Underground drilling tool vibration monitoring and restraining system based on multi-chip assembly

Abstract

The invention belongs to the technical field of mechanical measurement and automatic control, and particularly relates to an underground drilling tool vibration monitoring and restraining system based on a multi-chip assembly. The system comprises a data acquisition part, a data analysis part and a vibration suppression part, the data acquisition part is used for arranging a plurality of vibration sensors on a drill rod so as to obtain vibration signals at different positions and at different moments on the drill rod, preprocessing the vibration signals and evaluating local energy of each position at the same time; the data analysis part is used for describing drilling tool vibration propagation by adopting a one-dimensional rod piece vibration model to obtain error feedback; according to error feedback, decomposing space vibration into a plurality of independent vibration modes; and the vibration suppression part is used for reducing the overall vibration level by applying a suppression control force so as to ensure that each vibration mode is effectively suppressed. The real-time performance and the data precision of vibration monitoring are improved, and equipment abrasion and safety risks caused by vibration are effectively reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of mechanical measurement and automatic control, and in particular relates to a downhole drilling tool vibration monitoring and suppression system based on a multi-chip component. Background Art

[0002] In recent years, with the continuous deepening of oil and gas resource exploration and development, downhole drilling tools play a vital role in drilling engineering. During downhole operations, drilling tools often produce various forms of vibrations, such as axial vibration, bending vibration, and torsional vibration, due to the combined influence of formation forces, mechanical friction, changes in drilling parameters, and complex downhole working conditions. These vibrations not only affect drilling efficiency, but may also cause fatigue damage to drilling tools, reduce the service life of equipment, and even lead to serious safety accidents. Therefore, how to monitor and effectively suppress drilling tool vibration in real time has become an important technical problem that needs to be solved in the current field of drilling engineering.

[0003] In the prior art, the traditional vibration monitoring method mainly relies on a single or a small number of vibration sensors installed on the drill pipe, and the vibration state is judged by performing spectrum analysis on the collected acceleration or displacement signals. This type of method can reflect the vibration of the drill tool to a certain extent, but due to the complex spatial distribution and time-varying characteristics of the drill pipe vibration, it is difficult for a single sensor to capture the global vibration information. In addition, traditional data acquisition systems often have problems such as low sampling rate, large data transmission delay, and insufficient signal preprocessing, which makes it difficult for real-time and accuracy to meet the requirements of the high-dynamic working environment downhole. On the other hand, existing literature has adopted a vibration monitoring method based on multi-sensor fusion technology, attempting to achieve all-round monitoring by evenly arranging multiple sensors on the drill pipe. Although this method can theoretically improve the spatial resolution of data acquisition, in practical applications, due to the high temperature, high pressure and complex electromagnetic interference of the downhole environment, the anti-interference ability of the sensor and the real-time response performance of its data processing unit are often difficult to take into account. In addition, most of the existing multi-sensor systems adopt the traditional centralized data processing architecture, and their signal preprocessing and feature extraction mainly rely on a single time domain or frequency domain analysis method, which is difficult to take into account the comprehensive characteristics of the signal in the time and space domain, resulting in inaccurate extraction of key information such as local vibration energy, main vibration frequency and instantaneous frequency change, which restricts the design of subsequent active control strategies. At present, in terms of vibration signal analysis, short-time Fourier transform, time-frequency decomposition and other methods have been widely used in various mechanical vibration monitoring systems, but these methods are easily affected by factors such as window function selection, boundary effect and noise interference when processing non-stationary signals. Especially in the process of downhole drilling tool operation, the vibration signal is not only strongly non-stationary, but also affected by complex geological conditions and drilling process changes, and its frequency components and amplitude changes show obvious local characteristics. Traditional time-frequency analysis methods have limitations in capturing such local characteristics, and it is often difficult to take into account the instantaneous phase, local energy and frequency drift of the signal at the same time, resulting in an incomplete and detailed description of the vibration state of the drilling tool, which in turn affects the formulation and implementation of subsequent vibration suppression control strategies. Summary of the invention

[0004] The main purpose of the present invention is to provide a downhole drilling tool vibration monitoring and suppression system based on a multi-chip assembly. The system realizes real-time acquisition of drilling tool vibration signals by evenly arranging multiple high-precision vibration sensors on the drill pipe, and uses advanced time-space domain preprocessing, local time-frequency analysis and adaptive correction technology to finely process the collected data, thereby constructing a one-dimensional rod vibration model that can accurately reflect the dynamic response of the drill pipe, and then disassembles the overall vibration response into multiple independent vibration modes such as axial, bending and torsion through modal decomposition, and then designs an active control strategy based on the characteristics of each vibration mode, applies a corrected inhibitory force to each mode, and realizes accurate suppression of vibration energy. The system not only greatly improves the real-time performance and data accuracy of vibration monitoring, but also effectively reduces equipment wear and safety risks caused by vibration, improves the overall efficiency and safety of drilling operations, and has extremely high engineering application value and promotion prospects.

[0005] In order to solve the above technical problems, the present invention provides a downhole drilling tool vibration monitoring and suppression system based on a multi-chip module, the system comprising: a data acquisition part, a data analysis part and a vibration suppression part; The data acquisition part is used to arrange multiple vibration sensors on the drill pipe to obtain vibration signals at different positions and different times on the drill pipe and perform preprocessing, perform time-frequency analysis on the preprocessed vibration signals at each position, extract the local main vibration frequency and corresponding amplitude of each position by using local time-frequency conversion technology, and evaluate the local energy of each position; The data analysis part is used to describe the vibration propagation of the drilling tool by using a one-dimensional rod vibration model, and construct external excitation by using local energy; compare the actual displacement obtained by the vibration sensor with the displacement field of the one-dimensional rod vibration model to obtain error feedback; according to the error feedback, adaptively correct the one-dimensional rod vibration model; use the corrected one-dimensional rod vibration model to solve the corrected displacement field, perform modal decomposition on the displacement field, and decompose the spatial vibration into several independent vibration modes; The vibration suppression part is used to design an active control strategy according to the result of modal decomposition. The control strategy uses the vibration information of each vibration mode to reduce the overall vibration level by applying a suppressive control force to ensure that each vibration mode is effectively suppressed.

[0006] Furthermore, the data acquisition part evenly distributes multiple vibration sensors on the drill pipe, assuming that the vibration signal is ; is the total length of the drill pipe; For time; is the position along the drill pipe; the vibration signal is preprocessed by the following formula: ; in, is the vibration signal after preprocessing; is the time-integrated variable; is the distance integral variable; is the filter kernel, and the formula is as follows: ; in, is the absolute value operator; is the preset spatial attenuation constant, which reflects the attenuation speed of the vibration signal with the propagation distance, and its value range is 3 to 10; is the time diffusion parameter, ranging from 0.005 to 0.02; is the vibration signal wave velocity, ranging from 3000 to 5000; is the time window delay, ranging from 0.01 to 0.15.

[0007] Furthermore, the preprocessed vibration signal is subjected to time-frequency analysis at each position using the following formula: ; in, is the result of time-frequency analysis; Indicates at location The effective time window width for time-frequency analysis ensures that one or more local vibration cycles can be fully captured within the analysis window. , is the vibration frequency; is the imaginary number symbol; is the angular frequency; Indicates at location The instantaneous rate of change of frequency at .

[0008] Furthermore, the local main vibration frequency is calculated by the following formula: ; in, is the magnitude operator; is the local master frequency, is the corresponding amplitude; the instantaneous phase function is defined as ; then the instantaneous frequency change rate The calculation formula is: ; The local energy at each position is calculated using the following formula: ; in, For location The local energy at .

[0009] Furthermore, the one-dimensional bar vibration model is expressed using the following formula: ; in, is the drill pipe density; For Time, Location The displacement field at ; is the damping coefficient of the drill pipe; is the cross-sectional area of ​​the drill pipe; is the elastic modulus of the drill pipe; is the energy conversion coefficient, is the set value.

[0010] Furthermore, it is assumed that a vibration sensor is used in Time, Location The actual displacement obtained at ; Error feedback is ; The one-dimensional bar vibration model is adaptively corrected according to the error feedback through the following formula: ; By solving the corrected one-dimensional bar vibration model, the corrected displacement field is obtained .

[0011] Furthermore, the data analysis part will use the corrected displacement field Perform modal decomposition in space, the formula is as follows: ; in, is the total number of modes; the modes include at least: axial vibration, bending vibration and torsional vibration; is the modal factor, which is a preset positive or negative integer value. For different types of modes, different values ​​are taken according to their weights, satisfying ; For the Orthogonal mode functions.

[0012] Furthermore, Determined by the following eigenvalue problem: ; in, For the The eigenvalues ​​of the modes; For the The damping ratio of the mode.

[0013] Furthermore, the process of designing an active control strategy based on the results of modal decomposition includes: setting The magnitude of the initial restraining force of this mode is ; then according to The characteristic value of the mode is used to correct the initial inhibitory force using the following formula to obtain the corrected inhibitory force: ; in, is the corrected inhibitory force.

[0014] The downhole drilling tool vibration monitoring and suppression system based on the multi-chip module of the present invention has the following beneficial effects: First, the present invention utilizes a distributed sensor network to evenly arrange multiple high-precision vibration sensors on the drill pipe, so that vibration data at various locations can be collected simultaneously. By using multi-chip component integration technology in the harsh underground environment, not only high-speed signal acquisition, digital conversion and real-time transmission are achieved, but also the system's anti-interference ability to extreme conditions such as electromagnetic interference, high temperature and high pressure is greatly improved. This technical advantage enables the collected data to have high resolution and high reliability, providing a solid foundation for subsequent data processing and control.

[0015] Secondly, the system uses advanced signal preprocessing technology to perform convolution filtering on the original vibration signal in the time and space domain, thereby effectively reducing the impact of environmental noise and external interference on signal quality. This method fully considers the propagation characteristics of the drilling tool vibration signal in time and space, and ensures that the preprocessed signal can truly reflect the local vibration state of the drill pipe through weighted averaging and delay compensation. This not only eliminates interference caused by factors such as uneven formations and equipment friction, but also improves the smoothness and availability of the data, providing more accurate signal input for subsequent time-frequency analysis and modal decomposition.

[0016] Thirdly, using local time-frequency conversion technology, the system performs time-frequency analysis on the pre-processed vibration signal, which can not only extract the main vibration frequency and amplitude information of each monitoring position, but also capture the instantaneous phase and local energy changes of the signal. Through this time-frequency analysis method, the system can accurately locate vibration anomalies in complex and changeable underground operating environments and reveal the dynamic response characteristics of drilling tools under different working conditions. This method has great advantages in real-time and accuracy, and can provide detailed data support for the formulation of vibration suppression strategies.

[0017] In addition, the present invention mathematically describes the vibration response of the drill pipe by establishing a one-dimensional rod vibration model, combines the actual measured displacement signal with the theoretical prediction, and then uses error feedback for adaptive correction, so that the model prediction can be highly consistent with the actual state on site. By continuously adjusting the model parameters, the system achieves an accurate characterization of the dynamic behavior of the drilling tool vibration. This not only makes the monitoring of the vibration state more reliable, but also provides an accurate physical basis for active control, thereby achieving effective separation and control of the vibration mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0019] Figure 1 A schematic diagram of the system structure of a downhole drilling tool vibration monitoring and suppression system based on a multi-chip module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The method of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments of the present invention.

[0021] Example 1, reference Figure 1 : A downhole drilling tool vibration monitoring and suppression system based on a multi-chip module, the system comprising: a data acquisition part, a data analysis part and a vibration suppression part.

[0022] The data acquisition part is used to arrange multiple vibration sensors on the drill pipe to obtain vibration signals at different positions and different times on the drill pipe and perform preprocessing, perform time-frequency analysis on the preprocessed vibration signals at each position, use local time-frequency conversion technology to extract the local main vibration frequency and corresponding amplitude of each position, and evaluate the local energy of each position.

[0023] The data analysis part is used to describe the vibration propagation of the drilling tool by using a one-dimensional rod vibration model, and construct external excitation by using local energy; compare the actual displacement obtained by the vibration sensor with the displacement field of the one-dimensional rod vibration model to obtain error feedback; according to the error feedback, adaptively correct the one-dimensional rod vibration model; use the corrected one-dimensional rod vibration model to solve the corrected displacement field, perform modal decomposition on the displacement field, and decompose the spatial vibration into several independent vibration modes.

[0024] The vibration suppression part is used to design an active control strategy according to the result of modal decomposition. The control strategy uses the vibration information of each vibration mode to reduce the overall vibration level by applying a suppressive control force to ensure that each vibration mode is effectively suppressed.

[0025] Specifically, the data acquisition part mainly relies on installing multiple vibration sensors at different positions of the drill pipe to realize the real-time acquisition of the vibration signals generated by the drilling tool during the downhole operation. The drilling environment is complex. The drill pipe will be affected by various factors such as the formation, mechanical friction and drilling process during the operation, resulting in dynamic changes in the vibration signal in both time and frequency. Therefore, the sensors evenly arranged on the drill pipe can capture the vibration information at different positions, and integrate the signal acquisition, preliminary processing and data transmission into one module through the multi-chip module technology to improve the anti-interference performance and data transmission stability of the equipment under harsh downhole conditions. After the sensor converts the mechanical vibration on the drill pipe into an electrical signal, it first amplifies, filters and pre-processes the signal to eliminate the electromagnetic interference and random noise caused by the complex geological structure and the movement of the drilling equipment, so that the subsequent data can more accurately reflect the actual vibration of the drilling tool. The pre-processed signal is converted into a digital signal at high speed and then transmitted to the central data processing unit. In this process, the high integration design of the multi-chip module not only shortens the delay of the signal during transmission, but also ensures that the data will not be lost or distorted due to external interference during transmission. The data acquisition part also continuously monitors the instantaneous vibration generated during the drilling operation through the built-in multi-stage filtering and automatic correction mechanism, and extracts the main vibration frequency, amplitude and local energy information at each measuring point by analyzing the time-frequency characteristics of the collected signal. These parameters have direct application value in the subsequent use of physical models to describe vibration propagation and construct external excitation.

[0026] Through the local time-frequency conversion technology, the continuously changing signal is analyzed in two dimensions of time and frequency, and the vibration state information of each part of the drill pipe can be obtained, reflecting the distribution of vibration energy in different areas, and providing reliable data support for further establishing a one-dimensional rod vibration model. During the entire data acquisition process, the high precision of the sensor and the integrated design of the multi-chip component enable the system to maintain stable operation in the underground high temperature, high pressure and strong vibration environment, and through the real-time transmission and storage of the collected data, ensure that the changes in the vibration state of the drill tool at each moment can be fully recorded. Since the vibration signal changes rapidly during the drilling process, the system pays special attention to high-speed sampling and real-time processing capabilities in hardware design, so that the drill tool can respond and transmit data quickly when it is subjected to slight vibration changes, thereby providing accurate input for the subsequent data analysis module to build a model, perform error feedback and modal decomposition. The entire data acquisition part is closely coordinated with the overall design of the system. Through the integrated multi-chip component, signal acquisition, preprocessing, digital conversion and data transmission are realized, so that the system can efficiently obtain vibration information in the underground operation environment and dynamically monitor the vibration state of the drill tool, thereby providing sufficient and accurate raw data support for the vibration suppression part to formulate control strategies in real time. Using these preprocessed and preliminarily analyzed data, the subsequent data analysis module can use a one-dimensional rod vibration model to describe the vibration propagation, and at the same time construct an external excitation term in combination with local energy. By comparing and feedback with the actual measured displacement, the model parameters can be adaptively corrected, ultimately providing a precise control target for vibration suppression.

[0027] The data analysis part is responsible for converting the collected original vibration signals into an accurate description and prediction of the vibration state of the drill tool. By continuously analyzing the data preprocessed by multiple sensors, the system first describes the vibration fluctuations in the drill rod with the help of a one-dimensional rod vibration model. This model describes the propagation law of the vibration signal inside the drill rod and the attenuation characteristics of the vibration energy from a physical perspective, thereby establishing a theoretical framework for the system to predict the dynamic response of the drill tool. Using this model, the data analysis part compares the displacement, acceleration and other parameters measured at different positions of the drill rod with the propagation characteristics preset in the model to determine the deviation between the actual working state and the theoretical expectation. This comparison can not only reveal the non-ideal factors in the transmission process of the vibration signal, but also provide a basis for the subsequent correction of the model parameters. The data analysis process applies the local time-frequency conversion technology to the continuously collected vibration signal, so that the signal can be expanded in two dimensions of time and frequency, so that the main vibration frequency, amplitude and local energy distribution at each position of the drill rod can be extracted. By observing the energy distribution of the signal at different times, the system constructs an external excitation term that matches the actual working state of the drill. This excitation term reflects the real-time changes of the external disturbance and internal vibration energy of the drill pipe under specific working conditions. In the data analysis part, after the signal collected by the sensor is processed locally in time and frequency, the system begins to compare the actual measured displacement signal with the theoretical displacement field calculated using the one-dimensional rod model. By comparing the difference between the two, a feedback information reflecting the error is generated. The feedback information provides a real-time reference for the system to adaptively adjust the model parameters. The data analysis part uses this feedback mechanism to continuously correct the parameters in the model, so that the model prediction value can be closer to the actual measurement result, thereby realizing a detailed description of the vibration state of the drill. With the continuous deepening of data analysis, the system will also perform modal decomposition on the displacement field obtained after correction, and divide the overall vibration phenomenon into multiple independent vibration modes. Each mode represents a unique motion mode in the vibration response of the drill pipe. The separated modal data can not only reveal the local abnormal vibration that may occur in the working process of the drill, but also provide a clear direction for the subsequent design of targeted suppression strategies. The entire data analysis process leverages the high integration capabilities of multi-chip components, allowing the data to be calculated and processed at extremely high speeds after being transmitted to the central processing module. This not only ensures that the data analysis results can be fed back to the vibration suppression part in a timely manner, but also that the system can dynamically capture instantaneous changes in the vibration state of the drill bit during the data processing process.

[0028] The data analysis part not only uses traditional physical models and time-frequency analysis techniques to process vibration signals, but also combines actual measurement errors and environmental change factors, and continuously improves the vibration propagation model through an adaptive correction mechanism, so that the system can maintain a high analysis accuracy when facing complex and nonlinear vibration phenomena in the drilling process. The various processing methods used in the data analysis cooperate with each other, which not only ensures the accurate restoration of the drill pipe vibration signal, but also provides sufficient data basis for the next step of active control strategy design, so that each independent vibration mode obtained by modal decomposition can be directly converted into the controller input parameter, so as to achieve efficient vibration suppression in the subsequent process of applying targeted control force. In the process of data analysis, the system continuously adjusts and optimizes the model parameters, so that the deviation between the actual vibration state of the drill tool and the theoretical prediction is gradually reduced. This feedback adjustment process enables the system to maintain stable analysis accuracy in long-term operation. The realization of the data analysis part is inseparable from the support of multi-chip components. These components not only enable the various data processing modules to achieve efficient collaborative work in hardware, but also minimize the delay between the data transmission, storage and calculation links, thereby ensuring that the overall system can still monitor and accurately analyze the vibration of the drill tool in real time in the complex environment of the well. After integrating various data processing methods, the system can extract key features that reflect the working status of the drill tool from the vibration signal. These characteristic data not only provide an important reference for understanding the vibration mechanism of the drill tool, but also provide a basis for dynamic control of the vibration suppression part, so that the entire system can achieve closed-loop control from data acquisition to analysis to suppression in dynamic response.

[0029] The vibration suppression part mainly implements real-time intervention and adjustment of the vibration state of the drill tool through active control strategies. Its principle is to use the vibration mode decomposition results obtained from the data analysis part to disassemble the overall vibration response of the drill pipe into several independent vibration modes, and then apply corresponding inhibitory control forces to each mode, so that the overall vibration amplitude can be effectively reduced. Specifically, the system first uses the drill pipe vibration data collected by the sensor to calculate the theoretical displacement field through time-frequency analysis and one-dimensional rod vibration model, and combines the actual measurement data for error feedback. After adaptive correction, a displacement field that accurately reflects the current vibration state of the drill tool is generated. Subsequently, the displacement field is converted into several modes through modal decomposition technology, each of which represents the motion characteristics of the drill pipe in different spatial regions or different vibration modes. This decomposition process not only reveals the distribution of vibration energy in each mode, but also provides a basis for designing targeted control strategies. The vibration suppression part uses the control algorithm to calculate the reverse excitation force applied to the drill pipe according to the characteristics of each vibration mode. The principle is to use the feedback control idea to monitor the vibration amplitude and frequency information of each mode in real time, generate a control force opposite to the original vibration direction, and then dynamically offset the original vibration to achieve the dissipation of vibration energy. In order to achieve this goal, the system uses multi-chip components in hardware. These components integrate functions such as high-speed signal processing, data transmission and control instruction execution, so that the entire vibration suppression process can complete data acquisition, analysis and control response in a very short time. The highly integrated design of multi-chip components ensures that the system can still maintain efficient and stable operation under high temperature, high pressure and vibration environment underground, ensuring seamless connection of various control links, thereby improving the real-time and accuracy of the active control strategy. The control strategy adopted by the vibration suppression part not only takes into account the independence of vibration modes, but also makes full use of the possible mutual coupling relationship between modes. By dynamically adjusting the control parameters, the complex vibration field can be finely controlled. The entire control process is based on a closed-loop feedback mechanism, that is, the system continuously monitors the actual vibration state of the drill tool, compares the monitoring data with the control target, and adjusts the applied control force in real time to ensure that each vibration mode is within the expected suppression range. Since the drill tool may be affected by nonlinear factors when operating underground, the system updates the vibration model and control parameters in real time through an adaptive algorithm, so that the vibration suppression scheme can adapt to changes in working conditions and ensure that effective vibration attenuation can be achieved in different drilling stages. The design of the vibration suppression part relies on the vibration characteristics provided by high-precision data analysis, and makes full use of the high-speed data transmission and processing capabilities brought by multi-chip components, so that the system can achieve rapid response and precise control of drill tool vibration under extreme working conditions.The entire control process not only covers the direct control of a single mode, but also fully considers the synergistic effect between multiple modes. By applying appropriate suppression force at each control node, the overall vibration state is optimized, so that the vibration of each part of the drilling tool is evenly attenuated during operation, reducing the risk of wear and damage to the equipment caused by vibration.

[0030] Embodiment 2: Data collection part: Multiple vibration sensors are evenly distributed on the drill pipe. Suppose the vibration signal is ; is the total length of the drill pipe; For time; is the position along the drill pipe; the vibration signal is preprocessed by the following formula: ; in, is the vibration signal after preprocessing; is the time-integrated variable; is the distance integral variable; is the filter kernel, and the formula is as follows: ; in, is the absolute value operator; is the preset spatial attenuation constant, which reflects the attenuation speed of the vibration signal with the propagation distance, and its value range is 3 to 10; is the time diffusion parameter, ranging from 0.005 to 0.02; is the vibration signal wave velocity, ranging from 3000 to 5000; is the time window delay, ranging from 0.01 to 0.15.

[0031] Specifically, in this embodiment, the data acquisition part pre-processes the vibration signals at various locations on the drill pipe using a method based on time-space convolution. This method uses a filter kernel to perform weighted averaging on the original signal, thereby eliminating noise interference, correcting propagation delay, and reflecting signal attenuation characteristics. The entire pre-processing process is expressed as a double integral, where the integral variables correspond to the spatial position and time of the drill pipe respectively. The physical meaning of the integral is to comprehensively consider the signals at all acquisition points and all times on the drill pipe, so that at any position and time The preprocessed signal obtained on It is not just a simple sampling of the local signal, but a smoothing process in space and time, which can more truly reflect the propagation dynamics of the signal. In the integral formula, the original vibration signal Indicates a certain position on the drill pipe and time The vibration response measured at It plays the role of a weight function, and its structure embeds the physical characteristics of the vibration signal in spatial propagation and time diffusion. The filter kernel first contains a time normalization factor, which ensures that the overall amplitude will not be distorted by the filtering process when performing time domain filtering. Then the part of the filter kernel that appears in the form of a Gaussian function reflects the distribution characteristics caused by time delay during signal propagation. It is a key design for time alignment, which takes into account the signal from the position Send to location Required propagation time , plus a preset time window delay This design makes it possible for the signal to propagate at the expected speed. arrive When the time deviation is the smallest, the Gaussian function obtains the maximum weight, thereby emphasizing the signal components that conform to the laws of physical propagation, and giving lower weights to those signals that deviate from the expected delay due to noise or other interference factors; at the same time, a spatial attenuation factor is introduced in the filter kernel, which adopts the form of exponential attenuation. , which is used to describe the phenomenon that the vibration signal attenuates with distance due to material damping, energy dissipation, etc. in a complex medium such as a drill pipe. The parameter Represents the preset spatial attenuation constant, and its value range is usually set between 3 and 10. A smaller value indicates that the signal attenuates rapidly, which can effectively suppress the influence of long-distance signals, thereby ensuring that in the preprocessing results, signals far away from the current position are The contribution of is naturally weakened, which is of great significance for eliminating noise or irrelevant signals from distant areas. The double integration operation of the entire preprocessing formula makes it possible to calculate When processing the spatial and temporal convolution, the system not only considers the impact of signals at different spatial positions at the same time on the current position, but also fuses the information collected at different time points. This fusion method can smooth random noise and improve signal stability, especially in complex working conditions such as downhole drilling operations. Vibration signals are often interfered by various environments. Through spatiotemporal convolution processing, the system can extract the part that reflects the real physical characteristics of the signal from the chaotic raw data. In actual implementation, the high integration of multi-chip components enables this preprocessing process to be completed at a higher sampling rate and lower latency, allowing the system to obtain real-time It can not only reflect the instantaneous dynamic changes of the signal, but also retain the representative characteristic information due to physical propagation and energy attenuation, thus providing an accurate and reliable data basis for subsequent vibration model establishment, modal decomposition and active vibration suppression.

[0032] Embodiment 3: The pre-processed vibration signal is subjected to time-frequency analysis at each position by the following formula: ; in, is the result of time-frequency analysis; Indicates at location The effective time window width for time-frequency analysis ensures that one or more local vibration cycles can be fully captured within the analysis window. , is the vibration frequency; is the imaginary number symbol; is the angular frequency; Indicates at location The instantaneous rate of change of frequency at .

[0033] Specifically, in this embodiment, the process of performing time-frequency analysis on the preprocessed vibration signal is intended to reveal the frequency composition and amplitude change of the vibration signal at each monitoring point on the drill pipe at a specific moment, so as to provide accurate local vibration information for the subsequent vibration model establishment and active control strategy. The preprocessed signal on the local time domain is processed by a local time domain windowing, and the selected window width is Set according to the typical vibration period at that location, usually approximately The size of , which can ensure that one or more local vibration cycles are fully captured within the time window, so that the time-frequency analysis can truly reflect the dynamic characteristics of vibration. The entire time-frequency analysis process uses a complex-valued integral transform. The weighting function embedded in the transform includes a Gaussian function and a complex exponential factor. The role of the Gaussian function is to locally weight the signal, giving higher weights to adjacent moments, thereby smoothing out the vibration amplitude fluctuations caused by random noise or short-term interference. At the same time, the width of the Gaussian window is determined by the parameter The complex exponential factor not only contains a linear phase term, which reflects the basic frequency component of the signal in the frequency domain, but also introduces a quadratic phase term, whose coefficient is Describes the location This design is similar to adding compensation for instantaneous frequency modulation to the traditional short-time Fourier transform, so it can more accurately capture the characteristics of frequency changes over time in non-stationary vibration signals.

[0034] This process can be regarded as a localized and dynamic spectrum analysis, which analyzes the signal within a limited time at each moment to obtain the frequency distribution near that moment, so that the final output time-frequency representation It also reflects the local characteristics of the signal in both time and frequency dimensions. In practical applications, the spectral components of drill pipe vibration signals are often time-varying and locally non-stationary due to the influence of multiple factors such as downhole environment and mechanical operation. Therefore, the use of this time-frequency analysis method can significantly improve the accuracy of vibration characteristic extraction, help the system identify the main vibration frequency and other important frequency components, and capture the frequency drift caused by instantaneous disturbances during the operation. Combined with the overall design of the downhole drilling tool vibration monitoring and suppression system based on multi-chip components, the time-frequency analysis process can run in real time on each sensor node. The high parallel processing capability and high-speed data transmission function of the multi-chip component provide technical support for the real-time implementation of this computationally intensive algorithm, so that during the drilling operation, the system can complete data acquisition, preprocessing and time-frequency transformation in a very short time, so as to timely feedback the local vibration state of various parts of the drill pipe. Through this processing, the obtained time-frequency representation can not only show the change of the amplitude of the vibration signal over time, but also intuitively reflect the evolution of the spectral structure of the vibration signal, and further provide high-precision local frequency and amplitude data for the subsequent use of physical models to describe vibration propagation, construct external excitation, and error feedback correction. In particular, the use of complex exponential factors containing quadratic phase terms can effectively capture the instantaneous frequency changes caused by medium inhomogeneity or changes in working conditions, so that time-frequency analysis not only stays at the description of static spectrum, but further reveals the instantaneous modulation characteristics of vibration signals, providing richer descriptive information for the nonlinear and dynamic characteristics of drilling tool vibration. The entire time-frequency analysis process mathematically realizes the conversion from time domain signal to time-frequency domain representation by integrating the preprocessed signal and the complex-valued weighting function in the selected time window. This conversion enables the local spectral characteristics of the vibration signal at each position to be accurately captured and presented, providing clear frequency indication and amplitude reference for subsequent modal decomposition and vibration suppression.

[0035] Embodiment 4: The local main vibration frequency is calculated by the following formula: ; in, is the magnitude operator; is the local master frequency, is the corresponding amplitude; the instantaneous phase function is defined as ; then the instantaneous frequency change rate The calculation formula is: ; The local energy at each position is calculated using the following formula: ; in, For location The local energy at .

[0036] Specifically, the system first targets the location and time The obtained time-frequency domain data Amplitude calculation is used to determine which of all angular frequencies has the strongest response, that is, by finding the angular frequency that makes the amplitude reach the maximum value, the local main vibration frequency is determined. This process can be understood as finding the most important frequency component in a complex vibration signal, because in actual downhole drilling tool operations, the vibration signal often contains multiple frequency components, but only one or a limited number of frequency components are the main vibration characteristics, and these frequency components correspond to the main dynamic response of the equipment. Then, the system calculates the complex-valued signal at this frequency The amplitude of the vibration signal at this position is reflects the vibration intensity. In addition, the system further extracts the phase information of the complex-valued signal, which is defined as the instantaneous phase function , which reveals the phase distribution and changes of the vibration signal in the time and space domain. In the underground vibration environment, the phase of the signal can not only describe the propagation of the vibration wave, but also has important significance for understanding the small frequency drift and modulation characteristics in the vibration signal. In order to capture the subtle changes in frequency over time, the system approximates the instantaneous frequency change rate by the second-order difference method of phase. The calculation principle is to estimate the acceleration or change trend of the frequency based on the change of phase at adjacent moments, that is, to use , and This method can effectively reflect the instantaneous frequency changes of the drill pipe under complex working conditions due to material properties, structural damping or external disturbances, and provide accurate feedback signals for the system adaptive correction model. At the same time, the system also uses the amplitude data at the selected angular frequency to calculate the local energy by the square of the amplitude. This calculation method is based on the basic principle in physics that energy is proportional to the square of the signal amplitude, thereby intuitively quantifying the energy distribution of the vibration signal at each position.

[0037] The magnitude of local energy can not only characterize the strength of vibration, but also can be used as a direct description of the distribution of vibration energy when constructing external excitation in the subsequent process, providing an important basis for vibration propagation models and error feedback mechanisms. In the entire data processing process, the time-frequency data obtained in real time by multi-chip components is used so that the vibration characteristics at each position can be quickly and accurately extracted, and converted into parameter data that is easy for the system to process through the above series of mathematical operations. These parameter data will be used to establish a one-dimensional rod vibration model, construct external excitation, and perform model adaptive correction and modal decomposition in the subsequent links, thereby providing accurate input signals for active vibration suppression. The mathematical design of the entire process has strict logic and physical significance. First, the main vibration components in the signal are separated by finding the angular frequency corresponding to the maximum amplitude, and then the amplitude and phase information are obtained by using the amplitude and phase of the complex signal, and the instantaneous frequency change rate is further extracted by the second-order difference method, which not only helps to reflect the non-stationary characteristics of downhole vibration, but also provides a timely control basis for the dynamic response of the system. Based on this series of processing, the system can realize real-time monitoring and efficient suppression of the vibration status of the drill tool in a complex downhole operating environment, ensuring that the main vibration modes can be accurately identified under conditions of intense vibration and changing working conditions, and corresponding control strategies can be implemented accordingly, thereby reducing the risk of equipment damage caused by vibration and extending the service life of the drill tool.

[0038] Example 5: The one-dimensional rod vibration model is expressed using the following formula: ; in, is the drill pipe density; For Time, Location The displacement field at ; is the damping coefficient of the drill pipe; is the cross-sectional area of ​​the drill pipe; is the elastic modulus of the drill pipe; is the energy conversion coefficient, is the set value.

[0039] Specifically, the displacement field in this model is Describes any location (along the length of the drill pipe) and at any time The displacement of the drill pipe is generated by the combined action of multiple physical mechanisms. It reflects the inertial response of the drill pipe after being excited by external vibration. Indicates the density of the drill pipe material, is the cross-sectional area of ​​the drill pipe. These two parameters determine the mass per unit length of the drill pipe, while the second-order time derivative reflects the acceleration effect. Therefore, this term describes the inertial force generated by the drill pipe during vibration due to mass inertia. Physically speaking, this is the dynamic "inertia" that must be overcome in vibration motion. Next, the term The damping effect is introduced, and the parameter is the damping coefficient of the drill pipe, which reflects the internal friction of the material, the energy dissipation at the connection, and other energy losses caused by friction and viscosity effects. Therefore, this term can suppress the overly violent vibration response and make the vibration signal gradually attenuate during the propagation process. This is of great significance for preventing the vibration amplitude from increasing infinitely and protecting the drill structure. It represents the elastic restoring force of the drill pipe material. is the elastic modulus of the drill pipe, which describes the ability of the material to return to its original shape after being stressed, and Again, represents the cross-sectional area. The product of these two constitutes an important parameter describing the stiffness of the material. The derivative of the displacement gradient reflects the change in stress distribution along the drill pipe. This term actually reflects the spatial distribution of the internal force caused by the strain. It is this internal force that plays a role in counteracting external disturbances and restoring equilibrium during the vibration process. The external excitation term on the right The external input information is introduced into the vibration model. It is the local energy calculated from the previous data collection and time-frequency analysis. It objectively reflects the actual vibration energy of the drill pipe at a specific position and time. The preset energy conversion coefficient It is responsible for converting this energy into an equivalent excitation force, so that the model can directly use the measured data to drive the vibration response, thereby achieving a seamless connection between theoretical predictions and actual working conditions.

[0040] Through this external excitation, the system can not only capture the complex vibration characteristics caused by the drilling tool operating environment, drilling technology and formation characteristics, but also adjust the model parameters in time according to the feedback signal, so as to maintain high prediction accuracy and control effect under different working conditions. In the entire model, each item has a clear physical meaning: the inertia term represents the kinetic energy effect caused by the mass during the vibration process; the damping term reflects the process of energy dissipation and vibration attenuation; the elastic recovery term is an important factor in driving the system to return to the equilibrium state, and the external excitation term introduces real-time data from actual vibration energy into the model, making the entire model not only theoretically complete, but also having good practical adaptability. This mathematical description method not only helps the system to establish a one-dimensional rod vibration model and use it as the basis for subsequent modal decomposition, error feedback and active control, but also provides important data basis for realizing adaptive correction. By constantly comparing the measured values ​​with the model predicted values, the system can use the high-speed parallel processing capabilities of multi-chip components to adjust the parameters in the model in real time, so that the predicted displacement field It can be closer to the actual vibration situation, and then compensate and correct errors in real time during the dynamic process. This vibration model based on physical mechanism and data feedback can not only accurately characterize the vibration response of the drill pipe under complex working conditions, but also has high robustness. Even when encountering external environmental changes or slight fluctuations in equipment parameters during downhole operations, the system can respond and adjust in time to avoid vibration out of control. The construction and application of the entire vibration model fully reflects the advantages of system design based on multi-chip components. Through the close cooperation of multi-sensor data acquisition, time-frequency analysis and mathematical modeling, it realizes the accurate conversion from the local vibration signal of the drill pipe to the overall dynamic response. In particular, the introduction of external excitation terms enables the model to directly utilize local energy The feedback information not only improves the real-time performance of the model, but also provides key input for the active control strategy of the subsequent vibration suppression part; the control system can apply reverse excitation in time according to the vibration state predicted by the model to eliminate or reduce excessive vibration amplitude, thereby effectively reducing the risk of mechanical wear and equipment damage. In addition, in practical applications, the parameters of the drill pipe, such as density, cross-sectional area, elastic modulus, and damping coefficient, can usually be obtained through experiments or design data. The determination of these parameters provides a solid physical basis for the model; and the preset energy conversion coefficient It is necessary to debug according to the actual situation to ensure that the conversion from local vibration energy to external excitation force can not only reflect the real physical phenomenon, but also meet the control system's requirements for response speed and accuracy. Through this comprehensive consideration, the entire vibration model not only realizes the continuous description of the vibration process in mathematics, but also organically links the various influencing factors of drill pipe vibration in a physical sense, providing the system with a complete framework that can describe, predict and control the vibration state of the drill tool. Based on this model, the system can realize real-time monitoring and adaptive adjustment of the overall vibration state of the drill pipe. When facing complex downhole environments and changing working conditions, it can quickly capture vibration dynamics and effectively suppress unnecessary vibrations through active control strategies, thereby ensuring the safety of drilling operations and the long-term stable operation of equipment.

[0041] Embodiment 6: Assume that a vibration sensor is used Time, Location The actual displacement obtained at ; Error feedback is ; The one-dimensional bar vibration model is adaptively corrected according to the error feedback through the following formula: ; By solving the corrected one-dimensional bar vibration model, the corrected displacement field is obtained .

[0042] Specifically, this feedback quantity not only quantifies the deviation between the model prediction and the actual observation, but also provides a direct numerical basis for the subsequent adaptive correction of the model. In the drilling tool vibration monitoring and suppression system, due to the variability of the downhole environment and operating conditions, the traditional vibration model is difficult to always accurately reflect the actual vibration state of the drill pipe. Therefore, it is necessary to correct the model through real-time error feedback so that the system can continuously adjust its own parameters to adapt to the field conditions. To this end, the system will feedback the error It is introduced into the one-dimensional bar vibration model, and the damping, elastic restoring force and excitation terms of the model are corrected accordingly. Specifically, in the corrected vibration model, the inertia term remains unchanged to ensure accurate reflection of the physical mass effect; while the damping term is adjusted to , here is the original damping coefficient, which is obtained by subtracting the feedback error , so that when there is a large deviation between the model prediction and the actual value, the system will reduce the effective damping, thereby weakening the dissipation effect of the vibration energy to a certain extent, so as to respond and correct the deviation more quickly. At the same time, the elastic restoring force term is corrected to ,in is the elastic modulus of the drill pipe, is the cross-sectional area. The product originally describing the material stiffness introduces a factor with the error This design makes the system more sensitive to displacement gradient changes when the actual vibration is far from the model prediction, thereby prompting the model to adjust its deformation response more actively in the local area. In addition, in the excitation term on the right side of the model, the original external excitation is modified to ,in is the energy conversion coefficient, and Indicates at location The local vibration energy at When the feedback error is large, the system will use a larger external stimulus to drive the model response, thereby causing the predicted displacement to approach the actual displacement more quickly. Overall, this series of corrections actually constitutes a closed-loop feedback control system. The system continuously compares the actual measurement value with the model prediction value to calculate the error in real time. The vibration model is adaptively corrected according to the error, so that the corrected displacement field Closer to the actual situation.

[0043] In physical terms, adjusting the damping coefficient and elastic recovery term is equivalent to changing the energy dissipation and recovery characteristics of the actual structure, while amplifying the external excitation term is equivalent to introducing a compensation mechanism, which enables the model to quickly obtain additional driving force when it deviates from the actual vibration state, thereby achieving self-correction. This design idea makes full use of the high-precision, real-time vibration data collected from the multi-chip component, and dynamically adjusts the model parameters through the feedback correction mechanism in the mathematical model, so that the system can still maintain high prediction accuracy and control response speed when facing complex downhole environments and changes in working conditions. In practical applications, during drilling operations, since the drill pipe will be affected by various external disturbances and nonlinear effects of the internal structure, the original model often cannot fully describe its complex vibration behavior, and the error feedback mechanism plays a key role. It can capture the deviation between the prediction and the actual in time, and gradually eliminate this deviation through parameter correction to ensure that the system is always in the optimal state. In this process, the multi-chip component not only realizes efficient data acquisition and transmission, but also ensures the real-time nature of the error feedback and model correction process through parallel computing capabilities, so that the corrected displacement field It can be updated in a very short time, thus providing accurate status information for subsequent modal decomposition and active vibration suppression. It can be seen that this adaptive correction method fully considers the complexity of the drilling tool vibration system in the actual downhole environment. By adjusting the parameters such as damping, stiffness and external excitation in real time, the entire vibration model has a high degree of flexibility and robustness, thereby ensuring that the system can respond quickly and operate stably under various dynamic conditions. Finally, by solving the corrected one-dimensional rod vibration model, the system obtains a new displacement field This not only provides a reliable basis for further modal decomposition and active vibration suppression, but also achieves high-precision matching between the model and the actual vibration state, thereby effectively reducing the risk of mechanical wear and structural fatigue caused by vibration and improving the safety and efficiency of downhole drilling operations.

[0044] Embodiment 7: Data analysis part will correct the displacement field Perform modal decomposition in space, the formula is as follows: ; in, is the total number of modes; the modes include at least: axial vibration, bending vibration and torsional vibration; is the modal factor, which is a preset positive or negative integer value. For different types of modes, different values ​​are taken according to their weights, satisfying ; For the Orthogonal mode functions.

[0045] Specifically, in practical applications, the types of modes include at least axial vibration, bending vibration and torsional vibration. Each vibration mode corresponds to a unique response that may occur in the drill pipe during operation. In order to distinguish the contribution of different modes to the overall vibration response, the system pre-sets a set of modal factors. , these factors can be positive or negative integers, and their values ​​are determined by the weight of each vibration mode in the overall response, and are required to meet the normalization condition, that is, the sum of all modal factors is equal to 1, which ensures that the decomposed modes can fully describe the original displacement field in mathematical and physical terms. It describes the The functions of the spatial distribution of vibration modes usually have orthogonal properties, that is, different modes are independent of each other in the definition domain. Such orthogonality not only simplifies mathematical calculations, but also ensures the physical separation of various modes. Through modal decomposition, the overall vibration response can be understood as the superposition of various independent vibration modes. This method can effectively identify and separate various vibration phenomena caused by the structure, working condition changes and external disturbances of the drill pipe in a complex working environment, so that the system can suppress and control different vibration modes in a targeted manner.

[0046] In actual operation, the displacement field after adaptive correction It has accurately reflected the vibration response of the drill pipe during underground operation, but since the vibration response is often caused by the combined action of multiple factors, it is difficult to directly use the overall displacement data for vibration control. Through modal decomposition, the overall displacement field is decomposed into several modal functions with independent characteristics. After that, each mode can be regarded as a basic vibration form, and its corresponding modal factor It characterizes the proportion of this vibration mode in the overall response. For example, the axial vibration mode usually reflects the expansion and compression of the drill pipe along the length direction, while the bending vibration mode reflects the lateral displacement change caused by bending, and the torsional vibration mode corresponds to the rotational movement of the drill pipe around its axis. Under the joint action of multiple vibration modes, the overall vibration response of the drill pipe presents complex spatiotemporal variation characteristics, and modal decomposition effectively disassembles this complexity, so that each mode can be analyzed and processed independently, providing a clear control target for subsequent active vibration suppression.

[0047] From a mathematical point of view, modal decomposition requires solving a set of orthogonal modal functions , these functions are usually obtained by solving the eigenvalue problem of the one-dimensional rod vibration model. In essence, after assuming that the drill rod meets certain boundary conditions during the vibration process, the system can transform the vibration problem into an eigenvalue problem about spatial variables, and solve each eigenfunction and the corresponding eigenvalue. Each eigenfunction corresponds to a vibration mode, and the eigenvalue reflects the natural frequency information under this mode. In actual engineering, this decomposition not only simplifies the vibration analysis problem, but also allows each vibration mode to be individually controlled, so that different control resources and control methods can be allocated according to the vibration characteristics of different modes when implementing active control strategies. By adjusting the modal factors Make presets and ensure their normalized conditions Once this condition is met, the reproduction of the entire vibration response can be achieved by superimposing each mode. This method not only takes into account the precise mathematical decomposition, but also reflects the detailed physical distinction between different vibration forms.

[0048] In the downhole drilling tool vibration monitoring and suppression system, the practical application of modal decomposition is not only to decompose the vibration response, but also to provide key input data for the active vibration suppression strategy. By converting the actual measured vibration signal into each independent modal component, the system can design the corresponding suppression control force according to the characteristics of each mode, so as to weaken or eliminate the vibration caused by the specific mode in a targeted manner. Since the drill pipe may have multiple vibration forms at the same time during the operation, and different vibration forms may have different attenuation laws and propagation speeds, designing a control strategy for each mode can not only improve the control accuracy, but also reduce the waste of control energy. Based on the modal decomposition, the system can use the high-speed parallel processing capability of the multi-chip component to perform real-time calculation and control signal generation for each mode, ensuring that it can respond quickly and adjust the corresponding control parameters when the vibration changes, so as to achieve comprehensive suppression of drill pipe vibration.

[0049] In addition, the modal decomposition method has strong robustness and adaptability. In the actual downhole environment, due to the continuous changes in working conditions and formation conditions, the characteristics of the vibration signal may also change significantly, and the pre-set modal factors and orthogonal mode functions As the basis for describing vibration, its stability and orthogonality ensure that even under complex working conditions, the overall vibration response can still be accurately decomposed into multiple independent components, thus providing solid theoretical support for dynamic adjustment and adaptive control. In the entire modal decomposition process, the data analysis part not only relies on accurate displacement measurement and adaptively corrected displacement field, but also makes full use of the local vibration characteristics extracted by the previous time-frequency analysis. This information enables the modal decomposition to more accurately capture the spatiotemporal characteristics and dynamic change laws of each vibration mode. In this way, the system can effectively identify vibration anomalies caused by different vibration modes when monitoring drill pipe vibration, and then apply control force in a targeted manner during the active control stage, thereby reducing the overall vibration energy and preventing local vibration from being too severe, causing equipment damage or safety accidents.

[0050] Embodiment 8: Determined by the following eigenvalue problem: ; in, For the The eigenvalues ​​of the modes; For the The damping ratio of the mode.

[0051] Specifically, this eigenvalue problem not only reflects the balance relationship between stiffness and mass distribution in traditional beam vibration theory, but also introduces the damping ratio The energy dissipation effect of the system is described, so as to be closer to the dynamic characteristics of the actual downhole drilling tool vibration. represents the restoring force or stiffness effect determined by the elastic and geometric properties of the drill pipe, where is the elastic modulus, which reflects the ability of the material to return to its original shape after being subjected to force, and is the cross-sectional area of ​​the drill pipe, and together they describe the bending stiffness of the drill pipe. The damping term that follows is The effect of energy dissipation during vibration is introduced; here For the The damping ratio of the mode is The appearance of reflects the influence of the natural frequency (or natural frequency) of this mode. The existence of the damping term means that in the actual vibration process, there is not only a vibration response caused by the elastic restoring force, but also an energy loss effect. This energy loss will gradually attenuate the vibration, thus mathematically correcting the eigenvalue problem. It corresponds to the inertia effect, and its physical meaning is to link the inertia of the system with the modal response. can be regarded as the eigenvalue associated with this mode, which is usually proportional to the square of the modal natural frequency. In the ideal case of no damping, this eigenvalue problem is simplified to the classical beam vibration equation, but in this embodiment, by introducing the damping ratio As well as the correction terms related to the eigenvalues, the system can more realistically reflect the energy dissipation and frequency drift phenomena experienced by the drill pipe in the actual working environment.

[0052] Overall, this eigenvalue problem describes the vibration behavior of the drill pipe under external excitation and internal energy dissipation. Solving this differential equation can obtain a series of eigenfunctions and the corresponding eigenvalues ; These eigenfunctions form a complete orthogonal basis, which mathematically satisfy the orthogonality and normalization conditions and can be used to expand any displacement field that satisfies the boundary conditions into modal components. Specifically, each Corresponding to a certain vibration mode of the drill pipe, such as axial vibration, bending vibration or torsional vibration, the eigenvalue is a measure of the square of the natural frequency of the vibration mode. In practical applications, the boundary conditions of the drill pipe (such as the fixed end, free end or other combined boundaries) will directly affect the solution of the eigenfunction and eigenvalue. Therefore, when solving this eigenvalue problem, it is usually necessary to set the corresponding boundary conditions based on the actual physical constraints of the drill. The correction term has important physical significance. It not only adjusts the system's response to vibration energy, but also can more accurately describe the rate of energy decay of each vibration mode in dynamic modal decomposition. The damping ratio reflects the degree of energy dissipation in this mode. A high damping ratio means that the vibration energy decays faster, which makes the proportion of this mode in the overall vibration response lower. Conversely, the mode with a low damping ratio often plays a dominant role in the vibration system. By introducing the damping term, the equation not only considers the influence of material and geometric parameters on the vibration restoring force, but also integrates the information of vibration frequency. This makes it possible to obtain the shape function corresponding to the natural vibration mode and reflect the dynamic characteristics of energy dissipation in the actual vibration process when solving the mode. From an engineering perspective, by solving this eigenvalue problem, the system can obtain a set of modal functions based on physical characteristics. These modal functions are the basis for vibration signal decomposition and vibration control design. In the downhole drilling tool vibration monitoring and suppression system based on multi-chip modules, these orthogonal modes are not only used to convert complex displacement fields into The system can decompose the vibration modes into independent vibration modes, and also enable the subsequent active control strategy to apply suppression force to each mode in a targeted manner, thereby effectively reducing the overall vibration level of the drill pipe. In this way, the system can more accurately identify which vibration modes are the main source of problems and give priority to suppressing these modes during the control process, thereby achieving more efficient vibration suppression.

[0053] Embodiment 9: The process of designing an active control strategy according to the result of modal decomposition includes: setting The magnitude of the initial restraining force of this mode is ; then according to The characteristic value of the mode is used to correct the initial inhibitory force using the following formula to obtain the corrected inhibitory force: ; in, is the corrected inhibitory force.

[0054] Specifically, in this embodiment, the system uses the characteristic parameters of each vibration mode obtained by modal decomposition and combines it with the active control strategy to suppress the vibration of the drill pipe. The core idea is to correct the initial inhibitory force according to the inherent characteristics of each mode, so as to achieve targeted intervention in the vibration of each mode. In this mode, the system pre-sets an initial inhibitory force , the magnitude of this force can be determined by engineering experience or preliminary experimental data, and represents the control force that needs to be applied in order to achieve a certain suppression effect under this mode. However, since each vibration mode has different inherent characteristics, its corresponding modal eigenvalue It can reflect the dynamic characteristics and energy characteristics of the mode, which is usually proportional to the square of the natural frequency of the mode, and to a certain extent reveals the energy proportion of the mode in the vibration system. Therefore, in order to make the control system more accurately match the actual vibration state, the system is based on the The eigenvalue of the mode The initial inhibitory force is corrected to obtain the corrected inhibitory force. and modal eigenvalues Multiplication can dynamically adjust the control force so that when the modal energy is high and the vibration response is strong, the corrected control force will be amplified accordingly, thus more effectively canceling or weakening the vibration in this mode. In the mode with lower energy, due to the eigenvalue If the modal eigenvalue is smaller, the corrected inhibitory force will also be weakened, thus avoiding unnecessary energy waste and over-control, and ensuring the overall balance and robustness of the system. Different control forces are adopted for different vibration modes to achieve the purpose of refined control. From a physical point of view, the modal eigenvalue It is not just a mathematical parameter, but also represents the inherent natural frequency and energy distribution of the vibration system under this mode. Generally speaking, in a vibration system, a mode with a higher natural frequency usually corresponds to a smaller deformation range, while a low-frequency mode may bring a larger amplitude; at the same time, a high-energy mode often occupies a larger proportion of the overall vibration energy and has a more significant impact on the stability of the system. Therefore, by Multiplied by the initial inhibitory force, the system actually implements an adaptive control method, which enables the inhibitory force to be adjusted according to the characteristics of the signal itself, which not only meets the requirement of large control input for large energy modes, but also avoids secondary vibration or over-control caused by excessive intervention on low energy modes. In practical applications, the drilling tool vibration monitoring and suppression system obtains the vibration signals of the drill pipe at various positions and times through a sensor network, and obtains the orthogonal mode functions and their corresponding eigenvalues ​​of each vibration mode through multi-level data processing and modal decomposition. ; These data reflect the dynamic response of the drill pipe under various vibration modes such as axial, bending and torsion. For each mode, the system An active controller is designed to convert the corrected inhibitory force into It is applied to the corresponding actuator, such as a piezoelectric actuator or a servo motor, to generate a force opposite to the vibration, thereby weakening or even eliminating the vibration in this mode. It should be pointed out that the corrected inhibitory force plays a vital role in the entire active control process. It can not only compensate for the vibration deviation caused by the drill pipe structure and the working environment, but also respond to the change of vibration energy in real time to achieve closed-loop control. The control system will continuously detect the current vibration state, and continuously correct and update it by comparing the actual vibration response with the predicted value of the theoretical model. The value of enables the active control strategy to continuously optimize the control effect during the entire drilling operation.

[0055] In this process, the efficient computing and real-time processing capabilities of multi-chip components play a key role. The system uses high-speed data transmission and parallel computing technology to complete steps such as modal decomposition, eigenvalue extraction, and inhibitory force correction in a very short time, ensuring that it can respond at the moment when the drill bit vibration occurs and quickly feed back the control signal to the actuator. This real-time performance ensures that the active control strategy can always maintain a high level of accuracy and response speed under complex and changeable working conditions underground, thereby effectively preventing equipment fatigue or damage caused by vibration. In theory, the correction formula It embodies an adaptive feedback control mechanism based on physical characteristics. It is closely related to the dynamic characteristics of the vibration system. Therefore, this correction method has high adaptability and robustness, and can maintain a stable control effect when the system parameters change or the external environment is disturbed. On the other hand, this method also simplifies the implementation process of the active control strategy, because by organically combining modal decomposition with control force correction, the system can uniformly handle vibration suppression problems of different modes under the same framework, thereby improving the coordination and control efficiency of the overall system. During the operation of the system, as the drilling tool operating conditions and the downhole environment change, the vibration characteristics may also be adjusted accordingly. At this time, the modal eigenvalue The control system can adjust the inhibitory force in real time by continuously updating the modal decomposition results. The size of makes the active control strategy always match the current vibration state, thus achieving the best vibration suppression effect. It is this method based on modal eigenvalue correction of the inhibitory force that enables the entire downhole drilling tool vibration monitoring and suppression system based on multi-chip components to still achieve efficient and accurate vibration control in complex environments, greatly reducing the negative impact of vibration on drilling tool structure and operation safety.

[0056] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that these specific embodiments are only illustrative, and those skilled in the art may omit, replace, and change the details of the above methods and systems in various ways without departing from the principles and essence of the present invention. For example, merging the above method steps so as to perform substantially the same functions in substantially the same manner to achieve substantially the same results is within the scope of the present invention. Therefore, the scope of the present invention is limited only by the appended claims.

Claims

1. A downhole drilling tool vibration monitoring and suppression system based on a multi-chip module, characterized in that: The system comprises: a data acquisition part, a data analysis part and a vibration suppression part; The data acquisition part is used to arrange multiple vibration sensors on the drill pipe to obtain vibration signals at different positions and different times on the drill pipe and perform preprocessing, perform time-frequency analysis on the preprocessed vibration signals at each position, extract the local main vibration frequency and corresponding amplitude of each position by using local time-frequency conversion technology, and evaluate the local energy of each position; The data analysis part is used to describe the vibration propagation of the drilling tool by using a one-dimensional rod vibration model, and construct external excitation by using local energy; compare the actual displacement obtained by the vibration sensor with the displacement field of the one-dimensional rod vibration model to obtain error feedback; according to the error feedback, adaptively correct the one-dimensional rod vibration model; use the corrected one-dimensional rod vibration model to solve the corrected displacement field, perform modal decomposition on the displacement field, and decompose the spatial vibration into several independent vibration modes; The vibration suppression part is used to design an active control strategy according to the result of modal decomposition. The control strategy uses the vibration information of each vibration mode to reduce the overall vibration level by applying a suppressive control force to ensure that each vibration mode is effectively suppressed.

2. The downhole drilling tool vibration monitoring and suppression system based on a multi-chip module according to claim 1, characterized in that: The data acquisition part evenly distributes multiple vibration sensors on the drill pipe. Assume that the vibration signal is ; is the total length of the drill pipe; For time; is the position along the drill pipe; the vibration signal is preprocessed by the following formula: ； in, is the vibration signal after preprocessing; is the time-integrated variable; is the distance integral variable; is the filter kernel, and the formula is as follows: ； in, is the absolute value operator; is the preset spatial attenuation constant, which reflects the attenuation speed of the vibration signal with the propagation distance, and its value range is 3 to 10; is the time diffusion parameter, ranging from 0.005 to 0.02; is the vibration signal wave velocity, ranging from 3000 to 5000; is the time window delay, ranging from 0.01 to 0.

15.

3. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 2, characterized in that: The preprocessed vibration signal is analyzed in time and frequency at each position using the following formula: ； in, is the result of time-frequency analysis; Indicates at location The effective time window width for time-frequency analysis ensures that one or more local vibration cycles can be fully captured within the analysis window. , is the vibration frequency; is the imaginary number symbol; is the angular frequency; Indicates at location The instantaneous rate of change of frequency at .

4. The downhole drilling tool vibration monitoring and suppression system based on multi-chip modules as claimed in claim 2, characterized in that: The local master frequency is calculated by the following formula: ； in, is the magnitude operator; is the local master frequency, is the corresponding amplitude; the instantaneous phase function is defined as ; then the instantaneous frequency change rate The calculation formula is: ; The local energy at each position is calculated using the following formula: ； in, For location The local energy at .

5. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 4, characterized in that: The one-dimensional bar vibration model is expressed using the following formula: ； in, is the drill pipe density; For Time, Location The displacement field at ; is the damping coefficient of the drill pipe; is the cross-sectional area of ​​the drill pipe; is the elastic modulus of the drill pipe; is the energy conversion coefficient, is the set value.

6. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 5 is characterized in that Vibration sensors in Time, Location The actual displacement obtained at ; Error feedback is ; Adaptive correction is performed on the one-dimensional bar vibration model according to the error feedback through the following formula: ； By solving the corrected one-dimensional rod vibration model, the corrected displacement field is obtained .

7. The downhole drilling tool vibration monitoring and suppression system based on a multi-chip module according to claim 6, characterized in that: The data analysis part uses the corrected displacement field Perform modal decomposition in space, the formula is as follows: ； in, is the total number of modes; the modes include at least: axial vibration, bending vibration and torsional vibration; is the modal factor, which is a preset positive or negative integer value. For different types of modes, different values ​​are taken according to their weights, satisfying ; For the Orthogonal mode functions.

8. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 6, characterized in that: Determined by the following eigenvalue problem: ； in, For the The eigenvalues ​​of the modes; For the The damping ratio of the mode.

9. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 8, characterized in that: The process of designing an active control strategy based on the results of modal decomposition includes: setting The magnitude of the initial restraining force of this mode is ; then according to The characteristic value of the mode is used to correct the initial inhibitory force using the following formula to obtain the corrected inhibitory force: ； in, is the corrected inhibitory force.

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