Downhole Drill String Vibration Monitoring and Suppression System Based on Multi-Chip Components

Abstract

The present invention belongs to the technical fields of mechanical measurement and automatic control, and particularly relates to a downhole drill string vibration monitoring and suppression system based on a multi-chip component. The system includes: 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 pipe to acquire vibration signals at different positions and different times on the drill pipe and perform preprocessing, and at the same time evaluate the local energy of each position; the data analysis part is used for describing the vibration propagation of the drill string by using a one-dimensional rod vibration model to obtain an error feedback; according to the error feedback, decomposing the spatial vibration into a plurality of independent vibration modes; the vibration suppression part is used for reducing the overall vibration level by applying a suppression control force to ensure that each vibration mode is effectively suppressed. The present invention improves the real-time performance and data accuracy of vibration monitoring, and also effectively reduces equipment wear and safety risks caused by vibration.

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, traditional vibration monitoring methods mainly rely on single or a small number of vibration sensors installed on the drill pipe. By performing spectral analysis on the collected acceleration or displacement signals, the vibration state is judged. To a certain extent, such methods can reflect the vibration of the drill string. However, 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, resulting in the inability to meet the requirements of the high-dynamic downhole operation environment in terms of real-time performance and accuracy. On the other hand, vibration monitoring methods based on multi-sensor fusion technology have been adopted in existing literature, attempting to achieve omnidirectional 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 in the downhole environment, it is often difficult to balance the anti-interference ability of the sensors and the real-time response performance of their data processing units. In addition, most existing multi-sensor systems adopt traditional centralized data processing architectures, and their signal preprocessing and feature extraction mainly rely on single time-domain or frequency-domain analysis methods, making it difficult to consider the comprehensive characteristics of signals in the spatio-temporal domain. As a result, the extraction of key information such as local vibration energy, dominant vibration frequency, and instantaneous frequency change is not accurate enough, which restricts the design of subsequent active control strategies. Currently, in the analysis of vibration signals, methods such as short-time Fourier transform and time-frequency decomposition have been widely used in various mechanical vibration monitoring systems. However, these methods are easily affected by factors such as window function selection, boundary effects, and noise interference when dealing with non-stationary signals. Especially during the operation of downhole drill tools, the vibration signals not only have strong non-stationarity but are also affected by complex geological conditions and changes in drilling processes. Their frequency components and amplitude changes exhibit obvious local characteristics. Traditional time-frequency analysis methods have limitations in capturing such local characteristics and often have difficulty considering the instantaneous phase, local energy, and frequency drift problems of signals simultaneously, resulting in an incomplete and inaccurate description of the drill tool vibration state, and further affecting the formulation and implementation of subsequent vibration suppression control strategies. Summary of the Invention

[0004] The main object of the present invention is to provide a downhole drill string vibration monitoring and suppression system based on multi-chip components. The system realizes real-time acquisition of drill string vibration signals by evenly arranging a plurality of high-precision vibration sensors on the drill pipe, and uses advanced spatio-temporal domain preprocessing, local time-frequency analysis, and adaptive correction technologies to finely process the acquired data, thereby constructing a one-dimensional rod vibration model that can accurately reflect the dynamic response of the drill pipe. Then, through modal decomposition, the overall vibration response is disassembled into multiple independent vibration modes such as axial, bending, and torsion. Furthermore, based on the characteristics of each vibration mode, an active control strategy is designed to apply a corrected inhibitory force to each mode to achieve precise 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] To solve the above technical problems, the present invention provides a downhole drill string vibration monitoring and suppression system based on multi-chip components. The system includes: a data acquisition part, a data analysis part, and a vibration suppression part;

[0006] The data acquisition part is used to arrange a plurality of vibration sensors on the drill pipe to obtain vibration signals at different positions and different times on the drill pipe and perform preprocessing. Time-frequency analysis is performed on the preprocessed vibration signals at each position, and local main vibration frequencies and corresponding amplitudes at each position are extracted using local time-frequency conversion technology, and the local energy at each position is evaluated at the same time;

[0007] The data analysis part is used to describe the vibration propagation of the drill string using a one-dimensional rod vibration model, and at the same time use local energy to construct an external excitation; compare the actual displacement obtained by the vibration sensor with the displacement field of the one-dimensional rod vibration model to obtain an error feedback; according to the error feedback, perform adaptive correction on the one-dimensional rod vibration model; use the corrected one-dimensional rod vibration model to solve the corrected displacement field, and perform modal decomposition on the displacement field to decompose the spatial vibration into several independent vibration modes;

[0008] The vibration suppression part is used to design an active control strategy according to the results of modal decomposition. The control strategy uses the vibration information of each vibration mode to reduce the overall vibration level by applying an inhibitory control force to ensure that each vibration mode is effectively suppressed.

[0009] Further, the data acquisition part evenly distributes a plurality of vibration sensors on the drill pipe. Let the vibration signal be ; is the total length of the drill pipe; is the time; is the position along the drill pipe; The vibration signal is preprocessed through the following formula:

[0010] ;

[0011] wherein, is the vibration signal after preprocessing; is the time integration variable; is the distance integration variable; is the filter kernel, and the formula is as follows:

[0012] ;

[0013] wherein, is the absolute value operator; is the preset spatial attenuation constant, reflecting the attenuation speed of the vibration signal with the propagation distance, and the value range is from 3 to 10; is the time diffusion parameter, and the value range is from 0.005 to 0.02; is the wave speed of the vibration signal, and the value range is from 3000 to 5000; is the time window delay, and the value range is from 0.01 to 0.15.

[0014] Furthermore, the time-frequency analysis is performed on the vibration signal after preprocessing at each position through the following formula:

[0015] ;

[0016] wherein, is the result of the time-frequency analysis; represents the effective time window width for time-frequency analysis at position to ensure that one or more local vibration periods can be completely captured within the analysis window, , is the vibration frequency; is the imaginary symbol; is the angular frequency; represents the instantaneous frequency change rate at position .

[0017] Furthermore, the local dominant vibration frequency is calculated through the following formula:

[0018] ;

[0019] wherein, is the amplitude operator; is the local dominant vibration frequency, is the corresponding amplitude; define the instantaneous phase function as ; then the calculation formula of the instantaneous frequency change rate is: ; the local energy at each position is calculated through the following formula:

[0020] ;

[0021] wherein, is the local energy at position .

[0022] Furthermore, the one-dimensional rod vibration model is expressed by the following formula:

[0023] ;

[0024] wherein, is the drill pipe density; is at time, the displacement field at position ; is the drill pipe damping coefficient; is the cross-sectional area of the drill pipe; is the elastic modulus of the drill pipe; is the energy conversion coefficient, which is a set value.

[0025] Furthermore, it is assumed that the actual displacement obtained by the vibration sensor at time, position is ; the error feedback is ; according to the following formula, based on the error feedback, the one-dimensional rod vibration model is adaptively corrected:

[0026] ;

[0027] By solving the corrected one-dimensional rod vibration model, the corrected displacement field is obtained.

[0028] Furthermore, the data analysis part performs modal decomposition on the corrected displacement field in space, and the formula is as follows:

[0029] ;

[0030] wherein, is the total number of modes; the modes at least include: axial vibration, bending vibration and torsional vibration; is the modal factor, which is a preset positive integer or negative integer value. For different types of modes, depending on their different weights, the values are different and satisfy ; is the th orthogonal modal function.

[0031] Furthermore, is determined by the following eigenvalue problem:

[0032] ;

[0033] Among them, is the eigenvalue of the th mode; is the damping ratio of the th mode.

[0034] Furthermore, the process of designing an active control strategy based on the results of modal decomposition includes: Suppose the magnitude of the initial inhibitory force in the th mode is ; then, according to the eigenvalue of the th mode, the initial inhibitory force is corrected through the following formula to obtain the corrected inhibitory force:

[0035] ;

[0036] Among them, is the corrected inhibitory force.

[0037] The downhole drill string vibration monitoring and suppression system based on multi-chip modules of the present invention has the following beneficial effects:

[0038] First of all, the present invention uses a distributed sensor network to evenly arrange a plurality of high-precision vibration sensors on the drill pipe, enabling the simultaneous acquisition of vibration data at various positions. By adopting the multi-chip module integration technology in the harsh downhole environment, not only the high-speed acquisition, digital conversion, and real-time transmission of signals are realized, but also the anti-interference ability of the system to extreme conditions such as electromagnetic interference, high temperature, and high pressure is greatly improved. This technical advantage makes the collected data have high resolution and high reliability, providing a solid foundation for subsequent data processing and control.

[0039] Secondly, the system adopts advanced signal preprocessing technology to perform convolutional filtering on the original vibration signal in the time and space domains, thereby effectively reducing the influence of environmental noise and external interference on the signal quality. This method fully considers the propagation characteristics of the drill string vibration signal in time and space, and through weighted averaging and delay compensation, ensures that the preprocessed signal can truly reflect the local vibration state of the drill pipe. In this way, not only the interference caused by factors such as uneven formation and equipment friction is eliminated, but also the smoothness and usability of the data are improved, providing a more accurate signal input for subsequent time-frequency analysis and modal decomposition.

[0040] Secondly, using the local time-frequency conversion technology, the system performs time-frequency analysis on the preprocessed vibration signals. It can not only extract the main vibration frequencies and amplitude information at each monitoring position, but also capture the instantaneous phase and local energy changes of the signals. Through this time-frequency analysis method, the system can accurately locate vibration anomalies in the complex and changeable downhole operation environment, and reveal the dynamic response characteristics of the drill string under different working conditions. This method has great advantages in terms of real-time performance and accuracy, and can provide detailed data support for the formulation of vibration suppression strategies.

[0041] In addition, by establishing a one-dimensional rod vibration model, the present invention mathematically describes the vibration response of the drill pipe, combines the actually measured displacement signals with the theoretical predictions, and then uses error feedback for adaptive correction, so that the model predictions can be highly consistent with the actual on-site conditions. By continuously adjusting the model parameters, the system realizes the accurate characterization of the dynamic behavior of the drill string vibration. This not only makes the monitoring of the vibration state more reliable, but also provides an accurate physical basis for active control, and then realizes the effective separation and control of the vibration modes. Brief Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0043] Figure 1 It is a schematic structural diagram of a downhole drill string vibration monitoring and suppression system based on a multi-chip module provided by an embodiment of the present invention. Detailed Embodiments

[0044] The following will further elaborate on the method of the present invention in conjunction with the drawings and the embodiments of the present invention.

[0045] Embodiment 1, refer to Figure 1 : A downhole drill string vibration monitoring and suppression system based on a multi-chip module, the system includes: a data acquisition part, a data analysis part, and a vibration suppression part.

[0046] The data acquisition part is used to arrange a plurality of vibration sensors on the drill pipe to obtain vibration signals at different positions and different times on the drill pipe and perform preprocessing. Time-frequency analysis is performed on the preprocessed vibration signals at each position, and the local main vibration frequencies and corresponding amplitudes at each position are extracted using the local time-frequency conversion technology, and the local energy at each position is evaluated simultaneously.

[0047] The data analysis section is used to describe the vibration propagation of the drill string using a one-dimensional rod vibration model, and at the same time construct an external excitation 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 an error feedback; according to the error feedback, perform adaptive correction on 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.

[0048] The vibration suppression section is used to design an active control strategy according to the results of modal decomposition. This control strategy uses the vibration information of each vibration mode and reduces the overall vibration level by applying inhibitory control forces to ensure that each vibration mode is effectively suppressed.

[0049] Specifically, the data acquisition section mainly relies on installing multiple vibration sensors at different positions on the drill pipe to achieve real-time acquisition of the vibration signals generated by the drill string during downhole operations. The drilling environment is complex, and the drill pipe will be affected by various factors such as the formation, mechanical friction, and drilling technology during operation, resulting in dynamic changes in the vibration signals in both time and frequency. Therefore, sensors evenly arranged on the drill pipe can capture the vibration information at different positions, and through multi-chip module technology, signal acquisition, preliminary processing, and data transmission are integrated into one module 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, the signal is first amplified, filtered, and preprocessed to eliminate electromagnetic interference and random noise caused by the complex downhole geological structure and the movement of the drilling equipment, so that the subsequent data can more accurately reflect the actual vibration situation of the drill string. The preprocessed signal is rapidly converted into a digital signal 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 section also continuously monitors the instantaneous vibration generated during the operation of the drill string through an internal multi-stage filtering and automatic correction mechanism, and extracts the main vibration frequencies, amplitudes, and local energy information at each measurement point by analyzing the time-frequency characteristics of the acquired signals. These parameters have direct application value in subsequent use of physical models to describe vibration propagation and construct external excitations.

[0050] Through the local time-frequency conversion technology, the continuously changing signal can be analyzed by expanding it in two dimensions of time and frequency, so as to obtain the vibration state information of each part of the drill pipe, reflect the distribution of vibration energy in different regions, and provide reliable data support for further establishing a one-dimensional rod vibration model. During the entire data acquisition process, the high-precision sensors and the integrated design of multi-chip components enable the system to operate stably under high temperature, high pressure and strong vibration environments downhole. By real-time transmitting and storing the collected data, it is ensured that the changes in the vibration state of the drill tool at each moment can be completely recorded. Since the vibration signal changes rapidly during the drilling process, the system pays special attention to the high-speed sampling and real-time processing capabilities in the hardware design, so as to quickly respond and transmit data when the drill tool is subjected to small vibration changes, thus providing accurate inputs for the subsequent data analysis module to build models, perform error feedback and modal decomposition. The entire data acquisition part is closely coordinated with the overall system design. Through the integrated multi-chip components, signal acquisition, preprocessing, digital conversion and data transmission are realized, enabling the system to efficiently obtain vibration information in the downhole 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 the data after preprocessing and preliminary analysis, the subsequent data analysis module can use a one-dimensional rod vibration model to describe the vibration propagation, and at the same time combine the local energy to construct an external excitation term, and realize the adaptive correction of the model parameters through comparison and feedback with the actual measured displacement, and finally provide fine control targets for vibration suppression.

[0051] 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 string. By continuously analyzing the data preprocessed by multiple sensors, the system first describes the vibration fluctuations inside the drill pipe with a one-dimensional rod vibration model. This model depicts the propagation law of vibration signals inside the drill pipe and the attenuation characteristics of vibration energy from a physical perspective, thus establishing a theoretical framework for the system to predict the dynamic response of the drill string. Using this model, the data analysis part compares the parameters such as displacement and acceleration measured at different positions of the drill pipe with the preset propagation characteristics 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 existing in the transmission process of vibration signals but also provide a basis for the subsequent correction of model parameters. The data analysis process applies the local time-frequency conversion technology to the continuously collected vibration signals, enabling the signals to be unfolded in both the time and frequency dimensions, so that the main vibration frequencies, amplitudes, and local energy distribution of each position of the drill pipe 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 string. This excitation term reflects the external disturbances and the real-time changes in the internal vibration energy that the drill pipe experiences under specific working conditions. In the data analysis part, after the signals collected by the sensors are processed by local time-frequency, the system begins to compare the actually measured displacement signal with the theoretical displacement field calculated using the one-dimensional rod model. By comparing the differences between the two, a feedback information reflecting the error is generated, which 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, making the model prediction value closer to the actual measurement result, thereby achieving a fine description of the drill string vibration state. As the data analysis progresses, the system will also perform modal decomposition on the corrected displacement field, dividing the overall vibration phenomenon into multiple independent vibration modes. Each mode represents a unique motion pattern in the drill string vibration response. The separated modal data can not only reveal the possible local abnormal vibrations that occur during the operation of the drill string but also provide a clear direction for the subsequent design of targeted suppression strategies. The entire data analysis process benefits from the high integration ability of multi-chip components, enabling the data to be calculated and processed at an extremely high speed after being transmitted to the central processing module. This not only ensures that the data analysis results can be timely fed back to the vibration suppression part but also enables the system to dynamically capture the instantaneous changes in the drill string vibration state during the data processing process.

[0052] In the data analysis section, not only traditional physical models and time-frequency analysis techniques are used to process vibration signals, but also actual measurement errors and environmental change factors are considered. Through an adaptive correction mechanism, the vibration propagation model is continuously improved, enabling the system to maintain a high analysis accuracy even in the face of complex and non-linear vibration phenomena during drilling. The various processing methods used in data analysis cooperate with each other, not only ensuring the accurate restoration of drill pipe vibration signals, but also providing sufficient data basis for the design of the next active control strategy, enabling each independent vibration mode obtained through modal decomposition to be directly converted into controller input parameters, thus achieving efficient vibration suppression during the subsequent application of targeted control forces. During the data analysis process, the system continuously adjusts and optimizes model parameters, gradually reducing the deviation between the actual vibration state of the drill string and the theoretical prediction. This feedback adjustment process enables the system to maintain a stable analysis accuracy during long-term operation. The implementation of the data analysis section relies on the support of multi-chip components, which not only enable each data processing module to work efficiently in hardware, but also minimize the delay between data transmission, storage, and calculation, thus ensuring that the overall system can still monitor and accurately analyze drill string vibration in the complex downhole environment. After integrating various data processing methods, the system can extract key features reflecting the working state of the drill string from vibration signals. These feature data not only provide an important reference for understanding the drill string vibration mechanism, but also provide a basis for dynamic control for the vibration suppression section, enabling the entire system to achieve a closed-loop control from data acquisition to analysis and then to suppression in terms of dynamic response.

[0053] 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 modality but also fully considers the synergistic effects between multiple modalities. By applying appropriate damping forces at each control node, the overall vibration state is optimized, enabling the uniform attenuation of vibrations in each part of the drill string during operation and reducing the risk of wear and damage to the equipment caused by vibrations.

[0054] Embodiment 2: In the data acquisition part, a plurality of vibration sensors are evenly distributed on the drill pipe. Let the vibration signal be ; is the total length of the drill pipe; is the time; is the position along the drill pipe; The vibration signal is preprocessed through the following formula:

[0055] ;

[0056] where, is the preprocessed vibration signal; is the time integration variable; is the distance integration variable; is the filter kernel, and the formula is as follows:

[0057] ;

[0058] where, 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 from 3 to 10; is the time diffusion parameter, and its value range is from 0.005 to 0.02; is the wave speed of the vibration signal, and its value range is from 3000 to 5000; is the time window delay, and its value range is from 0.01 to 0.15.

[0059] Specifically, in this embodiment, the preprocessing of the vibration signals at various positions on the drill pipe in the data acquisition part adopts a method based on spatio-temporal domain convolution. This method uses the filter kernel to perform weighted averaging on the original signal, thereby eliminating noise interference, correcting propagation delay, and reflecting the signal attenuation characteristics. The entire preprocessing process is expressed as a double integral, where the integration 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 moments on the drill pipe, so that the preprocessed signal and time obtained at is not just a simple sampling of local signals but is smoothed in both space and time, and can more realistically reflect the propagation dynamics of the signal. In the integral formula, the original vibration signal represents at a certain position on the drill pipe and the moment at which the vibration response is measured, while the filtering kernel acts as a weight function, and the physical characteristics of the spatial propagation and temporal diffusion of the vibration signal are embedded in its structure. The filtering kernel first includes a time normalization factor, which ensures that the overall amplitude will not be distorted due to the filtering process during time-domain filtering. Subsequently, the part in the form of a Gaussian function in the filtering kernel reflects the distribution characteristics caused by time delay during the signal propagation process. Among them, in the expression is a key design for time alignment. This term takes into account the signal from position to position the required propagation time , plus the preset time window delay . This design makes it so that when the signal arrives at at the expected propagation speed , its time deviation is minimized, thus obtaining the maximum weight in the Gaussian function, and further emphasizing the signal components that conform to the physical propagation law, while 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 also introduced in the filtering kernel, and this factor adopts an exponential decay form to describe the phenomenon that the vibration signal decays with distance due to material damping, energy dissipation, etc. in a complex medium such as a drill pipe. Among them, 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 decays rapidly, which can effectively suppress the influence of signals at a long distance, thus ensuring that in the preprocessing result, the contribution of signals farther from the current position to is naturally weakened, which is of great significance for excluding noise or irrelevant signals from farther regions. The double integral operation of the entire preprocessing formula makes it so that when calculating , not only the influence of signals at different spatial positions at the same moment on the current position is considered, but also the information collected at different time points is fused together. This fusion method can smooth random noise and improve the stability of the signal. Especially in complex working conditions such as downhole drill tool operations, the vibration signal is often affected by various environmental interferences. Through spatio-temporal convolution processing, the system can extract the part that reflects the true 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 high sampling rate and with a low delay, making the obtained by the system in real time can not only reflect the instantaneous dynamic changes of the signal, but also retain the characteristic information that is representative 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.

[0060] Example 3: Perform time-frequency analysis on the preprocessed vibration signal at each position through the following formula:

[0061] ;

[0062] where is the result of time-frequency analysis; represents the effective time window width for time-frequency analysis at position , ensuring that one or more local vibration cycles can be completely captured within the analysis window, , is the vibration frequency; is the imaginary symbol; is the angular frequency; represents the instantaneous frequency change rate at position .

[0063] Specifically, in this embodiment, the process of performing time-frequency analysis on the preprocessed vibration signal aims to reveal the frequency composition and amplitude variation 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 subsequent vibration model establishment and active control strategies. In this method, the preprocessing signal at each position undergoes a local time-domain windowing process, and the selected window width is set according to the typical vibration period at this position, usually approximated to the size of , so as to ensure that one or more local vibration cycles can be completely captured within the time window, enabling the time-frequency analysis to truly reflect the dynamic change characteristics of the vibration. The entire time-frequency analysis process utilizes a complex-valued integral transform, and 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 controlled by the parameter , which determines the fineness of attention to signal changes in the time domain. The complex exponential factor not only includes a linear phase term, which reflects the basic frequency component of the signal in the frequency domain, but also introduces a quadratic phase term, and its coefficient describes the change rate of the instantaneous frequency of the signal at position . This design is similar to adding compensation for instantaneous frequency modulation on the basis of the traditional short-time Fourier transform, so as to be able to more accurately capture the characteristics of frequency changing with time in non-stationary vibration signals.

[0064] This process can be regarded as a localized and dynamic spectrum analysis. By analyzing the signal within a finite time duration at each moment, the frequency distribution near that moment is obtained, so that the finally output time-frequency representation simultaneously reflects the local characteristics of the signal in both the time and frequency dimensions. In practical applications, due to the influence of multiple factors such as the downhole environment and mechanical operations, the spectral components of the drill pipe vibration signal often have time-varying and locally non-stationary characteristics. Therefore, adopting this time-frequency analysis method can significantly improve the accuracy of extracting vibration characteristics, help the system identify the main vibration frequency and other important frequency components, and simultaneously capture the frequency drift caused by instantaneous disturbances during the operation process. Combining with the overall design of the downhole drill tool vibration monitoring and suppression system based on multi-chip modules, this time-frequency analysis process can run in real time on each sensor node. The high parallel processing ability and high-speed data transmission function of the multi-chip modules provide technical support for the real-time implementation of this computationally intensive algorithm, enabling the system to complete data acquisition, preprocessing, and time-frequency transformation in an extremely short time during the drilling operation, so as to timely feedback the local vibration states of various parts of the drill pipe. Through this processing, the obtained time-frequency representation can not only display the variation of the amplitude of the vibration signal with time, but also intuitively reflect the evolution of the spectral structure of the vibration signal, further providing high-precision local frequency and amplitude data for subsequent use of physical models to describe vibration propagation, construct external excitation, and error feedback correction. In particular, by using a complex exponential factor containing a quadratic phase term, it can effectively capture the instantaneous frequency changes caused by medium inhomogeneity or working condition changes, enabling the time-frequency analysis not to stay at the description of the static spectrum, but further revealing the instantaneous modulation characteristics of the vibration signal and providing more abundant descriptive information for the nonlinear and dynamic characteristics of the drill tool vibration. The entire time-frequency analysis process mathematically realizes the conversion from the time-domain signal to the time-frequency domain representation by integrating the preprocessed signal with a complex-valued weighting function within a 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 indications and amplitude references for subsequent modal decomposition and vibration suppression.

[0065] Example 4: The local main vibration frequency is calculated by the following formula:

[0066] ;

[0067] where is the amplitude operator; is the local main vibration frequency, is the corresponding amplitude; define the instantaneous phase function as ; then the calculation formula for the instantaneous frequency change rate is: ; The local energy at each position is calculated by the following formula:

[0068] ;

[0069] Where is the local energy at position .

[0070] Specifically, the system first uses amplitude operations on the time-frequency domain data obtained for position and time to determine which response is the strongest at all angular frequencies, that is, by finding the angular frequency that makes the amplitude reach the maximum value, thereby determining the local dominant vibration frequency . This process can be understood as finding the most dominant frequency component in a complex vibration signal. Because in actual downhole drill string 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 responses of the equipment. After obtaining , the system calculates the amplitude of the complex-valued signal at this frequency, and this amplitude is used as the amplitude of the vibration signal at this position, which reflects the vibration intensity. In addition, the system further extracts the phase information of this complex-valued signal, defined as the instantaneous phase function , and this function reveals the phase distribution and its changes of the vibration signal in the spatio-temporal domain. In the downhole vibration environment, the phase of the signal can not only describe the propagation of the vibration wave, but also be of great significance for understanding the small frequency drift and modulation characteristics in the vibration signal. To capture this subtle change of frequency over time, the system approximately calculates the instantaneous frequency change rate by the method of the second-order difference of the phase. Its calculation principle is to estimate the acceleration or change trend of the frequency based on the change of the phase at adjacent times, that is, by using , and for the difference relationship to achieve. This method can effectively reflect the instantaneous frequency change of the drill pipe under complex working conditions due to material characteristics, structural damping or external disturbances, and provides an accurate feedback signal for the system's adaptive correction model. At the same time, the system also uses the amplitude data at the selected angular frequency and calculates the local energy by squaring 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.

[0071] The magnitude of the local energy can not only characterize the intensity of vibration, but also serve as a direct description of the vibration energy distribution when constructing external excitation subsequently, providing an important basis for the vibration propagation model and the error feedback mechanism. In the entire data processing flow, the time-frequency data obtained in real-time by the multi-chip component enables the vibration characteristics at each position to be extracted quickly and accurately, and through the above series of mathematical operations, it is transformed into parameter data that is easy for the system to process. These parameter data will be used in subsequent steps to establish a one-dimensional rod vibration model, construct external excitation, and perform model adaptive correction and modal decomposition, so as to provide accurate input signals for active vibration suppression. The mathematical design of the whole process has strict logic and physical meaning. 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 using the amplitude and phase of the complex-valued signal respectively, and further the instantaneous frequency change rate is extracted through the second-order difference method. This not only helps to reflect the non-stationary characteristics of the downhole vibration, but also provides a timely regulation basis for the system dynamic response. Based on this series of processes, the system can realize real-time monitoring and efficient suppression of the vibration state of the drill string in a complex downhole operation environment, ensuring that in the case of intense vibration and changing working conditions, the main vibration modes can be accurately identified, and corresponding control strategies can be implemented accordingly, thereby reducing the risk of equipment damage caused by vibration and prolonging the service life of the drill string.

[0072] Embodiment 5: The one-dimensional rod vibration model is expressed by the following formula:

[0073] ;

[0074] Wherein, is the density of the drill pipe; is at time, the displacement field at position ; is the drill pipe damping coefficient; is the cross-sectional area of the drill pipe; is the elastic modulus of the drill pipe; is the energy conversion coefficient, which is a set value.

[0075] Specifically, the displacement field in this model describes the displacement of the drill pipe at any position (along the length direction of the drill pipe) and at any time , and this displacement field is generated by the combined action of multiple physical mechanisms. First, the term reflects the inertial response of the drill pipe after being excited by external vibration, where represents 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.

[0076] Through this external excitation, the system can not only capture the complex vibration characteristics caused by the drill string operating environment, drilling technology, and formation characteristics, but also adjust the model parameters in a timely manner according to the feedback signal, so as to maintain a high prediction accuracy and control effect under different working conditions. In the entire model, each term has a clear physical meaning: the inertial term represents the kinetic energy effect caused by 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 driving the system back to the equilibrium state, while the external excitation term introduces real-time data from the actual vibration energy into the model, making the entire model not only theoretically complete but also have good practical adaptability. This mathematical description method not only helps the system 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 an important data basis for realizing adaptive correction. By continuously comparing the measured values with the model prediction values, the system can utilize the high-speed parallel processing ability of multi-chip components to adjust the parameters in the model in real time, making the predicted displacement field be able to 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 depict 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 a timely manner to avoid out-of-control vibration. The construction and application of the entire vibration model fully reflect the advantages of the system design based on multi-chip components. Through the close cooperation of multi-sensor data acquisition, time-frequency analysis, and mathematical modeling, the accurate conversion from the local vibration signal of the drill pipe to the overall dynamic response is achieved. Especially the introduction of the external excitation term enables the model to directly utilize the feedback information of local energy . This not only improves the real-time performance of the model but also provides key inputs for the active control strategy in the subsequent vibration suppression part; the control system can apply reverse excitation in a timely manner according to the vibration state predicted by the model to eliminate or reduce the excessive vibration amplitude, thereby effectively reducing the risk of mechanical wear and equipment damage. In addition, in practical applications, 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, and the determination of these parameters provides a solid physical basis for the model; while the preset energy conversion coefficient Debugging is required 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 phenomena but also meet the requirements of the control system for response speed and accuracy. Through this comprehensive consideration, the entire vibration model not only continuously describes the vibration process mathematically but also organically links all the influencing factors of drill pipe vibration in terms of physical meaning, providing a complete framework for the system to describe, predict, and control the vibration state of the drill string. Based on this model, the system can achieve real-time monitoring and adaptive adjustment of the overall vibration state of the drill pipe. When facing a complex downhole environment and changing working conditions, it can quickly capture the vibration dynamics and effectively suppress unnecessary vibrations through an active control strategy, thereby ensuring the safety of drilling operations and the long-term stable operation of the equipment.

[0077] Example 6: Suppose the actual displacement obtained by the vibration sensor at time and position is ; the error feedback is ; according to the following formula, the one-dimensional rod vibration model is adaptively corrected based on the error feedback:

[0078] ;

[0079] By solving the corrected one-dimensional rod vibration model, the corrected displacement field is obtained.

[0080] 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 drill string vibration monitoring and suppression system, due to the variability of the downhole environment and operating conditions, traditional vibration models are 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 on-site conditions. For this purpose, the system introduces the feedback error into the one-dimensional rod vibration model and makes corresponding corrections to the damping, elastic restoring force, and excitation terms of the model. Specifically, in the corrected vibration model, the inertia term remains unchanged to ensure an accurate reflection of the physical mass effect; while the damping term is adjusted to , where is the original damping coefficient. By subtracting the feedback error , 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 vibration energy to a certain extent to respond and correct the deviation more quickly. At the same time, the elastic restoring force term is corrected to , where is the elastic modulus of the drill pipe, is the cross-sectional area, and the product originally describing the material stiffness introduces a factor proportional to the error in this design, when the gap between the actual vibration and the model prediction is large, the system will increase its sensitivity to the change in displacement gradient, thus prompting the model to more actively adjust its deformation response in the local area. In addition, in the excitation term on the right side of the model, the original external excitation is corrected to , where is the energy conversion coefficient, and represents the local vibration energy at position ; by dividing by , when the feedback error is large, the system will use a larger external excitation to drive the model response, thus prompting the predicted displacement to approach the actual displacement faster. 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, calculates the error in real time and adaptively corrects the vibration model according to this error, so that the corrected displacement field is closer to the actual situation.

[0081] Physically, adjusting the damping coefficient and the elastic recovery term is equivalent to changing the energy dissipation and recovery characteristics in the actual structure, and by amplifying the external excitation term, it is equivalent to introducing a compensation mechanism, enabling the model to quickly obtain an additional driving force when deviating from the actual vibration state, and then realizing self-correction. This design idea makes full use of the high-precision and real-time vibration data collected from the multi-chip module. Through the feedback correction mechanism in the mathematical model, the model parameters are dynamically adjusted, enabling the system to maintain a high prediction accuracy and control response speed in the face of complex downhole environments and working conditions changes. In practical applications, during the drilling operation, due to the drill pipe being affected by various external disturbances and internal structure nonlinear effects, the original model often cannot fully describe its complex vibration behavior, and the error feedback mechanism plays a key role, being able to timely capture the deviation between the prediction and the actual situation and gradually eliminate this deviation through parameter correction to ensure that the system is always in the optimal state. The multi-chip module not only realizes efficient data acquisition and transmission in this process, but also ensures the real-time nature of the error feedback and model correction process through its parallel computing ability, making the corrected displacement field It can be updated in an extremely short time, thus providing accurate state information for subsequent modal decomposition and active vibration suppression. It can be seen that this adaptive correction method fully considers the complexity of the drill string vibration system in the actual downhole environment. By adjusting parameters such as damping, stiffness, and external excitation in real time, the entire vibration model is highly flexible and robust, 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 , which not only provides a reliable basis for further modal decomposition and active vibration suppression, but also realizes a high-precision match between the model and the actual vibration state, thus effectively reducing the risks of mechanical wear and structural fatigue caused by vibration, and improving the safety and efficiency of downhole drill string operations.

[0082] Example 7: In the data analysis part, the corrected displacement field is decomposed into modes in space, and the formula is as follows:

[0083] ;

[0084] where is the total number of modes; the modes at least include: axial vibration, bending vibration, and torsional vibration; is the mode factor, which is a preset positive integer or negative integer value. For different types of modes, depending on their weights, the values are different and satisfy ; is the th orthogonal mode function.

[0085] Specifically, in practical applications, the types of modes at least cover three forms: axial vibration, bending vibration, and torsional vibration. Each vibration mode corresponds to a unique response that the drill pipe may exhibit during operation. To facilitate distinguishing the contributions of different modes to the overall vibration response, the system pre-sets a set of mode factors , which can be positive integers or negative integers. Their values are determined according to the weights of each vibration mode in the overall response and are required to satisfy the normalization condition, that is, the sum of all mode factors is equal to 1. This ensures that each decomposed mode can completely describe the original displacement field in terms of mathematical and physical meanings. The mode function describes the Functions of the spatial distribution of vibration modes, which usually have orthogonality properties, that is, different modes are independent of each other within the domain of definition. Such orthogonality not only simplifies mathematical calculations but also ensures the physical separation between each mode. Through modal decomposition, the overall vibration response can be understood as the superposition of independent vibration modes. This method can effectively identify and separate various vibration phenomena of the drill pipe caused by structural, working condition changes, and external disturbances in complex working environments, enabling the system to suppress and control different vibration modes specifically.

[0086] In actual operation, the displacement field after adaptive correction has already reflected the vibration response of the drill pipe during downhole operations relatively accurately. However, since the vibration response is often generated by the combined action of multiple factors, there are certain difficulties in directly using 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 represents the proportion of this vibration form in the overall response. For example, the axial vibration mode usually reflects the stretching and compression of the drill pipe along its length direction, while the bending vibration mode reflects the lateral displacement changes caused by bending, and the torsional vibration mode corresponds to the rotational movement of the drill pipe around its axis. Under the combined action of multiple vibration modes, the overall vibration response of the drill pipe exhibits complex spatio-temporal variation characteristics. Modal decomposition effectively disassembles this complexity, enabling each mode to be analyzed and processed independently, providing a clear control target for subsequent active vibration suppression.

[0087] From a mathematical perspective, modal decomposition requires solving a set of orthogonal modal functions , which are usually obtained by solving the eigenvalue problem of the one-dimensional rod vibration model. Essentially, after assuming that the drill pipe satisfies certain boundary conditions during vibration, the vibration problem can be transformed into an eigenvalue problem regarding the spatial variable, and each eigenfunction and the corresponding eigenvalue are solved. Each eigenfunction corresponds to a vibration mode, and the eigenvalue reflects the natural frequency information of that mode. In actual engineering, this decomposition not only simplifies the vibration analysis problem but also enables each vibration mode to be regulated independently, so that different control resources and control methods can be allocated according to the vibration characteristics of different modes when implementing the active control strategy. By presetting each modal factor and ensuring that its normalization condition is satisfied, the reproduction of the entire vibration response can be achieved through the superposition of each mode. This method not only takes into account the accurate decomposition in mathematics but also reflects the detailed distinction of different vibration forms in physics.

[0088] In the downhole drill string vibration monitoring and suppression system, the practical application of modal decomposition lies not only in the decomposition of vibration responses, but more importantly, in providing key input data for the active vibration suppression strategy. By converting the actually measured vibration signals into individual modal components, the system can design corresponding suppression control forces according to the characteristics of each mode, thereby specifically weakening or eliminating the vibrations caused by specific modes. Since multiple vibration forms may occur simultaneously during the operation of the drill pipe, and there may be different attenuation laws and propagation speeds between different vibration forms, designing control strategies separately for each mode can not only improve the control accuracy, but also reduce the waste of control energy. Based on modal decomposition, the system can utilize the high-speed parallel processing ability of multi-chip components to perform real-time calculations and generate control signals for each mode, ensuring that it can quickly respond and adjust the corresponding control parameters when the vibration changes, thereby achieving comprehensive suppression of drill pipe vibration.

[0089] 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 vibration signals may also change significantly, while the pre-set modal factors and orthogonal modal functions As the basis for describing vibrations, their 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 a solid theoretical support for dynamic adjustment and adaptive control. During the entire modal decomposition process, the data analysis part not only relies on accurate displacement measurements and the displacement field after adaptive correction, but also makes full use of the local vibration characteristics extracted from the previous time-frequency analysis. These information enables modal decomposition to more accurately capture the spatio-temporal characteristics and dynamic change laws of each vibration mode. Through this method, the system can effectively identify vibration anomalies caused by different vibration modes when monitoring drill pipe vibration, and then specifically apply control forces during the active control stage, thereby reducing the overall vibration energy and preventing local vibrations from being too intense, which may cause equipment damage or safety accidents.

[0090] Example 8: Determined by the following eigenvalue problem:

[0091] ;

[0092] where is the eigenvalue of the th mode; is the damping ratio of the th mode.

[0093] Specifically, this eigenvalue problem not only reflects the balance relationship between stiffness and mass distribution in traditional beam vibration theory, but also describes the energy dissipation effect of the system by introducing the damping ratio so as to be closer to the dynamic characteristics exhibited during actual downhole drill string vibration. The first term on the left side of the equation represents the restoring force or stiffness effect determined by the elastic and geometric properties of the drill pipe, where is the elastic modulus, reflecting the ability of the material to return to its original state after being stressed, and is the cross-sectional area of the drill pipe, and they jointly describe the flexural stiffness of the drill pipe. The damping term that follows then introduces the influence of energy dissipation during vibration; here is the damping ratio of the th mode, and the appearance of reflects the influence of the natural frequency (or fundamental frequency) of this mode, and characterizes the mass distribution per unit length. The existence of the damping term means that during actual vibration, there is not only the vibration response generated by the elastic restoring force, but also an energy loss effect, and this energy loss will cause the vibration to gradually decay, thus having a corrective effect on the eigenvalue problem mathematically. The term on the right side of the equation corresponds to the inertial effect, and its physical meaning is to relate the inertia of the system to the modal response, can be regarded as the eigenvalue related to this mode, and is usually proportional to the square of the natural frequency of the mode. In the ideal case of no damping, this eigenvalue problem simplifies to the classical beam vibration equation, but in this embodiment, by introducing the damping ratio and the correction term related to the eigenvalue, the system can more realistically reflect the energy dissipation and frequency drift phenomena experienced by the drill pipe in the actual working environment.

[0094] Overall, this eigenvalue problem describes the vibration behavior of the drill pipe under the action of 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, and they satisfy the orthogonality and normalization conditions mathematically and can be used to expand any displacement field that satisfies the boundary conditions into modal components. Specifically, each corresponds to a certain vibration mode of the drill pipe, such as axial vibration, bending vibration or torsional vibration, and the eigenvalue It 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 fixed end, free end or other combined boundaries) will directly affect the solution results of the eigenfunctions and eigenvalues. Therefore, when solving this eigenvalue problem, it is usually necessary to set the corresponding boundary conditions according to the actual physical constraints of the drill string. Introducing the damping ratio 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 mode decomposition. The damping ratio reflects the degree of energy dissipation in this mode. A high damping ratio means that the vibration energy decays faster, so that the proportion of this mode in the overall vibration response is lower; on the contrary, the mode with a low damping ratio often plays a dominant role in the vibration system. By introducing into the damping term, the equation not only considers the influence of material and geometric parameters on the vibration restoring force, but also synthesizes the information of the vibration frequency. This enables obtaining the shape function corresponding to the natural vibration mode when solving the mode, and reflecting the dynamic characteristics of energy dissipation in the actual vibration process. 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 drill string vibration monitoring and suppression system based on multi-chip components, these orthogonal modes are not only used to decompose the complex displacement field into individual vibration modes, but also enable subsequent active control strategies to apply inhibitory forces to each mode specifically, thereby effectively reducing the overall vibration level of the drill pipe. Through this method, the system can more accurately identify which vibration modes are the main sources of problems and preferentially suppress these modes during the control process, thus achieving more efficient vibration suppression.

[0095] Example 9: The process of designing an active control strategy according to the results of mode decomposition includes: assuming that the magnitude of the initial inhibitory force in the th mode is ; then, according to the eigenvalue of the th mode, the initial inhibitory force is corrected through the following formula to obtain the corrected inhibitory force:

[0096] ;

[0097] where is the corrected inhibitory force.

[0098] Specifically, in this embodiment, the system uses the vibration mode characteristic parameters obtained by modal decomposition and combines an 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 on the vibration of each mode. Specifically, in the th mode, the system pre-sets an initial inhibitory force , and the magnitude of this force can be determined by engineering experience or previous experimental data, representing the control force required to achieve a certain suppression effect in this mode. However, since each vibration mode has different inherent characteristics, its corresponding modal eigenvalue can reflect the dynamic characteristics and energy characteristics of this mode, is usually proportional to the square of the natural frequency of the mode, and to a certain extent reveals the energy proportion of this mode in the vibration system. Therefore, in order to make the control system more accurately match the actual vibration state, the system corrects the initial inhibitory force according to the eigenvalue of the th mode to obtain the corrected inhibitory force. By multiplying the initial inhibitory force by the modal eigenvalue , the control force can be dynamically adjusted, so that when the modal energy is high and the vibration response is strong, the corrected control force will be correspondingly amplified, so as to more effectively cancel or weaken the vibration in this mode. In the mode with lower energy, since the eigenvalue is small, the corrected inhibitory force will also be weakened, which avoids unnecessary energy waste and over-control, and ensures the overall balance and robustness of the system. Different control intensities are adopted for different vibration modes to achieve the purpose of refined control. From a physical perspective, the modal eigenvalue is not only a mathematical parameter, but more represents the inherent natural frequency and energy distribution of the vibration system in this mode. Generally speaking, in a vibration system, the mode with a higher natural frequency usually corresponds to a smaller deformation range, while the low-frequency mode may bring a larger amplitude; at the same time, the high-energy mode often occupies a larger proportion in the overall vibration energy and has a more significant impact on the system stability. Therefore, by multiplying by the initial inhibitory force, the system actually realizes an adaptive control method, which enables the inhibitory force to be adjusted according to the characteristics of the signal itself, meeting the requirement of large energy modes for larger control inputs and avoiding the phenomenon of secondary vibration or over-control that may be caused by excessive intervention on low-energy modes. In practical applications, the drill string 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 modal functions and their corresponding eigenvalues of each vibration mode through multi-level data processing and modal decomposition; These data reflect the dynamic responses of the drill pipe under various vibration forms such as axial, bending, and torsional vibrations. For each mode, the system, according to the preset initial inhibitory force designed an active controller, and through the control algorithm, applied the corrected inhibitory force to the corresponding actuators, such as piezoelectric actuators or servo motors, etc., to generate a force opposite to the vibration, thereby weakening or even eliminating the vibration in this mode. It should be noted that the corrected inhibitory force plays a crucial role in the entire active control process. It can not only compensate for the vibration deviation caused by the drill pipe structure and operating environment, but also respond to the change of vibration energy in real time to achieve closed-loop control. The control system continuously detects the current vibration state, and by comparing the actual vibration response and the predicted value of the theoretical model, continuously corrects and updates the value, so that the active control strategy can continuously optimize the control effect during the entire drilling operation process.

[0099] In this process, the high-efficiency computing and real-time processing capabilities of the multi-chip module play a key role. The system uses high-speed data transmission and parallel computing technologies, and can complete steps such as modal decomposition, eigenvalue extraction, and inhibitory force correction in a very short time, ensuring that a response can be made instantly when the drill string vibration occurs and quickly feedback the control signal to the actuator. This real-time nature ensures that under the complex and changeable downhole working conditions, the active control strategy can always maintain a high precision and response speed, thus effectively preventing equipment fatigue or damage caused by vibration. Theoretically, the correction formula embodies an adaptive feedback control mechanism based on physical characteristics. Since itself is closely related to the dynamic characteristics of the vibration system, this correction method has high adaptability and robustness, and can still maintain a stable control effect when the system parameters change or the external environment interference is large. On the other hand, this method also simplifies the implementation process of the active control strategy, because by organically combining modal decomposition and control force correction, the system can uniformly handle the vibration suppression problems of different modes in the same framework, thereby improving the overall coordination and control efficiency of the system. During the operation of the system, as the operating conditions of the drill string and the downhole environment change, the vibration characteristics may also be adjusted accordingly. At this time, the modal eigenvalues will also change accordingly. The control system can continuously adjust the magnitude of the inhibitory force by continuously updating the modal decomposition results, so that the active control strategy always matches the current vibration state, thereby achieving the best vibration suppression effect. It is precisely this method of correcting the inhibitory force based on modal eigenvalues that enables the entire downhole drill string vibration monitoring and suppression system based on multi-chip modules to still achieve efficient and precise vibration control in a complex environment, greatly reducing the negative impact of vibration on the drill string structure and operation safety.

[0100] Although the specific embodiments of the present invention have been described above, those skilled in the art should understand that these specific embodiments are merely illustrative. Without departing from the principles and essence of the present invention, those skilled in the art can make various omissions, substitutions, and changes to the details of the above methods and systems. For example, combining the above method steps so as to perform substantially the same function in a substantially the same manner to achieve substantially the same result falls within the scope of the present invention. Therefore, the scope of the present invention is only defined 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, and 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; 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.

2. The downhole drilling tool vibration monitoring and suppression system based on a multi-chip module according to claim 1, 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 .

3. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to 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 .

4. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 3, 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.

5. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 4 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 bar vibration model, the corrected displacement field is obtained .

6. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 5, 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.

7. The downhole drilling tool vibration monitoring and suppression system based on a 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.

8. The downhole drilling tool vibration monitoring and suppression system based on multi-chip module according to claim 7, 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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