Drilling tool rotating body angular velocity measuring method, system and equipment and storage medium

Abstract

The invention relates to the technical field of angular velocity measurement, and discloses a drilling tool rotating body angular velocity measurement method, system and device and a storage medium, and the method comprises the steps: generating a compensation database of the incidence relation between temperature gradient data and angular velocity deviation data; an asymmetric elastic supporting structure is installed, and energy dissipation parameters are generated; establishing an association rule of the temperature gradient data and the energy dissipation parameters, and generating a dynamic compensation rule under the combined action of temperature and vibration; decomposing the angular velocity deviation data according to a dynamic compensation rule to generate a dynamic compensation amount, and adjusting weight distribution of temperature and vibration intensity in the dynamic compensation amount through an acquired accelerometer feedback signal; and continuously injecting the adjusted dynamic compensation amount into a drift correction loop to enable the corrected gyroscope output signal and the accelerometer feedback signal to form closed-loop control, and maintaining stable output of the angular velocity measurement value of the rotary body through autonomous iterative optimization of a dynamic compensation rule. According to the invention, the angular velocity measurement precision and stability can be improved.

Description

Technical Field

[0001] This invention relates to the field of angular velocity measurement technology, and in particular to a method, system, device, and storage medium for measuring the angular velocity of a drill bit's rotating body. Background Technology

[0002] During the dynamic drilling process of a fully rotating vertical drilling system, maintaining high-precision measurement of the angular velocity of the rotating body is crucial to ensuring the accuracy of the drilling trajectory. However, the downhole environment is extremely complex and harsh. The drill string assembly faces a combination of interferences from strong vibrations, high temperatures and pressures, and drilling fluid erosion when rotating at high speeds, which poses a severe challenge to the measurement stability of gyroscopes and accelerometers.

[0003] Existing technologies face the following bottlenecks: First, gyroscopes are extremely sensitive to temperature fluctuations. The frictional heat generated between the drill bit and the formation, as well as the conduction of high underground temperatures, create a drastically changing temperature gradient within the sensor cavity, inducing thermal stress deformation and causing significant low-frequency drift in the angular velocity output signal. Second, the impact loads generated when the drill bit cuts into different rock formations excite high-frequency vibrations. This vibration, combined with the stick-slip vibration of the drill string and sudden changes in drilling pressure, not only directly interferes with sensor readings and introduces high-frequency noise, but also couples with temperature effects, producing complex coupling errors, rendering traditional single-factor compensation methods ineffective.

[0004] Existing technologies employ passive isolation or single-dimensional compensation strategies. For example, vibration isolators with symmetrical structures are used to isolate vibrations, or gyroscope drift is compensated using a fixed temperature lookup table. However, these methods have significant limitations: passive vibration damping structures are often effective only at specific frequencies and are unable to cope with broadband downhole vibrations, nor can they adapt to changing operating conditions; while a single temperature compensation model cannot handle the nonlinear errors caused by the interaction of vibration and temperature, resulting in deviations in the compensated angular velocity measurements during dynamic drilling, which in turn leads to wellbore inclination angle shifts and tool face instability, ultimately affecting the accuracy and reliability of vertical drilling.

[0005] Therefore, this application provides a method, system, device, and storage medium for measuring the angular velocity of a drill bit's rotating body to solve the above-mentioned technical problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method, system, device and storage medium for measuring the angular velocity of a drill bit's rotating body, in order to solve the technical problem that the measured angular velocity value after compensation still has deviations in the prior art, which affects the accuracy and reliability of vertical drilling.

[0007] To address the aforementioned technical problems, this invention provides a method for measuring the angular velocity of a drill bit's rotating body, comprising: In response to the correlation analysis between continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data is generated; Install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data; Establish a correlation rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the combined action of temperature and vibration is generated. The angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount that matches the current temperature and vibration intensity. The weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted by the acquired accelerometer feedback signal. The adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control. Through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the rotating body angular velocity measurement value is maintained.

[0008] In some specific embodiments, in response to the correlation analysis of continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database including the correlation relationship between the temperature gradient data and the angular velocity deviation data is generated, further including: Collect temperature gradient data at different locations and simultaneously record the raw angular velocity signal output by the gyroscope; Extract the angular velocity deviation data caused by temperature fluctuations from the original angular velocity signal; Analyze the correlation strength between the temperature gradient data and the angular velocity deviation data, and eliminate spurious correlations; The verified relationships are categorized and stored according to temperature ranges to form the compensation database.

[0009] In some specific embodiments, an asymmetric elastic support structure is installed, and energy dissipation parameters are generated, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data, and further include: By utilizing the elastic differences of materials in orthogonal directions, directional absorption of vibrational energy can be achieved; The deformation response of the asymmetric elastic support structure under vibration at different frequencies was measured, and the curve of vibration energy absorption rate as a function of frequency was recorded. Elastic waves generated by microscopic deformation inside the asymmetric elastic support structure are collected, and the scattering intensity data is quantified to characterize the energy dissipation efficiency. The energy dissipation parameter is generated by integrating the vibration energy absorption rate and the scattering intensity data.

[0010] In some specific embodiments, a correlation rule is established between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the combined effect of temperature and vibration is generated, further including: Calculate the rate of change of the temperature gradient data; The rate of change of the temperature gradient data is coupled with the vibration energy absorption rate in the energy dissipation parameters to establish a correlation model for the resonance amplification of the asymmetric elastic support structure caused by temperature fluctuations. The rate of change of temperature gradient data, vibration energy absorption rate, and scattering intensity data are projected onto a high-dimensional feature space to generate dynamic compensation rules.

[0011] In some specific embodiments, the angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount that matches the current temperature and vibration intensity. The weighting of temperature and vibration intensity in the dynamic compensation amount is adjusted using the acquired accelerometer feedback signal. This further includes: Based on the dynamic compensation rule, the angular velocity deviation data is decomposed to separate the low-frequency component dominated by temperature and the high-frequency component dominated by vibration. Based on the real-time temperature, a basic dynamic compensation amount is generated by matching the compensation coefficients in the compensation database. The accelerometer feedback signal is introduced to verify the vibration compensation effect, and the weighting ratio of temperature and vibration intensity in the dynamic compensation is adjusted. Phase calibration is performed on the dynamic compensation amount after weight adjustment.

[0012] In some specific embodiments, the adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control, and the dynamic compensation rule is autonomously iteratively optimized to maintain a stable output of the rotational body angular velocity measurement value, further including: The adjusted dynamic compensation amount is injected into the drift correction loop to offset the original deviation; The difference between the compensated gyroscope output and the accelerometer feedback signal is compared. If the residual exceeds a preset range, an online learning mechanism is triggered. The parameters of the dynamic compensation rule are autonomously and iteratively optimized using a reinforcement learning algorithm.

[0013] In some specific embodiments, the adjusted dynamic compensation amount is injected into the drift correction loop to offset the original deviation; before comparing the difference between the compensated gyroscope output and the accelerometer feedback signal, and triggering the online learning mechanism if the residual exceeds a preset range, the method further includes: The dynamic compensation amount is superimposed with the angular velocity deviation data of the current gyroscope output signal and the real-time data of the accelerometer feedback signal to generate a correction signal. The amplitude of the correction signal is adjusted based on the difference between the correction signal and the accelerometer feedback signal, so that the adjusted correction signal amplitude matches the current temperature gradient data and the changing trend of vibration energy absorption rate. The adjusted correction signal is injected into the drift correction loop, the corrected gyroscope output signal is acquired in real time, and a closed-loop comparison is performed with the accelerometer feedback signal to generate an error signal. The weighting of temperature and vibration intensity in the dynamic compensation rule is adjusted according to the rate of change of the error signal, and the compensation amount generation logic in the dynamic compensation rule is updated through autonomous iterative optimization.

[0014] Based on the same concept, the present invention also provides a drill bit rotation angular velocity measurement system, comprising: The compensation database generation module is configured to perform correlation analysis on continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal to generate a compensation database that includes the correlation relationship between the temperature gradient data and the angular velocity deviation data. An asymmetric elastic support structure installation and energy dissipation parameter generation module is configured to install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data. The dynamic compensation rule generation module is configured to establish the association rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, dynamic compensation rules under the combined action of temperature and vibration are generated. The dynamic compensation quantity generation and adjustment module is configured to decompose the angular velocity deviation data according to the dynamic compensation rules, generate a dynamic compensation quantity that matches the current temperature and vibration intensity, and adjust the weight allocation of temperature and vibration intensity in the dynamic compensation quantity through the acquired accelerometer feedback signal. The rotating body angular velocity measurement output module is configured to continuously inject the adjusted dynamic compensation amount into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control, and maintain the stable output of the rotating body angular velocity measurement value through the autonomous iterative optimization of the dynamic compensation rule.

[0015] Based on the same concept, the present invention also provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of a method for measuring the angular velocity of a drill bit rotation.

[0016] Based on the same concept, the present invention also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a method for measuring the angular velocity of a drill bit rotation.

[0017] Compared with existing technologies, its advantages are as follows: This invention discloses a method, system, device, and storage medium for measuring the angular velocity of a drill bit's rotating body, which realizes the self-adaptation and intelligence of the compensation process and improves the accuracy and stability of angular velocity measurement in complex environments. Attached Figure Description

[0018] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating some specific embodiments of the method for measuring the angular velocity of a drill bit's rotating body according to the present invention; Figure 2 This is a schematic diagram of the structure of a drill bit rotation angular velocity measurement system according to some specific embodiments of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device according to some specific embodiments of the present invention; In the diagram, 710 is the processor; 720 is the memory; 730 is the input device; and 740 is the output device. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0021] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0022] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0023] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0024] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0025] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0026] Reference Figure 1 A method for measuring the angular velocity of a drill bit's rotating body, comprising: S101, in response to the correlation analysis of continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database including the correlation relationship between the temperature gradient data and the angular velocity deviation data is generated; S102, Install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data; S103, establish the association rule between the temperature gradient data and the energy dissipation parameter, and generate a dynamic compensation rule under the combined action of temperature and vibration by coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data. S104, decompose the angular velocity deviation data according to the dynamic compensation rule, generate a dynamic compensation amount that matches the current temperature and vibration intensity, and adjust the weight distribution of temperature and vibration intensity in the dynamic compensation amount through the acquired accelerometer feedback signal. S105, the adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control, and the dynamic compensation rule is autonomously iteratively optimized to maintain a stable output of the rotating body angular velocity measurement value.

[0027] Specifically, in this embodiment of the invention, in response to the correlation analysis between continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a temperature sensor array is arranged inside the gyroscope cavity to acquire temperature readings at different locations at millisecond-level frequencies and calculate gradient changes. Simultaneously, the original angular velocity signal output by the gyroscope is recorded. Signal processing algorithms are used to extract the deviation component caused by temperature fluctuations. Then, a correlation analysis method is used to calculate the quantitative relationship between temperature gradient and angular velocity deviation, and pseudo-correlation is eliminated. Finally, the data is classified and stored according to temperature range to form a structured compensation database. Subsequently, an asymmetric elastic support structure made of a specific material is installed. The orthogonal elastic differences in the structure are used to achieve directional absorption and scattering of vibration energy. The vibration energy absorption rate curve is obtained by measuring the deformation response of the structure under vibration at different frequencies, and the internal elastic wave signal is collected to quantify the scattering intensity. This data is then integrated to generate energy dissipation parameters containing absorption rate and scattering intensity data. This establishes a correlation between temperature gradient data and energy dissipation. The correlation rules for scattering parameters are constructed by calculating the rate of change of temperature gradient and performing multi-dimensional coupling analysis with vibration energy absorption rate and scattering intensity data to build a mathematical model of the joint effect of temperature and vibration. A machine learning algorithm is then used to generate dynamic compensation rules with adaptability to operating conditions. Based on the dynamic compensation rules, modal decomposition is performed on the real-time acquired angular velocity deviation data to separate the temperature and vibration-dominant components. An initial dynamic compensation amount is generated by matching the compensation database, and the accelerometer feedback signal is introduced to optimize the distribution ratio of temperature and vibration factors in the compensation amount through a weight adjustment algorithm. Finally, the optimized dynamic compensation amount is injected into the drift correction loop for real-time signal compensation. An error signal is generated by comparing the difference between the corrected gyroscope output and the accelerometer feedback signal. Based on the error change rate, a reinforcement learning algorithm is used to iteratively update the weight allocation logic and parameter generation strategy in the dynamic compensation rules, forming a closed-loop control link to maintain stable output of angular velocity measurements under continuous temperature fluctuations and vibration interference.

[0028] For example, temperature sensor array data is acquired at a millisecond sampling frequency. The temperature gradient change rate between adjacent sensors is calculated as the temperature change per millimeter per second. Assuming the detected temperature gradient change rate is 0.5℃ / (mm·s), and the gyroscope output angular velocity deviation is recorded as 0.2° / s, wavelet transform is used to extract the temperature-induced deviation component. Grey relational analysis is then used to calculate the correlation between the temperature gradient and the deviation, finding it to be 0.85. False data with a correlation below 0.6 are removed, and the valid data are categorized into 0-50℃ and 50-100℃ ranges and stored in the database. During the vibration parameter acquisition phase, the deformation response of the asymmetric support structure at a vibration frequency of 200Hz is measured, yielding a vibration energy absorption rate of 65%. Simultaneously, the scattering intensity is measured as 80mV using an acoustic emission sensor. These parameters are then integrated to generate an energy dissipation parameter set. In the rule generation phase, the coupling value between the temperature gradient change rate and vibration parameters is calculated. For example, when the temperature change rate reaches 1℃ / s and the vibration absorption rate exceeds 60%, the dynamic compensation rule coefficient is output as 1.2 using a support vector regression model. In the compensation calculation phase, a base compensation of -0.1° / s is matched from the database for the current temperature range. Then, based on the angular velocity fluctuation amplitude fed back by the accelerometer (e.g., high-frequency fluctuation amplitude exceeding 0.05° / s is detected), the vibration weight is adjusted from 50% to 70%, generating a final compensation of -0.12° / s. In the closed-loop optimization phase, after injecting the compensation, the residual error signal change rate is detected to be 0.01° / s². The vibration weight coefficient is optimized from 0.7 to 0.75 using the Q-learning algorithm, and the decision threshold in the rule base is updated, ultimately stabilizing the angular velocity output error within 0.01° / s.

[0029] In some applications, in response to the correlation analysis between continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database is generated that includes the correlation between the temperature gradient data and the angular velocity deviation data. This includes acquiring temperature gradient data at different locations and simultaneously recording the original angular velocity signal output by the gyroscope; extracting angular velocity deviation data caused by temperature fluctuations from the original angular velocity signal; analyzing the correlation strength between the temperature gradient data and the angular velocity deviation data and eliminating false correlations; and storing the verified correlations according to temperature ranges to form the compensation database.

[0030] Understandably, high-precision temperature readings are simultaneously acquired at multiple key locations inside the gyroscope cavity, and spatial temperature gradient distribution data is calculated. The raw angular velocity signal output by the gyroscope in real time is recorded with strict alignment using millisecond-level timestamps. A signal decomposition algorithm is used to separate the low-frequency drift component caused by temperature fluctuations from the raw angular velocity signal as angular velocity deviation data. The quantitative correlation strength between the temperature gradient data and the angular velocity deviation data is calculated using a correlation analysis method, and a correlation threshold is set to filter out pseudo-correlation relationships caused by random interference. The verified temperature-deviation data with significant correlation are classified and structured according to the range of their temperature values, thereby forming a temperature-deviation compensation database for subsequent real-time querying and matching.

[0031] For example, data is collected by three temperature sensors positioned along the X, Y, and Z axes of the gyroscope cavity. The axial temperature gradient is calculated to be 0.3℃ / mm, and the original angular velocity signal output by the gyroscope at this moment is recorded as 15.5° / s. Wavelet transform is used to decompose this signal, extracting low-frequency components below 1Hz, which are identified as temperature-induced angular velocity deviation data, with a value of 0.4° / s. Grey relational analysis is used to calculate the correlation between the current temperature gradient data and the angular velocity deviation data, yielding a correlation of 0.78. A correlation threshold of 0.6 is set; values ​​above this threshold are considered valid correlations, while values ​​below are discarded as false correlations. This valid data is then categorized according to temperature values. If the current average temperature is 75℃, it is stored in a database partition corresponding to the 70-80℃ temperature range. A single data record in this partition can be represented as: temperature gradient 0.3℃ / mm, corresponding angular velocity deviation 0.4° / s, correlation 0.78. Data is continuously accumulated to form a database covering different temperature ranges, which can be used for real-time compensation queries.

[0032] In some applications, an asymmetric elastic support structure is installed, and energy dissipation parameters are generated. These parameters include vibration energy absorption rate and scattering intensity data. The process involves utilizing the elastic differences of the material in orthogonal directions to achieve directional absorption of vibration energy; measuring the deformation response of the asymmetric elastic support structure under vibration at different frequencies and recording the curve of vibration energy absorption rate versus frequency; acquiring elastic waves generated by microscopic deformation within the asymmetric elastic support structure and quantifying the scattering intensity data to characterize energy dissipation efficiency; and integrating the vibration energy absorption rate and the scattering intensity data to generate the energy dissipation parameters.

[0033] Understandably, by utilizing the different elastic moduli of a specific material in three orthogonal directions, an asymmetric structural form is designed to achieve the directional absorption and conversion of vibration energy along a specific direction. External vibration excitations of different frequencies are applied to the installed asymmetric elastic support structure, and its dynamic deformation response data at each frequency point is measured and recorded. The vibration energy absorption rate is then calculated, and its characteristic curve as a function of frequency is plotted. Simultaneously, elastic wave signals generated by the internal micro-deformation of the support structure during vibration are acquired. Time-frequency analysis and energy quantization of these signals are performed to obtain scattering intensity data characterizing the structure's ability to convert vibration energy into elastic waves and scatter them outwards. Finally, the vibration energy absorption rate curve characterizing energy absorption and the scattering intensity data characterizing energy scattering are integrated and formatted in multiple dimensions to generate a comprehensive set of energy dissipation parameters describing the energy dissipation performance of the support structure in a vibration environment.

[0034] For example, an asymmetric support structure made of titanium alloy has elastic moduli of 110 GPa, 110 GPa, and 45 GPa in the X, Y, and Z directions, respectively. This anisotropy allows vibration energy to be preferentially absorbed along the Z-axis (low stiffness direction). In vibration testing, a frequency sweep excitation from 50 Hz to 500 Hz is applied to the structure, and its vibration response is measured. For instance, at 250 Hz, the measured response amplitude is 30% of the basic excitation amplitude, leading to a calculated vibration energy absorption rate of 70% at this frequency. Elastic wave signals generated within the structure at this frequency are acquired using piezoelectric sensors, and their acoustic emission energy is analyzed to be 85 dB, which is quantified as a scattering intensity reference value. The data at this frequency point is integrated into an energy dissipation parameter record: frequency 250 Hz, vibration energy absorption rate 70%, scattering intensity 85 dB. By integrating the full-band sweep data, an energy dissipation parameter database is generated, indexed by frequency and containing the correspondence between absorption rate and scattering intensity, providing a basis for subsequent composite compensation.

[0035] In some applications, a correlation rule is established between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the combined effect of temperature and vibration is generated. This includes calculating the rate of change of the temperature gradient data; performing a coupling analysis between the rate of change of the temperature gradient data and the vibration energy absorption rate in the energy dissipation parameter to establish a correlation model for the resonance amplification of the asymmetric elastic support structure caused by temperature fluctuations; and projecting the rate of change of the temperature gradient data, the vibration energy absorption rate, and the scattering intensity data onto a high-dimensional feature space to generate a dynamic compensation rule.

[0036] Understandably, based on continuously collected temperature gradient data, the rate of change per unit time is calculated through differential operations to quantify the severity of temperature fluctuations. The calculated rate of change of the temperature gradient is coupled with the vibration energy absorption rate in the energy dissipation parameter through multi-dimensional analysis. By establishing a transfer function model, the physical correlation mechanism of temperature fluctuations causing resonant frequency shifts and changes in vibration energy absorption characteristics of asymmetric elastic support structures is revealed. The rate of change of the temperature gradient, which characterizes the intensity of thermal disturbance, the vibration energy absorption rate, which characterizes the vibration absorption characteristics, and the scattering intensity data, which characterizes the energy dispersion characteristics, are jointly mapped to a high-dimensional feature space. In this space, machine learning algorithms are used to mine the nonlinear interaction relationships between multiple parameters and fit their joint distribution characteristics. Based on the coupling relationships in this high-dimensional feature space, dynamic compensation rules with adaptive adjustment capabilities that can simultaneously respond to the combined disturbances of temperature and vibration are generated.

[0037] For example, the calculated rate of change of the current temperature gradient is 0.8℃ / s, reflecting a rapid temperature increase. Querying the energy dissipation parameters of the asymmetric elastic support structure under the current operating conditions, we obtain the vibration energy absorption rate at the dominant vibration frequency of 300Hz at this moment as 75%, and the scattering intensity as 90dB. Coupled analysis of these three parameters (0.8℃ / s, 75%, 90dB) is performed: analysis using a pre-defined transfer function model shows that the current rate of temperature change has a high probability of causing resonance in the support structure around 305Hz, potentially amplifying vibration interference. The three parameters are then fed into a support vector regression model based on radial basis function kernels for high-dimensional feature mapping and calculation. This model, through internal calculations, outputs the decision coefficients of the dynamic compensation rules; for example, the rule coefficient K is calculated to be 1.25. This coefficient K is used to adjust the generation amplitude of subsequent compensation. The dynamic compensation rule can be expressed as follows: when the temperature change rate is higher than 0.5℃ / s and occurs simultaneously with high absorption rate and high scattering intensity, the gain coefficient of the vibration compensation component is set to 1.25 times the reference value to cope with possible resonance amplification effects, thereby achieving accurate compensation under the combined action of temperature and vibration.

[0038] In some applications, the angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount that matches the current temperature and vibration intensity. The weighting of temperature and vibration intensity in the dynamic compensation amount is adjusted using the acquired accelerometer feedback signal. This includes decomposing the angular velocity deviation data based on the dynamic compensation rule to separate the temperature-dominated low-frequency component and the vibration-dominated high-frequency component; generating a basic dynamic compensation amount by matching the compensation coefficients in the compensation database with the real-time temperature; verifying the vibration compensation effect by introducing the accelerometer feedback signal and adjusting the weighting ratio of temperature and vibration intensity in the dynamic compensation amount; and performing phase calibration on the dynamic compensation amount after weight adjustment.

[0039] Understandably, based on the frequency characteristic information contained in the established dynamic compensation rules, an adaptive signal decomposition algorithm is used to perform frequency domain analysis on the real-time acquired angular velocity deviation data, separating the low-frequency drift component caused by temperature changes and the high-frequency fluctuation component caused by mechanical vibration. The compensation database is queried based on the currently acquired real-time temperature data to match the basic temperature compensation coefficient corresponding to that temperature point, and the initial basic dynamic compensation amount is generated by combining it with the amplitude adjustment coefficient output by the dynamic compensation rules. The real-time angular velocity signal fed back from the accelerometer is introduced as an independent reference benchmark. The vibration compensation effect is quantitatively evaluated by calculating the residual between this signal and the compensated signal in the high-frequency band. Based on the evaluation results, a weight optimization algorithm is used to dynamically adjust the weight distribution ratio of the temperature compensation component and the vibration compensation component in the basic dynamic compensation amount. The dynamically compensated amount after weight adjustment is subjected to phase lag calibration to ensure that its phase characteristics are synchronized with the error phase of the actual output signal of the gyroscope, ensuring that the compensation amount can be accurately injected and effectively offset the original deviation.

[0040] For example, applying dynamic compensation rules: the rules indicate that attention should be paid to the low-frequency band below 1Hz and the high-frequency band above 100Hz. Using a variational mode decomposition algorithm to decompose the angular velocity deviation data (e.g., the current value is 0.5° / s), a low-frequency component of 0.3° / s (determined to be temperature-induced) and a high-frequency component of 0.2° / s (determined to be vibration-induced) were successfully separated. The current temperature was read as 85℃, and the basic temperature compensation coefficient at this temperature was found to be -0.28° / s in the compensation database. Combining this with the current vibration gain coefficient of 1.2 given by the dynamic compensation rules, the initial basic dynamic compensation amount was calculated to be -0.28° / s × 1.2 = -0.336° / s. The high-frequency signal energy fed back by the accelerometer was read as 0.15° / s, which was found to be higher than the expected threshold of 0.1° / s, indicating that the vibration compensation was insufficient. Weight adjustment is initiated, increasing the weight of the vibration component from the initial 50% to 65%, while the weight of the temperature component is correspondingly reduced from 50% to 35%. The adjusted dynamic compensation amount becomes (-0.336° / s × 35%) + (a vibration compensation value for the 0.2° / s high-frequency component × 65%). A 5-millisecond phase lag is detected between the compensation amount and the original deviation signal. Phase lead compensation is performed through an all-pass filter to eliminate this lag, ensuring that the compensation signal and the error signal are precisely aligned in time before being injected into the correction loop.

[0041] In some applications, the adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control. The dynamic compensation rule is autonomously iteratively optimized to maintain a stable output of the rotational body angular velocity measurement value. This includes injecting the adjusted dynamic compensation amount into the drift correction loop to offset the original deviation; comparing the difference between the compensated gyroscope output and the accelerometer feedback signal, and triggering an online learning mechanism if the residual exceeds a preset range; and autonomously iteratively optimizing the parameters of the dynamic compensation rule through a reinforcement learning algorithm.

[0042] Understandably, the final dynamic compensation amount, after weight adjustment and phase calibration, is injected into the gyroscope's drift correction loop in real time through a high-precision digital-to-analog converter interface. This is superimposed on the original gyroscope output signal at the analog signal level to directly offset the combined temperature and vibration deviations. The difference between the compensated gyroscope output signal and the angular velocity signal fed back by the accelerometer at the same moment is continuously collected and compared to calculate the real-time residual signal. When the amplitude or energy of the residual signal exceeds the preset stability threshold range, the built-in online autonomous learning mechanism is immediately triggered. Then, a reinforcement learning algorithm framework is invoked to construct a reward function with the goal of reducing the residual signal. Through multiple iterations, the impact of different adjustment strategies of key parameters in the dynamic compensation rule on the long-term compensation effect is explored and evaluated. The mechanism autonomously optimizes and updates the weight allocation coefficients, frequency characteristic parameters, or gain adjustment factors in the rule. Finally, the optimized new parameter set is fed back to the dynamic compensation rule generation module, enabling it to adapt to time-varying environments and thus continuously maintain a stable and high-precision output of the rotating body's angular velocity measurement value throughout the entire closed-loop control process.

[0043] For example, the adjusted dynamic compensation of -0.38° / s is injected into the gyroscope's drift correction circuit via a 16-bit DAC. After compensation, the gyroscope's output signal changes from the original 15.5° / s to 15.12° / s. The accelerometer's feedback signal is simultaneously read as 15.10° / s, and the residual between the two is calculated to be 0.02° / s. This residual exceeds the preset stability threshold (0.015° / s), triggering the online learning mechanism. The Q-learning algorithm is then initiated for optimization: the algorithm defines the current state as (temperature change rate = 0.8℃ / s, residual = 0.02° / s). After simulation evaluation, increasing the vibration weight coefficient from the current 0.65 to 0.75 predicts that the residual can be reduced to 0.01° / s within the next 5 control cycles, thus obtaining the maximum reward value. Based on this, the vibration weight coefficient parameter in the dynamic compensation rule is updated to 0.75. This updated rule will be used to generate the dynamic compensation amount for the next control cycle, thereby achieving the closed-loop control objective of continuously improving output stability through autonomous iterative optimization.

[0044] In some applications, the adjusted dynamic compensation amount is injected into the drift correction loop to offset the original deviation. Before comparing the difference between the compensated gyroscope output and the accelerometer feedback signal, and triggering the online learning mechanism if the residual exceeds a preset range, the process further includes superimposing the dynamic compensation amount with the angular velocity deviation data of the current gyroscope output signal and the real-time data of the accelerometer feedback signal to generate a correction signal. The amplitude of the correction signal is adjusted according to the difference between the correction signal and the accelerometer feedback signal so that the amplitude of the adjusted correction signal matches the changing trend of the current temperature gradient data and the vibration energy absorption rate. The adjusted correction signal is injected into the drift correction loop, the corrected gyroscope output signal is collected in real time, and a closed-loop comparison is performed with the accelerometer feedback signal to generate an error signal. The weight allocation of temperature and vibration intensity in the dynamic compensation rule is adjusted according to the rate of change of the error signal, and the compensation amount generation logic in the dynamic compensation rule is updated through autonomous iterative optimization.

[0045] Understandably, the generated dynamic compensation quantity is processed by multi-source data synchronization and weighted superposition with the angular velocity deviation data contained in the current gyroscope output signal and the angular velocity signal fed back by the accelerometer in real time. A preliminary correction signal is generated through a digital signal synthesis algorithm. The instantaneous difference between this correction signal and the accelerometer feedback signal in the time domain is calculated in real time. Based on the amplitude characteristics and changing trend of this difference, combined with the magnitude of the currently acquired temperature gradient data and the real-time value of the vibration energy absorption rate, an adaptive gain adjustment strategy is used to dynamically adjust the amplitude of the correction signal so that its amplitude change matches the changing trends of the temperature gradient and vibration energy. The amplitude-adjusted correction signal is then converted from digital to analog. A drift correction loop is injected to perform preliminary compensation, and the gyroscope output signal after this compensation is acquired simultaneously. This signal is then compared and analyzed in both the time and frequency domains with the accelerometer feedback signal, which serves as a reference. The residual characteristics between the two signals are extracted, and a quantized error signal is generated. The error signal is differentiated to obtain its rate of change. Based on the direction and magnitude of this rate, it is determined whether the main source of the current error is temperature or vibration. The allocation ratio of temperature weight and vibration weight in the dynamic compensation rule is then adjusted accordingly. The condition threshold and output coefficient of the compensation amount generation logic in the rule are updated through an autonomous iterative optimization algorithm based on reinforcement learning, forming a dual optimization mechanism that combines feedforward and feedback.

[0046] For example, the dynamic compensation value of -0.12° / s, the angular velocity deviation data of 0.5° / s in the current gyroscope output, and the accelerometer real-time feedback signal of 15.1° / s are superimposed: using a weighted superposition algorithm, the dynamic compensation value is assigned a weight of 0.6, the deviation data a weight of 0.3, and the accelerometer signal a weight of 0.1, generating an initial correction signal value of (-0.12×0.6+0.5×0.3+15.1×0.1)=1.588° / s. The difference between this correction signal and the accelerometer feedback signal of 15.1° / s is calculated to be -13.512° / s. The current temperature gradient data is detected to be 0.8℃ / s and the vibration energy absorption rate is 70%. According to the preset adjustment strategy, when the temperature gradient is large and the vibration absorption rate is high, the amplitude of the correction signal needs to be increased by 15%. After adjustment, the amplitude of the correction signal is 1.588×1.15=1.826° / s. After injecting this signal into the drift correction loop, the new output value of the gyroscope was acquired to be 16.326° / s. Compared with the accelerometer reference value of 15.1° / s, an error signal of 1.226° / s was generated. Differentiating this error signal, its rate of change was found to be 0.05° / s². This positive value indicates that the error is expanding and is mainly caused by vibration factors. Based on this, the vibration weight in the dynamic compensation rule was increased from 60% to 68%, and the temperature weight was decreased from 40% to 32%. The vibration gain coefficient in the compensation amount generation logic was updated from 1.2 to 1.35 using the Q-learning algorithm, thus completing the autonomous iterative optimization of the rule based on the error change trend.

[0047] The following describes another embodiment of the method for measuring the angular velocity of a drill bit's rotating body according to the present invention: In this embodiment, temperature gradient data of the gyroscope cavity and deviation data of angular velocity caused by temperature changes in the gyroscope output signal are continuously collected. The temperature gradient data and deviation data are then correlated to form a compensation database containing the correlation between them. A high-precision temperature sensor array is arranged inside the gyroscope cavity to continuously collect temperature gradient data at different locations with a millisecond-level sampling frequency, while simultaneously recording the original angular velocity signal output by the gyroscope. The deviation data caused by temperature fluctuations in the angular velocity signal is extracted using a wavelet transform algorithm, establishing a time-stamp-aligned temperature-deviation correspondence. Grey relational analysis is used to calculate the correlation strength between temperature gradient changes and angular velocity deviations, eliminating false correlations caused by random interference. The verified correlations are categorized and stored according to temperature ranges, forming a structured compensation database, where each record includes a temperature gradient pattern, corresponding deviation amount, and confidence score.

[0048] An asymmetric elastic support structure made of titanium alloy is installed between the rotating body and the external base. Taking into account the elastic differences of the titanium alloy in the orthogonal directions, energy dissipation parameters of the asymmetric elastic support structure are generated. These parameters include vibration energy absorption rate and scattering intensity data. A specially configured titanium alloy support structure is designed at the junction of the rotating body and the external base, utilizing the different elastic moduli of titanium alloy in the X, Y, and Z orthogonal directions to achieve directional absorption of vibration energy. The deformation response of the support structure under vibration at different frequencies is measured using a laser Doppler vibrometer, and the curve of its vibration energy absorption rate as a function of frequency is recorded. An acoustic emission sensor is used to collect elastic waves generated by the microscopic deformation inside the structure, and the scattering intensity data is quantified to characterize the energy dissipation efficiency. The absorption rate and scattering intensity indices are integrated to generate an energy dissipation parameter comparison table describing the dynamic characteristics of the support structure, providing a physical basis for vibration compensation.

[0049] A correlation rule is established between temperature gradient data and energy dissipation parameters to generate a dynamic compensation amount that matches the current temperature and vibration intensity. This correlation rule couples the rate of change of temperature gradient data with vibration energy absorption rate and scattering intensity data to generate a dynamic compensation rule under the combined effect of temperature and vibration. Historical temperature gradient data change patterns are extracted from the compensation database, and the maximum slope of temperature fluctuation per unit time is calculated as the rate of change index. The rate of change is coupled with the vibration energy absorption rate in the energy dissipation parameters to establish a correlation model for the amplification of resonance in the support structure caused by temperature fluctuations. The temperature change rate, absorption rate, and scattering intensity are projected into a high-dimensional feature space using kernel function mapping, and a support vector regression algorithm is used to generate dynamic compensation rules. A working condition adaptive module is added to the rule set to adjust the coupling weights of temperature and vibration factors based on real-time sensor data.

[0050] The deviation data of the gyroscope output signal is decomposed according to the dynamic compensation rule to generate a dynamic compensation quantity that matches the current temperature and vibration intensity. The weight distribution of temperature and vibration intensity in the dynamic compensation quantity is adjusted by the acquired accelerometer feedback signal. Variational mode decomposition is performed on the gyroscope deviation data based on the dynamic compensation rule to separate the temperature-dominated low-frequency component and the vibration-dominated high-frequency component. The basic dynamic compensation quantity is generated by matching the compensation coefficients in the rule library with the real-time reading of the current temperature sensor. The vibration compensation effect is verified by introducing the accelerometer feedback signal. If the residual vibration energy exceeds the threshold, the weight distribution ratio of temperature and vibration factors in the compensation quantity is adjusted by the gradient descent method. The compensation quantity is phase-calibrated to ensure that its injection timing is strictly synchronized with the gyroscope signal processing cycle.

[0051] The dynamic compensation amount is continuously injected into the gyroscope's drift correction loop, forming a closed-loop control between the corrected gyroscope output signal and the accelerometer feedback signal. This closed-loop control process, through autonomous iterative optimization of the dynamic compensation rules, ensures stable output of the angular velocity measurement value of the rotating body even in environments with continuous temperature fluctuations and vibration disturbances. The optimized dynamic compensation amount is injected into the gyroscope's drift correction loop via a digital-to-analog converter, directly offsetting the original deviation during signal conditioning. The difference between the compensated gyroscope output and the accelerometer feedback signal is compared in real time; if the residual exceeds the allowable range, an online learning mechanism of the rule base is triggered. Then, the parameters of the dynamic compensation rules are autonomously iteratively optimized using a reinforcement learning algorithm, such as adjusting the slope coefficient of the temperature-vibration coupling function. This forms a complete control chain from sensor acquisition and deviation analysis to closed-loop correction, enabling the gyroscope to maintain a stable output with an angular velocity measurement error of less than 0.01° / h even under a temperature range of -40℃ to 85℃ and a vibration impact of 15g.

[0052] The dynamic compensation amount is continuously injected into the gyroscope's drift correction loop, forming a closed-loop control between the corrected gyroscope output signal and the accelerometer feedback signal. This closed-loop control process, through autonomous iterative optimization of the dynamic compensation rules, ensures stable output of the body's angular velocity measurement in environments with continuous temperature fluctuations and vibration disturbances. This includes superimposing the dynamic compensation amount with the deviation data of the current gyroscope output signal and the real-time data of the accelerometer feedback signal to generate a correction signal; acquiring the dynamic compensation amount, the original gyroscope deviation data, and the real-time data stream of the accelerometer feedback signal from the signal processing unit, and ensuring strict alignment of the three sets of data through a time synchronization module. Digital signal superposition technology is used to initially synthesize the dynamic compensation amount and deviation data to generate an intermediate correction signal. Using the accelerometer feedback signal as a reference value, a weighted fusion algorithm is used to superimpose the intermediate correction signal and the accelerometer data a second time, ensuring that vibration disturbance characteristics are fully preserved. The superimposed correction signal undergoes amplitude normalization processing to eliminate the influence of dimensional differences between different signal sources, preparing for subsequent amplitude adjustments.

[0053] The amplitude of the corrected signal is adjusted based on the difference between the corrected signal and the accelerometer feedback signal to match the changing trends of the current temperature gradient data and vibration energy absorption rate. The instantaneous difference between the corrected signal and the accelerometer feedback signal is calculated in real time, and the changing trend of the difference is analyzed using a sliding window statistical method. The latest temperature gradient data and vibration energy absorption rate are obtained from the environmental monitoring unit, and a multidimensional correlation model with the signal difference is established. A fuzzy logic controller is used to dynamically adjust the gain coefficient of the corrected signal: increasing the compensation amplitude when the temperature gradient changes drastically and decreasing the compensation amplitude when the vibration energy absorption rate increases. Phase calibration is performed on the adjusted corrected signal to ensure that its waveform characteristics remain synchronized with the changing rhythm of environmental interference, forming an optimized signal dynamically matched to the environment.

[0054] The adjusted correction signal is injected into the gyroscope's drift correction loop. The corrected gyroscope output signal is acquired in real time and compared with the accelerometer feedback signal in a closed loop to generate an error signal. The adjusted correction signal is then injected into the gyroscope's drift correction loop via a digital-to-analog converter (DAC) to compensate the gyroscope output in real time at the analog signal level. A high-precision ADC module is used to acquire the compensated gyroscope output signal and compare it with the accelerometer feedback signal in the time domain to calculate the instantaneous differences in acceleration, angular velocity, and other dimensions. System errors and random noise are separated using digital filtering techniques, and error signal features characterizing the compensation effect are extracted. The error signal is standardized and encoded, including key parameters such as amplitude, frequency, and phase, providing a quantitative basis for rule optimization.

[0055] The weighting of temperature and vibration intensity in the dynamic compensation rule is adjusted based on the rate of change of the error signal. The compensation quantity generation logic in the dynamic compensation rule is updated through autonomous iterative optimization. The error signal is differentiated to calculate its rate of change per unit time, identifying the hysteresis characteristics of the system response. The coupling relationship between the rate of change and temperature gradient data and vibration energy absorption rate is analyzed; when temperature change dominates the error, the temperature weight is increased, and when vibration dominates, the vibration weight is increased. The rule base is autonomously iteratively optimized using a reinforcement learning algorithm: the Q-learning method is used to evaluate the long-term compensation effect of different weighting strategies, retaining the strategy that achieves the fastest error convergence speed. Finally, the decision tree structure of the dynamic compensation rule is updated, and the conditional judgment threshold and output calculation coefficients in the compensation quantity generation logic are optimized.

[0056] The updated dynamic compensation rules are re-injected into the drift correction loop to continuously correct the gyroscope output signal. The corrected signal and accelerometer feedback signal are then synchronously fed back to the compensation database, forming a closed-loop feedback chain. The updated dynamic compensation rules are compiled into a set of control instructions executable by the embedded system, which are seamlessly switched to the gyroscope's drift correction loop through a double-buffering mechanism. The compensation effect under the new rules is continuously monitored. When an improvement in the matching degree between the corrected signal and the accelerometer feedback signal is detected, the feature parameters and compensation parameters of successful cases are packaged and fed back to the compensation database. The incremental learning module of the database automatically extracts effective features from new cases, expanding the coverage of the rule base. This forms a complete closed-loop feedback chain from signal acquisition, real-time compensation to rule evolution, maintaining an attitude measurement accuracy of 0.005° / h even in extreme environments ranging from -55℃ to 125℃.

[0057] A correlation rule is established between temperature gradient data and energy dissipation parameters to generate a dynamic compensation quantity that matches the current temperature and vibration intensity. This correlation rule couples the rate of change of temperature gradient data with vibration energy absorption rate and scattering intensity data to generate a dynamic compensation rule under the combined effect of temperature and vibration. This includes collecting the rate of change of the current temperature gradient data and real-time values ​​of vibration energy absorption rate and scattering intensity data; acquiring the rate of temperature change of the temperature gradient data and the vibration energy absorption rate and scattering intensity data of the asymmetric elastic support structure through sensors; and obtaining real-time temperature readings of different areas at millisecond-level sampling frequencies using an array of temperature sensors distributed at key locations within the gyroscope cavity, and calculating the rate of change of temperature gradient data between adjacent sensors to form a quantitative index reflecting the rate of temperature fluctuation. Piezoelectric sensors installed on the asymmetric elastic support structure synchronously collect structural deformation data, extract the vibration energy absorption rate at characteristic frequencies using fast Fourier transform, and simultaneously measure the elastic wave scattering characteristics inside the structure using acoustic emission sensors to generate scattering intensity data. The three types of data are time-stamp aligned and unit-unified to ensure consistency in subsequent analysis.

[0058] The weighting of vibration energy absorption rate and scattering intensity data is adjusted based on the rate of change of temperature gradient data; the larger the value corresponding to the rate of temperature change, the higher the weighting ratio of the vibration parameters. A grading standard for the rate of temperature change is established, dividing the continuously collected temperature gradient change rate into three levels: stable, fluctuating, and drastic. Secondly, a dynamic weighting strategy is designed: when a drastic temperature change is detected, the weight coefficient of vibration energy absorption rate is increased by 40%, and the weight of scattering intensity data is increased by 30%; when the temperature change is stable, the basic weighting ratio is maintained. A sliding window mechanism is used to monitor the stability of the vibration parameters after weight adjustment; if parameter oscillation occurs, a weight smoothing transition algorithm is triggered to avoid system jitter caused by sudden parameter changes. A weighted vibration parameter dataset is generated to prepare for multi-source data fusion.

[0059] The weighted vibration energy absorption rate and scattering intensity data are superimposed with temperature gradient data to generate a dynamic parameter combination of the combined effect of temperature and vibration. The weighted vibration energy absorption rate and scattering intensity data are normalized to eliminate dimensional differences. A wavelet packet transform algorithm is used to decompose the vibration parameters into different frequency bands, and components overlapping with the characteristic frequency bands of temperature change are selected for focused fusion. Temperature gradient data and the selected vibration parameters are projected into a high-dimensional feature space using kernel function mapping, and the boundary features of the dynamic parameter combination are constructed using support vector data description methods. Principal component analysis is performed on the combined parameters to reduce dimensionality, and the top three principal components that best characterize the combined effect of temperature and vibration are extracted as core feature quantities.

[0060] Based on the correlation between temperature gradient data and deviation data in the compensation database, the dynamic parameter combination is mapped to an initial compensation amount matching the current temperature and vibration intensity. This normalizes the weighted vibration energy absorption rate and scattering intensity data, eliminating dimensional differences. A wavelet packet transform algorithm is used to decompose the vibration parameters into different frequency bands, selecting components overlapping with the temperature change characteristic frequency bands for focused fusion. The temperature gradient data and the selected vibration parameters are projected into a high-dimensional feature space using kernel function mapping, and the boundary features of the dynamic parameter combination are constructed using support vector data description methods. Principal component analysis is performed on the combined parameters to reduce dimensionality, extracting the top three principal components that best characterize the combined temperature-vibration effect as core feature quantities.

[0061] The weighting of temperature and vibration in the initial compensation amount is adjusted based on the real-time fluctuation amplitude of the angular velocity in the accelerometer feedback signal, generating the final dynamic compensation amount and updating the parameter generation logic in the dynamic compensation rules. The angular velocity spectrum characteristics of the accelerometer feedback signal are analyzed to identify whether the primary interference source is temperature or vibration. When the angular velocity fluctuation amplitude exceeds a threshold, a weight rebalancing mechanism is activated: if the fluctuation exhibits low-frequency characteristics, the temperature weight is increased; if it exhibits high-frequency characteristics, the vibration weight is increased. A fuzzy PID controller is used to dynamically adjust the mixing ratio of each component in the initial compensation amount, generating a final dynamic compensation amount that balances response speed and stability. The parameter adjustment trajectory of this optimization process is recorded in the knowledge base of the dynamic compensation rules. The conditional judgment threshold and output gain coefficient of the compensation amount generation logic are updated through a case-based reasoning algorithm, enabling the system to continuously evolve.

[0062] The following describes this embodiment in conjunction with an application scenario: In fully rotating vertical drilling systems, the high-speed rotation of the downhole drill string assembly and formation impact cause drastic temperature changes and mechanical vibrations inside the gyroscope measurement chamber, affecting guidance accuracy. A ring-shaped temperature sensor array is installed on the outer wall of the gyroscope chamber to collect real-time data on the axial temperature gradient caused by drill bit frictional heat generation and underground high-temperature conduction (e.g., temperature difference distribution between the top and bottom of the drill pipe). Simultaneously, the angular velocity deviation curve caused by thermal stress deformation in the gyroscope output signal is recorded. By analyzing the spatiotemporal correlation between the direction of temperature gradient change and the deviation amplitude, a temperature-deviation mapping compensation database is constructed. To isolate high-frequency downhole vibration interference, a titanium alloy asymmetric bellows support structure is installed at the connection between the drill string's rotating body and the drive shaft. Utilizing its high radial elasticity and high axial damping characteristics, the vibration energy generated by the drill bit impacting the formation is converted into bellows deformation absorption and multi-directional scattering field distribution, outputting energy absorption rate and scattering intensity parameters in real time. When the drill bit cuts into hard rock formations, a sharp increase in temperature gradient is detected due to heat generated by rock friction. Simultaneously, the bellows triggers a peak in scattering intensity due to a surge in vibration energy. At this point, the rate of temperature change and vibration scattering intensity are dynamically coupled: if the rate of increase in temperature gradient exceeds a set threshold, the weight of vibration parameters in the compensation rules is automatically increased, generating a joint compensation factor that integrates thermal expansion suppression and vibration scattering cancellation. This factor matches the initial compensation amount by querying historical temperature change-deviation correlation models in the compensation database, and then dynamically adjusts the weight ratio of temperature and vibration components based on the actual drill bit vibration trajectory (such as lateral oscillation characteristics) fed back by the accelerometer, forming the final compensation amount. After this compensation amount is injected into the gyroscope signal correction loop, the corrected angular velocity value is compared in real time with the actual drill bit movement direction calculated by the accelerometer. When a new error signal caused by a sudden change in lithology when encountering a fault is detected, the compensation rules are immediately iteratively optimized—for example, increasing the weight of vibration scattering intensity from 50% to 65% to enhance shock resistance. At the same time, the updated rules are synchronized to the compensation database, forming a complete link from downhole data acquisition, dynamic rule generation to closed-loop correction. Ultimately, under the combined interference of a 200°C temperature range downhole and a 10kHz high-frequency vibration, the measurement error of the drill string's rotating angular velocity was ensured to be less than 0.01° / s, maintaining the accuracy of the vertical drilling trajectory.

[0063] For the purpose of simplicity, the method steps disclosed in the above embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0064] like Figure 2 As shown, the present invention also provides a drill bit rotation angular velocity measurement system, comprising: The compensation database generation module 201 is configured to perform correlation analysis on continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal to generate a compensation database including the correlation relationship between the temperature gradient data and the angular velocity deviation data. The asymmetric elastic support structure installation and energy dissipation parameter generation module 202 is configured to install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data. The dynamic compensation rule generation module 203 is configured to establish the association rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, dynamic compensation rules under the combined action of temperature and vibration are generated. The dynamic compensation quantity generation and adjustment module 204 is configured to decompose the angular velocity deviation data according to the dynamic compensation rules, generate a dynamic compensation quantity that matches the current temperature and vibration intensity, and adjust the weight allocation of temperature and vibration intensity in the dynamic compensation quantity through the acquired accelerometer feedback signal. The rotating body angular velocity measurement output module 205 is configured to continuously inject the adjusted dynamic compensation amount into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control, and maintain the stable output of the rotating body angular velocity measurement value through the autonomous iterative optimization of the dynamic compensation rule.

[0065] It is worth noting that although only some basic functional modules are disclosed in the embodiments of this invention, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, what this embodiment intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be considered as the scope of protection of the claims of this invention being limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above device is described separately according to its functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0066] like Figure 3As shown, the present invention also provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of a method for measuring the angular velocity of a drill bit rotation.

[0067] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. For example... Figure 3 The structure shown in this embodiment of the invention includes an electronic device comprising one or more processors 710 and a memory 720; the processors 710 in this electronic device may be one or more. Figure 3 Taking a processor 710 as an example; a memory 720 is used to store one or more programs; the one or more programs are executed by the one or more processors 710, so that the one or more processors 710 implement a drill bit rotation angular velocity measurement method as described in any one of the embodiments of the present invention.

[0068] The electronic device may also include an input device 730 and an output device 740.

[0069] The processor 710, memory 720, input device 730, and output device 740 in this electronic device can be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0070] The memory 720 in this electronic device serves as a computer-readable storage medium, capable of storing one or more programs. These programs can be software programs, computer-executable programs, or modules, such as the program instructions / modules corresponding to the drill bit rotation angular velocity measurement method provided in this embodiment of the invention. The processor 710 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 720, thereby implementing the drill bit rotation angular velocity measurement method described in the above embodiment.

[0071] The memory 720 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device. Furthermore, the memory 720 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 720 may further include memory remotely located relative to the processor 710, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0072] Input device 730 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 740 may include display devices such as a display screen.

[0073] The present invention also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a method for measuring the angular velocity of a drill bit rotation.

[0074] Specifically, the computer storage medium in this embodiment of the invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be—but is not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: 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 embodiment, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring the angular velocity of a drill bit's rotating body, characterized in that, include: In response to the correlation analysis between continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database including the correlation relationship between the temperature gradient data and the angular velocity deviation data is generated; Install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data; Establish a correlation rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the combined action of temperature and vibration is generated. The angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount that matches the current temperature and vibration intensity. The weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted by the acquired accelerometer feedback signal. The adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control. Through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the rotating body angular velocity measurement value is maintained.

2. The method for measuring the angular velocity of a drill bit's rotating body according to claim 1, characterized in that, In response to the correlation analysis of continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal, a compensation database including the correlation relationship between the temperature gradient data and the angular velocity deviation data is generated, further including: Collect temperature gradient data at different locations and simultaneously record the raw angular velocity signal output by the gyroscope; Extract the angular velocity deviation data caused by temperature fluctuations from the original angular velocity signal; Analyze the correlation strength between the temperature gradient data and the angular velocity deviation data, and eliminate spurious correlations; The verified relationships are categorized and stored according to temperature ranges to form the compensation database.

3. The method for measuring the angular velocity of a drill bit's rotating body according to claim 1, characterized in that, An asymmetric elastic support structure is installed, and energy dissipation parameters are generated, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data, and further include: By utilizing the elastic differences of materials in orthogonal directions, directional absorption of vibrational energy can be achieved; The deformation response of the asymmetric elastic support structure under vibration at different frequencies was measured, and the curve of vibration energy absorption rate as a function of frequency was recorded. Elastic waves generated by microscopic deformation inside the asymmetric elastic support structure are collected, and the scattering intensity data is quantified to characterize the energy dissipation efficiency. The energy dissipation parameter is generated by integrating the vibration energy absorption rate and the scattering intensity data.

4. The method for measuring the angular velocity of a drill bit's rotating body according to claim 1, characterized in that, Establish a correlation rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the combined effect of temperature and vibration is generated, further including: Calculate the rate of change of the temperature gradient data; The rate of change of the temperature gradient data is coupled with the vibration energy absorption rate in the energy dissipation parameters to establish a correlation model for the resonance amplification of the asymmetric elastic support structure caused by temperature fluctuations. The rate of change of temperature gradient data, vibration energy absorption rate, and scattering intensity data are projected onto a high-dimensional feature space to generate dynamic compensation rules.

5. The method for measuring the angular velocity of a drill bit's rotating body according to claim 1, characterized in that, The angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount that matches the current temperature and vibration intensity. The weighting of temperature and vibration intensity in the dynamic compensation amount is adjusted using the acquired accelerometer feedback signal. This further includes: Based on the dynamic compensation rule, the angular velocity deviation data is decomposed to separate the low-frequency component dominated by temperature and the high-frequency component dominated by vibration. Based on the real-time temperature, a basic dynamic compensation amount is generated by matching the compensation coefficients in the compensation database. The accelerometer feedback signal is introduced to verify the vibration compensation effect, and the weighting ratio of temperature and vibration intensity in the dynamic compensation is adjusted. Phase calibration is performed on the dynamic compensation amount after weight adjustment.

6. The method for measuring the angular velocity of a drill bit's rotating body according to claim 1, characterized in that, The adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control. Furthermore, through the autonomous iterative optimization of the dynamic compensation rule, a stable output of the rotating body angular velocity measurement value is maintained. The adjusted dynamic compensation amount is injected into the drift correction loop to offset the original deviation; The difference between the compensated gyroscope output and the accelerometer feedback signal is compared. If the residual exceeds a preset range, an online learning mechanism is triggered. The parameters of the dynamic compensation rule are autonomously and iteratively optimized using a reinforcement learning algorithm.

7. The method for measuring the angular velocity of a drill bit's rotating body according to claim 6, characterized in that, The adjusted dynamic compensation amount is injected into the drift correction loop to offset the original deviation; Before comparing the difference between the compensated gyroscope output and the accelerometer feedback signal, and triggering the online learning mechanism if the residual exceeds a preset range, the method further includes: The dynamic compensation amount is superimposed with the angular velocity deviation data of the current gyroscope output signal and the real-time data of the accelerometer feedback signal to generate a correction signal. The amplitude of the correction signal is adjusted based on the difference between the correction signal and the accelerometer feedback signal, so that the adjusted correction signal amplitude matches the current temperature gradient data and the changing trend of vibration energy absorption rate. The adjusted correction signal is injected into the drift correction loop, the corrected gyroscope output signal is acquired in real time, and a closed-loop comparison is performed with the accelerometer feedback signal to generate an error signal. The weighting of temperature and vibration intensity in the dynamic compensation rule is adjusted according to the rate of change of the error signal, and the compensation amount generation logic in the dynamic compensation rule is updated through autonomous iterative optimization.

8. A drilling tool rotation body angular velocity measurement system, characterized in that, include: The compensation database generation module is configured to perform correlation analysis on continuously acquired temperature gradient data and angular velocity deviation data in the gyroscope output signal to generate a compensation database that includes the correlation relationship between the temperature gradient data and the angular velocity deviation data. An asymmetric elastic support structure installation and energy dissipation parameter generation module is configured to install an asymmetric elastic support structure and generate energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data. The dynamic compensation rule generation module is configured to establish the association rule between the temperature gradient data and the energy dissipation parameter. By coupling the rate of change of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, dynamic compensation rules under the combined action of temperature and vibration are generated. The dynamic compensation quantity generation and adjustment module is configured to decompose the angular velocity deviation data according to the dynamic compensation rules, generate a dynamic compensation quantity that matches the current temperature and vibration intensity, and adjust the weight allocation of temperature and vibration intensity in the dynamic compensation quantity through the acquired accelerometer feedback signal. The rotating body angular velocity measurement output module is configured to continuously inject the adjusted dynamic compensation amount into the drift correction loop, so that the corrected gyroscope output signal and the accelerometer feedback signal form a closed-loop control, and maintain the stable output of the rotating body angular velocity measurement value through the autonomous iterative optimization of the dynamic compensation rule.

9. An electronic device, characterized in that, include: The system includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method according to any one of claims 1 to 7.

Images