A method, system, device and storage medium for measuring the angular velocity of a drill tool body

Abstract

The present application relates to the technical field of angular velocity measurement, and discloses a drilling tool rotating body angular velocity measurement method, system, device and storage medium, which comprises a compensation database for generating a correlation between temperature gradient data and angular velocity deviation data; an asymmetric elastic support structure is installed, and an energy dissipation parameter is generated; a correlation rule between the temperature gradient data and the energy dissipation parameter is established, and 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, a dynamic compensation amount is generated, and the weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal; the adjusted dynamic compensation amount is continuously injected into a drift correction loop, so that the corrected gyro output signal and the accelerometer feedback signal form a closed-loop control, and through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the rotating body angular velocity measurement value is maintained. The present application can improve the angular velocity measurement accuracy and stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of angular velocity measurement, and in particular to a drilling tool rotary body angular velocity measurement method, system, device and storage medium. BACKGROUND

[0002] In the dynamic drilling process of the full-rotation vertical drilling system, maintaining high-precision measurement of the rotary body angular velocity is the core to ensure the accuracy of the drilling trajectory. However, the downhole environment is extremely complex and harsh, and the drilling assembly is subjected to the combined interference of strong vibration, high temperature and high pressure, and drilling fluid erosion when rotating at high speed, which poses a severe challenge to the measurement stability of the gyroscope and accelerometer.

[0003] The existing technology mainly faces the following bottlenecks: first, the gyroscope is extremely sensitive to temperature fluctuations, and the heat generated by the friction between the drill bit and the formation and the conduction of the underground high temperature will form a dramatic temperature gradient in the sensor cavity, causing thermal stress deformation and resulting in significant low-frequency drift of the angular velocity output signal. Second, the impact load generated when the drill bit cuts into different rock layers will excite high-frequency vibration, which, combined with the stick-slip vibration of the drill string and the sudden change in drilling pressure, will not only directly interfere with the sensor readings and introduce high-frequency noise, but also will be coupled with the temperature effect to produce complex coupling errors, making the traditional single-factor compensation method ineffective.

[0004] The existing technology adopts passive isolation or single-dimensional compensation strategies. For example, a vibration damper with a symmetrical structure is used to isolate vibration, or a fixed temperature lookup table method is used to compensate for gyroscope drift. However, these methods have obvious limitations: passive vibration isolation structures are often effective at specific frequencies and cannot adapt to wideband downhole vibrations, and cannot adapt to changing conditions; and a single temperature compensation model cannot handle the nonlinear errors produced by the interaction of vibration and temperature, resulting in deviations in the angular velocity measurement value after compensation during dynamic drilling, which in turn causes deviation of the inclination angle and instability of the tool face, ultimately affecting the accuracy and reliability of vertical drilling.

[0005] Therefore, the present application provides a drilling tool rotary body angular velocity measurement method, system, device and storage medium to solve the above technical problems. SUMMARY

[0006] The purpose of the present application is to provide a drilling tool rotary body angular velocity measurement method, system, device and storage medium to solve the technical problem of deviation in the angular velocity measurement value after compensation in the prior art, which affects the accuracy and reliability of vertical drilling.

[0007] To solve the above technical problems, the present application provides a drilling tool rotary body angular velocity measurement method, comprising:

[0008] correlating the continuously collected temperature gradient data with angular velocity deviation data in the gyro output signal to generate a compensation database including a correlation between the temperature gradient data and the angular velocity deviation data;

[0009] installing an asymmetric elastic support structure and generating an energy dissipation parameter, wherein the energy dissipation parameter includes vibration energy absorption rate and scattering intensity data;

[0010] establishing a correlation rule between the temperature gradient data and the energy dissipation parameter, and generating a dynamic compensation rule under the joint action of temperature and vibration by coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data;

[0011] According to the dynamic compensation rule, the angular velocity deviation data is decomposed to generate a dynamic compensation amount matched with the current temperature and vibration intensity, and the weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal;

[0012] The adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyro output signal and the accelerometer feedback signal form a closed-loop control, and through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the angular velocity measurement value of the rotating body is maintained.

[0013] In some embodiments, in response to the correlation analysis of the continuously collected temperature gradient data and the angular velocity deviation data in the gyro output signal, a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data is generated, further comprising:

[0014] Collecting temperature gradient data at different positions and synchronously recording the original angular velocity signal output by the gyro;

[0015] Extracting angular velocity deviation data caused by temperature fluctuations from the original angular velocity signal;

[0016] Analyzing the correlation strength of the temperature gradient data and the angular velocity deviation data, and eliminating false correlations;

[0017] The verified correlation relationship is stored according to temperature intervals to form the compensation database.

[0018] In some embodiments, an asymmetric elastic support structure is installed and an energy dissipation parameter is generated, wherein the energy dissipation parameter includes vibration energy absorption rate and scattering intensity data, further comprising:

[0019] Utilizing the elastic difference of the material in the orthogonal direction to realize directional absorption of vibration energy;

[0020] Measuring the deformation response of the asymmetric elastic support structure under vibration at different frequencies, recording the curve of vibration energy absorption rate changing with frequency;

[0021] Collecting the elastic waves generated by the microscopic deformation inside the asymmetric elastic support structure, quantifying the scattering intensity data to represent the energy dissipation efficiency;

[0022] Integrating the vibration energy absorption rate and the scattering intensity data to generate the energy dissipation parameter.

[0023] In some embodiments, the correlation between the temperature gradient data and the energy dissipation parameter is established, and the dynamic compensation rule under the joint action of temperature and vibration is generated by coupling the change rate of temperature gradient data with the vibration energy absorption rate and the scattering intensity data, further comprising:

[0024] Calculating the change rate of the temperature gradient data;

[0025] Coupling the change rate of the temperature gradient data with the vibration energy absorption rate in the energy dissipation parameter to establish a correlation model of temperature fluctuation triggering resonance amplification of the asymmetric elastic support structure;

[0026] Projecting the change rate of the temperature gradient data, the vibration energy absorption rate and the scattering intensity data into a high-dimensional feature space to generate a dynamic compensation rule.

[0027] In some embodiments, the angular velocity deviation data is decomposed according to the dynamic compensation rule to generate a dynamic compensation amount matching the current temperature and vibration intensity, and the weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal, further comprising:

[0028] Decomposing the angular velocity deviation data based on the dynamic compensation rule to separate the temperature-dominant low-frequency component and the vibration-dominant high-frequency component;

[0029] Generating a basic dynamic compensation amount according to the real-time temperature matching the compensation coefficient in the compensation database;

[0030] Introducing the accelerometer feedback signal to verify the vibration compensation effect and adjusting the weight distribution proportion of temperature and vibration intensity in the dynamic compensation amount;

[0031] Phase calibration is performed on the dynamic compensation amount after adjusting the weight.

[0032] In some embodiments, the adjusted dynamic compensation quantity is injected into the drift correction loop to form a closed loop control with the accelerometer feedback signal, and is iteratively optimized by the autonomous reinforcement learning algorithm to maintain stable output of the measured angular velocity of the rotating body, further comprising:

[0033] injecting the adjusted dynamic compensation quantity into the drift correction loop to offset the original bias;

[0034] comparing the difference between the compensated gyro output and the accelerometer feedback signal, and triggering the online learning mechanism if the residual error exceeds the preset range;

[0035] iteratively optimizing the parameters of the dynamic compensation rule by the reinforcement learning algorithm.

[0036] In some embodiments, the adjusted dynamic compensation quantity is injected into the drift correction loop to offset the original bias; before comparing the difference between the compensated gyro output and the accelerometer feedback signal, and triggering the online learning mechanism if the residual error exceeds the preset range, the method further comprises:

[0037] superimposing the dynamic compensation quantity with the angular velocity bias data of the current gyro output signal and the real-time data of the accelerometer feedback signal to generate a correction signal;

[0038] adjusting the amplitude of the correction signal according to the difference between the correction signal and the accelerometer feedback signal, so that the adjusted amplitude of the correction signal matches the current temperature gradient data and the change trend of the vibration energy absorption rate;

[0039] injecting the adjusted correction signal into the drift correction loop, collecting the corrected gyro output signal in real time, and comparing it with the accelerometer feedback signal in a closed loop to generate an error signal;

[0040] adjusting the weight distribution of temperature and vibration intensity in the dynamic compensation rule according to the change rate of the error signal, and updating the compensation quantity generation logic in the dynamic compensation rule by autonomous iterative optimization.

[0041] Based on the same concept, the present application also provides a drilling tool rotating body angular velocity measurement system, comprising:

[0042] a compensation database generation module configured to perform correlation analysis on the continuously collected temperature gradient data and the angular velocity bias data in the gyro output signal, and generate a compensation database including the correlation between the temperature gradient data and the angular velocity bias data;

[0043] 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;

[0044] A dynamic compensation rule generation module is configured to establish an association rule of the temperature gradient data and the energy dissipation parameters, and generate a dynamic compensation rule under the joint action of temperature and vibration by coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data.

[0045] A dynamic compensation amount generation and adjustment module is configured to decompose the angular velocity deviation data according to the dynamic compensation rule, generate a dynamic compensation amount matched with the current temperature and vibration intensity, and adjust the weight distribution of the temperature and vibration intensity in the dynamic compensation amount through the obtained accelerometer feedback signal.

[0046] A rotary body angular velocity measurement value output module is configured to continuously inject the adjusted dynamic compensation amount into a drift correction loop, so that the corrected gyro output signal and the accelerometer feedback signal form a closed-loop control, and through autonomous iterative optimization of the dynamic compensation rule, the stable output of the rotary body angular velocity measurement value is maintained.

[0047] Based on the same concept, the application also provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the rotary body angular velocity measurement method of the drilling tool.

[0048] Based on the same concept, the application also provides a computer readable storage medium, which stores a computer program executable by an electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the rotary body angular velocity measurement method of the drilling tool.

[0049] Compared with the prior art, the application has the beneficial effects that:

[0050] The application discloses a rotary body angular velocity measurement method, system, device and storage medium of a drilling tool, realizes adaptive and intelligent compensation process, and improves the precision and stability of angular velocity measurement in a complex environment. BRIEF DESCRIPTION OF DRAWINGS

[0051] Other features, objects and advantages of the application will become more apparent through reading the following detailed description of non-limiting embodiments made with reference to the accompanying drawings:

[0052] Figure 1is a flowchart of a method for measuring angular velocity of a rotary body of a drilling tool according to some embodiments of the present application;

[0053] Figure 2 is a structural diagram of a system for measuring angular velocity of a rotary body of a drilling tool according to some embodiments of the present application;

[0054] Figure 3 is a structural diagram of an electronic device according to some embodiments of the present application;

[0055] In the figure, 710 is a processor; 720 is a memory; 730 is an input device; and 740 is an output device. DETAILED DESCRIPTION

[0056] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0057] The terms used in the embodiments of the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the present application. The singular forms "a", "an" and "the" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Multiple" generally includes at least two.

[0058] It should be understood that the term "and / or" used herein only describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship.

[0059] It should be understood that although the terms first, second, third, etc. can be used in the embodiments of the present application to describe, these descriptions should not be limited to these terms. These terms are only used to distinguish the description. For example, without departing from the scope of the embodiments of the present application, the first can also be called the second, and similarly, the second can also be called the first.

[0060] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if [a stated condition or event] is detected" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event]."

[0061] It is also important to note that the terms "comprises", "comprising", or other variations thereof are intended to cover a non-exclusive inclusion, such that a product or method that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such product or method. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the product or method that includes the element.

[0062] It is particularly important to note that the symbols and / or numbers present in the specification, if not marked in the description of the figures, are not figure references.

[0063] Referring to Figure 1 A method for measuring the angular velocity of a drill tool rotating body, comprising:

[0064] S101, in response to the correlation analysis of the continuously collected temperature gradient data and the angular velocity deviation data in the gyro output signal, a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data is generated;

[0065] S102, an asymmetric elastic support structure is installed, and an energy dissipation parameter is generated, wherein the energy dissipation parameter includes vibration energy absorption rate and scattering intensity data;

[0066] S103, the correlation rule between the temperature gradient data and the energy dissipation parameter is established, and by coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data, a dynamic compensation rule under the joint action of temperature and vibration is generated;

[0067] S104, according to the dynamic compensation rule, the angular velocity deviation data is decomposed, a dynamic compensation amount matched with the current temperature and vibration intensity is generated, and the weight distribution of the temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal;

[0068] S105, the adjusted dynamic compensation quantity is continuously injected into the drift correction loop to form a closed loop control with the accelerometer feedback signal, and through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the gyro output signal is maintained.

[0069] Specifically, in the embodiment of the present application, the temperature gradient data continuously collected is associated with the angular velocity deviation data in the gyro output signal for analysis, specifically by arranging a temperature sensor array in the gyro cavity to collect temperature readings at different positions at a millisecond level frequency and calculate the gradient change, while synchronously recording the original angular velocity signal output by the gyro, using a signal processing algorithm to extract the deviation component caused by temperature fluctuations, and then calculating the quantitative relationship between the temperature gradient and the angular velocity deviation by correlation analysis and eliminating false correlations, and finally storing the structured compensation database according to the temperature interval classification; then install an asymmetric elastic support structure composed of a specific material, use the elastic difference in the orthogonal direction to realize directional absorption and scattering of vibration energy, obtain the vibration energy absorption rate curve by measuring the deformation response of the structure under different frequency vibrations, and collect the internal elastic wave signal to quantify the scattering intensity, and integrate to generate energy dissipation parameters containing absorption rate and scattering intensity data; further establish the correlation rule between the temperature gradient data and the energy dissipation parameters, calculate the temperature gradient change rate and couple it with the vibration energy absorption rate and scattering intensity data for multi-dimensional coupling analysis, construct a mathematical model of the combined action of temperature and vibration, and generate a dynamic compensation rule with working condition adaptive ability using a machine learning algorithm; according to the dynamic compensation rule, the real-time collected angular velocity deviation data is mode decomposed to separate the temperature and vibration dominated components, and the initial dynamic compensation quantity is matched and generated by combining the compensation database, and the accelerometer feedback signal is introduced to optimize the allocation proportion of temperature and vibration factors in the compensation quantity by weight adjustment algorithm; finally, the optimized dynamic compensation quantity is injected into the drift correction loop for real-time signal compensation, the error signal is generated by comparing the corrected gyro output with the accelerometer feedback signal, the weight distribution logic and parameter generation strategy in the dynamic compensation rule are iteratively updated based on the error change rate using a reinforcement learning algorithm, forming a closed loop control link, and maintaining the stable output of the angular velocity measurement value in the continuous temperature fluctuation and vibration interference environment.

[0070] For example, the temperature sensor array data is acquired at a millisecond-level sampling frequency, and the temperature gradient change rate between adjacent sensors is calculated to be a temperature change per millimeter per second. Assuming that the temperature gradient change rate is detected to be 0.5°C / (mm·s), and the gyro output angular velocity deviation value is recorded as 0.2° / s at the same time; after extracting the temperature-induced deviation component using wavelet transform, the correlation degree between the temperature gradient and the deviation is calculated to be 0.85 through grey correlation analysis. Pseudo-data with a correlation degree lower than 0.6 is removed, and the effective data is classified and stored in the database according to the temperature interval of 0-50°C and 50-100°C. In the vibration parameter acquisition stage, the deformation response of the asymmetric support structure under a vibration frequency of 200 Hz is measured, and the vibration energy absorption rate is obtained to be 65%. At the same time, the scattering intensity is measured by the acoustic emission sensor to be 80 mV; and the energy dissipation parameter set is generated after integration. In the rule generation stage, the temperature gradient change rate and the vibration parameter coupling value are calculated. For example, when the temperature change rate reaches 1°C / s and the vibration absorption rate exceeds 60%, the dynamic compensation rule coefficient is output to be 1.2 through the support vector regression model. In the compensation amount calculation stage, the basic compensation amount corresponding to the current temperature interval is matched from the database to be -0.1° / s, and the vibration weight is adjusted from 50% to 70% according to the angular velocity fluctuation amplitude fed back by the accelerometer (such as detecting that the high-frequency fluctuation amplitude exceeds 0.05° / s), and the final compensation amount is generated to be -0.12° / s. In the closed-loop optimization stage, after injecting the compensation amount, 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 through the Q-learning algorithm, and the decision threshold in the rule library is updated, so that the angular velocity output error is finally stabilized within 0.01° / s.

[0071] In some applications, in response to the correlation analysis of the continuously collected temperature gradient data and the angular velocity deviation data in the gyro output signal, a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data is generated, including collecting temperature gradient data at different positions, and synchronously recording the original angular velocity signal output by the gyro; extracting the angular velocity deviation data caused by temperature fluctuation from the original angular velocity signal; analyzing the correlation strength of the temperature gradient data and the angular velocity deviation data, and removing pseudo-correlation; storing the verified correlation relationship according to the temperature interval to form the compensation database.

[0072] It can be understood that high-precision temperature readings are synchronously collected at multiple key positions inside the gyro cavity to form spatial temperature gradient distribution data, and the original angular velocity signal output by the gyro in real time is recorded in a strictly aligned manner with millisecond-level timestamps; a signal decomposition algorithm is used to separate the low-frequency drift component caused by temperature fluctuations from the original 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 by a correlation analysis method, and a correlation threshold is set to filter out false correlation relationships caused by random interference; temperature-deviation data pairs that pass the verification and have significant correlation are classified and stored according to the interval range to which their temperature values belong, thereby forming a temperature-deviation compensation database for subsequent real-time query and matching.

[0073] For example, by arranging three temperature sensors on the X, Y, and Z axes of the gyro cavity to collect data, the axial temperature gradient value is calculated to be 0.3°C / mm, and the original angular velocity signal output by the gyro at this moment is recorded as 15.5° / s; a wavelet transform algorithm is used to decompose the signal, and a low-frequency component with a frequency lower than 1 Hz is extracted, which is confirmed as temperature-induced angular velocity deviation data with a value of 0.4° / s. The correlation degree between the current temperature gradient data and the angular velocity deviation data is calculated by a grey correlation analysis method, and the correlation degree is 0.78. The correlation threshold is set to 0.6, and if it is higher than this threshold, it is determined to be valid correlation, and if it is lower than this value, it is excluded as false correlation. The valid data pair is classified according to the temperature value, and if the current average temperature is 75°C, it is stored in the database partition of the 70-80°C temperature interval. This partition can represent a data record as follows: temperature gradient 0.3°C / mm, corresponding angular velocity deviation 0.4° / s, and correlation degree 0.78. The data is continuously accumulated to form a database covering different temperature intervals that can be used for real-time compensation query.

[0074] In some applications, an asymmetric elastic support structure is installed, and an energy dissipation parameter is generated, wherein the energy dissipation parameter includes vibration energy absorption rate and scattering intensity data, including directional absorption of vibration energy by utilizing the elastic difference of materials in orthogonal directions; the deformation response of the asymmetric elastic support structure under different frequency vibrations is measured, and the curve of the vibration energy absorption rate changing with frequency is recorded; the elastic wave generated by the microscopic deformation inside the asymmetric elastic support structure is collected, and the scattering intensity data is quantified to represent the energy dissipation efficiency; the vibration energy absorption rate and the scattering intensity data are integrated to generate the energy dissipation parameter.

[0075] It can be understood that by utilizing the different elastic modulus characteristics of a specific material in three orthogonal directions, the directional absorption and conversion of vibration energy in a specific direction is achieved by designing an asymmetric structure. By applying external vibration excitation of different frequencies to the installed asymmetric elastic support structure, the dynamic deformation response data at each frequency point is measured and recorded, and then the vibration energy absorption rate is calculated and the characteristic curve of the change in frequency is drawn. The elastic wave signals generated by the internal micro-deformation of the support structure during vibration are simultaneously collected, and through time-frequency analysis and energy quantization of the signals, the scattering intensity data representing the ability of the structure to convert vibration energy into elastic waves and scatter outward is obtained. Finally, the vibration energy absorption rate curve representing the energy absorption characteristics and the scattering intensity data representing the energy scattering characteristics are integrated and formatted in multiple dimensions to generate an energy dissipation parameter set that comprehensively describes the energy dissipation performance of the support structure in a vibrating environment.

[0076] 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. By utilizing this anisotropic property, vibration energy is preferentially absorbed along the Z-axis direction (low stiffness direction). In the vibration test, the structure is subjected to frequency scanning excitation from 50 Hz to 500 Hz, and its vibration response is measured. For example, at a frequency of 250 Hz, the measured response amplitude of the structure is 30% of the base excitation amplitude, and the calculated vibration energy absorption rate at this frequency is 70%. The elastic wave signals generated inside the structure at this frequency are collected by a piezoelectric sensor, and the acoustic emission energy is analyzed to be 85 dB, which is quantized as a scattering intensity reference value. The data at this frequency point are integrated into an energy dissipation parameter record: frequency 250 Hz, vibration energy absorption rate 70%, scattering intensity 85 dB. By integrating the full-band scanning data, an energy dissipation parameter database is generated, which includes the corresponding relationship between absorption rate and scattering intensity, and provides a basis for subsequent composite compensation.

[0077] In some applications, a correlation rule between the temperature gradient data and the energy dissipation parameters is established, and by coupling the change rate 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, including calculating the change rate of the temperature gradient data; coupling and analyzing the change rate of the temperature gradient data with the vibration energy absorption rate in the energy dissipation parameters to establish a correlation model of temperature fluctuation-induced resonance amplification of the asymmetric elastic support structure; projecting the change rate of the temperature gradient data, the vibration energy absorption rate, and the scattering intensity data to a high-dimensional feature space to generate a dynamic compensation rule.

[0078] It can be understood that the temperature gradient data collected continuously is differentiated to calculate the change rate per unit time to quantify the intensity of temperature fluctuation; the calculated temperature gradient change rate is coupled with the vibration energy absorption rate in the energy dissipation parameter for multi-dimensional analysis, and a transfer function model is established to reveal the physical correlation mechanism of temperature fluctuation causing the asymmetric elastic support structure to deviate from the resonance frequency and change the vibration energy absorption characteristics; the temperature gradient change rate representing the intensity of thermal disturbance, the vibration energy absorption rate representing the vibration absorption characteristics, and the scattering intensity data representing the energy dispersion characteristics are mapped to a high-dimensional feature space, and a machine learning algorithm is used to mine the nonlinear interaction relationship between multiple parameters and fit the joint distribution characteristics in the space; based on the coupling relationship in the high-dimensional feature space, a dynamic compensation rule is generated which can respond to temperature and vibration compound interference and has self-adaptive adjustment capability.

[0079] For example, the calculated change rate of the current temperature gradient data is 0.8°C / s, which reflects that the temperature is rising rapidly. Query the energy dissipation parameters of the asymmetric elastic support structure under the current working condition, and obtain the corresponding vibration energy absorption rate of 75% and the scattering intensity data of 90 dB at the dominant vibration frequency of 300 Hz at this moment. Coupling analysis is performed on the three parameters (0.8°C / s, 75%, 90 dB): through the preset transfer function model analysis, it is concluded that the current temperature change rate has a high probability of causing the support structure to resonate near 305 Hz, which may amplify the vibration interference. The three parameters are input into the support vector regression model based on the radial basis function for high-dimensional feature mapping and calculation. The model outputs the decision coefficient of the dynamic compensation rule through internal operation, for example, the rule coefficient K is calculated as 1.25. This coefficient K is used to adjust the generation amplitude of the subsequent compensation amount, and the dynamic compensation rule can be expressed as: when the temperature change rate is higher than 0.5°C / s and appears 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 the possible resonance amplification effect, thereby achieving accurate compensation under the combined action of temperature and vibration.

[0080] In some applications, the angular velocity deviation data is decomposed according to the dynamic compensation rule, a dynamic compensation amount matching the current temperature and vibration intensity is generated, and the weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal, including decomposing the angular velocity deviation data according to the dynamic compensation rule to separate the low-frequency component dominated by temperature and the high-frequency component dominated by vibration; generating a basic dynamic compensation amount according to the real-time temperature matching the compensation coefficient in the compensation database; introducing the accelerometer feedback signal to verify the vibration compensation effect and adjusting the weight distribution proportion of temperature and vibration intensity in the dynamic compensation amount; and phase calibrating the dynamic compensation amount after adjusting the weight.

[0081] It can be understood that, based on the frequency characteristic information contained in the established dynamic compensation rule, the adaptive signal decomposition algorithm is used to analyze the frequency domain of the real-time collected angular velocity deviation data, and the low-frequency drift component caused by temperature change and the high-frequency fluctuation component caused by mechanical vibration are separated; the current real-time temperature data is queried in the compensation database, the basic temperature compensation coefficient corresponding to the temperature point is matched and obtained, and the initial basic dynamic compensation amount is generated in combination with the amplitude adjustment coefficient output by the dynamic compensation rule; the angular velocity signal fed back by the accelerometer in real time is introduced as an independent reference benchmark, the vibration compensation effect is quantitatively evaluated by calculating the residual of the signal and the compensated signal in the high-frequency band, and the weight optimization algorithm is used to dynamically adjust the weight distribution proportion of the temperature compensation component and the vibration compensation component in the basic dynamic compensation amount according to the evaluation result; the dynamic compensation amount after adjusting the weight is subjected to phase lag calibration processing, so that the phase characteristic error of the compensation amount and the actual output signal of the gyroscope is kept synchronous, and it is ensured that the compensation amount can be accurately injected and effectively offset the original deviation.

[0082] For example, the dynamic compensation rule is applied: the rule indicates that the low-frequency band below 1 Hz and the high-frequency band above 100 Hz need to be concerned. The angular velocity deviation data (for example, the current value is 0.5° / s) is decomposed by using the variational mode decomposition algorithm, and 0.3° / s of low-frequency component (judged as caused by temperature) and 0.2° / s of high-frequency component (judged as caused by vibration) are successfully separated. The current temperature is read as 85°C, the basic temperature compensation coefficient under the temperature is obtained by querying the compensation database, and the initial basic dynamic compensation amount is calculated and generated as-0.28° / s×1.2=-0.336° / s in combination with the current vibration gain coefficient 1.2 given by the dynamic compensation rule. The high-frequency signal energy fed back by the accelerometer is read as 0.15° / s, which is found to be higher than the expected threshold 0.1° / s, indicating that the vibration compensation is not sufficient. The weight adjustment is started, the weight of the vibration component is increased from the initial 50% to 65%, and the weight of the temperature component is correspondingly reduced from 50% to 35%, and the adjusted dynamic compensation amount becomes (-0.336° / s×35%)+(a vibration compensation value for 0.2° / s high-frequency component×65%). It is detected that the compensation amount has a phase lag of 5 milliseconds relative to the original deviation signal, and the phase lead compensation is performed by using a all-pass filter to eliminate the lag, so as to ensure that the compensation signal and the error signal are accurately aligned in time after being injected into the correction loop.

[0083] In some applications, the adjusted dynamic compensation quantity is continuously injected into the drift correction loop to form a closed-loop control of the modified gyroscope output signal and the accelerometer feedback signal, and is iteratively optimized by the autonomous dynamic compensation rule to maintain stable output of the measured angular velocity of the rotating body, including injecting the adjusted dynamic compensation quantity 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 the online learning mechanism if the residual error exceeds the preset range; and iteratively optimizing the parameters of the dynamic compensation rule by the reinforcement learning algorithm.

[0084] It can be understood that the final dynamic compensation quantity after weight adjustment and phase calibration is injected into the drift correction loop of the gyroscope in real time through a high-precision digital-to-analog conversion interface, and is superimposed on the original gyroscope output signal at the analog signal level to directly offset the temperature and vibration compound deviation contained therein; the numerical difference between the compensated and corrected gyroscope output signal and the angular velocity signal fed back by the accelerometer at the same time is continuously collected and compared, and a real-time residual error signal is calculated, and when the amplitude or energy of the residual error signal is monitored to exceed the preset stable threshold range, the built-in online autonomous learning mechanism is triggered; and then the reinforcement learning algorithm framework is called to construct a reward function guided by the residual error signal, and the influence of different adjustment strategies of the key parameters in the dynamic compensation rule on the long-term compensation effect is explored and evaluated through multiple iterations, and the weight distribution coefficient, frequency characteristic parameter or gain adjustment factor in the rule is autonomously optimized and updated; finally, the optimized new parameter set is fed back to the dynamic compensation rule generation module, so that the module has the ability to adapt to time-varying environments, thereby continuously maintaining stable and high-precision output of the measured angular velocity of the rotating body in the entire closed-loop control process.

[0085] For example, the adjusted dynamic compensation quantity -0.38° / s is injected into the drift correction loop of the gyroscope through a 16-bit DAC. After compensation, the output signal of the gyroscope changes from the original 15.5° / s to 15.12° / s. The feedback signal of the accelerometer is read synchronously as 15.10° / s, and the residual error between the two is calculated as 0.02° / s. The residual error exceeds the preset stable threshold (0.015° / s), triggering the online learning mechanism. The Q-learning algorithm is then started for optimization: the algorithm defines the current state as (temperature change rate = 0.8 °C / s, residual error = 0.02° / s), and after simulation evaluation, the vibration weight coefficient is increased from the current 0.65 to 0.75, which is predicted to reduce the residual error to 0.01° / s in the next 5 control periods, thereby obtaining the maximum reward value. Accordingly, the vibration weight coefficient parameter in the dynamic compensation rule is updated to 0.75. The updated rule will be used to generate the dynamic compensation quantity for the next control period, thereby achieving the closed-loop control goal of continuously improving the output stability through autonomous iterative optimization.

[0086] In some applications, the adjusted dynamic compensation quantity is injected into the drift correction loop to offset the original deviation; before triggering the online learning mechanism, the difference between the compensated gyro output and the accelerometer feedback signal is compared, and if the residual error exceeds the preset range, the dynamic compensation quantity is superimposed with the angular velocity deviation data of the current gyro 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 current temperature gradient data and the change trend of the vibration energy absorption rate; the adjusted correction signal is injected into the drift correction loop, the corrected gyro output signal is collected in real time, and compared with the accelerometer feedback signal in a closed loop to generate an error signal; the weight distribution of temperature and vibration intensity in the dynamic compensation rule is adjusted according to the change rate of the error signal, and the compensation quantity generation logic in the dynamic compensation rule is updated by autonomous iterative optimization.

[0087] It can be understood that the generated dynamic compensation quantity is subjected to multi-source data synchronization and weighted superposition processing with the angular velocity deviation data contained in the current gyro output signal and the angular velocity signal fed back by the accelerometer in real time, and a preliminary correction signal is generated by a digital signal synthesis algorithm; the instantaneous difference between the correction signal and the accelerometer feedback signal in the time domain is calculated in real time, and the amplitude characteristic and change trend of the difference are combined with the current collected temperature gradient data and the real-time value of the vibration energy absorption rate, and an adaptive gain adjustment strategy is used to dynamically adjust the amplitude of the correction signal, so that the amplitude change matches the change trend of the temperature gradient and the vibration energy; the amplitude-adjusted correction signal is injected into the drift correction loop through a digital-to-analog conversion interface to implement preliminary compensation, and the gyro output signal after compensation is collected synchronously, and compared with the accelerometer feedback signal as a reference in time and frequency domains, and the residual error characteristics between the two are extracted and a quantized error signal is generated; the change rate of the error signal is obtained by differential processing, and the main source of the current error is determined according to the direction and size of the rate value, i.e. whether it is caused by temperature or vibration, and then the distribution proportion of the temperature weight and the vibration weight in the dynamic compensation rule is adjusted accordingly, and the condition threshold and output coefficient of the compensation quantity generation logic in the rule are updated by an autonomous iterative optimization algorithm based on reinforcement learning, forming a dual optimization mechanism combining feedforward and feedback.

[0088] For example, the dynamic compensation amount -0.12° / s, the angular velocity deviation data 0.5° / s in the current gyro output and the real-time feedback signal 15.1° / s of the accelerometer are superimposed: using a weighted superposition algorithm, the dynamic compensation amount is given a weight of 0.6, the deviation data is given a weight of 0.3, and the accelerometer signal is given a weight of 0.1, and a preliminary correction signal value of (-0.12*0.6+0.5*0.3+15.1*0.1)=1.588° / s is generated. The difference between the correction signal and the accelerometer feedback signal 15.1° / s is -13.512° / s, the current temperature gradient data is monitored to be 0.8°C / 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%, and the adjusted correction signal amplitude is 1.588*1.15=1.826° / s. After injecting this signal into the drift correction loop, the new output value of the gyro collected is 16.326° / s, compared with the accelerometer reference value 15.1° / s to generate an error signal 1.226° / s. The change rate of the error signal is 0.05° / s² obtained by differentiation, which is a positive value indicating that the error is expanding and mainly caused by vibration factors; accordingly, the vibration weight in the dynamic compensation rule is increased from 60% to 68%, and the temperature weight is reduced from 40% to 32%, and the vibration gain coefficient in the compensation amount generation logic is updated from 1.2 to 1.35 through the Q-learning algorithm, thereby completing the rule autonomous iterative optimization based on the error change trend.

[0089] The following describes another embodiment of a method for measuring the angular velocity of a rotary body of a drilling tool according to the present application:

[0090] In this embodiment, temperature gradient data of a cavity where the gyro is located and deviation data of the angular velocity caused by temperature change in the gyro output signal are continuously collected, and the temperature gradient data and the deviation data are associated and analyzed to form a compensation database containing the association relationship between the temperature gradient data and the deviation data; a high-precision temperature sensor array is arranged in the gyro cavity to continuously collect temperature gradient data at different positions at a millisecond-level sampling frequency, while synchronously recording the original angular velocity signal output by the gyro. The deviation data caused by temperature fluctuation in the angular velocity signal is extracted through a wavelet transform algorithm to establish a timestamp-aligned temperature-deviation correspondence. The association strength of the temperature gradient change and the angular velocity deviation is calculated using a grey relational analysis method to eliminate pseudo-association caused by accidental interference. The verified association relationship is stored by temperature interval to form a structured compensation database, wherein each record contains a temperature gradient pattern, a corresponding deviation amount and a confidence score.

[0091] An asymmetric elastic support structure made of titanium alloy material is installed between the rotating body and the external base, and the elastic difference of the titanium alloy material in the orthogonal direction is combined to generate the energy dissipation parameters of the asymmetric elastic support structure, which include vibration energy absorption rate and scattering intensity data; a special configuration of titanium alloy support structure is designed at the joint between the rotating body and the external base, and the directional absorption of vibration energy is realized by using the different elastic modulus characteristics of titanium alloy in X / Y / Z three orthogonal directions. The deformation response of the support structure under different frequency vibrations is measured by a laser Doppler vibration meter, and the curve of the vibration energy absorption rate changing with frequency is recorded. The elastic wave generated by the micro deformation inside the structure is collected by an acoustic emission sensor, and the scattering intensity data is quantified to represent the energy dissipation efficiency. The absorption rate and scattering intensity indicators are integrated to generate an energy dissipation parameter table describing the dynamic characteristics of the support structure, providing a physical basis for vibration compensation.

[0092] The correlation rule between temperature gradient data and energy dissipation parameters is established to generate dynamic compensation quantity matched with current temperature and vibration intensity, and the correlation rule is generated by coupling the change rate of temperature gradient data with vibration energy absorption rate and scattering intensity data to generate dynamic compensation rule under the joint action of temperature and vibration; the change mode of historical temperature gradient data is extracted from the compensation database, and the maximum slope of temperature fluctuation per unit time is calculated as the change rate index. The change rate is coupled with the vibration energy absorption rate in the energy dissipation parameters for analysis, and the correlation model of temperature fluctuation causing resonance amplification of the support structure is established. The temperature change rate, absorption rate and scattering intensity are projected to a high-dimensional feature space by kernel function mapping, and a support vector regression algorithm is used to generate a dynamic compensation rule. A working condition adaptive module is added to the rule set, so that it can adjust the coupling weight of temperature and vibration factors according to real-time sensor data.

[0093] According to the dynamic compensation rule, the deviation data of the gyro output signal is decomposed to generate a dynamic compensation quantity matched with the current temperature and vibration intensity, and the weight distribution of temperature and vibration intensity in the dynamic compensation quantity is adjusted through the obtained accelerometer feedback signal; based on the dynamic compensation rule, the gyro deviation data is decomposed by variational modal decomposition, and the low-frequency component dominated by temperature and the high-frequency component dominated by vibration are separated. According to the real-time reading of the current temperature sensor, the compensation coefficient in the rule library is matched to generate a basic dynamic compensation quantity. The accelerometer feedback signal is introduced to verify the vibration compensation effect, and if the residual vibration energy exceeds the threshold, the weight distribution proportion of temperature and vibration factors in the compensation quantity is adjusted by gradient descent method. The compensation quantity is phase calibrated to ensure that its injection time is strictly synchronized with the gyro signal processing period.

[0094] The dynamic compensation quantity is continuously injected into the drift correction loop of the gyroscope, 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 closed-loop control process ensures the stable output of the angular velocity measurement value of the gyroscope in the environment with continuous temperature fluctuations and changing vibration disturbances. The optimized dynamic compensation quantity is injected into the drift correction loop of the gyroscope through a digital-to-analog converter, and the original deviation is directly offset in the signal conditioning link. The difference between the compensated gyroscope output and the accelerometer feedback signal is compared in real time, and if the residual error exceeds the allowed range, the online learning mechanism of the rule base is triggered. Then, through the reinforcement learning algorithm, the parameters of the dynamic compensation rule are autonomously iteratively optimized, such as adjusting the slope coefficient of the temperature-vibration coupling function. A complete control chain is formed from sensor acquisition, deviation analysis to closed-loop correction, so that the gyroscope can still maintain a stable output with an angular velocity measurement error of less than 0.01° / h in a temperature range of -40℃ to 85℃ and a vibration impact of 15g.

[0095] The dynamic compensation quantity is continuously injected into the drift correction loop of the gyroscope, 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 closed-loop control process ensures the stable output of the angular velocity measurement value of the gyroscope in the environment with continuous temperature fluctuations and changing vibration disturbances, including superimposing the dynamic compensation quantity 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; obtaining the dynamic compensation quantity, the original deviation data of the gyroscope and the real-time data stream of the accelerometer feedback signal from the signal processing unit, and ensuring strict alignment of the three groups of data through a time synchronization module. The dynamic compensation quantity and the deviation data are preliminarily synthesized by using digital signal superposition technology to generate an intermediate correction signal. The accelerometer feedback signal is used as a reference value, and the intermediate correction signal and the accelerometer data are superimposed again through a weighted fusion algorithm to ensure that the vibration disturbance characteristics are fully retained. The superimposed correction signal is subjected to amplitude normalization processing to eliminate the influence of the dimension difference of different signal sources and prepare for subsequent amplitude adjustment.

[0096] 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 change trend of the current temperature gradient data and the vibration energy absorption rate; the instantaneous difference between the correction signal and the accelerometer feedback signal is calculated in real time, and the change trend of the difference is analyzed by using a sliding window statistical method. The latest temperature gradient data and vibration energy absorption rate are obtained from the environment monitoring unit, and a multi-dimensional correlation model with the signal difference is established. The gain coefficient of the correction signal is dynamically adjusted by using a fuzzy logic controller: the compensation amplitude is increased when the temperature gradient changes sharply, and the compensation amplitude is reduced when the vibration energy absorption rate increases. The adjusted correction signal is subjected to phase calibration to ensure that its waveform characteristics are synchronized with the change rhythm of the environmental disturbance, forming an optimized signal that matches the environment dynamically.

[0097] The adjusted correction signal is injected into the drift correction loop of the gyroscope, the corrected gyroscope output signal is collected in real time, and the error signal is generated by comparing the accelerometer feedback signal in closed loop; the adjusted correction signal is injected into the drift correction loop of the gyroscope through the digital-to-analog converter, and the gyroscope output is compensated in real time at the analog signal level. The high-precision ADC module is used to collect the compensated gyroscope output signal, and the accelerometer feedback signal is compared in time domain, and the instantaneous difference between the two in acceleration, angular velocity and other dimensions is calculated. The system error and random noise are separated by digital filtering technology, and the error signal characteristic quantity representing the compensation effect is extracted. The error signal is standardized and encoded, including amplitude, frequency and phase, etc. Key parameters provide quantitative basis for rule optimization.

[0098] According to the change rate of the error signal, the weight distribution of temperature and vibration intensity in the dynamic compensation rule is adjusted, and the compensation amount generation logic in the dynamic compensation rule is updated by autonomous iterative optimization; the error signal is differentiated to calculate its change rate per unit time, and the lag characteristics of system response are identified. The coupling relationship between the change rate and the temperature gradient data and the vibration energy absorption rate is analyzed, the temperature weight is increased when the temperature change dominates the error, and the vibration weight is increased when the vibration dominates. The rule base is iteratively optimized by reinforcement learning algorithm: the Q-learning method is used to evaluate the long-term compensation effect of different weight distribution strategies, and the strategy that makes the error converge the fastest is retained. Finally, the decision tree structure of the dynamic compensation rule is updated, and the condition judgment threshold and output amount calculation coefficient in the compensation amount generation logic are optimized.

[0099] The updated dynamic compensation rule is re-injected into the drift correction loop to continuously correct the gyroscope output signal, and the corrected signal is returned to the compensation database synchronously with the accelerometer feedback signal to form a closed-loop feedback link. The updated dynamic compensation rule is compiled into a control instruction set executable by the embedded system, and seamlessly switched to the drift correction loop of the gyroscope through the double buffering mechanism. The compensation effect under the new rule is continuously monitored, and when the matching degree between the corrected signal and the accelerometer feedback signal is improved, the feature parameters and compensation parameters of the successful case are packaged and returned to the compensation database. The incremental learning module of the database automatically extracts the effective features in the new case to expand the coverage of the rule base. A complete closed-loop feedback link is formed from signal collection, real-time compensation to rule evolution, which can still maintain a pose measurement accuracy of 0.005° / h in an extreme environment of-55℃~125℃.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] According to the correlation between the temperature gradient data and the deviation data in the compensation database, the dynamic parameter combination is mapped to the initial compensation amount matched with the current temperature and vibration intensity. The weighted vibration energy absorption rate and scattering intensity data are normalized to eliminate the dimensional differences. The wavelet packet transform algorithm is used to decompose the vibration parameters into different frequency bands, and the components coinciding with the temperature change characteristic frequency band are selected for emphasis fusion. The temperature gradient data and the screened vibration parameters are projected into a high-dimensional feature space through kernel function mapping, and the boundary features of the dynamic parameter combination are constructed by using the support vector data description method. The combined parameters are subjected to principal component analysis for dimension reduction, and the first three principal components that can best represent the temperature-vibration combined effect are extracted as the core feature quantities.

[0104] The real-time fluctuation amplitude of the angular velocity in the accelerometer feedback signal is combined to adjust the weight distribution of temperature and vibration in the initial compensation amount, to generate the final dynamic compensation amount and update the parameter generation logic in the dynamic compensation rule. The angular velocity frequency spectrum characteristics of the accelerometer feedback signal are analyzed to identify whether the current main interference source comes from temperature or vibration. When the angular velocity fluctuation amplitude exceeds the threshold, the weight rebalancing mechanism is started: if the fluctuation presents low frequency characteristics, the temperature weight is increased, and if the fluctuation presents 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 to generate the final dynamic compensation amount that takes into account the response speed and stability. The parameter adjustment trajectory of the current optimization process is recorded in the knowledge base of the dynamic compensation rule, and the condition judgment threshold and output gain coefficient of the compensation amount generation logic are updated through the case reasoning algorithm, so that the system has the ability of continuous evolution.

[0105] The following describes this embodiment in combination with application scenarios:

[0106] In the full-rotation vertical drilling system, the high-speed rotation of the downhole drilling assembly and the impact of the formation cause severe temperature changes and mechanical vibrations inside the gyroscope measuring cavity, affecting the guiding accuracy. An annular temperature sensor array is arranged on the outer wall of the gyroscope cavity to collect real-time axial temperature gradient data (such as the temperature difference distribution between the top and bottom of the drill pipe) caused by the heat generated by the drill bit friction and the high temperature conduction underground, and to record the angular velocity deviation curve in the gyroscope output signal caused by thermal stress deformation. By analyzing the spatial correlation between the direction of temperature gradient change and the amplitude of deviation, a compensation database of temperature-deviation mapping is constructed. To isolate the high-frequency vibration interference underground, a titanium alloy asymmetric bellows support structure is installed at the connection between the drill tool rotating body and the drive shaft, which has 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 multidirectional scattering field distribution, and the energy absorption rate and scattering intensity parameters are output in real time. When the drill bit cuts into hard rock, the temperature gradient is detected to rise sharply due to the heat generated by rock friction, and the scattering intensity peak is triggered due to the surge of vibration energy. At this time, the temperature change rate and the vibration scattering intensity are dynamically coupled: if the temperature gradient increases by more than a set threshold, the weight ratio of the vibration parameter in the compensation rule is automatically increased, and a joint compensation factor that combines thermal expansion suppression and vibration scattering cancellation is generated. The factor queries the historical temperature change-deviation correlation model in the compensation database to match the initial compensation amount, and then combines the actual vibration trajectory of the drill bit (such as the lateral swing characteristics) fed back by the accelerometer to dynamically adjust the weight ratio of the temperature and vibration components, forming the final compensation amount. After the compensation amount is injected into the gyroscope signal correction loop, the real-time angular velocity value after correction is compared with the actual movement direction of the drill bit calculated by the accelerometer. When a new error signal is detected due to the sudden change of lithology when drilling through a fault, the compensation rule is immediately iteratively optimized, for example, the vibration scattering intensity weight is increased from 50% to 65% to enhance the impact resistance, and the updated rule is synchronized to the compensation database to form a complete link from downhole data collection, dynamic rule generation to closed-loop correction. Finally, under the combined interference of 200°C temperature change and 10kHz high-frequency vibration underground, the angular velocity measurement error of the drill tool rotating body is less than 0.01° / s, and the vertical drilling trajectory accuracy is maintained.

[0107] For the method steps disclosed in the above embodiments, the method steps are described as a series of action combinations for the purpose of simple description, but those skilled in the art should know that the embodiments of the present application are not limited by the order of the described actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily necessary for the embodiments of the present application.

[0108] As Figure 2 shown, the present application also provides a drill tool rotating body angular velocity measurement system, comprising:

[0109] The compensation database generating module 201 is configured to generate a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data in the gyro output signal in response to the correlation analysis of the continuously collected temperature gradient data and the angular velocity deviation data;

[0110] The asymmetric elastic support structure installation and energy dissipation parameter generating 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;

[0111] The dynamic compensation rule generating module 203 is configured to establish a correlation rule between the temperature gradient data and the energy dissipation parameters, and generate a dynamic compensation rule under the combined action of temperature and vibration by coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data;

[0112] The dynamic compensation amount generating and adjusting module 204 is configured to decompose the angular velocity deviation data according to the dynamic compensation rule, generate a dynamic compensation amount matched with the current temperature and vibration intensity, and adjust the weight distribution of the temperature and vibration intensity in the dynamic compensation amount through the obtained accelerometer feedback signal;

[0113] The output module 205 is configured to continuously inject the adjusted dynamic compensation amount into the drift correction loop, form a closed-loop control between the corrected gyro output signal and the accelerometer feedback signal, and maintain the stable output of the gyroscope angular velocity measurement value through the autonomous iterative optimization of the dynamic compensation rule.

[0114] It is worth noting that, although only some basic functional modules are disclosed in the embodiments of the present application, it does not mean that the composition of the system is limited to only the above basic functional modules. On the contrary, the meaning expressed in the embodiments is that on the basis of the above basic functional modules, those skilled in the art can add one or more functional modules to form infinite embodiments or technical solutions in combination with the prior art. That is, the system is open rather than closed, and it cannot be considered that the protection scope of the present application is limited to the disclosed basic functional modules only because the embodiments only disclose individual basic functional modules. At the same time, for the convenience of description, the above devices are described as various units and modules in terms of functions. Of course, the functions of the units and modules can be realized in the same software and / or hardware in the implementation of the present application.

[0115] As Figure 3As shown, the present application also provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete the communication among each other through the communication bus; the memory stores a computer program, when the computer program is executed by the processor, the processor executes the steps of a drilling tool body angular velocity measurement method.

[0116] Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. As shown in the structural diagram, Figure 3 the electronic device provided by the embodiment of the present application comprises: one or more processors 710 and a memory 720; the processor 710 in the electronic device can be one or more, Figure 3 In the embodiment, the processor 710 is taken as an example; the memory 720 is used for storing 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 drilling tool body angular velocity measurement method according to any one of the embodiments of the present application.

[0117] The electronic device can further comprise: an input device 730 and an output device 740.

[0118] The processor 710, the memory 720, the input device 730 and the output device 740 in the electronic device can be connected through a bus or other means, Figure 3 In the embodiment, the connection through the bus is taken as an example.

[0119] The memory 720 in the electronic device is a computer readable storage medium, which can be used to store one or more programs, and the program can be a software program, a computer executable program and a module, such as the program instruction / module corresponding to the drilling tool body angular velocity measurement method provided by the embodiment of the present application. The processor 710 executes the software program, instruction and module stored in the memory 720, thereby executing various function applications and data processing of the electronic device, that is, implementing the drilling tool body angular velocity measurement method in the above method embodiment.

[0120] The memory 720 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs required by at least one function, and the like. The data storage area can store data created according to usage of the electronic device, and the like. Furthermore, the memory 720 can include a high-speed random access memory and also include a non-volatile memory such as at least one of a magnetic disk storage device, a flash memory device, or other non-volatile solid state storage device. In some examples, the memory 720 can further include a memory remotely located with respect to the processor 710, which can be connected to the device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0121] The input device 730 can be used to receive input digital or character information and to generate key signal input relating to user settings and function controls of the electronic device. The output device 740 can include a display device such as a display screen.

[0122] The present application also provides a computer readable storage medium storing a computer program executable by an electronic device, which when executed on the electronic device causes the electronic device to perform the steps of a method for measuring the angular velocity of a drill tool body.

[0123] In particular, the computer storage medium of the embodiments of the present application can employ any combination of one or more computer readable media. The computer readable media can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0124] Finally, it should be noted that the above-described embodiments are merely intended to illustrate the technical solutions of the present application, and not to limit the same; even though the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still make modifications to the technical solutions described in the foregoing embodiments, or make equivalent replacements to some or all of the technical features; and such modifications or replacements 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 application.

Claims

1. A method of measuring the angular velocity of a body of revolution of a drilling tool, characterized in that, The method comprises the following steps: correlating analysis of the continuously collected temperature gradient data and the angular velocity deviation data in the gyro output signal, generating a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data; installing an asymmetric elastic support structure and generating energy dissipation parameters, wherein the energy dissipation parameters include vibration energy absorption rate and scattering intensity data; establishing the correlation between the temperature gradient data and the energy dissipation parameters, coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data to generate a dynamic compensation rule under the combined action of temperature and vibration; According to the dynamic compensation rule, the angular velocity deviation data is decomposed to generate a dynamic compensation amount matched with the current temperature and vibration intensity, and the weight distribution of temperature and vibration intensity in the dynamic compensation amount is adjusted through the obtained accelerometer feedback signal; The adjusted dynamic compensation amount is continuously injected into the drift correction loop, so that the corrected gyro output signal and the accelerometer feedback signal form a closed-loop control, and the stable output of the angular velocity measurement value of the rotating body is maintained through the autonomous iterative optimization of the dynamic compensation rule.

2. The method of claim 1, wherein, In response to the continuous collection of temperature gradient data and the angular velocity deviation data in the gyro output signal, the correlation analysis is performed to generate a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data, further comprising: Collecting temperature gradient data at different positions and synchronously recording the original angular velocity signal output by the gyro; Extracting the angular velocity deviation data caused by temperature fluctuation from the original angular velocity signal; Analyzing the correlation strength of the temperature gradient data and the angular velocity deviation data, and eliminating pseudo-correlation; The verified correlation is stored according to temperature interval to form the compensation database.

3. The method of claim 1, wherein, 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, further comprising: Utilizing the elastic difference of the material in the orthogonal direction to realize directional absorption of vibration energy; Measuring the deformation response of the asymmetric elastic support structure under different frequency vibrations, and recording the curve of vibration energy absorption rate changing with frequency; Collecting the elastic wave generated by the micro-deformation inside the asymmetric elastic support structure, and quantifying the scattering intensity data to represent the energy dissipation efficiency; Integrate the vibration energy absorption rate and the scattering intensity data to generate the energy dissipation parameters.

4. The method of claim 1, wherein, Establish the correlation between the temperature gradient data and the energy dissipation parameters, and couple the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data to generate a dynamic compensation rule under the combined action of temperature and vibration, further comprising: Calculate the change rate of the temperature gradient data; Coupling analysis of the change rate of the temperature gradient data and the vibration energy absorption rate in the energy dissipation parameters to establish a correlation model of temperature fluctuation-induced resonance amplification of the asymmetric elastic support structure; Project the change rate of the temperature gradient data, the vibration energy absorption rate and the scattering intensity data to a high-dimensional feature space to generate a dynamic compensation rule.

5. The method of claim 1, wherein, According to the dynamic compensation rule, the angular velocity deviation data is decomposed, a dynamic compensation quantity matching the current temperature and vibration intensity is generated, and the weight distribution of temperature and vibration intensity in the dynamic compensation quantity is adjusted through the obtained accelerometer feedback signal, and further comprising: Based on the dynamic compensation rule, the angular velocity deviation data is decomposed, and the temperature dominant low frequency component and the vibration dominant high frequency component are separated out; According to the real-time temperature, the compensation coefficient in the compensation database is matched to generate a basic dynamic compensation quantity; Introducing the accelerometer feedback signal to verify the vibration compensation effect, and adjusting the weight distribution proportion of temperature and vibration intensity in the dynamic compensation quantity; The phase of the dynamic compensation quantity after adjusting the weight is calibrated.

6. The method of claim 1, wherein, The adjusted dynamic compensation quantity is continuously injected into the drift correction loop, so that the corrected gyro output signal and the accelerometer feedback signal form a closed loop control, and through the autonomous iterative optimization of the dynamic compensation rule, the stable output of the angular velocity measurement value of the rotating body is maintained, and further comprising: The adjusted dynamic compensation quantity is injected into the drift correction loop to offset the original deviation; Compare the difference between the compensated gyro output and the accelerometer feedback signal, if the residual error exceeds the preset range, trigger the online learning mechanism; Through the reinforcement learning algorithm, the parameters of the dynamic compensation rule are iteratively optimized.

7. A method of measuring the angular velocity of a rotating body of a drilling tool according to claim 6, characterized in that, The adjusted dynamic compensation quantity is injected into the drift correction loop to offset the original deviation; Before comparing the difference between the compensated gyro output and the accelerometer feedback signal, if the residual error exceeds the preset range, triggering the online learning mechanism, the method further comprises: Superimpose the dynamic compensation quantity with the angular velocity deviation data of the current gyro output signal and the real-time data of the accelerometer feedback signal to generate a correction signal; According to the difference between the correction signal and the accelerometer feedback signal, adjust the amplitude of the correction signal, so that the amplitude of the adjusted correction signal matches the change trend of the current temperature gradient data and the vibration energy absorption rate; The adjusted correction signal is injected into the drift correction loop, and the corrected gyro output signal is collected in real time, and compared with the accelerometer feedback signal in a closed loop to generate an error signal; According to the change rate of the error signal, adjust the weight distribution of temperature and vibration intensity in the dynamic compensation rule, and update the compensation quantity generation logic in the dynamic compensation rule through autonomous iterative optimization.

8. A system for measuring the angular velocity of a rotating body of a drilling tool, characterized in that Comprising: The compensation database generation module is configured to respond to the correlation analysis of the continuously collected temperature gradient data and the angular velocity deviation data in the gyro output signal, and generate a compensation database including the correlation between the temperature gradient data and the angular velocity deviation data; The non-symmetrical elastic support structure installation and energy dissipation parameter generation module is configured to install a non-symmetrical elastic support structure and generate an energy dissipation parameter, wherein the energy dissipation parameter includes vibration energy absorption rate and scattering intensity data; The dynamic compensation rule generation module is configured to establish an association rule between the temperature gradient data and the energy dissipation parameter, and to generate a dynamic compensation rule under the combined action of temperature and vibration by coupling the change rate of the temperature gradient data with the vibration energy absorption rate and the scattering intensity data. The dynamic compensation amount generation and adjustment module is configured to decompose the angular velocity deviation data according to the dynamic compensation rule, to generate a dynamic compensation amount matched with the current temperature and vibration intensity, and to adjust the weight distribution of the temperature and vibration intensity in the dynamic compensation amount through the obtained accelerometer feedback signal. The rotary body angular velocity measurement value output module is configured to continuously inject the adjusted dynamic compensation amount into a drift correction loop, to form a closed-loop control between the corrected gyro output signal and the accelerometer feedback signal, and to maintain the stable output of the rotary body angular velocity measurement value through the autonomous iterative optimization of the dynamic compensation rule.

9. An electronic device, comprising: The computer program is stored in the memory and can be executed by the electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the method in any one of claims 1 to 7. The computer program is stored in the memory and can be executed by the electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the method in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, ​

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