Vibration control method and system for drilling equipment

Abstract

The invention relates to the technical field of equipment control, in particular to a vibration control method and system for drilling equipment. The method comprises the following steps that vibration information collected by a vibration sensor on drilling equipment and drill bit damage state information of the drilling equipment in the cutting process are obtained; confirming a vibration characteristic fingerprint mode based on the vibration information and the drill bit damage state information; based on the vibration characteristic fingerprint mode and a preset vibration suppression library, obtaining a vibration suppression mode corresponding to the vibration characteristic fingerprint mode; and based on the vibration suppression mode, driving control is conducted on an active vibration reduction actuator, so that vibration control is conducted on the drilling equipment. The vibration control method aims at solving the problem that when an existing vibration control method for the drilling equipment is under the non-standard operation condition or is used for treating heterogeneous composite materials, complex vibration modes are difficult to effectively deal with, and consequently the drilling equipment cannot be effectively controlled.

Description

Technical Field

[0001] This invention relates to the field of equipment control technology, and specifically to a vibration control method and system for drilling equipment. Background Technology

[0002] Drilling equipment is typically equipped with a vibration control system to ensure drilling efficiency and equipment lifespan. Existing vibration control systems mainly monitor equipment vibration and adjust operating parameters according to preset rules to maintain vibration within a certain range. For example, when drilling equipment faces non-standard operating conditions or needs to handle heterogeneous composite materials, the drill bit's cutting edge will be subjected to severe periodic impact loads when frequently cutting into high-hardness steel bars; this can lead to damage to the drill bit's cutting edge, resulting in complex vibration modes with strong impact characteristics.

[0003] However, complex vibration modes may not only exceed the measurement range of conventional vibration sensors, leading to data distortion, but also make it difficult for existing vibration control methods to correctly identify and analyze impact vibrations caused by drill bit chipping. They may mistakenly identify high-intensity, short-duration impact events as routine frictional vibrations, or filter out key high-frequency information indicating impact occurrence as noise during digital filtering. This prevents existing control methods from generating targeted and effective suppression commands, thus failing to provide effective suppression measures. Consequently, the control strategy of the drilling equipment becomes ineffective, the performance of critical connecting components deteriorates, and even serious mechanical failures occur, affecting operational safety and quality. Summary of the Invention

[0004] The purpose of this invention is to provide a vibration control method and system for drilling equipment, which solves the problem that existing vibration control methods for drilling equipment are unable to effectively cope with complex vibration modes under non-standard operating conditions or when dealing with heterogeneous composite materials, resulting in the inability to effectively control the drilling equipment.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a vibration control method for drilling equipment, comprising the following steps:

[0006] Acquire vibration information collected by vibration sensors on the drilling equipment and information on the damage status of the drill bit during the cutting process;

[0007] Based on the vibration information and the drill bit damage status information, the vibration characteristic fingerprint pattern is confirmed.

[0008] Based on the vibration feature fingerprint pattern and the preset vibration suppression library, a vibration suppression pattern corresponding to the vibration feature fingerprint pattern is obtained;

[0009] Based on the vibration suppression mode, the active vibration damping actuator is driven and controlled to control the vibration of the drilling equipment.

[0010] Preferably, the step of confirming the vibration feature fingerprint pattern based on the vibration information and the drill bit damage status information includes:

[0011] After confirming the high-frequency components of the vibration information, the instantaneous envelope of the high-frequency components of the vibration information is analyzed to obtain the instantaneous kurtosis and instantaneous skewness of the envelope.

[0012] Based on the drill bit damage status information, the average rate of change of the cutting torque of the drilling equipment and the average rate of change of the acoustic emission event are confirmed.

[0013] Based on the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy, the vibration characteristic fingerprint pattern is confirmed.

[0014] Preferably, the step of confirming the vibration characteristic fingerprint pattern based on the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy includes:

[0015] The instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate were verified by data to obtain the verified instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate.

[0016] Based on the verified instantaneous kurtosis, instantaneous skewness, average change rate of cutting torque, and average change rate of energy, a preset fingerprint pattern model is used for identification to confirm the vibration characteristic fingerprint pattern.

[0017] Preferably, after the step of driving and controlling the active vibration damping actuator based on the vibration suppression mode to control the vibration of the drilling equipment, the method further includes:

[0018] Monitor the control signal of the active vibration damping actuator after responding to the drive control;

[0019] Based on the control signal, vibration level parameters including vibration amplitude, frequency components, and impact events are confirmed.

[0020] The vibration level parameters are compared with the vibration level threshold to obtain the vibration comparison results;

[0021] Based on the vibration comparison results and the preset feedback information model, the vibration feedback information is determined;

[0022] The vibration feedback information is used to further control and adjust the active vibration damping actuator.

[0023] Preferably, the step of confirming the vibration level parameters, including vibration amplitude, frequency components, and impact event, based on the control signal includes:

[0024] Based on the control signal, the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate are confirmed.

[0025] By using the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate, a parameter evaluation model is obtained by model matching from the preset evaluation model.

[0026] Based on the energy consumption parameters and drill bit wear rate, a parameter evaluation model is used to evaluate the parameters and obtain vibration level parameters including vibration amplitude, frequency components, and impact events.

[0027] Preferably, the step of confirming the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate based on the control signal includes:

[0028] Based on the control signals, confirm the drilling environment parameters and the operating status of the drilling equipment;

[0029] Data analysis was performed on the drilling environment parameters and the operating status of the drilling equipment to confirm the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate.

[0030] Preferably, the step of confirming the drilling environment parameters and the operating status of the drilling equipment based on the control signal includes:

[0031] Based on the control signal, the initial parameters of the drilling environment and the initial operating state of the drilling equipment are obtained.

[0032] The initial parameters of the drilling environment and the initial operating state of the drilling equipment are denoised to obtain the denoised initial parameters of the drilling environment and the denoised initial operating state of the drilling equipment.

[0033] The initial parameters of the denoised drilling environment and the initial operating state of the denoised drilling equipment are verified by data validation to confirm the drilling environment parameters and the operating state of the drilling equipment.

[0034] Preferably, the step of acquiring vibration information collected by vibration sensors on the drilling equipment includes:

[0035] Obtain raw vibration data collected by vibration sensors on the drilling equipment;

[0036] Based on the original vibration data, vibration information including the instantaneous rise slope and high-frequency components is determined.

[0037] The vibration information is obtained by preprocessing the vibration information, which includes the instantaneous rise slope and high-frequency components.

[0038] Preferably, the step of obtaining a vibration suppression mode corresponding to the vibration feature fingerprint pattern based on the vibration feature fingerprint pattern and a preset vibration suppression library includes:

[0039] The vibration feature fingerprint pattern is matched using a preset vibration suppression library to obtain multiple candidate vibration suppression patterns after matching.

[0040] Based on the vibration feature fingerprint pattern, a pattern judgment analysis is performed on multiple candidate vibration suppression patterns to obtain the vibration suppression pattern corresponding to the vibration feature fingerprint pattern.

[0041] The present invention also provides a vibration control system for drilling equipment, the system comprising:

[0042] The information acquisition module is used to acquire vibration information collected by vibration sensors on the drilling equipment and information on the damage status of the drill bit during the cutting process.

[0043] The first confirmation module is used to confirm the vibration feature fingerprint pattern based on the vibration information and the drill bit damage status information.

[0044] The second confirmation module is used to obtain the vibration suppression mode corresponding to the vibration feature fingerprint mode based on the vibration feature fingerprint mode and the preset vibration suppression library;

[0045] The drive control module is used to drive and control the active vibration damping actuator based on the vibration suppression mode, so as to control the vibration of the drilling equipment.

[0046] Compared with the prior art, the drilling equipment vibration control method and system of the present invention have the following advantages:

[0047] This invention acquires vibration information from vibration sensors on the drilling equipment and drill bit damage information during the cutting process, and identifies vibration characteristic fingerprint patterns. Subsequently, based on the vibration characteristic fingerprint patterns and a preset vibration suppression library, a vibration suppression mode corresponding to the vibration characteristic fingerprint patterns is obtained. The active vibration damping actuator is then driven and controlled based on the vibration suppression mode to control the vibration of the drilling equipment. By introducing vibration characteristic fingerprint patterns, this invention can more accurately identify and classify complex vibration phenomena. Combined with drill bit damage information, this makes the vibration suppression strategy more targeted. This significantly improves the accuracy and adaptability of vibration control, enabling effective control of the drilling equipment. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0049] Figure 1 This is a flowchart of a vibration control method for drilling equipment according to the present invention.

[0050] Figure 2 This is a structural block diagram of a vibration control system for drilling equipment according to the present invention.

[0051] In the diagram: 210, Information Acquisition Module; 220, First Confirmation Module; 230, Second Confirmation Module; 240, Drive Control Module.

[0052] The implementation and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] The following drawings disclose several embodiments of the present invention. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0054] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0055] Furthermore, in this invention, the use of terms such as "first" and "second" is for descriptive purposes only and does not specifically refer to any order or sequence, nor is it intended to limit the invention. They are merely used to distinguish components or operations described using the same technical terms, and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed by this invention.

[0056] Existing vibration control systems primarily monitor equipment vibration and adjust operating parameters according to preset rules to maintain vibration within a normal range. However, when drilling equipment faces non-standard operating conditions or needs to handle heterogeneous composite materials, unexpected damage to the drill bit cutting edge can occur, leading to complex vibration modes with strong impact characteristics. These complex vibration modes may not only exceed the measurement range of conventional vibration sensors, causing data distortion, but also make it difficult for existing control systems to accurately determine the source and nature of the vibration. Existing vibration control methods are ineffective in controlling these vibrations and thus cannot provide effective suppression measures. This can lead to fatigue and performance degradation of critical connecting components, even causing serious mechanical failures, affecting operational safety and quality.

[0057] To further understand the content, features, and effects of this invention, the following embodiments are provided, and detailed descriptions are given below in conjunction with the accompanying drawings:

[0058] Please see Figure 1 This invention provides a vibration control method for drilling equipment, comprising the following steps:

[0059] S100. Acquire vibration information collected by vibration sensors on the drilling equipment and drill bit damage status information during the cutting process. Vibration information refers to raw or pre-processed data on the vibration state of the drilling equipment acquired by vibration sensors. This data may include parameters such as frequency, amplitude, and phase, used to characterize the dynamic response of the equipment. Drill bit damage status information reflects damage conditions such as wear, chipping, and breakage of the drill bit during the cutting process. Vibration information can be acquired in various ways in this step. For example, an accelerometer can be used to directly measure the vibration acceleration at different locations on the drilling equipment, and then the analog signal can be converted into a digital signal for storage and processing. Another method is to use a laser Doppler vibrometer to measure the vibration velocity on the equipment surface non-contactly, thereby obtaining high-precision vibration data. Additionally, strain gauge sensors can be used to indirectly reflect the vibration situation by measuring the strain changes of the equipment's structural components. One way to acquire drill bit damage status information is to use a force sensor installed on the drilling equipment to monitor changes in cutting torque in real time. When the drill bit is damaged, the cutting torque usually exhibits abnormal fluctuations. Another approach is to utilize acoustic emission sensors. By capturing acoustic emission signals generated during drill bit cutting, the characteristics of these signals (such as event rate and energy) can reflect the degree of damage to the drill bit. Vision sensors, such as high-speed cameras, can also be used to acquire real-time images of the drill bit and analyze the wear of the drill bit's cutting edge using image processing techniques.

[0060] S200. Based on the vibration information and the drill bit damage state information, confirm the vibration characteristic fingerprint pattern. The vibration characteristic fingerprint pattern is a unique identifier formed after comprehensive analysis of the vibration information and drill bit damage state information. It accurately describes the type and severity of the current vibration state and is unique and identifiable. Specifically, after acquiring the vibration information and drill bit damage state information, these data need to be analyzed in depth to confirm the vibration characteristic fingerprint pattern. By performing time-domain and frequency-domain analysis on the collected vibration information, parameters such as vibration amplitude, dominant frequency, harmonic components, and envelope characteristics are extracted. Simultaneously, the drill bit damage state information is processed, for example, by calculating the root mean square value of the cutting torque, the peak factor, or the average energy of the acoustic emission signal. Then, the extracted feature parameters are input into a pre-trained pattern recognition model, such as a support vector machine (SVM) or a neural network model. The model can then identify the corresponding vibration characteristic fingerprint pattern based on these feature parameters. Furthermore, signal processing techniques such as wavelet transform or empirical mode decomposition (EMD) can be used to extract energy distribution characteristics of different frequency bands from vibration information. Combined with the abnormal event count or damage index in drill bit damage information, the vibration characteristic fingerprint pattern can be comprehensively judged and confirmed through a fuzzy logic reasoning system.

[0061] S300. Based on the vibration characteristic fingerprint pattern and the preset vibration suppression library, a vibration suppression mode corresponding to the vibration characteristic fingerprint pattern is obtained. The preset vibration suppression library is a database storing various vibration suppression strategies, each corresponding to a specific vibration characteristic fingerprint pattern, aiming to provide the optimal vibration reduction solution. The vibration suppression mode selects the specific suppression strategy from the preset vibration suppression library that best matches the current vibration characteristic fingerprint pattern, guiding the driving mode of the active vibration damping actuator. Specifically, the preset vibration suppression library can be a database storing the mapping relationship between various vibration characteristic fingerprint patterns and their corresponding vibration suppression strategies. When the current vibration characteristic fingerprint pattern is identified, a search is directly performed in the database to match a predefined vibration suppression mode. For example, if the identified vibration characteristic fingerprint pattern is a high-frequency impact vibration pattern caused by drill bit chipping, the corresponding suppression mode might be adjusting the spindle speed and applying a reverse excitation at a specific frequency. Simultaneously, the preset vibration suppression library can contain a series of parameterized control algorithms, each targeting a specific type of vibration characteristic fingerprint pattern. After confirming the vibration characteristic fingerprint pattern, the corresponding control algorithm parameters are selected and configured according to the characteristics of the pattern, thereby generating a customized vibration suppression mode. For example, for low-frequency vibration modes caused by resonance, the suppression library may provide an adaptive notch filter algorithm and dynamically adjust the filter parameters according to the resonance frequency.

[0062] S400. Based on the vibration suppression mode, drive control is applied to the active vibration damping actuator to control the vibration of the drilling equipment. The active vibration damping actuator is a device capable of generating a reaction force or reverse vibration according to a control signal, thereby canceling or reducing equipment vibration, such as a piezoelectric actuator, electromagnetic actuator, or hydraulic actuator. Specifically, after obtaining the vibration suppression mode, it needs to be converted into a specific drive signal to control the active vibration damping actuator. The vibration suppression mode may include parameters such as the actuator's target output force, frequency, and phase. A corresponding voltage or current signal is then generated to drive the piezoelectric actuator to produce a force opposite in direction and phase to the equipment vibration, thereby canceling the vibration. For example, if the suppression mode indicates the need to generate a reverse force of a specific frequency and amplitude, the controller calculates the voltage waveform required to drive the piezoelectric actuator and applies it to the actuator. Alternatively, the vibration suppression mode can be a control law, such as PID control parameters or fuzzy control rules. Based on this control law, combined with the real-time monitored vibration feedback signal, the output of the active vibration damping actuator is dynamically adjusted to achieve real-time suppression of the drilling equipment vibration. For example, if the suppression mode is an adaptive control algorithm, it continuously optimizes the actuator's drive strategy based on the current vibration level and drill bit damage state to achieve the best vibration reduction effect.

[0063] The vibration control method for drilling equipment proposed in this application integrates vibration information with drill bit damage status information to construct a more refined vibration feature fingerprint pattern recognition mechanism. By acquiring vibration information collected by vibration sensors on the drilling equipment and drill bit damage status information during the cutting process, this invention can comprehensively capture the dynamic response of the equipment and the health status of the drill bit. This allows for the identification of unique vibration feature fingerprint patterns, which not only reflect the physical characteristics of the vibration but also incorporate deeper information about the damage state, thus achieving accurate judgment of the vibration source and its nature. After identifying the vibration feature fingerprint pattern, this invention further obtains a vibration suppression mode corresponding to the vibration feature fingerprint pattern based on this pattern and a preset vibration suppression library. The preset vibration suppression library stores optimized suppression strategies for different vibration feature fingerprint patterns, enabling the selection of the most suitable solution based on the specific vibration problem currently identified. For example, for high-frequency vibration caused by slight drill bit wear, a suppression mode that finely adjusts the spindle speed and applies a small reverse excitation might be selected; while for strong impact vibration caused by drill bit chipping, a more powerful suppression mode with rapid response characteristics may be needed. This significantly improves the accuracy and effectiveness of vibration control. Finally, based on the obtained vibration suppression mode, the active vibration damping actuator is driven and controlled to control the vibration of the drilling equipment. Upon receiving precise drive commands, the active vibration damping actuator generates a reaction force that counteracts the equipment vibration, effectively reducing the vibration amplitude and suppressing vibration propagation. Furthermore, this invention significantly improves the accuracy of vibration identification by introducing drill bit damage state information and combining it with vibration information to construct a vibration characteristic fingerprint pattern. This refined identification capability can distinguish vibrations caused by normal cutting, minor wear, or severe damage, allowing the selection of the most appropriate suppression mode from a preset vibration suppression library. For example, when initial wear occurs in the drill bit, a specific vibration fingerprint can be identified, and a mild suppression mode can be selected to extend the drill bit's life; conversely, when severe chipping is detected, a strong suppression mode is immediately activated to prevent further damage to the equipment. This significantly improves the operational stability, processing accuracy, and service life of the drilling equipment, and enhances the precision of vibration control.

[0064] In some embodiments of this application described above, the step of confirming the vibration characteristic fingerprint pattern based on the vibration information and the drill bit damage state information includes:

[0065] After confirming the high-frequency components of the vibration information, a feature analysis of the instantaneous envelope of the high-frequency components is performed to obtain the instantaneous kurtosis and instantaneous skewness of the envelope. Specifically, after acquiring the vibration information collected by the vibration sensor on the drilling equipment, it is first necessary to confirm the high-frequency components of the vibration information. High-frequency components typically contain rich information related to minor impacts, friction, and early damage during the drill bit cutting process. Subsequently, a feature analysis of the instantaneous envelope of the high-frequency components of the vibration information is performed. Instantaneous envelope analysis is a commonly used signal processing technique that can effectively extract the amplitude modulation information of the signal and reveal the impact characteristics hidden in the carrier signal. By performing feature analysis on the envelope, the instantaneous kurtosis and instantaneous skewness of the envelope can be obtained. Instantaneous kurtosis is a statistical measure of the sharpness of the signal waveform; a high instantaneous kurtosis value usually indicates the presence of impact vibration. Instantaneous skewness reflects the symmetry of the signal waveform; its variation can indicate the asymmetric development of wear or damage.

[0066] Based on the drill bit damage status information, the average rate of change of the cutting torque and the average rate of change of the acoustic emission events of the drilling equipment are confirmed. The drill bit damage status information can be obtained from various monitoring methods, such as monitoring the cutting torque through a force sensor and monitoring acoustic emission events through an acoustic emission sensor. The average rate of change of the cutting torque reflects the load change trend experienced by the drill bit during cutting; drill bit wear or damage can lead to abnormal fluctuations or a continuous increase in the cutting torque. The average rate of change of the acoustic emission events can capture the transient elastic wave energy generated by phenomena such as microscopic fracture and friction in the material; energy change is a sensitive indicator of early drill bit damage.

[0067] Based on the instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate, a vibration characteristic fingerprint pattern is identified. Specifically, the instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate characterize the vibration state of the drilling equipment and the degree of drill bit damage from different dimensions, collectively forming a unique vibration characteristic fingerprint pattern.

[0068] This embodiment, through high-frequency component extraction and instantaneous envelope feature analysis of vibration information, can sensitively capture minute impacts and frictional vibrations caused by drill bit wear and chipping during drilling. These impact characteristics are quantified using instantaneous kurtosis and instantaneous skewness. Simultaneously, by combining drill bit damage status information and monitoring the average rate of change of cutting torque and the average energy rate of change of acoustic emission events, it can more comprehensively and accurately reflect the actual working state and damage degree of the drill bit from both macroscopic load and microscopic damage mechanism perspectives. This allows the identified vibration characteristic fingerprint pattern to more finely distinguish different types of vibration sources and damage states, providing a more precise basis for subsequent vibration suppression. This not only improves the sensitivity of identifying early faults in drilling equipment and drill bit damage but also more accurately characterizes vibration characteristics under different operating conditions, thus providing more reliable and accurate input for subsequent active vibration damping actuator drive control, significantly improving the accuracy and effectiveness of drilling equipment vibration control.

[0069] In some embodiments of this application described above, the step of confirming the vibration characteristic fingerprint pattern based on the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy includes:

[0070] The instantaneous kurtosis, instantaneous skewness, average cutting torque rate of change, and average energy rate of change are each validated using data to obtain validated instantaneous kurtosis, instantaneous skewness, average cutting torque rate of change, and average energy rate of change. Specifically, data validation refers to quality checks and screening of the originally collected or calculated instantaneous kurtosis, instantaneous skewness, average cutting torque rate of change, and average energy rate of change. Its purpose is to eliminate abnormal data, noise interference, or data points that do not meet preset conditions, ensuring that the parameters used for pattern recognition have high reliability and accuracy. For example, statistical methods (such as Z-score or IQR) or machine learning-based anomaly detection algorithms can be used to validate the data. Through data validation, pattern misjudgment caused by data quality issues can be effectively avoided.

[0071] Based on the verified instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy, a preset fingerprint pattern model is used for identification to confirm the vibration characteristic fingerprint pattern. The preset fingerprint pattern model can be understood as a trained and optimized pattern recognition algorithm or model that internally stores typical features or discrimination rules for different vibration characteristic fingerprint patterns. It can match and classify known vibration patterns based on the combined features of input parameters. Specifically, the model can be a support vector machine (SVM), neural network, decision tree, or rule-based expert system, etc. Its purpose is to provide an intelligent recognition mechanism capable of accurately identifying the current vibration characteristic fingerprint pattern from complex parameter combinations.

[0072] Specifically, during drilling, vibration sensors collect vibration information and, combined with drill bit damage status information, obtain instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate. First, data validation is performed. For example, a threshold range can be set; if the instantaneous kurtosis value exceeds the normal range (e.g., deviating from the mean by more than three standard deviations), it is marked as an outlier and discarded or corrected. Similarly, outlier detection and processing are performed on the instantaneous skewness, average cutting torque change rate, and average energy change rate to ensure the validity of all parameters. Second, the validated instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate are used as inputs to a preset fingerprint pattern model. The model may be based on a deep learning neural network, which has learned a large number of parameter combinations corresponding to different vibration modes (such as normal cutting, tool wear, and poor chip breaking) during the training phase. When a validated parameter input is received, the neural network classifies the learned modes and outputs the vibration characteristic fingerprint pattern of the current drilling equipment, such as a slight wear mode or an intermittent cutting mode. Even if the original data has a certain degree of fluctuation or anomaly, after data verification and model identification, it is still possible to accurately identify the current vibration characteristic fingerprint pattern, providing precise guidance for subsequent vibration suppression strategies.

[0073] This application's solution introduces a data verification step. First, it preprocesses the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy, effectively filtering out noise and outliers in the data, thus ensuring the purity and reliability of the data used for subsequent pattern recognition. Because of this rigorous verification, the pre-defined fingerprint pattern model can make judgments based on high-quality data when identifying vibration feature fingerprint patterns, avoiding recognition biases caused by data quality issues. Based on this, the pre-defined fingerprint pattern model is used to identify verified parameters. The model can accurately map the current vibration state of the drilling equipment to specific vibration feature fingerprint patterns according to its internally established complex mapping relationships, thereby achieving accurate diagnosis of the drilling equipment's vibration state.

[0074] In some embodiments of this application described above, after the step of driving and controlling the active vibration damping actuator based on the vibration suppression mode to control the vibration of the drilling equipment, the method further includes:

[0075] The control signals of the active vibration damping actuator are monitored after responding to the drive control. Specifically, after the active vibration damping actuator completes the initial drive control, its control signals need to be monitored in real time. The control signals can be understood as various electrical, mechanical, or performance parameter signals generated by the active vibration damping actuator when performing vibration suppression tasks, such as the actuator's current, voltage, displacement, and force output, to obtain a direct reflection of the actuator's actual working state.

[0076] Based on the control signals, vibration level parameters, including vibration amplitude, frequency components, and impact events, are identified. These vibration level parameters provide a comprehensive quantitative description of the current vibration state of the drilling equipment. Vibration amplitude reflects the intensity of the vibration, frequency components reveal the main frequency characteristics of the vibration, and impact events indicate potential transient impacts or abnormal vibrations. This allows for a comprehensive assessment of the current vibration suppression effect.

[0077] The vibration level parameters are compared with the vibration level threshold to obtain the vibration comparison result. The vibration level threshold is an acceptable upper limit for vibration levels set based on drilling process requirements, equipment safety standards, or empirical data. By comparing the results, it can be determined whether the current vibration level is within a controllable range or whether there are any abnormalities requiring further adjustment.

[0078] Based on the vibration comparison results and the preset feedback information model, vibration feedback information is determined. The preset feedback information model is a pre-established decision model whose purpose is to generate specific adjustment instructions or suggestions based on the comparison results (e.g., whether the vibration level exceeds a threshold and the degree of exceeding the threshold), thus forming effective vibration feedback information.

[0079] The vibration feedback information is used to further control and adjust the active vibration damping actuator. This further control and adjustment refers to real-time correction of the actuator's drive parameters (such as drive frequency, amplitude, and phase) based on the feedback information. This achieves more precise vibration suppression that is better adapted to the current working conditions, aiming to form a closed-loop control system that ensures the drilling equipment is always in the optimal vibration control state.

[0080] For example, in deep hole drilling operations, the drilling equipment is initially subjected to a specific vibration suppression mode based on a vibration characteristic fingerprint pattern. As the drilling depth increases, drill bit wear gradually intensifies, and the cutting resistance also changes, causing subtle alterations in the vibration characteristics of the drilling equipment. At this point, the control signals (e.g., actuator drive current and displacement feedback) of the active vibration damping actuator are monitored in real time after responding to drive control. Based on the control signals, the current vibration level parameters are confirmed; for example, a slight increase in vibration amplitude is detected, and a new harmonic peak appears at a specific frequency component, accompanied by a minor impact event. The confirmed vibration level parameters are then compared with a preset vibration level threshold. If the comparison shows that the current vibration amplitude or specific frequency component is close to or slightly exceeds the threshold, vibration feedback information that requires adjustment of the active vibration damping actuator is determined based on a preset feedback information model. For example, the feedback information may indicate the need to fine-tune the actuator's drive frequency to counteract the new harmonic vibration and slightly increase the drive force to suppress the rising vibration amplitude. Finally, using vibration feedback information, the active vibration damping actuator is adjusted again, thereby bringing the vibration level of the drilling equipment back within an acceptable range, ensuring the stability and efficiency of the drilling process. Through real-time feedback adjustments, excellent vibration control can be maintained even under dynamically changing drilling conditions.

[0081] In this embodiment, after the active vibration damping actuator performs initial vibration control, its control signal is continuously monitored, enabling real-time acquisition of the actuator's actual response and operating status. Based on the control signal, vibration level parameters, including vibration amplitude, frequency components, and impact events, can be identified, thus providing a comprehensive and accurate assessment of the drilling equipment's current vibration state. Subsequently, by comparing the vibration level parameters with preset vibration level thresholds, it can be determined whether the current vibration suppression effect meets expectations or whether there are aspects requiring improvement. Once a deviation or anomaly is detected, based on the vibration comparison results and a preset feedback information model, specific vibration feedback information can be intelligently determined. This feedback information includes instructions for adjusting the actuator. Finally, using the vibration feedback information, the active vibration damping actuator is further controlled and adjusted. This ensures that the vibration control strategy can be optimized in real-time according to actual changes during the drilling process, avoiding the limitations of a fixed mode.

[0082] In some embodiments of this application described above, the step of confirming vibration level parameters, including vibration amplitude, frequency components, and impact events, based on the control signal includes:

[0083] Based on the control signals, the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate are confirmed. Specifically, confirming the energy consumption parameters of the active vibration damping actuator refers to calculating or estimating its energy consumption over a specific time period based on the control signals after the actuator responds to the drive control. This includes monitoring the actuator's electrical parameters such as current, voltage, and power, and performing integral calculations based on its operating time to quantify the energy cost incurred by the actuator in suppressing vibration. The aim is to reflect the vibration reduction effect and system efficiency from the perspective of energy consumption. Confirming the drill bit wear rate can be understood as assessing the degree of drill bit wear per unit time based on the drill bit damage status information during the drilling process, combined with the control signals. This is obtained indirectly or directly by analyzing data such as cutting torque, acoustic emission signals, and changes in drill bit geometry. The purpose is to incorporate the drill bit's service life and wear status into the vibration level assessment system to achieve more comprehensive equipment health monitoring.

[0084] Using the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate, a parameter evaluation model is obtained by model matching from a preset evaluation model. The preset evaluation model is a pre-established mathematical model or algorithm library used to correlate energy consumption parameters, drill bit wear rate, and vibration level parameters. This model can be trained and optimized through extensive experimental data, simulation analysis, or expert experience, for example, using machine learning algorithms (such as support vector machines and neural networks) or regression analysis methods based on physical models. Its purpose is to provide an intelligent evaluation framework capable of dynamically generating or selecting the most suitable parameter evaluation model based on input parameters. Model matching refers to the system searching the preset evaluation model library for the evaluation model that best matches the current working conditions or data characteristics based on the characteristics of the currently acquired energy consumption parameters and drill bit wear rate. For example, different drilling materials, drill bit types, or cutting parameters may correspond to different wear and energy consumption patterns; therefore, matching appropriate evaluation models is necessary to improve the accuracy of the evaluation.

[0085] Based on the energy consumption parameters and drill bit wear rate, a parameter evaluation model is used to evaluate the vibration level parameters, including vibration amplitude, frequency components, and impact events. The parameter evaluation model is a specific model obtained through model matching, designed specifically for evaluating vibration level parameters under the current operating conditions. Based on this parameter evaluation model, it is possible to comprehensively consider energy consumption parameters and drill bit wear rate, and to accurately quantify vibration level parameters such as vibration amplitude, frequency components, and impact events. The aim is to provide a customized evaluation tool to ensure reliable vibration level parameters are obtained under different operating conditions.

[0086] Specifically, during drilling operations, after the active vibration damping actuator is driven and controlled, its control signal indicates that the actuator operates at a high frequency continuously for a period of time. Simultaneously, a significant increase in its average power consumption is detected, which is confirmed as a high energy consumption parameter. At the same time, analysis of cutting torque and acoustic emission signals reveals that the drill bit wear rate also shows an upward trend. At this point, using a pre-defined evaluation model, a parameter evaluation model is matched to assess high-load and high-wear conditions based on the characteristics of the energy consumption parameter and the drill bit wear rate. The parameter evaluation model may be based on a neural network, with its input layer receiving the energy consumption parameter and drill bit wear rate, and its output layer providing vibration level parameters including vibration amplitude, frequency components, and impact events. For example, the model might output that the current vibration amplitude has reached a critical value, there is a risk of resonance at a specific frequency, and the frequency of impact events has also increased significantly. Based on the vibration level parameters, the active vibration damping actuator is further controlled and adjusted more precisely, such as adjusting the drive frequency or damping coefficient, to effectively suppress vibration while considering both energy consumption and drill bit life.

[0087] This embodiment effectively addresses the limitations of relying solely on control signals to confirm vibration level parameters by introducing energy consumption parameters of the active vibration damping actuator and drill bit wear rate, combined with a preset evaluation model for model matching and parameter evaluation. Specifically, confirming the energy consumption parameter quantifies the workload and efficiency of the vibration damping actuator from the perspective of energy consumption, while the drill bit wear rate confirms the health status of the drill bit. This allows the evaluation of vibration level parameters to move beyond instantaneous vibration response and consider the long-term effects of system operation and component wear. Model matching using the preset evaluation model allows for the selection of the most suitable evaluation algorithm based on different operating conditions and data characteristics, ensuring the accuracy and adaptability of the evaluation. The resulting parameter evaluation model more comprehensively and accurately reflects the actual vibration level of the drilling equipment, providing a more reliable basis for subsequent feedback control adjustments.

[0088] In some embodiments of this application described above, the step of confirming the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate based on the control signal includes:

[0089] Based on the control signals, the drilling environment parameters and the operating status of the drilling equipment are confirmed. Confirming the drilling environment parameters and the operating status of the drilling equipment based on the control signals means analyzing and processing the control signals of the active vibration damping actuator after responding to drive control to extract parameters related to the drilling environment and the current operating status information of the drilling equipment. Specifically, drilling environment parameters may include, but are not limited to, drilling depth, geological conditions, coolant flow rate, and ambient temperature, which directly affect energy consumption and drill bit wear during the drilling process. The operating status of the drilling equipment may include spindle speed, feed rate, depth of cut, and tool load, key indicators reflecting the equipment's workload and efficiency.

[0090] Data analysis is performed on the drilling environment parameters and the operating status of the drilling equipment to confirm the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate. Specifically, this step involves using data processing and analysis techniques, after obtaining the aforementioned environmental parameters and operating status information, to deduce the actual energy consumption of the active vibration damping actuator and the drill bit wear rate. For example, by establishing a mathematical model or employing machine learning algorithms, using the environmental parameters and operating status as input, energy consumption parameters (such as instantaneous power and cumulative energy consumption) and drill bit wear rates (such as wear per unit time and wear degree level) can be predicted or calculated. By comprehensively considering the external environment and the internal operating conditions of the equipment, the performance of the active vibration damping actuator and the service life of the drill bit can be more accurately evaluated.

[0091] This embodiment first confirms the drilling environment parameters and the operating status of the drilling equipment, providing comprehensive foundational data for subsequent confirmation of energy consumption parameters and drill bit wear rate. The control signals contain actuator response information under specific environmental and operating conditions, allowing for accurate extraction of key factors affecting energy consumption and wear. Subsequently, through in-depth data analysis of these parameters and statuses, a quantitative relationship between energy consumption and environmental and operating conditions can be established, as well as the correlation between drill bit wear and these factors. This avoids the limitations of single-parameter evaluation, making the confirmation of energy consumption parameters and drill bit wear rate more comprehensive and accurate.

[0092] In some embodiments of this application described above, the step of confirming the drilling environment parameters and the operating status of the drilling equipment based on the control signal includes:

[0093] Based on the control signal, initial parameters of the drilling environment and the initial operating state of the drilling equipment are acquired. The control signal refers to the signal generated by the active vibration damping actuator in response to drive control, which contains the actuator's operating state information. By analyzing this control signal, initial data related to the drilling environment and equipment operation can be obtained indirectly or directly. Initial parameters of the drilling environment may include, but are not limited to, temperature, humidity, material hardness, and coolant flow rate, while the initial operating state of the drilling equipment may include, but is not limited to, spindle speed, feed rate, depth of cut, and tool wear. The initial parameters and states are raw, unprocessed data and may contain noise or outliers.

[0094] The initial parameters of the drilling environment and the initial operating state of the drilling equipment are denoised to obtain denoised initial parameters and initial operating states of the drilling equipment. Specifically, the purpose of denoising is to eliminate random noise, interference signals, or measurement errors present in the original data, thereby improving the purity and usability of the data. For example, various signal processing algorithms, such as wavelet transform, Fourier transform, moving average filtering, and median filtering, can be used to process the obtained initial parameters of the drilling environment and the initial operating state of the drilling equipment. Denoising effectively filters out irrelevant components in the data, making subsequent data analysis more accurate.

[0095] Data verification is performed on the initial parameters of the denoised drilling environment and the initial operating state of the denoised drilling equipment to confirm their operation. This data verification aims to further validate the effectiveness and consistency of the denoised data, eliminating outliers or unreasonable data points. For example, a reasonable threshold range can be set to check the range of the denoised parameters; or statistical methods, such as outlier detection algorithms (e.g., box plots and Z-scores), can be used to identify and process outliers. Through data verification, it can be ensured that the finally confirmed drilling environment parameters and drilling equipment operating state are accurate, reliable, and consistent with actual working conditions. The finally confirmed drilling environment parameters and drilling equipment operating state will be used for subsequent confirmation of energy consumption parameters and drill bit wear rate.

[0096] This embodiment effectively improves the accuracy of confirming drilling environment parameters and the operating status of drilling equipment. The initial drilling environment parameters and the initial operating status of the drilling equipment often contain noise and uncertainties. Directly using the raw data for subsequent analysis may lead to accumulated errors. By denoising the initial parameters and status, interference information can be effectively filtered out, making the data cleaner and laying the foundation for subsequent accurate analysis. Furthermore, data verification of the denoised data can identify and eliminate outliers or unreasonable data points, ensuring that the confirmed parameters are logically and physically reasonable. The accuracy and reliability of the drilling environment parameters and the operating status of the drilling equipment after denoising and verification are significantly improved, providing high-quality input data for the accurate evaluation of the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate.

[0097] In some embodiments of this application described above, the step of acquiring vibration information collected by a vibration sensor on a drilling device includes:

[0098] Acquire raw vibration data from vibration sensors on the drilling equipment. This step involves using vibration sensors installed on the drilling equipment, such as accelerometers, velocity sensors, or displacement sensors, to monitor the vibration of the drilling equipment in real time during the cutting operation and collect its raw signals. The raw vibration data is typically an unprocessed electrical or digital signal and may contain environmental noise, equipment noise, and other interference.

[0099] Based on the raw vibration data, vibration information including the instantaneous rise-edge slope and the instantaneous energy distribution of high-frequency components is determined. Specifically, the instantaneous rise-edge slope can be understood as the rate at which the amplitude of the vibration signal increases rapidly within a very short time. It can effectively reflect impact events that may occur during drilling, such as sudden contact between the drill bit and the workpiece, cutting interruption, or tool breakage. The instantaneous energy distribution of high-frequency components refers to the distribution of energy in the high-frequency part of the vibration signal over time. High-frequency vibrations are often closely related to early or subtle anomalies such as drill bit wear, cutting instability, or local equipment failure. By analyzing its instantaneous energy distribution, potential problems can be detected more sensitively. Signal processing techniques such as wavelet transform, Hilbert transform, or short-time Fourier transform can be used to perform time-frequency analysis on the raw vibration data to extract the instantaneous rise-edge slope and the instantaneous energy distribution of high-frequency components. For example, high-pass filtering can be applied to the raw vibration data to separate high-frequency components and determine their instantaneous energy; simultaneously, the rise-edge of the signal can be detected and its slope determined.

[0100] The vibration information, including the instantaneous rise-edge slope and high-frequency components of the instantaneous energy distribution, is preprocessed to obtain vibration information. The preprocessing steps may include, but are not limited to, filtering, noise reduction, normalization, and feature fusion. For example, filtering and noise reduction techniques remove environmental noise and sensor noise from the vibration information to improve the signal-to-noise ratio; normalization eliminates differences in the dimensions and numerical ranges of different features, making them comparable; and feature fusion effectively integrates the instantaneous rise-edge slope and high-frequency components of the instantaneous energy distribution to form more comprehensive and representative vibration information. This ensures the accuracy and reliability of subsequent vibration feature fingerprint pattern confirmation.

[0101] This embodiment first acquires raw vibration data from vibration sensors, ensuring the real-time and direct nature of the vibration information source. By determining the vibration information, which includes the instantaneous rise-edge slope and the instantaneous energy distribution of high-frequency components, features that are more sensitive to changes in the drilling equipment's condition and have diagnostic value can be extracted from the raw data. The instantaneous rise-edge slope can effectively capture impact events during drill bit cutting, such as tool chipping or material hardening, while the instantaneous energy distribution of high-frequency components can reveal early or subtle anomalies such as drill bit wear and cutting instability. Subsequently, the vibration information containing specific features is preprocessed, such as through noise reduction, filtering, and feature fusion, to eliminate interference in the data, standardize feature parameters, and integrate multi-dimensional information, thereby obtaining purer, more accurate, and representative vibration information. This provides high-quality input for subsequent confirmation of vibration feature fingerprint patterns, ensuring the effectiveness and robustness of the entire vibration control method.

[0102] In some embodiments of this application described above, the step of obtaining a vibration suppression mode corresponding to the vibration feature fingerprint pattern based on the vibration feature fingerprint pattern and a preset vibration suppression library includes:

[0103] The vibration feature fingerprint pattern is matched using a pre-defined vibration suppression library to obtain multiple candidate vibration suppression patterns. This step involves comparing the currently acquired vibration feature fingerprint pattern with various vibration suppression patterns stored in the pre-defined vibration suppression library. This matching process can employ various algorithms, such as pattern recognition based on correlation analysis, distance metrics (e.g., Euclidean distance, cosine similarity), or machine learning models, to identify vibration suppression patterns with a certain similarity or correlation to the current vibration feature fingerprint pattern. The purpose is to initially screen out all potentially usable vibration suppression schemes. Specifically, obtaining multiple candidate vibration suppression patterns means that during the pattern matching stage, more than one vibration suppression pattern is typically identified that reaches a preset similarity threshold with the current vibration feature fingerprint pattern. The patterns initially screened are the candidate vibration suppression patterns, all of which may suppress the current vibration to some extent, but their effectiveness and applicability may differ.

[0104] Based on the vibration characteristic fingerprint pattern, pattern judgment analysis is performed on multiple candidate vibration suppression patterns to obtain the vibration suppression mode corresponding to the vibration characteristic fingerprint pattern. This step refers to the need for further in-depth evaluation and comparison of these candidate modes after obtaining multiple candidate vibration suppression modes. By comprehensively considering the detailed characteristics of the vibration characteristic fingerprint pattern, such as the frequency components, amplitude, duration, and impact characteristics of the vibration, and combining preset optimization objectives (such as maximizing vibration reduction effect, minimizing energy consumption, and minimizing the impact on drill bit wear), each candidate mode is carefully evaluated. Specifically, expert systems, fuzzy logic reasoning, multi-criteria decision analysis, or more complex machine learning models can be used for decision-making. The purpose is to accurately select the vibration suppression mode most suitable for the current vibration characteristic fingerprint pattern from multiple similar candidate solutions. Obtaining the vibration suppression mode corresponding to the vibration characteristic fingerprint pattern means that through the above pattern judgment analysis, the optimal vibration suppression mode is finally determined, which is considered to be able to most effectively cope with the specific vibration characteristic fingerprint pattern exhibited by the current drilling equipment.

[0105] Specifically, during the drilling process, vibration information collected by vibration sensors and drill bit damage status information are processed to identify a specific vibration characteristic fingerprint pattern. This pattern indicates the presence of high-frequency, low-amplitude periodic flutter. A pre-set vibration suppression library is used to perform pattern matching on this vibration characteristic fingerprint pattern. For example, the pre-set vibration suppression library may contain multiple suppression strategies for different flutter patterns. After pattern matching, three candidate vibration suppression patterns are initially identified: Pattern 1 (focusing on high-frequency damping), Pattern 2 (focusing on frequency shift), and Pattern 3 (focusing on amplitude suppression). These three patterns all have a high degree of similarity to the current high-frequency, low-amplitude periodic flutter pattern. Subsequently, based on this vibration characteristic fingerprint pattern, pattern judgment analysis will be performed on these three candidate vibration suppression patterns. If the flutter pattern is characterized by a low amplitude but a frequency close to the equipment's natural frequency, potentially leading to resonance risk, then the pattern that can effectively shift the frequency may be prioritized during the pattern judgment analysis. If, after analysis, Mode 2 shows the best performance in terms of frequency shift and its impact on other performance indicators (such as energy consumption and response speed) is within an acceptable range, then Mode 2 will ultimately be determined as the vibration suppression mode corresponding to the current vibration characteristic fingerprint pattern. Therefore, the active vibration damping actuator will be driven and controlled based on Mode 2 to precisely suppress this high-frequency, low-amplitude periodic flutter.

[0106] This embodiment, through pattern matching, can comprehensively identify all candidate suppression modes related to the current vibration characteristic fingerprint pattern from a preset vibration suppression library, avoiding the risk of missing potential effective solutions. Secondly, based on multiple candidate modes, pattern judgment analysis is introduced, enabling a deeper evaluation and comparison of candidate modes according to the specific details of the vibration characteristic fingerprint pattern and preset optimization objectives. This two-stage refined processing ensures that the finally selected vibration suppression mode more accurately matches the current vibration state, thereby providing more targeted drive control commands for the active vibration damping actuator, ensuring the effectiveness and efficiency of vibration control.

[0107] For a drilling equipment vibration control method based on any of the above embodiments, please refer to [link to relevant documentation]. Figure 2 The present invention also provides a vibration control system for drilling equipment, which includes an information acquisition module 210, a first confirmation module 220, a second confirmation module 230 and a drive control module 240.

[0108] The information acquisition module 210 is used to acquire vibration information collected by the vibration sensor on the drilling equipment and information on the damage status of the drill bit during the cutting process.

[0109] The first confirmation module 220 is used to confirm the vibration feature fingerprint pattern based on the vibration information and the drill bit damage status information.

[0110] The second confirmation module 230 is used to obtain a vibration suppression mode corresponding to the vibration feature fingerprint pattern based on the vibration feature fingerprint pattern and a preset vibration suppression library.

[0111] The drive control module 240 is used to drive and control the active vibration damping actuator based on the vibration suppression mode, so as to control the vibration of the drilling equipment.

[0112] In this embodiment, the information acquisition module 210 comprehensively acquires vibration information and drill bit damage status information, laying the foundation for subsequent accurate analysis. The first confirmation module 220 and the second confirmation module 230 work together, enabling the system to confirm unique vibration characteristic fingerprint patterns based on multi-source information and intelligently match the most suitable vibration suppression mode from a preset vibration suppression library. This allows the system to provide customized solutions for different types of vibration problems, rather than using a single general control strategy. For example, when the drill bit shows initial wear, the system can identify a specific vibration fingerprint and select a mild suppression mode to extend the drill bit's life; while when severe chipping is detected, a strong suppression mode is immediately activated to prevent further damage to the equipment. Finally, the drive control module 240 can efficiently drive the active vibration damping actuator according to precise suppression mode commands, achieving precise vibration control of the drilling equipment. This invention significantly improves the operational stability, processing accuracy, and service life of drilling equipment.

[0113] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention specification.

Claims

1. A vibration control method for drilling equipment, characterized in that, Includes the following steps: Acquire vibration information collected by vibration sensors on the drilling equipment and information on the damage status of the drill bit during the cutting process; Based on the vibration information and the drill bit damage status information, the vibration characteristic fingerprint pattern is confirmed. Based on the vibration feature fingerprint pattern and the preset vibration suppression library, a vibration suppression pattern corresponding to the vibration feature fingerprint pattern is obtained; Based on the vibration suppression mode, the active vibration damping actuator is driven and controlled to control the vibration of the drilling equipment.

2. The vibration control method for drilling equipment according to claim 1, characterized in that, Based on the vibration information and the drill bit damage status information, the steps for confirming the vibration feature fingerprint pattern include: After confirming the high-frequency components of the vibration information, the instantaneous envelope of the high-frequency components of the vibration information is analyzed to obtain the instantaneous kurtosis and instantaneous skewness of the envelope. Based on the drill bit damage status information, the average rate of change of the cutting torque of the drilling equipment and the average rate of change of the acoustic emission event are confirmed. Based on the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy, the vibration characteristic fingerprint pattern is confirmed.

3. The vibration control method for drilling equipment according to claim 2, characterized in that, The steps for confirming the vibration characteristic fingerprint pattern based on the instantaneous kurtosis, instantaneous skewness, average rate of change of cutting torque, and average rate of change of energy include: The instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate were verified by data to obtain the verified instantaneous kurtosis, instantaneous skewness, average cutting torque change rate, and average energy change rate. Based on the verified instantaneous kurtosis, instantaneous skewness, average change rate of cutting torque, and average change rate of energy, a preset fingerprint pattern model is used for identification to confirm the vibration characteristic fingerprint pattern.

4. The vibration control method for drilling equipment according to claim 1, characterized in that, Following the step of driving and controlling the active vibration damping actuator based on the vibration suppression mode to control the vibration of the drilling equipment, the method further includes: Monitor the control signal of the active vibration damping actuator after responding to the drive control; Based on the control signal, vibration level parameters including vibration amplitude, frequency components, and impact events are confirmed. The vibration level parameters are compared with the vibration level threshold to obtain the vibration comparison results; Based on the vibration comparison results and the preset feedback information model, the vibration feedback information is determined; The vibration feedback information is used to further control and adjust the active vibration damping actuator.

5. The vibration control method for drilling equipment according to claim 4, characterized in that, Based on the control signal, the steps for confirming vibration level parameters including vibration amplitude, frequency components, and impact events include: Based on the control signal, the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate are confirmed. By using the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate, a parameter evaluation model is obtained by model matching from the preset evaluation model. Based on the energy consumption parameters and drill bit wear rate, a parameter evaluation model is used to evaluate the parameters and obtain vibration level parameters including vibration amplitude, frequency components, and impact events.

6. The vibration control method for drilling equipment according to claim 5, characterized in that, Based on the control signal, the steps for confirming the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate include: Based on the control signals, confirm the drilling environment parameters and the operating status of the drilling equipment; Data analysis was performed on the drilling environment parameters and the operating status of the drilling equipment to confirm the energy consumption parameters of the active vibration damping actuator and the drill bit wear rate.

7. The vibration control method for drilling equipment according to claim 6, characterized in that, Based on the control signals, the steps for confirming the drilling environment parameters and the operating status of the drilling equipment include: Based on the control signal, the initial parameters of the drilling environment and the initial operating state of the drilling equipment are obtained. The initial parameters of the drilling environment and the initial operating state of the drilling equipment are denoised to obtain the denoised initial parameters of the drilling environment and the denoised initial operating state of the drilling equipment. The initial parameters of the denoised drilling environment and the initial operating state of the denoised drilling equipment are verified by data validation to confirm the drilling environment parameters and the operating state of the drilling equipment.

8. The vibration control method for drilling equipment according to claim 1, characterized in that, The steps for acquiring vibration information collected by vibration sensors on drilling equipment include: Obtain raw vibration data collected by vibration sensors on the drilling equipment; Based on the original vibration data, vibration information including the instantaneous rise slope and high-frequency components is determined. The vibration information is obtained by preprocessing the vibration information, which includes the instantaneous rise slope and high-frequency components.

9. The vibration control method for drilling equipment according to claim 1, characterized in that, The step of obtaining the vibration suppression mode corresponding to the vibration feature fingerprint pattern based on the vibration feature fingerprint pattern and the preset vibration suppression library includes: The vibration feature fingerprint pattern is matched using a preset vibration suppression library to obtain multiple candidate vibration suppression patterns after matching. Based on the vibration feature fingerprint pattern, a pattern judgment analysis is performed on multiple candidate vibration suppression patterns to obtain the vibration suppression pattern corresponding to the vibration feature fingerprint pattern.

10. A vibration control system for drilling equipment, characterized in that, The system includes: The information acquisition module is used to acquire vibration information collected by the vibration sensors on the drilling equipment and information on the damage status of the drill bit during the cutting process. The first confirmation module is used to confirm the vibration feature fingerprint pattern based on the vibration information and the drill bit damage status information. The second confirmation module is used to obtain the vibration suppression mode corresponding to the vibration feature fingerprint mode based on the vibration feature fingerprint mode and the preset vibration suppression library; The drive control module is used to drive and control the active vibration damping actuator based on the vibration suppression mode, so as to control the vibration of the drilling equipment.

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