thermal conductivity difference ratio data is persistently stored for fault tracing.

[0046] Furthermore, the corrected ambient temperature value includes: calculating the adjacent vehicle interference factor using a thermal radiation transfer model.

[0047]

[0048] Where, k int The adjacent vehicle interference factor reflects the heat radiation transfer efficiency, A is the drill bit's heated area, h is the convective heat transfer coefficient, ∈ is the emissivity, σ is the Stefan-Boltzmann constant, and T en T represents the surface temperature of the adjacent vehicle. env For ambient temperature, T 4 The radiant energy is proportional to the fourth power of the absolute temperature, and d is the distance between the vehicle and the adjacent vehicle.

[0049] Calculate the corrected ambient temperature value based on the adjacent vehicle interference factor:

[0050] ΔT corr =ΔT env +β corr ·k int ,

[0051] Where, ΔT corr To correct for ambient temperature values, β corr To correct the sensitivity coefficient, the environmental temperature variable parameters in the basic cooling compensation scheme are updated in real time based on the corrected ambient temperature value.

[0052] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0053] A rock stratum interface identification mechanism driven by reflected wave intensity difference is used to achieve precise positioning of rock stratum interfaces; a graded control strategy based on thermal conductivity difference ratio is used to construct a closed-loop response chain of predicted temperature rise, dynamic load reduction, and enhanced cooling, eliminating the contradiction between cooling control and operating conditions; through adjacent vehicle interference correction and graded early warning protocol guided by thermal field distribution map, safety protection is moved forward, significantly suppressing the risks of thermal fracturing and stuck drill bit; finally, relying on the dynamic update mechanism of compensation coefficient and multimodal data fusion architecture, a full-link collaborative optimization is formed, which improves temperature control accuracy while reducing overall energy consumption and extending drill bit service life. Attached Figure Description

[0054] Figure 1 This is a flowchart of the drill bit temperature adaptive control method based on drilling sensing in an embodiment of the present invention. Detailed Implementation

[0055] To facilitate understanding of the present invention, a more complete description of this application will be given below with reference to the accompanying drawings, which illustrate preferred embodiments of the invention. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to enable a more thorough and complete understanding of the disclosure of the present invention.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to limit the invention; the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0057] Example 1: As Figure 1 As shown, an adaptive control method for drill bit temperature based on drilling sensing is proposed.

[0058] S1: Acquire multimodal data including reflected waves, drilling pressure and rotation speed; calculate the intensity difference between adjacent sampling points based on the reflected wave intensity sequence; identify the rock layer interface location based on the intensity difference; and calculate the thermal conductivity difference ratio on both sides of the interface and the interface location coordinates through the rock layer property model.

[0059] Specifically, at the start of drilling, the central controller sends a synchronization signal to activate the sensor array. Every 10ms, a data packet is collected, including: reflected wave sequence, drill pressure, rotational speed, drilling depth, timestamp, and ambient temperature. The multi-source data is fused using a Kalman filter to eliminate noise and generate a data stream with unified spatiotemporal coordinates. The multimodal data of reflected waves, drill pressure, and rotational speed constitutes drilling sensing.

[0060] The reflected wave intensity difference includes: emitting pulsed acoustic waves using a high dynamic range sensor and receiving the reflected signals from the borehole wall; and collecting a sequence of reflected wave intensity values ​​{I1, I2, ..., I...} along the borehole depth direction. n}, where each I k The unit is dB, the sampling interval is 1 cm, calculate the change in reflected wave intensity between adjacent sampling points:

[0061] ΔI k =|I k -I k-1 |,

[0062] Where, ΔI k I represents the difference in intensity of the reflected waves. k Let ΔI be the intensity value of the reflected wave. k When the value is greater than 10dB, the location is determined to be a rock stratum interface.

[0063] Specifically, drilling pressure parameters are acquired in real time through pressure sensors installed in the drilling rig's hydraulic system, and the output is the drilling pressure value. The sampling frequency is synchronized with the reflected wave to ensure data time alignment. The drilling pressure data needs to be compensated according to the drill pipe inclination angle, and the correction formula is as follows:

[0064] P corr =P·cosθ,

[0065] Among them, P corr To correct the drilling pressure and eliminate the influence of angular deviation on pressure measurement, P is the drilling pressure before correction, and cosθ is the drill pipe inclination angle.

[0066] The rotational speed is obtained via a Hall effect encoder on the drill bit spindle, with a sampling frequency of 100Hz. The rotational speed needs to be converted to the linear velocity of the drill bit edge using the following formula:

[0067]

[0068] Where V is the linear velocity of the drill bit edge, D is the drill bit diameter, n is the rotational speed, 60 is the conversion factor, and π is pi.

[0069] The thermal conductivity difference ratio includes: converting reflected wave intensity into rock layer density.

[0070] ρ = a·log(I / I0) + b,

[0071] Where ρ is the rock density, I is the reflected wave intensity, I0 is the reference reflected intensity, and a is the density sensitivity coefficient to the acoustic response, determined through core calibration experiments; for example, in sandstone, a ≈ 250 kg / m³. 3 For every 10 dB increase in reflection intensity, the density increases by approximately 250 kg / m³. 3 b is the minimum baseline density;

[0072] Converting rock density to rock hardness:

[0073] H=C1·ρ n +C2,

[0074] Where H represents the rock layer hardness, and C1 is the scale factor of hardness density, determined experimentally, such as 5 × 10⁻⁶ for granite. -5 n is a nonlinear exponent, such as [1.5, 2.0] for crystalline rocks and [0.8, 1.2] for sedimentary rocks, and C2 is the basic hardness term;

[0075] Converting rock hardness into rock thermal conductivity:

[0076] DR = a·H B ,

[0077] Wherein, DR is the thermal conductivity of the rock strata, a is the scale coefficient, such as granite, with a value range of [0.8, 1.2], and B is the nonlinear index, such as granite, with a value range of [-0.25, 0.18]. All coefficients are calibrated through core experiments.

[0078] Calculate the difference in thermal conductivity:

[0079]

[0080] Among them, G k The thermal conductivity difference ratio, DR a For the thermal conductivity of the rock strata in front of the interface, DR b The thermal conductivity of the rock strata behind the interface reflects the degree of change in the heat conduction capacity on both sides of the interface.

[0081] With the borehole starting point as the origin, the location of the rock strata interface is:

[0082] Z k = k × 1 cm,

[0083] Among them, Z k Let k be the depth coordinate, and k be the coordinate that satisfies ΔI. k Sampling point number >10dB;

[0084] The borehole azimuth and dip angles are obtained using the drill rig's attitude sensor, and the three-dimensional coordinates are calculated based on the depth.

[0085]

[0086] Where θ is the borehole inclination angle. Generate coordinates (x, y, z) for the borehole azimuth.

[0087] S2: When the thermal conductivity difference ratio reaches the temperature rise prediction threshold, the temperature rise is predicted based on multimodal data, and a basic cooling compensation scheme is generated.

[0088] Specifically, when the thermal conductivity difference reaches the temperature rise prediction threshold, the temperature rise prediction calculation process is triggered. The temperature rise prediction threshold is calibrated through rock thermal shock experiments. For example, the temperature rise prediction threshold for sandstone and granite is [0.6, 0.8], and the temperature rise prediction threshold for shale and granite is [0.3, 0.5].

[0089] The predicted temperature rise includes: calculating the expected temperature rise range based on the difference in hardness between the preceding and following rock layers.

[0090]

[0091] Where, ΔT p To predict the temperature rise, P is the drilling rig pressure, V is the drill bit edge linear velocity, μ is the drill bit rock friction coefficient, and Δt is the heat accumulation time (m·°C). p For the heat capacity of the drill bit, λ·G k For the thermal resistance gain at the rock interface, ΔT env β represents the environmental temperature variable, and β is the environmental sensitivity coefficient.

[0092] The basic cooling compensation scheme includes: calculating the initial cooling flow rate based on the predicted temperature rise and cooling efficiency coefficient.

[0093] Q init =k·ΔT p ,

[0094] Among them, Q init Let Q be the initial cooling flow rate, k be the cooling efficiency coefficient, and Q be... init Converted to current signal:

[0095]

[0096] Among them, I out For current signals, Q min Q is the minimum flow threshold for the cooling system.max The maximum flow rate threshold for the cooling system is defined by 4, where 4 represents the 4mA offset and 16 represents the 16mA dynamic range. The flow rate range [Q] is defined as follows: min Q max A linear mapping is made to [4,20] mA. If I out <3.8mA, trigger signal loss alarm, switch to backup PID controller; if I out >20.5mA, forcibly locking the valve opening to 95%.

[0097] Step S2 also includes: when the thermal conductivity difference ratio rises to the suppression response threshold, generating an enhanced cooling compensation scheme based on the predicted temperature rise and parameters after unloading;

[0098] Specifically, the suppression response threshold is calibrated through rock impact experiments:

[0099] Y z =min{G k |T w ≥50%, S max},

[0100] Among them, Y z To suppress the response threshold, T w S is the measured temperature rise rate. max For safety limits, when G k When the rate of temperature rise approaches 50% of the safety limit, take this value as G. k To suppress the response threshold.

[0101] The enhanced cooling compensation scheme includes: when the thermal conductivity difference is greater than G k Rise to the suppression response threshold Y z At that time, the load reduction ratio is set based on the difference in thermal conductivity:

[0102]

[0103] Among them, P re U is the drilling pressure after deloading, P is the drilling pressure before deloading, and U is the drilling pressure before deloading. re U is the rotational speed after unloading, and U is the rotational speed before unloading. The coefficients 0.6 and 0.4 are calibrated through rock impact tests and are usually between [0.3, 0.7].

[0104] Calculate the enhancement compensation based on the initial cooling flow rate:

[0105]

[0106] Where ΔQ is the reinforcement compensation term, and η is the reinforcement coefficient. For nonlinear thermal accumulation in hard rock layers, the index 1.5 is derived by fitting experimental data on thermal accumulation in hard rock layers such as granite and quartzite, reflecting the nonlinear characteristics of thermal accumulation.

[0107] Calculate the total cooling flow based on the enhancement compensation term and the initial cooling flow:

[0108] Q total =Q init +ΔQ,

[0109] Among them, Q total For the total cooling flow rate, Q total Converted to valve control current, if I out >20.5mA, forcibly locks the valve opening to 95% and activates overload protection.

[0110] S3: Monitor actual temperature rise data in real time, compare the error range with the predicted temperature rise, and update the compensation coefficient of the basic cooling compensation scheme based on the predicted error range; when the actual temperature rise exceeds the critical threshold, trigger the graded early warning protocol and execute shutdown protection.

[0111] Specifically, the compensation coefficients for updating the basic cooling compensation scheme include: updating the compensation coefficients based on the predicted temperature rise error magnitude:

[0112]

[0113] Where C is the compensation coefficient, C old λ is the compensation coefficient for the previous cycle, ΔT is the update sensitivity coefficient, and ΔT is the value of ΔT. act This represents the actual temperature rise. To predict the relative error of temperature rise;

[0114] Adjust the cooling flow rate according to the compensation coefficient:

[0115] Q ad =Q init ·C,

[0116] Among them, Q ad To compensate for the cooling flow rate.

[0117] Specifically, calculate the critical threshold:

[0118] T crit =β s ·S max +ΔT env ,

[0119] Among them, T crit β is the critical threshold. s For safety factor, the default safety factor is 0.9, providing a 10% safety margin.

[0120] The graded early warning protocol includes: triggering a three-level response mechanism when the actual temperature rise exceeds a preset safety threshold; in the first-level early warning state, audible and visual alarm devices are activated and high-temperature risk points at the borehole location are marked, and potential danger areas are marked in real time on the thermal field distribution map; in the second-level early warning state, an enhanced cooling compensation scheme is forcibly activated and the load reduction ratio is increased, environmental parameters are corrected through a thermal radiation model, and a real-time adjustment panel pops up on the drilling rig control interface; in the third-level early warning state, the power supply is immediately cut off and the hydraulic lock is released, a borehole risk analysis report is generated based on the rock stratum interface location, and thermal conductivity difference ratio data is persistently stored for fault tracing.

[0121] Specifically, when the actual temperature rise exceeds 80% of the critical threshold, a level one warning is triggered, activating the audible and visual alarm device. The alarm signal is simultaneously transmitted to the control room and mobile terminal, and the high-temperature coordinates are located based on the thermal field distribution map.

[0122]

[0123] Mark the risk areas in the 3D thermal field map and store the current G. k ΔT act The coordinates are then marked as potential hazard points.

[0124] When ΔT act >T crit When the time is right, a level 2 warning is triggered, and the enhanced cooling compensation scheme is forcibly started. The real-time temperature rise curve, parameters after load reduction, and cooling flow adjustment value are dynamically displayed on the drilling rig control interface.

[0125] When ΔT act >1.2×T crit When a Level 3 early warning is triggered, the main circuit is disconnected via a solid-state relay with a response delay of ≤7ms. The hydraulic system pressure relief valve opens, the drill pipe mechanical lock is released, and a risk analysis report is generated, including thermal conductivity difference ratio, rock interface coordinates, peak temperature, trigger time, and rock type. This report is stored in G. k Sequence,S max The temperature rise curve is uploaded to the cloud database to support fault tracing.

[0126] For example, during a deep-hole drilling project operating within a stable granite layer, the drill rig's sensors suddenly detected a drastic change in lithology. The system determined that the drill bit was entering a harder quartzite interlayer from the granite, facing a risk of uncontrolled temperature rise. The reflected wave sensor mounted on the drill pipe first captured a strong signal abrupt change, with an intensity difference reaching 38 dB, far exceeding the 30 dB threshold. Within 0.1 seconds, the system identified this as a rock interface and precisely located it at a drilling depth of 205.7 meters. Based on the reflected wave characteristics, the rock layer property model determined that the quartzite layer ahead was extremely hard, with a calculated thermal conductivity difference ratio as high as 0.75. The system immediately classified the temperature rise risk level as high. The system is based on a G value as high as 0.75. k Based on real-time drill pressure and rotation speed data, the system predicted that the drill bit temperature would rapidly rise above 40 degrees Celsius within a short period. The control system automatically generated a basic cooling command, increasing the initial cooling water flow rate from the usual 5 liters / minute to 6.35 liters / minute to address the anticipated temperature rise. The high-temperature thermocouple near the drill bit continuously transmitted data. The system detected an actual temperature rise to 45.8 degrees Celsius, approximately 8.3% higher than the predicted 42.3 degrees Celsius. A dynamic compensation mechanism was immediately activated, slightly increasing the cooling flow rate to 6.6 liters / minute to precisely eliminate the error. Due to the extremely hard rock formation, the system automatically determined that the basic cooling solution was insufficient and immediately triggered a higher-level enhanced cooling compensation scheme. Ultimately, the drill bit temperature was effectively suppressed before reaching the dangerous critical value of 50 degrees Celsius and stabilized within a safe range of approximately 43 degrees Celsius. The system simultaneously highlighted this high-risk location in red on the thermal distribution map on the operating interface and archived all operation logs and rock formation data.

[0127] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0128] This application achieves millimeter-level precise positioning of rock strata interfaces through a rock interface identification mechanism driven by reflected wave intensity difference, solving the problem of missed detection of interface temperature rise jumps caused by traditional single-point temperature measurement. Based on a graded control strategy of thermal conductivity difference ratio, a closed-loop response chain of predicted temperature rise, dynamic load reduction, and enhanced cooling is constructed. By matching cooling flow rate with rock strata heat accumulation characteristics in real time, the dual contradiction of insufficient cooling of hard rock strata and excessive cooling of soft rock strata is eliminated. Combined with adjacent vehicle interference correction guided by thermal field distribution map and a three-level early warning protocol, safety protection is moved forward to the early stage of temperature rise. Through multi-level responses such as audible and visual alarms, forced parameter adjustment, and emergency shutdown, the risk of drill bit thermal cracking and stuck drill bit is significantly suppressed. Finally, relying on the dynamic update mechanism of compensation coefficient and multi-modal data fusion architecture, a full-link collaborative optimization is formed, which simultaneously improves temperature control accuracy and energy efficiency ratio without manual intervention, extends drill bit service life, and reduces overall operation and maintenance costs.

[0129] Example 2: In Example 1, the rock stratum interface recognition mechanism driven by the intensity difference of reflected waves achieved millimeter-level precise positioning of the rock stratum interface, solving the problem of missed detection of interface temperature rise jump caused by traditional single-point temperature measurement. However, the problem of heat radiation interference from adjacent vehicles was not fully considered. This example makes further optimizations based on Example 1.

[0130] S4: Construct a thermal field distribution map based on multimodal data and interface location coordinates, mark high-temperature hot spots, solve the interference from adjacent vehicles through a thermal radiation transfer model, output the corrected ambient temperature value, and update the parameters of the basic cooling compensation scheme.

[0131] Specifically, the system acquires the surface temperature distribution of surrounding vehicles through an in-vehicle infrared camera, collects the 3D contours and spatial positions of neighboring vehicles through LiDAR point cloud acquisition, obtains the ambient temperature, humidity, and wind speed in real time through sensors, and obtains the relative position and orientation angle of the vehicle and neighboring vehicles through GPS. The system also acquires the distance data of neighboring vehicles in real time through in-vehicle radar. An infrared thermal imager is used to collect the peak surface temperature of the vehicles at a frequency of 10Hz. The infrared temperature data is mapped to the 3D point cloud coordinate system constructed by LiDAR to generate a continuous thermal field distribution map. High-temperature areas are identified based on threshold segmentation and clustering algorithms, and the coordinate boundaries and peak temperatures are output.

[0132] The corrected ambient temperature value includes: calculating the adjacent vehicle interference factor using a thermal radiation transfer model.

[0133]

[0134] Where, k int The adjacent vehicle interference factor reflects the heat radiation transfer efficiency, A is the drill bit's heated area, h is the convective heat transfer coefficient, ∈ is the emissivity, and σ is the Stefan-Boltzmann constant (5.67 × 10⁻⁶). -8 W / m 2 ·K 4 ), T en T represents the surface temperature of the adjacent vehicle. env For ambient temperature, T 4 The radiant energy is proportional to the fourth power of the absolute temperature, and d is the distance between the vehicle and the adjacent vehicle.

[0135] Calculate the corrected ambient temperature value based on the adjacent vehicle interference factor:

[0136] ΔT corr =ΔT env +β corr ·k int ,

[0137] Where, ΔT corr To correct for ambient temperature values, β corr To correct the sensitivity coefficient, the default value is 0.6, when G kWhen the coefficient is greater than 0.7, it is increased by 20% to enhance the suppression of interference from hard rock layers. The environmental temperature variable parameters in the basic cooling compensation scheme are updated in real time based on the corrected environmental temperature value.

[0138] Specifically, the influence domain of neighboring vehicle interference is superimposed on the thermal field distribution map, when k int When the value is greater than 0.3, the area affected by the interference is marked with orange contour lines on the thermal field distribution map, and the ambient temperature correction and compensation module is automatically triggered to update ΔT in the cooling flow calculation formula. env Parameters; real-time input of ambient temperature value into the basic cooling compensation scheme to trigger recalculation of cooling flow:

[0139] Q init =k·ΔT p | ΔTenv →ΔT corr ,

[0140] Simultaneously through the current signal I out Drive the intelligent regulating valve to achieve dynamic flow adaptation.

[0141] For example, in a scenario where multiple vehicles are drilling in parallel in a tunnel, the distance between adjacent vehicles is d = 15m and the surface temperature is 120℃. The system calculates k. int =0.42, the corrected ambient temperature rise compensation value increased by 8.3℃. Cooling flow rate increased by 12%, and the measured drill bit temperature decreased by 11.2% compared to the uncorrected scheme.

[0142] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0143] This application effectively solves the problem of ambient temperature distortion in multi-vehicle collaborative operation scenarios by introducing a dynamic correction mechanism for thermal radiation interference. Based on the spatial fusion technology of infrared thermal imaging and lidar, the interference intensity of neighboring vehicle thermal radiation on the drill bit of the own vehicle is accurately quantified; combined with the dynamic adjustment characteristics of the difference ratio of rock thermal conductivity, the correction parameters are adaptively optimized to ensure the real-time performance and accuracy of ambient temperature compensation; through multi-dimensional risk marking of the thermal field distribution map, the hidden threat of thermal interference from neighboring vehicles is transformed into a visual early warning signal, which is linked to the cooling system to implement proactive intervention. Ultimately, this significantly improves temperature control accuracy under complex working conditions, eliminates abnormal temperature rise of the drill bit caused by external thermal radiation, extends equipment life and ensures operational safety.

[0144] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A drill bit temperature adaptive control method based on drilling sensing, characterized in that, include: S1: Acquire multimodal data including reflected waves, drilling pressure and rotation speed; calculate the intensity difference between adjacent sampling points based on the reflected wave intensity sequence; identify the rock layer interface location based on the intensity difference; and calculate the thermal conductivity difference ratio on both sides of the interface and the interface location coordinates through the rock layer property model. S2: When the thermal conductivity difference ratio reaches the temperature rise prediction threshold, the predicted temperature rise is calculated based on multimodal data to generate a basic cooling compensation scheme; when the thermal conductivity difference ratio rises to the suppression response threshold, an enhanced cooling compensation scheme is generated based on the predicted temperature rise and the parameters after load reduction. S3: Monitor actual temperature rise data in real time, compare the error range with the predicted temperature rise, and update the compensation coefficient of the basic cooling compensation scheme based on the predicted error range; when the actual temperature rise exceeds the critical threshold, trigger the graded early warning protocol and execute shutdown protection. S4: Construct a thermal field distribution map based on multimodal data and interface location coordinates, mark high-temperature hot spots, solve the interference from adjacent vehicles through a thermal radiation transfer model, output the corrected ambient temperature value, and update the parameters of the basic cooling compensation scheme.

2. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The reflected wave intensity difference includes: a sequence of reflected wave intensity values ​​{I1, I2, ..., I...} collected along the borehole depth direction. n } Calculate the change in reflected wave intensity between adjacent sampling points: ΔI k =|I k -I k-1 |, Where, ΔI k I represents the difference in intensity of the reflected wave. k Let ΔI be the intensity value of the reflected wave. k When the value is greater than 10dB, the location is determined to be a rock stratum interface.

3. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The thermal conductivity difference ratio includes: converting reflected wave intensity into rock layer density. ρ = a·log(I / I0) + b, Where ρ is the rock density, I is the reflected wave intensity value, I0 is the reference reflected intensity, a is the density sensitivity coefficient to the acoustic response, and b is the minimum reference density. Converting rock density to rock hardness: H=C1·ρ n +C2, Where H is the rock layer hardness, C1 is the scale coefficient of hardness density, n is the nonlinear exponent term, and C2 is the basic hardness term. Converting rock hardness into rock thermal conductivity: DR=a·H B , Wherein, DR is the thermal conductivity of the rock strata, a is the scale coefficient, and B is the nonlinear exponent. All coefficients are calibrated through core experiments. Calculate the difference in thermal conductivity: Among them, G k The thermal conductivity difference ratio, DR a For the thermal conductivity of the rock strata in front of the interface, DR b The thermal conductivity of the rock strata behind the interface reflects the degree of change in the heat conduction capacity on both sides of the interface.

4. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The predicted temperature rise includes: calculating the expected temperature rise range based on the difference in hardness between the preceding and following rock layers. Where, ΔT p To predict the temperature rise, P is the drilling rig pressure, V is the drill bit edge linear velocity, μ is the drill bit rock friction coefficient, and Δt is the heat accumulation time (m·°C). p For the heat capacity of the drill bit, λ·G k For the thermal resistance gain at the rock interface, ΔT env β represents the environmental temperature variable, and β is the environmental sensitivity coefficient.

5. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The basic cooling compensation scheme includes: calculating the initial cooling flow rate based on the predicted temperature rise and cooling efficiency coefficient. Q init =k·ΔT p , Among them, Q init Let Q be the initial cooling flow rate, k be the cooling efficiency coefficient, and Q be... init It is converted into a current signal to drive the intelligent cooling regulating valve to execute the basic cooling compensation scheme.

6. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The enhanced cooling compensation scheme includes: setting a load reduction ratio based on the thermal conductivity difference ratio. Among them, P re U is the drilling pressure after deloading, P is the drilling pressure before deloading, and U is the drilling pressure before deloading. re U represents the rotational speed after unloading, and U represents the rotational speed before unloading. The coefficients 0.6 and 0.4 were calibrated through rock impact tests. Calculate the enhancement compensation based on the initial cooling flow rate: Where ΔQ is the reinforcement compensation term, and η is the reinforcement coefficient. Nonlinear thermal accumulation in hard rock layers; Calculate the total cooling flow based on the enhancement compensation term and the initial cooling flow: Q total =Q init +ΔQ, Among them, Q total To compensate for the total cooling flow rate, additional cooling capacity is added to the basic cooling compensation scheme to prevent the drill bit from overheating and being damaged.

7. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The compensation coefficients for the updated basic cooling compensation scheme include: updating the compensation coefficients based on the predicted temperature rise error magnitude. Where C is the compensation coefficient, C old λ is the compensation coefficient for the previous cycle, ΔT is the update sensitivity coefficient, and ΔT is the value of ΔT. act This represents the actual temperature rise. To predict the relative error of temperature rise; Adjust the cooling flow rate according to the compensation coefficient: Q ad =Q init ·C, Among them, Q ad To compensate for the cooling flow rate.

8. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The graded early warning protocol includes: triggering a three-level response mechanism when the actual temperature rise exceeds a preset safety threshold; in the first-level early warning state, audible and visual alarm devices are activated and high-temperature risk points at the borehole location are marked, and potential danger areas are marked in real time on the thermal field distribution map; in the second-level early warning state, an enhanced cooling compensation scheme is forcibly activated and the load reduction ratio is increased, environmental parameters are corrected through a thermal radiation model, and a real-time adjustment panel pops up on the drilling rig control interface; in the third-level early warning state, the power supply is immediately cut off and the hydraulic lock is released, a borehole risk analysis report is generated based on the rock stratum interface location, and thermal conductivity difference ratio data is persistently stored for fault tracing.

9. The drill bit temperature adaptive control method based on drilling sensing as described in claim 1, characterized in that, The corrected ambient temperature value includes: calculating the adjacent vehicle interference factor using a thermal radiation transfer model. Where, k int The adjacent vehicle interference factor reflects the heat radiation transfer efficiency, A is the drill bit's heated area, h is the convective heat transfer coefficient, ∈ is the emissivity, σ is the Stefan-Boltzmann constant, and T en T represents the surface temperature of the adjacent vehicle. env For ambient temperature, T 4 The radiant energy is proportional to the fourth power of the absolute temperature, and d is the distance between the vehicle and the adjacent vehicle. Calculate the corrected ambient temperature value based on the adjacent vehicle interference factor: ΔT corr =ΔT env +b corr ·k int , Where, ΔT corr To correct for ambient temperature values, β corr To correct the sensitivity coefficient, the environmental temperature variable parameters in the basic cooling compensation scheme are updated in real time based on the corrected ambient temperature value.

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