Aircraft shell part valve core hole processing method

Abstract

This invention relates to the fields of precision machining and intelligent manufacturing technology, and discloses a method for machining valve core holes in aerospace housing parts. This method employs an intelligent tool system integrated with a piezoelectric ceramic stack, which enables self-sensing monitoring and active vibration suppression closed-loop control of machining chatter. When the detected chatter amplitude exceeds an activation threshold, the system switches from monitoring to active vibration suppression, generating high-frequency vibrations by exciting the stack to suppress chatter, while simultaneously completing the finishing of the hole wall. When the chatter amplitude falls below a safety threshold, the system returns to monitoring mode. This invention solves the problems of system response lag and low integration by highly integrating sensing and execution functions into a single component; it improves machining efficiency and surface quality by merging cutting and finishing; and it ensures the stability of the machining process through dual-threshold hysteresis control.

Description

Technical Field

[0001] This invention relates to the fields of precision machining and intelligent manufacturing technology, specifically a method for machining valve core holes in aircraft housing parts. Background Technology

[0002] Precision machining of valve core holes in aerospace housing components is a critical step in aerospace manufacturing. These parts typically feature thin walls and deep holes, making them highly susceptible to chatter during boring due to cutting forces, tool wear, and material inhomogeneity. To ensure dimensional accuracy, surface quality, and fatigue performance of the holes, current mainstream machining methods rely on high-rigidity machine tools, precision tool selection, and optimized cutting parameters to avoid or mitigate chatter. Some advanced technologies also attempt to introduce external sensors (such as accelerometers and force sensors) for chatter monitoring or use independent piezoelectric actuators for active vibration control. However, these technologies mostly focus on passive suppression or independent monitoring / actuation, and do not fundamentally solve the problem of dynamic chatter during machining.

[0003] Current technologies still have some limitations in addressing machining chatter. The current design, which separates the chatter monitoring unit from the active damping actuator, complicates the system structure and limits its spatial integration. When chatter occurs, an unavoidable time delay occurs throughout the entire chain, from sensor detection and signal transmission to controller calculation and actuator response. This lag, in dynamically changing machining environments, can lead to poor chatter suppression and even exacerbate system instability, making it difficult to effectively guarantee the machining accuracy and surface integrity of valve core holes in aerospace housing parts.

[0004] In the machining of aerospace parts that demand high precision and surface quality, an additional independent surface finishing or strengthening process, such as burnishing or extrusion, is typically required after the cutting process. This separation of cutting and finishing not only increases the number of processes and total machining time, reducing production efficiency, but also introduces new positioning errors with each workpiece reclamping or process change, negatively impacting the final machining accuracy and surface consistency. Furthermore, two separate machining processes also mean higher energy consumption and more complex equipment management. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for machining valve core holes in aerospace housing parts. This method solves the problems of low system integration and delayed control response caused by the separation of flutter monitoring and vibration suppression execution units in existing technologies, as well as low machining efficiency, high energy consumption, and difficulty in simultaneously ensuring the surface quality of the hole wall caused by the separation of the machining process and surface finishing process.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for machining valve core holes in aircraft housing parts, comprising the following steps:

[0007] First, set a chatter activation threshold and a safety threshold before processing.

[0008] Subsequently, baseline boring is performed using an intelligent tooling system integrating a piezoelectric ceramic stack and a cutting head. During machining, the machining status is monitored in real time using the piezoelectric ceramic stack. This monitoring process includes acquiring a feedback electrical signal and demodulating the feedback electrical signal to extract a chatter characteristic signal.

[0009] Next, the real-time jitter amplitude of the jitter characteristic signal is evaluated to determine whether the amplitude is greater than the preset jitter activation threshold.

[0010] If the judgment result is yes, then active vibration suppression is activated, that is, a high-power driving voltage is applied to the piezoelectric ceramic stack to excite the cutter head to generate high-frequency mechanical vibration.

[0011] During active vibration suppression, the real-time flutter amplitude is continuously monitored. When the amplitude drops to no more than a preset safety threshold, the application of the high-power drive voltage is stopped, and the process returns to the baseline processing and monitoring steps.

[0012] In one specific embodiment of the present invention, the real-time monitoring process using a piezoelectric ceramic stack is based on a carrier modulation principle. Specifically, a high-frequency carrier excitation voltage is applied to the piezoelectric ceramic stack. When a low-frequency flutter mechanical vibration occurs during processing, this vibration causes a periodic change in the electrical impedance of the piezoelectric ceramic stack. This impedance change modulates the electrical signal fed back from the piezoelectric ceramic stack. By receiving this modulated feedback electrical signal and using a specific signal demodulation algorithm, the flutter characteristic signal can be extracted from it.

[0013] Furthermore, the signal demodulation algorithm can employ detection or a demodulation method based on the Hilbert transform. This algorithm is used to extract the real-time flutter amplitude, frequency, and phase characteristic signals of low-frequency flutter from the amplitude envelope of the modulated feedback electrical signal.

[0014] In another specific embodiment of the invention, the tool head includes a main cutting edge. During active vibration suppression, the applied high-frequency mechanical vibration changes the cutting process of the main cutting edge from continuous cutting to high-frequency intermittent cutting. This change in cutting mode disrupts the phase-locking condition necessary for chatter regeneration, thereby suppressing the occurrence and development of chatter.

[0015] Furthermore, the cutting head may also include a setter edge. While the main cutting edge performs high-frequency intermittent cutting, the high-frequency mechanical vibration also acts on the setter edge, driving it to perform synchronous integrated finishing on the hole wall surface already machined by the main cutting edge.

[0016] To ensure the stability of the control process, the safety threshold is set below the flutter activation threshold. By setting two different thresholds, a hysteresis interval is formed in the control logic to prevent the active vibration suppression process from being frequently started and stopped when the real-time flutter amplitude fluctuates slightly around the activation threshold.

[0017] To improve the adaptability of the method, a chatter risk database can be established during the preparation step. This database is used to characterize the risk level of chatter under different machining depths and cutting parameter combinations. This database can be established in one of the following ways: Method 1: Based on finite element simulation, perform dynamic characteristic simulation of the machining system consisting of the tool, spindle, and workpiece, and construct the database by combining the cutting dynamics model to draw the chatter stability lobe diagram of the system; Method 2: Based on the analysis of historical machining data, establish an empirical mapping relationship or machine learning model between chatter characteristics and machining parameters to generate the database.

[0018] To improve the reliability of state switching, the judgment condition in the state switching step may also include a time confirmation mechanism, that is, to determine whether the condition that the real-time jitter amplitude is not greater than the safety threshold has been maintained for a preset stable time.

[0019] In one specific embodiment of the present invention, the tool head of the intelligent tool system is a boring-solidifying integrated tool head, which integrates the main cutting edge and the solidifying edge in an integral structure.

[0020] This invention provides a method for machining valve core holes in aircraft housing parts. It has the following advantages:

[0021] 1. This invention achieves chatter monitoring and active vibration suppression by using a single piezoelectric ceramic stack, highly integrating sensing and execution functions. This solution eliminates the need for independent external sensors, simplifying the physical structure of the intelligent tooling system. Furthermore, because sensing and execution are located in the same component, the response delay of the control loop is eliminated, improving the real-time performance and effectiveness of chatter suppression.

[0022] 2. This invention utilizes an integrated tool head that combines a main cutting edge and a setter edge. With the assistance of high-frequency mechanical vibration, boring and finishing of the hole wall are integrated into a single process. This method eliminates the need for secondary clamping or separate steps for surface strengthening in traditional processes, shortening the overall machining cycle and improving production efficiency. Simultaneously, vibration-assisted finishing helps improve the quality of the machined surface.

[0023] 3. This invention introduces hysteresis characteristics into the control algorithm by setting differentiated chatter activation and safety thresholds. This design effectively avoids frequent switching of control commands when the system is in a chatter critical state, enhances the stability and reliability of processing state switching, and reduces unnecessary energy consumption. Attached Figure Description

[0024] Figure 1 This is a flowchart of the method of the present invention;

[0025] Figure 2 This is a schematic diagram of the intelligent tool system architecture of the present invention;

[0026] Figure 3 This is a schematic diagram of the flutter self-sensing principle of the present invention;

[0027] Figure 4 This is a schematic diagram of the active vibration damping and integrated finishing of the present invention;

[0028] Figure 5 This is a schematic diagram of the state switching logic of the processing method of the present invention. Detailed Implementation

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Reference Figure 1 , Figure 1 This is a schematic flowchart of a method according to an embodiment of the present invention. The present invention provides a method for machining valve core holes in aircraft housing parts, comprising the following steps:

[0031] S100, the pre-processing preparation stage, including establishing a flutter risk potential field database and pre-setting flutter activation threshold and safety threshold;

[0032] The S200 performs baseline boring and uses the sensing function of piezoelectric elements to monitor the machining status in real time, and obtains feedback electrical signals to demodulate chatter characteristic signals.

[0033] S300, dynamically assess the amplitude of the flutter characteristic signal to determine whether it exceeds the preset flutter bud activation threshold.

[0034] S400, if the judgment result is yes, the high-fidelity module is activated, causing the tool head to generate high-frequency radial vibration and executing the active vibration suppression control law, while completing boring and impact hardening;

[0035] S500: During the active vibration suppression process, the amplitude of the flutter characteristic signal is continuously monitored to determine whether it has been reduced to below a preset safety threshold.

[0036] The method also includes closed-loop flow logic between steps: if the evaluation result of step S300 is negative, the process returns to step S200; if the evaluation result of step S500 is positive, the process returns to step S200; if the evaluation result of step S500 is negative, the process remains at step S400.

[0037] To further clarify the technical content of the embodiments of the present invention, the specific implementation methods and technical principles of the foregoing steps will be described in detail below.

[0038] S101: Clamp and fix the workpiece to be machined, and install the intelligent tooling system. For example, fix the valve body of an aircraft housing part onto the worktable or fixture of a CNC boring machine or a five-axis machining center. Install the intelligent tooling system, which integrates a piezoelectric ultrasonic tool holder and a boring-fixing integrated tool head as described in the previous embodiment, onto the machine tool spindle. The installation and tool setting of the machine tool, workpiece, and tool can be achieved by those skilled in the art using conventional methods, which are well-known technologies in the field and will not be described in detail here.

[0039] S102: Establish a flutter risk potential field database Flutter Risk Potential Field Database Used to characterize different processing depths and specific cutting parameters (such as rotational speed) Feed Under these conditions, the probability of machining chatter occurring is... Or risk level. The database can be established in (but is not limited to) the following two ways:

[0040] One approach is based on the finite element method (FEM). This involves performing dynamic characteristic simulations on the machining system comprised of the tool, tool holder, spindle, and workpiece, and then performing modal analysis to obtain the system's properties at different machining depths. The natural frequencies, mode shapes, and dynamic stiffness under varying workpiece or tool overhang ratios are determined. A chatter stability lobe diagram of the system is plotted using the cutting dynamics model and stability theory. This lobe diagram allows for the pre-identification of different machining depths. At that time, which speeds and depth of cut (radial cutting amount) The combination of these factors forms an unstable region (high-risk region), thereby constructing a flutter risk potential field database. During this process, the system extracts the theoretical vibration amplitude corresponding to the critical cutting depth on the boundary of the stability lobe diagram, and uses it as a unified reference benchmark—the theoretical limit amplitude—under this working condition. Stored in a database.

[0041] Another approach is based on analyzing historical machining data. This involves collecting signals from previous machining processes of similar parts, monitored by external sensors (such as accelerometers and acoustic emission sensors) or machine tool-built-in sensors (such as spindle motor current and servo drive load). These signals are then correlated with actual chatter events (identified through the surface morphology of the machined hole wall or machining sounds) to establish a relationship between chatter characteristics and machining parameters. Empirical mapping relationships or machine learning models between these relationships are used to generate a flutter risk potential field database. During this process, the maximum peak value of the normal cutting signal when chatter does not occur is used as the reference noise amplitude. The signal amplitude at which slight flutter occurs is statistically analyzed and used as a unified reference benchmark—the empirical critical amplitude. Stored in a database. Although both of the above methods rely on input parameters ( or Although their focuses differ, their ultimate goal is to obtain the critical amplitude reference value under the current operating conditions. or This provides a unified quantitative basis for setting the threshold in S103.

[0042] S103: Set key control thresholds, mainly including the flutter bud activation threshold. and model degradation safety threshold The aforementioned The threshold is set based on the principle that its value should be significantly higher than the system's inherent vibration noise amplitude under stable baseline processing conditions, but lower than the amplitude at which flutter enters the nonlinear severe vibration stage (i.e., complete instability). Used to sensitively capture the nascent stage of flutter, i.e., flutter amplitude. The initial stage of unstable growth. Specifically, in one embodiment, without relying on a database, statistical principles are directly used to determine this. This involves acquiring a segment of background signal from the system under stable cutting conditions and calculating its mean. and standard deviation ,Will Set as ,in The first safety factor is set (e.g., a value ranging from 3 to 6); in another embodiment, based on the database in step S102, regardless of whether the database is based on simulation or historical data, the system reads the stored critical amplitude reference value. or ), and Set as a percentage of this reference value (e.g., set) or This eliminates the differences caused by different modeling input parameters.

[0043] The The basis for this setting is that its value should be lower than ,Right now In the control logic, two different thresholds are used ( and This is to create a hysteresis interval. The purpose of this hysteresis interval is to prevent the system from fluctuating at certain amplitudes. Critical to When nearby fluctuations occur, the active vibration suppression module is frequently triggered (step S400) and deactivated (step S500) to ensure the stability of the entire closed-loop control process and prevent chattering in the control system. The specific determination method is as follows: Select one based on the required machining control accuracy: For scenarios where the hysteresis range needs to be dynamically adjusted according to the operating conditions, [the module is selected]. Set as A scaling factor (e.g.) ,in The value ranges from 0.6 to 0.8. This is for high-precision machining scenarios where the system needs to be forced to revert to an absolutely stable baseline. Set to a fixed value slightly higher than the background vibration noise amplitude (e.g.) The value ranges from 1.5 to 2.5, and This ensures that the active vibration suppression state is only discontinued when the vibration energy substantially drops back to near the stable cutting level.

[0044] In some embodiments, these thresholds and They are not fixed. They can be determined based on the information established in step S102. The database is dynamically adjusted. For example, when the processing enters a known high-risk area for flutter ( When the temperature is very high, the control system can actively reduce it. The value can be adjusted to improve monitoring sensitivity; in low-risk areas, the value can be appropriately increased. The value is adjusted to reduce false triggering caused by normal fluctuations in cutting force. In summary, whether the threshold is fixed or dynamically adjusted, its value depends on the simulation calculation or historical data statistics before machining (S102), that is, before the baseline machining starts in step S200, all the criteria ( , All of these have been established or planned and do not depend on real-time signals generated during the current workpiece processing.

[0045] Reference Figures 2-3 , Figure 2This is a schematic diagram of an intelligent tooling system architecture according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the flutter self-sensing principle according to an embodiment of the present invention.

[0046] In one embodiment, step S200 (baseline processing and flutter self-sensing) may specifically include the following sub-steps:

[0047] S201: The system performs baseline machining. In this state, the main cutting edge of the intelligent tool system ( The process involves conventional mechanical boring. The ultrasonic drive power supply in the closed-loop control system can be in a switched-off state or a low-power operating state when there is no need for active vibration suppression. When the ultrasonic drive power supply is switched off, the chatter self-sensing module independently sends a weak probe excitation signal to the piezoelectric ceramic stack (PZT) to achieve sensing functionality. When the ultrasonic drive power supply is in a low-power operating state, its output signal also serves as the probe excitation. In this state, the chatter self-sensing module is activated to monitor the machining process in real time.

[0048] S202: Perform flutter self-sensing. To achieve self-sensing, the ultrasonic drive power supply or flutter self-sensing module applies a high-frequency carrier excitation voltage to the piezoelectric ceramic stack (PZT). .

[0049] ;

[0050] In the formula: It is the applied carrier excitation voltage It is time This is the carrier excitation amplitude, typically a small value, chosen to avoid affecting normal cutting or consuming excessive energy. The carrier excitation amplitude is a known control constant preset by the system. Its selection principle is: while ensuring the signal-to-noise ratio (SNR) is sufficient for subsequent circuit detection, it should be as small as possible, so as not to induce macroscopic cutting vibration or consume excessive energy. In a specific embodiment, The value range is set to 5V to 30V (or set to 2% to 5% of the high power drive voltage amplitude Ad in subsequent step S402). At this time, the micron-level micro-amplitude vibration generated by PZT is mainly used to detect impedance changes and does not have a cutting function.

[0051] It is the carrier excitation frequency (e.g.) The selection principles for the carrier excitation frequency include: it should be far away from the natural frequency and potential chatter frequency of the cutting system to avoid interfering with the machining process; at the same time, it should be located in the frequency band where the PZT element has good electromechanical coupling performance to ensure its efficient response as a sensor and actuator. The specific determination method is as follows: during the machining preparation stage, use an impedance analyzer to perform a frequency scan (Sweep Test) on the installed intelligent tool system, obtain the system's admittance circle diagram or impedance curve, and select the frequency near the system's local resonance point or anti-resonance point as the carrier excitation frequency. (For example, select the frequency point with the largest impedance change rate, usually between 18kHz and 25kHz), and then embed that frequency into the control program.

[0052] When low-frequency chatter occurs during processing, this mechanical vibration (frequency: The amplitude is The piezoelectric effect acts on the PZT element. This mechanical vibration causes periodic changes in the mechanical and electrical impedance of the PZT. This impedance change affects the feedback electrical signal of the PZT. This generates a modulation effect. The feedback electrical signal It can be a feedback voltage signal or a feedback current signal, which can be approximated as:

[0053] ;

[0054] In the formula: It is the modulated electrical signal fed back by PZT, which is a known timing signal obtained by real-time acquisition through a voltage / current sensor and digitization by an analog-to-digital converter (ADC); It is the baseline amplitude of the feedback signal, the value of which depends on the inherent characteristics of PZT and the external circuit parameters. It is a constant measured by the system in a static state (without cutting vibration) and represents the static response amplitude of the carrier signal in the loop. It is the electromechanical coupling modulation coefficient, which reflects the degree of modulation of the electrical signal by mechanical vibration. It is determined by the piezoelectric constant of PZT material and the preload of the tool structure. For a given hardware system, it is regarded as a calibration constant. The amplitude of the low-frequency flutter represents the intensity of the flutter and is the unknown variable to be solved, which is the target feature that this invention aims to extract through signal processing. It is the frequency of low-frequency flutter, which is usually much lower than the carrier excitation frequency. ; It is the phase of low-frequency flutter; It is the phase of the feedback carrier signal, which is related to the phase of the applied carrier excitation voltage, and is a known or measurable system parameter.

[0055] The above formula is not used for direct algebraic calculation, but to describe the physical modulation mechanism of the flutter signal, proving that the feedback signal conforms to the characteristics of amplitude modulation (AM) signal, thus providing a theoretical basis for the subsequent step (S203) to demodulate using envelope detection or Hilbert transform.

[0056] S203: Perform flutter signal demodulation. The flutter self-sensing module receives this feedback electrical signal. The flutter self-sensing module employs a signal demodulation algorithm to detect flutter from high-frequency carrier signals. In the process, low-frequency flutter characteristic signals are demodulated and extracted. Specific implementations of signal demodulation algorithms can include envelope-detection or demodulation methods based on the Hilbert transform. Signal demodulation algorithms include those from... Remove the baseline amplitude (DC component) from the amplitude envelope. The demodulation of such high-frequency carrier signals can be achieved by conventional digital or analog signal processing techniques, which are well-known in the field and will not be elaborated further here.

[0057] The flutter characteristic signal obtained after demodulation (Assuming here) The proportionality coefficients (after normalization) are as follows:

[0058] ;

[0059] The normalization process refers to introducing a pre-calibrated system sensitivity coefficient into the signal processing algorithm. (The system sensitivity coefficient is obtained through standard vibration table calibration), eliminating the influence of circuit gain and piezoelectric constant, and converting the demodulated voltage signal into a value characterizing the actual physical displacement. This signal Characterizes the real-time amplitude of chatter during actual processing. ,frequency and phase It should be noted that, although It is a time-varying sinusoidal waveform, but in the subsequent judgment logic of step S300, the system does not directly use the waveform itself. Instead, it uses a peak detection algorithm or a root mean square (RMS) calculation algorithm to obtain the waveform from the waveform. Extract the real-time scalar amplitude representing the intensity of vibrational energy. (i.e., the amplitude envelope of the signal), using this scalar value and the threshold Perform real-time size comparison.

[0060] The signal It is transmitted in real time to the active vibration damping control unit for dynamic risk assessment in subsequent step S300.

[0061] The following section elaborates on step S300 (Dynamic Risk Assessment and Activation Logic). Step S300 is the decision-making link connecting self-sensing and active control, and may include the following sub-steps:

[0062] S301: The active vibration suppression control unit (e.g., a digital signal processor (DSP) or microcontroller (MCU)) receives the flutter characteristic signal transmitted in step S203 (flutter signal demodulation) in real time. In one embodiment, if For analog signals, the active vibration damping control unit first samples and digitizes them at high speed using its built-in or external analog-to-digital converter (ADC) to obtain a discrete-time sequence for subsequent digital signal processing. .

[0063] S302: This control unit processes the acquired flutter characteristic signal ( or Perform real-time amplitude calculation to obtain the real-time flutter amplitude. Real-time amplitude calculation is performed within each operation cycle of the control unit to ensure the immediacy of the evaluation. The specific implementation methods may include the following, and the system will select one based on the current computing power of the controller and the signal-to-noise ratio characteristics of the processing environment:

[0064] Method 1: Execute the PeakDetection algorithm to find peaks within the most recent time window. The maximum absolute value of the chatter amplitude is the fastest way to respond to sudden changes in the chatter amplitude. This method has the least amount of computation and is suitable for scenarios with limited computing resources (such as using low-cost microcontrollers) or where there is a very high time requirement to protect the tool from instantaneous impact damage.

[0065] Method 2: Calculate the true effective value (RMS) of the signal and multiply it by the corresponding peak value factor (e.g., for a sine wave). The amplitude obtained by this method can better reflect the energy level of chatter. This method has an integral smoothing effect and is suitable for steady-state cutting scenarios where there is a lot of electromagnetic interference or random mechanical noise at the machining site and energy averaging is needed to reduce the false trigger rate.

[0066] Method 3: For Perform a Hilbert transform to obtain its instantaneous envelope, which is the envelope that changes in real time. This method offers the highest analytical accuracy but also has high computational complexity. It is suitable for precision machining scenarios that require precise tracking of the instantaneous envelope changes of non-stationary flutter signals, where high-performance digital signal processors (DSPs or FPGAs) are configured. For the extraction of such signal amplitudes, those skilled in the art can use conventional signal processing methods, which are well-known technologies in the field and will not be elaborated upon here.

[0067] S303: The control unit performs each evaluation cycle (e.g., corresponding to...) Within each sampling point (or every N sampling points), the real-time flutter amplitude value obtained in step S302 is... Compared with the preset flutter budding activation threshold in step S103 Perform numerical comparisons.

[0068] S304: When the control unit determines At this point, the control unit determines that chatter has begun or occurred, and its intensity exceeds a preset acceptable range. The control unit then determines that the activation condition has been met. Subsequently, the control unit sends an activation command to the ultrasonic drive power supply via its output interface (e.g., a GPIO pin, SPI bus, or CAN bus). This activation command can be a level-to-level signal (e.g., changing from low to high) or a specific digital command. This command triggers the ultrasonic drive power supply to switch from low-power / standby mode to high-power operating mode, causing the entire processing flow to proceed to step S400 to perform active vibration suppression and integrated finishing.

[0069] S305: If the control unit determines If the current processing state is stable and the flutter amplitude is within the safe threshold (or at the background noise level), it indicates that the current processing state is stable and the flutter amplitude is within the safe threshold (or at the background noise level). At this time, the control unit determines that the activation condition is not met, does not send an activation command, and keeps the ultrasonic drive power supply in a low power or off state. The entire processing flow returns to step S200 to continue to execute baseline processing and flutter self-sensing. The monitoring loop consisting of baseline processing and flutter self-sensing (S200) and dynamic risk assessment (S300) is continuously executed to ensure that the system can detect flutter at the moment it occurs, i.e., at S304 ( The system responds immediately when the conditions are met, and also ensures that the high-power vibration damping module will not be accidentally activated when the processing is stable, thus realizing intelligent and efficient closed-loop control until the processing is completed.

[0070] Reference Figure 4 , Figure 4 This is a schematic diagram of active vibration damping and integrated finishing according to an embodiment of the present invention.

[0071] The following is a detailed explanation of step S400 (active vibration damping and integrated finishing). Step S400 is triggered when the activation condition of step S304 is met, and may specifically include the following sub-steps:

[0072] S401: After receiving the activation command sent in step S304, the active vibration damping control unit confirms the state switch. The active vibration damping control unit sends a high-power operation command to the ultrasonic drive power supply.

[0073] S402: The ultrasonic drive power supply switches from a low-power / off state to a high-power operating mode. In this mode, the ultrasonic drive power supply generates a high-frequency drive voltage. This driving voltage is applied to a piezoelectric ceramic stack (PZT). It can be characterized as:

[0074] ;

[0075] In the formula: It is a high-power drive voltage, which is a known control command signal output by the controller to the power amplifier; This is the amplitude of the driving voltage. Much larger than the carrier excitation amplitude used for self-sensing in step S202 Its value is set to be sufficient to excite PZT to produce high-power mechanical vibrations on the order of meters to tens of micrometers. The specific selection principle is determined based on the intermittent cutting separation conditions, that is, the selected voltage. The tool needs to be driven to generate amplitude. , making the maximum vibration velocity greater than the cutting linear velocity at the workpiece rotation point This ensures that the cutting edge periodically detaches from the workpiece surface, thus disrupting the chatter regeneration mechanism. In practice, this value is typically set to 80%–95% of the ultimate withstand voltage of the piezoelectric ceramic stack (e.g., 300V–800V), a preset known constant; it is the driving frequency. The driving frequency is usually selected as the resonant frequency of the PZT or the entire intelligent tooling system (e.g., the frequency in S202). (Same or similar) to achieve the most efficient electromechanical energy conversion. The driving frequency value is determined by frequency sweep test of impedance analyzer before processing. The frequency point where the system admittance is maximum is selected and used as a known constant input into the driving control algorithm.

[0076] It is the phase of the drive signal, determined by the phase-locked loop (PLL) circuit or digital controller of the drive power supply, and is usually kept constant or follows the system resonance phase shift.

[0077] S403: The piezoelectric ceramic stack (PZT) in Under high-power excitation, high-frequency (frequency ) generation occurs through the inverse piezoelectric effect. Controlled mechanical vibration. This mechanical vibration (i.e., ultrasonic vibration) is transmitted through the tool holder to the main cutting edge of the boring-stabilizing integrated tool head. ).

[0078] This high-frequency vibration causes the main cutting edge ( The cutting process is transformed into high-frequency intermittent cutting. This intermittent cutting mode fundamentally changes the cutting dynamics, disrupting the phase-locking condition necessary for the regenerative effect that leads to chatter. Therefore, the cutting force is reset within the vibration cycle, preventing its accumulation and the formation of unstable vibrations, thus restoring stability to the cutting process and achieving the goal of actively suppressing chatter.

[0079] S404: On the main cutting edge ( While performing ultrasonic vibration-assisted cutting (i.e., active vibration suppression), the setter edge (e.g., a burnishing head or a diamond extrusion head) of the boring-setter integrated tool head sets off the main cutting edge ( The newly processed hole wall surface undergoes simultaneous integrated finishing (consolidation) treatment.

[0080] The high-frequency vibration applied in S403 also acts on the straightening blade. This vibration helps to reduce the hardening edge (). This process reduces frictional resistance between the machined hole and the hole wall surface, and promotes the plastic flow of the metal material on the hole wall surface. While actively suppressing chatter and eliminating chatter marks, this process further improves the surface quality of the machined hole wall (e.g., significantly reducing surface roughness Ra), and can introduce beneficial residual compressive stress on the hole wall surface, thereby increasing the fatigue life of the part.

[0081] S405: During the execution of step S400 (active vibration suppression and integrated finishing), the monitoring functions of step S200 (flutter self-sensing) and step S300 (dynamic risk assessment) continue to be executed in parallel.

[0082] At this time, the flutter self-sensing module (S200) is in Under the background of high-power drive signal, continuously monitor the feedback electrical signal of PZT. Given Since it is also a high-frequency signal, the flutter self-sensing module needs to use advanced signal processing techniques such as synchronous demodulation or frequency domain filtering to distinguish the response from the drive signal from the signal components caused by low-frequency flutter, thereby demodulating the flutter characteristic signal. And demodulate the flutter characteristic signal. Obtain real-time (suppressed) flutter amplitude values. .

[0083] The comparison logic of the active vibration damping control unit (S300) is switched, and the real-time amplitude is instead... Compared with the preset model degradation safety threshold in step S103 Perform consecutive comparisons. As long as... The control unit determines that the flutter risk has not been completely eliminated (i.e., although the flutter has been suppressed, the amplitude is still higher than the minimum safe level). Therefore, the system remains in step S400, and the ultrasonic drive power supply continues to output a high-power drive voltage. This is to maintain active vibration damping and integrated finishing. The state of S400 will continue until the triggering condition of step S500 is met.

[0084] Reference Figure 5 , Figure 5 This is a schematic diagram of the state switching logic of a processing method according to an embodiment of the present invention.

[0085] The following section elaborates on step S500 (model degradation evaluation and state reversal). Step S500 is executed in parallel with step S400 (active vibration damping and integrated fine-tuning) and is used to evaluate when to terminate high-power active vibration damping. Specifically, it may include the following sub-steps:

[0086] S501: During the execution of step S400, the active vibration suppression control unit (S300) executes the comparison logic described in S405 in parallel and continuously. This control unit will use the real-time acquired, suppressed flutter amplitude value... (This value is provided by the flutter self-sensing module operating under high power conditions as described in S405) and the model degradation safety threshold preset in step S103. Conduct continuous comparisons.

[0087] S502: The control unit performs a model degradation assessment. When the control unit determines... At this point, the condition indicates that the active vibration suppression in step S400 has taken effect, and flutter has been successfully suppressed to below a safe level. In one embodiment, to prevent the system from... exist For frequent state switching (i.e., jitter) caused by small fluctuations near the threshold, the evaluation logic may include a time-delay confirmation mechanism.

[0088] Specifically, the control unit must not only determine This instantaneous condition also requires determining whether the state has persisted for a preset stable time. .in, This is a preset stabilization time threshold (e.g., 50 milliseconds or several jitter cycles). This mechanism ensures that the control unit only triggers subsequent state revert when it confirms that the jitter has been stabilized and eliminated, rather than being a momentary fluctuation.

[0089] S503: When the model degradation evaluation condition in step S502 is met (e.g., ... Duration less than or equal to The control unit determines that the state cut-off condition has been met. The control unit then sends a degradation command or a stop high-power drive command to the ultrasonic drive power supply through its output interface. This command causes the ultrasonic drive power supply to stop the high-power drive voltage in S402. The output of .

[0090] S504: After receiving the degradation command, the ultrasonic drive power supply switches back to the low-power operation state or the off state described in step S201. At this time, the high-power ultrasonic vibration of the PZT stops, and the active vibration suppression in step S403 and the integrated finishing in step S404 also stop.

[0091] The entire processing flow switches back to step S200, and the system returns to the baseline processing and chatter self-sensing state. This forms a complete closed-loop control of "sensing (S200) - activation (S300) - suppression (S400) - evaluation (S500) - degradation (S500) - re-sensing (S200)". This logic ensures that high-power vibration suppression is activated only when necessary (triggered by S304) and stops immediately after the risk is eliminated (triggered by S500), thereby significantly reducing the additional energy consumption of the system throughout the processing while ensuring processing quality.

[0092] The following is a specific embodiment designed to machine precision valve core holes in aerospace housing parts (e.g., made of high-temperature alloys or aluminum alloys).

[0093] In this embodiment, the intelligent tooling system used in this method includes a boring bar with an integrated piezoelectric ceramic stack (PZT) and a composite tool head containing a main cutting edge and an integrated settling edge (e.g., a burnishing head).

[0094] Before processing begins, the control system pre-sets two key vibration amplitude thresholds based on the processing requirements of the valve core hole: a high flutter bud activation threshold and a very low model degradation safety threshold.

[0095] At the start of machining, the system performs baseline machining and chatter self-sensing. The boring bar cuts the hole wall at a normal speed and feed rate. Simultaneously, the chatter self-sensing module is activated, applying a weak high-frequency detection excitation signal to the PZT and continuously monitoring its feedback electrical signal to sense the cutting status.

[0096] In the initial stages of machining (e.g., in the shallow part of a hole), the cutting system exhibits good rigidity, and the machining process is stable. The active vibration suppression control unit, by demodulating the feedback signal, obtains a real-time chatter amplitude that is far below the set chatter bud activation threshold. The control unit determines that the condition is not met and does not issue an activation command. The system maintains this low-power monitoring and baseline machining state.

[0097] When the tool cuts to a depth in the hole (e.g., increased overhang leads to a decrease in system rigidity), cutting force fluctuations begin to trigger regenerative chatter. The chatter self-sensing module immediately detects a low-frequency chatter signal in the feedback signal that is significantly different from the high-frequency detection excitation frequency.

[0098] The active vibration suppression control unit (i.e., the dynamic risk assessment module) calculates the amplitude of the low-frequency flutter in real time and compares it with a threshold. When the control unit detects that the amplitude has increased and exceeded the preset flutter bud activation threshold, the control unit determines that flutter has occurred and is beyond the acceptable range.

[0099] The control unit immediately sends an activation command (i.e., triggers active vibration suppression) to the ultrasonic drive power supply. The ultrasonic drive power supply then switches from low-power detection mode to high-power drive mode, applying a high-amplitude, high-frequency (e.g., matching the system resonant frequency) drive voltage to the PZT.

[0100] Driven by high power, PZT drives the entire tool head (including the main cutting edge and the setter edge) to generate high-frequency ultrasonic vibration. The cutting behavior of the main cutting edge thus transforms into high-frequency intermittent cutting, which disrupts the conditions for the regenerative effect of chatter, allowing the cutting process to quickly return to stability. Simultaneously, with the assistance of ultrasonic vibration, the setter edge performs synchronous burnishing / extrusion (i.e., integrated finishing) on ​​the freshly cut surface, eliminating any slight chatter marks that may have occurred and improving surface roughness.

[0101] During active vibration suppression and integrated fine-tuning, the monitoring functions of the self-sensing module and control unit did not cease. The control unit continuously monitored the real-time flutter amplitude after suppression (which was rapidly suppressed under high-power drive) and compared it with the model degradation safety threshold.

[0102] As long as the real-time amplitude remains above the safety threshold, the control unit determines that the risk of chatter has not been completely eliminated and maintains the high power output of the ultrasonic drive power supply to ensure processing quality.

[0103] Subsequently, when the control unit detects that the real-time amplitude has been suppressed to below the model degradation safety threshold, the model degradation evaluation logic is triggered. The control unit waits for a short, preset stabilization time (e.g., tens of milliseconds) to confirm that the chatter has been stably eliminated, rather than being a momentary signal fluctuation.

[0104] Once the real-time amplitude remains stable below or equal to the safety threshold for a period exceeding the preset stabilization time, the control unit determines that the state cut-off condition has been met. The control unit then sends a degradation command to the ultrasonic drive power supply.

[0105] The ultrasonic drive power supply stops high-power output, the PZT stops high-frequency vibration, and the active vibration suppression and integrated finishing also cease. The entire processing flow seamlessly switches back to baseline processing and chatter self-sensing state, and the system returns to normal baseline processing while maintaining low-power chatter self-sensing monitoring. This cycle continues throughout the entire processing until the hole processing task is completed.

Claims

1. A method for machining valve core holes in aircraft housing parts, characterized in that, Includes the following steps: S100, preparation steps: Pre-set a flutter activation threshold and a safety threshold; S200, Baseline Machining and Monitoring Steps: Baseline boring is performed using an intelligent tool system integrating a piezoelectric ceramic stack and a cutting head. At the same time, the machining status is monitored in real time using the piezoelectric ceramic stack, feedback electrical signals are obtained, and chatter characteristic signals are demodulated from the feedback electrical signals. S300, Dynamic risk assessment step: Obtain the real-time flutter amplitude value of the flutter characteristic signal, and determine whether the real-time flutter amplitude value is greater than the flutter activation threshold; S400, Active vibration suppression step: If the real-time chatter amplitude is greater than the chatter activation threshold, a high-power driving voltage is applied to the piezoelectric ceramic stack to excite the cutter head to generate high-frequency mechanical vibration in order to perform active vibration suppression; S500, State Switchback Step: During active vibration suppression, the real-time flutter amplitude is continuously monitored. If the real-time flutter amplitude decreases to no more than the safety threshold, the high-power drive voltage is stopped, and the baseline processing and monitoring steps are returned to be executed.

2. The method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, The baseline processing and monitoring step includes a method for real-time monitoring of the processing status using the piezoelectric ceramic stack, comprising: A high-frequency carrier excitation voltage is applied to the piezoelectric ceramic stack; When low-frequency flutter occurs during processing, the mechanical vibration acts on the piezoelectric ceramic stack through the positive piezoelectric effect, causing its electrical impedance to change periodically, thereby modulating the feedback electrical signal. The modulated feedback electrical signal is received, and the flutter characteristic signal is extracted through a signal demodulation algorithm.

3. The method for machining valve core holes in aircraft housing parts according to claim 2, characterized in that, The signal demodulation algorithm includes envelope detection or a demodulation method based on Hilbert transform, used to extract flutter characteristic signals representing the real-time flutter amplitude, frequency, and phase of the low-frequency flutter from the amplitude envelope of the modulated feedback electrical signal.

4. The method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, In the active vibration suppression step, the cutter head includes a main cutting edge, and the high-frequency mechanical vibration transforms the cutting process of the main cutting edge into high-frequency intermittent cutting, thereby disrupting the regenerative effect conditions that lead to chatter.

5. A method for machining valve core holes in aircraft housing parts according to claim 4, characterized in that, The cutter head also includes a setter blade. While the main cutting edge performs active vibration suppression, the setter blade, with the assistance of the high-frequency mechanical vibration, performs a synchronous integrated finishing process on the hole wall surface that has been processed by the main cutting edge.

6. The method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, In the preparation step, the safety threshold is set to be lower than the flutter activation threshold, so that when the real-time flutter amplitude fluctuates near the flutter activation threshold, a hysteresis interval is formed to prevent frequent triggering and cancellation of active vibration suppression.

7. A method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, The preparation steps also include: A chatter risk database is established to characterize the risk level of machining chatter under different machining depths and cutting parameters.

8. A method for machining valve core holes in aircraft housing parts according to claim 7, characterized in that, The flutter risk database is established through one of the following methods: Based on the finite element simulation method, the dynamic characteristics of the machining system are simulated, and the chatter stability lobe diagram is drawn by combining the cutting dynamics model to construct the system. Based on the analysis of historical processing data, an empirical mapping relationship or machine learning model is established between flutter characteristics and processing parameters to generate [the data].

9. A method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, In the state reversal step, determining the condition that the real-time jitter amplitude value has decreased to no more than the safety threshold also includes determining that the condition has lasted for a preset stable time.

10. A method for machining valve core holes in aircraft housing parts according to claim 1, characterized in that, The intelligent tooling system has a boring-solidifying integrated tool head, which integrates the main cutting edge and the solidifying edge.

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