Multi-cycle cryogenic vibration compound aging size stabilization treatment process for mold ejector pin

Abstract

This application relates to the field of mold ejector pin processing technology, and particularly to a multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins. The method includes: obtaining the batch feature vector of the current batch of ejector pins; determining processing safety weights, processing efficiency weights, and robustness weights based on the batch feature vector; generating a batch target evaluation function based on the processing safety weights, processing efficiency weights, and robustness weights; selecting the process mode with the lowest overall processing cost based on the batch target evaluation function as the first process mode for the current batch; obtaining the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins; determining the corresponding vibration threshold based on the real-time dynamic modulus; and sending a vibration signal based on the real-time resonance sharpness, real-time dynamic modulus, and vibration threshold. Therefore, the method provided in this application can solve the problems of lacking real-time safety gating or excessively high costs preventing mass production applications in cryogenic vibration aging treatment.

Description

Technical Field

[0001] This application belongs to the field of mold ejector pin processing technology, and in particular relates to a multi-cycle deep cryogenic vibration composite aging dimensional stabilization process for mold ejector pins. Background Technology

[0002] In precision injection and die casting molds, ejector pins are key ejection components, and their dimensional stability directly affects mold life and product precision.

[0003] Ejector pins generate significant residual stress during quenching, grinding, and other machining processes. This stress is slowly released during subsequent storage and service, leading to micron-level dimensional drift and ultimately failure due to jamming or excessive clearance. Existing technologies often employ cryogenic treatment and vibration aging to reduce residual stress. However, current technologies lack a method for real-time, safe vibration gating of each ejector pin in a cryogenic environment, resulting in either reluctance to vibrate or micro-damage caused by improper vibration. Furthermore, highly individualized strategy decision-making requires expensive and time-consuming online precise modeling and multi-strategy parallel computation for each low-value ejector pin, making the system cost severely disproportionate to the pin's value and impractical for industrial economics.

[0004] Therefore, existing technologies suffer from problems such as lack of real-time safety gating in cryogenic vibration aging treatment or excessive cost preventing mass production applications. Summary of the Invention

[0005] This application provides a multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins, which can solve the problems of lack of real-time safety gating or excessive cost preventing mass production in cryogenic vibration aging treatment.

[0006] In a first aspect, embodiments of this application provide a multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins, including: Obtain the batch feature vector of the current batch of ejector pins; wherein, the batch feature vector is used to reflect the resonance characteristics and geometric features of the ejector pins; Based on the batch feature vector, determine the processing security weight, processing efficiency weight, and robustness weight; A batch target evaluation function is generated based on the processing security weight, the processing efficiency weight, and the robustness weight; According to the batch target evaluation function, the process mode with the lowest overall processing cost is selected from the candidate mode set containing at least two process modes and is used as the first process mode of the current batch. When performing vibration treatment according to the first process mode, the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins are obtained at fixed intervals. The corresponding vibration threshold is determined based on the real-time dynamic modulus. Vibration signals are sent based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold.

[0007] The technical solutions described in this application embodiment have at least the following technical effects: The multi-cycle cryogenic vibration combined aging dimensional stabilization process for mold ejector pins provided in this application embodiment obtains the batch feature vector of the current batch of ejector pins; determines the processing safety weight, processing efficiency weight, and robustness weight based on the batch feature vector; generates a batch target evaluation function based on the processing safety weight, processing efficiency weight, and robustness weight; selects the process mode with the minimum comprehensive processing cost from a candidate mode set containing at least two process modes, based on the batch target evaluation function, as the first process mode for the current batch; when performing vibration processing according to the first process mode, obtains the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins at fixed intervals; determines the corresponding vibration threshold based on the real-time dynamic modulus; and sends a vibration signal based on the real-time resonance sharpness, real-time dynamic modulus, and vibration threshold. Therefore, the multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins provided in this application extracts batch feature vectors reflecting the resonance characteristics and geometric features of the ejector pins, and generates a batch target evaluation function that integrates the weights of processing safety, processing efficiency, and robustness. This enables the automatic selection of the first process mode that best matches the characteristics of the current batch from multiple process candidate modes. At the same time, during the vibration processing, the vibration threshold is dynamically determined by real-time resonance sharpness and real-time dynamic modulus, and the vibration signal is controlled in a closed loop. This allows the selection of the process mode and the execution of vibration parameters to be adaptively adjusted according to the actual material characteristics of different batches of ejector pins. This helps to solve the problem of over-vibration damage or under-vibration caused by batch differences in fixed parameter schemes, and at the same time ensures the consistency of processing safety, efficiency, and results in mass production scenarios.

[0008] In one possible implementation of the first aspect, determining the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector includes: Based on the aspect ratio in the batch feature vector, the bending instability risk component is determined using a preset slender rod bending instability risk function. Based on the degree of deviation of the resonance sharpness value in the batch feature vector from the historical median data, the cumulative risk adjustment coefficient is determined. The result of correcting the bending instability risk component with the cumulative risk adjustment coefficient is used as the processing safety weight.

[0009] In one possible implementation of the first aspect, determining the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector further includes: Calculate the overall deviation between the batch feature vector and the preset standard reference vector; Based on the preset positive correlation mapping relationship, the robustness weight value corresponding to the comprehensive deviation is obtained.

[0010] In one possible implementation of the first aspect, determining the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector further includes: The processing efficiency weight is obtained by subtracting the sum of the processing security weight and the robustness weight from the preset total weight value.

[0011] In one possible implementation of the first aspect, selecting the process mode with the lowest overall processing cost from a candidate mode set containing at least two process modes, based on the batch target evaluation function, as the first process mode for the current batch, includes: For each candidate process mode in the preset candidate mode set, its pre-calibrated safety cost, efficiency cost, and robustness cost are obtained, and then substituted into the batch target evaluation function to calculate the comprehensive processing cost. The candidate process mode with the lowest overall processing cost is determined as the first process mode.

[0012] In one possible implementation of the first aspect, obtaining the batch feature vector of the current batch of thimbles includes: A sweep frequency excitation was applied to the sample pin to acquire the first vibration response signal; Extract the first bending resonant frequency and the first half-power bandwidth from the first vibration response signal; Based on the first bending resonance frequency and the first half-power bandwidth, calculate the resonance sharpness value that reflects the micro-defects and the original stress state. The resonance sharpness value and the aspect ratio of the sample pin are used as the batch feature vector.

[0013] In one possible implementation of the first aspect, acquiring the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins at fixed intervals includes: The second vibration response signal is acquired at fixed time intervals via the vibration measurement module; The current second bending resonance frequency and second half-power bandwidth are obtained based on the second vibration response signal; The real-time resonance sharpness and real-time dynamic modulus are calculated based on the second bending resonance frequency and the second half-power bandwidth.

[0014] In one possible implementation of the first aspect, sending the vibration signal based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold includes: The ratio of the real-time resonance sharpness to the initial resonance sharpness value is calculated to obtain the resonance sharpness retention rate; The ratio of the real-time dynamic modulus to the reference modulus at the same temperature is calculated to obtain the modulus retention rate; The vibration signal is sent when the resonance sharpness retention rate is less than or equal to the resonance sharpness threshold in the vibration threshold, and the modulus retention rate is greater than or equal to the modulus threshold in the vibration threshold.

[0015] In one possible implementation of the first aspect, determining the vibration threshold based on the real-time dynamic modulus includes: Obtain the cumulative vibration time of the ejector pin; If it is determined that the safety boundary condition has not been exceeded based on the real-time dynamic modulus and the cumulative vibration time, then the first threshold corresponding to the first process mode is used as the current vibration threshold; wherein, the safety boundary condition refers to the preset upper limit of the cumulative vibration time or the preset upper limit of the modulus reduction of the real-time dynamic modulus relative to the initial dynamic modulus at the start of the processing. If the vibration exceeds the safety boundary condition based on the real-time dynamic modulus and the cumulative vibration time, then the second threshold corresponding to the second process mode is used as the current vibration threshold.

[0016] In one possible implementation of the first aspect, the method further includes: When the safety boundary conditions are exceeded, the subsequent vibration operation of the first process mode is stopped; Subsequent vibration operations are performed according to the process parameters of the second process mode.

[0017] Secondly, embodiments of this application provide a multi-cycle cryogenic vibration combined aging dimensional stabilization treatment apparatus for mold ejector pins, comprising: The first acquisition module is used to acquire the batch feature vector of the current batch of ejector pins; wherein, the batch feature vector is used to reflect the resonance characteristics and geometric features of the ejector pins; The weighting module is used to determine the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector. The batch target evaluation function module is used to generate a batch target evaluation function based on the processing security weight, the processing efficiency weight, and the robustness weight. The first process mode module is used to select the process mode with the lowest overall processing cost from a candidate mode set containing at least two process modes, based on the batch target evaluation function, as the first process mode for the current batch. The second acquisition module is used to acquire the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins at fixed intervals when vibration processing is performed according to the first process mode. The vibration threshold module is used to determine the corresponding vibration threshold based on the real-time dynamic modulus. The vibration signal module is used to send vibration signals based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold.

[0018] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any one of the first aspects above.

[0019] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the first aspects above.

[0020] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any one of the first aspects above.

[0021] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic flowchart of a multi-cycle cryogenic vibration composite aging dimensional stabilization treatment process for mold ejector pins provided in an embodiment of this application; Figure 2 This is a schematic diagram of the implementation process of steps S100, S200 and S400 in the multi-cycle cryogenic vibration composite aging dimensional stabilization treatment process of mold ejector pin provided in an embodiment of this application; Figure 3 This is a schematic diagram of the implementation process of steps S500 and S700 in the multi-cycle cryogenic vibration composite aging dimensional stabilization treatment process of mold ejector pins provided in an embodiment of this application. Figure 4 This is a schematic diagram of the implementation process of step S600 in the multi-cycle cryogenic vibration composite aging dimensional stabilization treatment process for mold ejector pins provided in an embodiment of this application; Figure 5 This is a schematic diagram of the multi-cycle deep cryogenic vibration composite aging dimensional stabilization treatment device for mold ejector pins provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0024] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0025] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0026] In related technologies, significant residual stress is generated in ejector pins during quenching, grinding, and other processing. This stress is slowly released during subsequent storage and service, leading to micron-level dimensional drift and ultimately failure due to jamming or excessive clearance. Existing technologies often employ methods such as cryogenic treatment and vibration aging to reduce residual stress. However, existing technologies do not provide a method for real-time safe vibration gating of each ejector pin in a cryogenic environment, resulting in a reluctance to vibrate or micro-damage caused by improper vibration. Furthermore, if highly individualized strategy decision-making schemes are adopted, expensive and time-consuming online accurate modeling and multi-strategy parallel calculations are required for each low-value ejector pin. The system cost is severely mismatched with the value of the ejector pin, making it economically infeasible in industrial applications.

[0027] To address the aforementioned issues, this application provides a multi-cycle cryogenic vibration combined with aging dimensional stabilization process for mold ejector pins. In this method, the batch feature vector of the current batch of ejector pins is obtained; based on the batch feature vector, processing safety weight, processing efficiency weight, and robustness weight are determined; a batch target evaluation function is generated based on the processing safety weight, processing efficiency weight, and robustness weight; according to the batch target evaluation function, the process mode with the lowest overall processing cost is selected from a candidate mode set containing at least two process modes as the first process mode for the current batch; during vibration processing according to the first process mode, the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins are obtained at fixed intervals; a corresponding vibration threshold is determined based on the real-time dynamic modulus; and a vibration signal is sent based on the real-time resonance sharpness, real-time dynamic modulus, and vibration threshold. Therefore, the multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins provided in this application extracts batch feature vectors reflecting the resonance characteristics and geometric features of the ejector pins, and generates a batch target evaluation function that integrates the weights of processing safety, processing efficiency, and robustness. This enables the automatic selection of the first process mode that best matches the characteristics of the current batch from multiple process candidate modes. At the same time, during the vibration processing, the vibration threshold is dynamically determined by real-time resonance sharpness and real-time dynamic modulus, and the vibration signal is controlled in a closed loop. This allows the selection of the process mode and the execution of vibration parameters to be adaptively adjusted according to the actual material characteristics of different batches of ejector pins. This helps to solve the problem of over-vibration damage or under-vibration caused by batch differences in fixed parameter schemes, and at the same time ensures the consistency of processing safety, efficiency, and results in mass production scenarios.

[0028] The multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the executing entity of the multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0029] For example, the electronic device is communicatively connected to a pneumatic / electric clamp and an electric / electromagnetic / piezoelectric vibrator used to fix the ejector pin so that it does not slip during excitation. The arc-shaped copper pad jaws inside the pneumatic / electric clamp clamp the lower outer cylindrical surface of the ejector pin with clearance fit. The upper end of the ejector rod is threadedly connected to the ejector rod head of the electric / electromagnetic / piezoelectric vibrator. The electronic device can be an embedded control system, an industrial computer, a programmable logic controller, a distributed control system, etc., but is not limited to these.

[0030] To better understand the multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins provided in this application embodiment, the specific implementation process of the multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins provided in this application embodiment will be described below by way of example.

[0031] Figure 1 This illustration shows a schematic flowchart of the multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins provided in an embodiment of this application. The multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins includes: S100: Obtain the batch feature vector of the current batch of ejector pins. The batch feature vector is used to reflect the resonance characteristics and geometric features of the ejector pins.

[0032] For example, n sample pins (e.g., n=3) can be randomly selected from the batch and clamped one by one onto the V-shaped support fixture inside the cryogenic cavity. The piezoelectric excitation module is then controlled to input a peak voltage V to each sample pin. p A uniform white noise sweep signal of 0.1V was used, with a frequency range of 20Hz to 5000Hz and a sweep duration of t=1s. The signal was repeatedly sampled and averaged to suppress random noise. A laser vibration module synchronously acquired the vibration velocity response signal v(t) at the center of the pin at a sampling rate of at least 10kHz. A Fast Fourier Transform was performed on the acquired signal to obtain the frequency response function H(f), from which the first bending resonance frequency f0 (i.e., the frequency corresponding to the first peak of the amplitude-frequency curve) was identified. The resonance sharpness Q was calculated using the half-power bandwidth method: first, the resonance peak value |H(f0)| was found, then the amplitude decreased to |H(f0)| / Given two corresponding frequency points f1 and f2, Q = f0 / (f2−f1). After calculating for each of the n samples, the median is taken as the batch system-level reference resonant sharpness Q. sys0 The actual length L and diameter D of the sample ejector pin are measured, and the length-to-diameter ratio L / D is calculated. Finally, the batch feature vector is F. batch ={Q sys0 ,L / D}.

[0033] S200 determines the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector.

[0034] For example, based on Euler's buckling theory for slender rods, the critical buckling stress σ can be determined. cr ∝(D / L) 2 Based on a standard reference length-to-diameter ratio (L / D)ref=15, and with the current batch having L / D=25, the buckling risk amplification factor is (15 / 25)²=0.36, meaning the critical stress is only 36% of the standard bar. As specified in the pre-defined mapping table, when L / D ∈ [20,30], the foundation safety weight W... s_base =0.60, Q sys0 =3200, therefore α=1.0+200 / 10000=1.02, take α=1.1. The processing security weight is obtained: W s =Ws_base ×α = 0.60 × 1.1 = 0.66. Calculate the batch feature vector F. batch Compared with standard reference vectors (such as F) std ={Q std =3000,(L / D) std =15}) comprehensive deviation Ω. The Euclidean distance is calculated after normalizing both dimensions: Ω= For example: Ω = (200 / 3000) 2 +(10 / 15) 2 =0.0044 + 0.4444 = 0.4488 ≈ 0.67. After normalizing to the [0,1] interval, take Ω. norm =0.35 (because the preset upper limit is 1). According to the preset mapping table, Ω norm When ∈ [0.3, 0.4], the robustness weight Wr = 0.25. Processing efficiency weight: W e =1−W s -W r =1−0.66−0.25=0.09.

[0035] S300 generates a batch target evaluation function based on processing security weights, processing efficiency weights, and robustness weights.

[0036] For example, it can be based on the processing security weight W s Processing efficiency weight W e and robustness weight W r Obtain the batch target evaluation function, such as J batch =W s C s +W e C e +W r C r , where C s For the sake of security, C e For the sake of efficiency, C r This comes at the cost of robustness. s =max(0,(R realtime -R safe ) / R safe ) 2 R realtime R represents the current resonance sharpness of the target pin. safe The safety threshold is obtained by multiplying the initial resonance sharpness value of the sample pin by a safety factor. C e =n current / n target , where n currentn represents the number of cryogenic and vibrational cycles completed. target The preset target number of iterations. (C) r =σ R / μ R , where σ R μ represents the standard deviation of the resonance sharpness of the current batch of ejector pins. R This represents the average resonance sharpness of the current batch of ejector pins.

[0037] S400: Based on the batch objective evaluation function, select the process mode with the lowest overall processing cost from the candidate mode set containing at least two process modes, and use it as the first process mode for the current batch.

[0038] For example, a candidate pattern set S = {S} can be preset. A ,S B ,S C ,…}, each process mode S i It includes a complete set of process parameters: vibration threshold, amplitude limit, number of cycles, cumulative vibration time limit, and modulus reduction limit. For each process mode, its comprehensive processing cost is calculated according to the batch objective evaluation function, and the process mode with the lowest comprehensive processing cost is selected as the first process mode for this batch.

[0039] S500, when performing vibration processing according to the first process mode, acquires the real-time resonance sharpness and real-time dynamic modulus of the ejector pins of the current batch at fixed intervals.

[0040] For example, in batch production, after each ejector pin enters the cryogenic station, it can undergo multi-cycle cryogenic and vibration treatment according to the first process mode. During the cryogenic holding or cooling stage of each cycle (temperature range −180℃ to −150℃), the laser vibration measurement module continuously collects the vibration velocity signal v(t) at the measuring point in the middle of the ejector pin at a fixed sampling interval Δt=0.5s. For each signal segment collected (usually 256 sampling points, corresponding to a data window of approximately 0.05s), a short-time Fourier transform (STFT) is performed to extract the bending resonance frequency f at the current temperature. curr and the corresponding real-time resonance sharpness Q curr =f curr / Δf curr ,where Δf curr This represents the half-power bandwidth of the amplitude-frequency curve at the current temperature. The real-time dynamic modulus E is calculated using the relationship between the bending resonant frequency and the dynamic elastic modulus. curr =(2πL 2 f curr / 1.875 2 ) 2 ρA / I, where I=πD 4 / 64 is the moment of inertia of the cross section, A=πD2 / 4 represents the cross-sectional area, and ρ represents the material density.

[0041] S600 determines the corresponding vibration threshold based on the real-time dynamic modulus.

[0042] It is understandable that the vibration threshold includes the modulus threshold and the resonance sharpness threshold.

[0043] It is understandable that the real-time dynamic modulus E curr This reflects the current structural integrity of the ejector pin. If E curr A significant drop compared to the reference value indicates that the material has undergone significant microplastic softening or microcrack initiation. In this case, vibration tolerance conditions should be tightened; for example, when E... curr Relative to E ref When the reduction δE < 3%, the vibration threshold is the original preset value; when 3% ≤ δE < 5%, the vibration threshold is 80% of the original preset value; when δE ≥ 5%, vibration is prohibited.

[0044] The S700 sends vibration signals based on real-time resonance sharpness, real-time dynamic modulus, and vibration threshold.

[0045] For example, it could be if Q curr / Q init ≤Q th If δE < 3%, then a vibration signal is sent to the exciter; if Q curr / Q init ≤Q th However, if 3% ≤ δE < 5%, it is considered a restricted permission, and a reduced amplitude vibration signal is sent; if Q curr / Q init Q th If δE ≥ 5%, then no vibration signal is transmitted, where Q curr / Q init Q is the ratio of the real-time resonance sharpness to the initial resonance sharpness value. th It is the resonance sharpness threshold, and δE is the decrease in real-time dynamic modulus relative to the reference modulus at the same temperature.

[0046] In one possible implementation, please refer to Figure 2 S200, based on batch feature vectors, determines processing security weights, processing efficiency weights, and robustness weights, including: S210, based on the aspect ratio in the batch feature vector, uses a preset slender rod bending instability risk function to determine the bending instability risk component.

[0047] For example, the bending instability risk component R can be obtained by using a piecewise power-law mapping based on a pre-defined slender rod bending instability risk function. buckle For example, R buckle = , 15<L / D≤30, wherein L / D is the aspect ratio.

[0048] S220, determining a cumulative risk adjustment coefficient based on the degree of deviation of the resonance sharpness value in the batch feature vector from the historical median data.

[0049] For example, the resonance sharpness value Q can be extracted from the batch eigenvector sys0 , which is compared with the historical median data Q h to determine a cumulative risk adjustment coefficient α according to the deviation direction and deviation amplitude. For example, α=1.0+β (Q sys0 −Q h ) / Q h , wherein β is a sensitivity coefficient, and β=0.5 is obtained through experimental calibration.

[0050] S230, taking the result of the bending instability risk component corrected by the cumulative risk adjustment coefficient as the processing safety weight.

[0051] For example, the bending instability risk component can be multiplied by the cumulative risk adjustment coefficient to obtain the final processing safety weight.

[0052] If individual modeling and decision-making are performed for each ejector pin, the system needs to configure expensive online modeling and multi-strategy parallel computing for each low-value ejector pin, the total cost far exceeds the value of the ejector pin itself, and it is economically unfeasible. If fixed parameters are adopted, the difference between batches is completely ignored, and high-risk batches may be scrapped in batches due to blind vibration. Through the above steps S210 to S230, the decision is completed at one time at the batch level, and the single-piece processing cost is controlled to a level close to that of conventional mass production processes, which perfectly matches the production characteristics of low value and large batch of ejector pins.

[0053] In a possible implementation, please refer to Figure 2 , S200, determining the processing safety weight, processing efficiency weight and robustness weight based on the batch feature vector, further comprising: S240, calculating the comprehensive deviation degree between the batch feature vector and a preset standard reference vector.

[0054] For example, the batch feature vector and the preset standard reference vector can be normalized: δ Q =|Q sys0 −Q std | / Q std ,δ L / D =|(L / D)−(L / D) std | / (L / D) std , then the comprehensive deviation degree Ω is obtained by Euclidean distance synthesis raw = .

[0055] S250, based on the preset positive correlation mapping relationship, obtains the robustness weight value corresponding to the comprehensive deviation.

[0056] For example, the overall deviation Ω can be converted into a robustness weight W through a preset positive correlation mapping relationship. r The default mapping function is: W r =W r,min +(W r,max -W r,min )×ln(1+k Ω) / ln(1+k), where W r,min W is the minimum value of the robustness weight. r,max Ω represents the maximum value of the robustness weight, and k=3.0 is the curve steepness coefficient. Multiple discrete Ω values ​​corresponding to W can be preset. r The value is obtained by nearest neighbor interpolation at runtime.

[0057] Through the above steps S240 to S250, the batch characteristics are automatically driven to allocate weights, enabling the same process system to adaptively cover the entire spectrum from standard batches to extreme batches without the need for manual intervention to adjust parameters.

[0058] In one possible implementation, please refer to Figure 2 S200, which determines processing security weights, processing efficiency weights, and robustness weights based on batch feature vectors, also includes: S260, subtract the sum of the processing security weight and robustness weight from the preset total weight value to obtain the processing efficiency weight.

[0059] For example, the processing efficiency weight W e =W total -W s -W r Among them, W total =1.0 is the preset total weight value, W s W represents the processing security weights output by S230. r The robustness weights output by S250.

[0060] Through the above step S260, when the batch risk is high, the processing efficiency weight is compressed and the system selects a conservative strategy; when the batch risk is low, the system has sufficient room for efficiency optimization and can select a fast strategy.

[0061] In one possible implementation, please refer to Figure 2 S400, based on the batch objective evaluation function, selects the process mode with the lowest overall processing cost from the candidate mode set containing at least two process modes, and uses it as the first process mode for the current batch, including: S410: For each candidate process mode in the preset candidate mode set, obtain its pre-calibrated safety cost, efficiency cost, and robustness cost, and substitute them into the batch objective evaluation function to calculate the comprehensive processing cost.

[0062] For example, for each candidate process mode in a preset candidate mode set, its pre-calibrated three-dimensional cost nominal value (C) can be read. s C e C r Substituting these values ​​into the batch objective evaluation function, the corresponding comprehensive processing cost is calculated. The batch objective evaluation function is: J batch =W s C s +W e C e +W r C r , where C s C e C r These represent the security cost, efficiency cost, and robustness cost, respectively, all ranging from [0,1].

[0063] S420 identifies the candidate process mode with the lowest overall processing cost as the first process mode.

[0064] For example, the strategy with the lowest overall processing cost can be directly selected as the first process mode.

[0065] Through the above steps S410 to S420, the evaluation function is applied to the candidate process modes in batches to output the optimal process mode. Furthermore, the corresponding process mode can be output for different batches.

[0066] In one possible implementation, please refer to Figure 2 S100, obtain the batch feature vector of the current batch of pins, including: S110, apply a sweep frequency excitation to the sample pin to acquire the first vibration response signal.

[0067] For example, the piezoelectric excitation module integrated into the cryogenic treatment device can be controlled to apply a uniform white noise sweep frequency signal to the central measuring point of the sample pin. The signal is a linear sweep frequency sine wave with a frequency range of 20Hz to 5000Hz, a sweep rate of 100Hz / s (i.e., the frequency increases by 100Hz per second), and a single sweep duration of t = (5000−20) / 100 = 49.8 ≈ 50 seconds. To suppress the masking of weak resonance peaks by random noise, each sample pin is swept multiple times (e.g., 3 times), and multiple (e.g., 3 segments) of independent first vibration response signals are collected.

[0068] S120, extract the first bending resonant frequency and the first half-power bandwidth from the first vibration response signal.

[0069] For example, the frequency sweep response signals of each sample pin can be truncated into 50-second effective segments, and a Hanning window can be applied to each segment to suppress spectral leakage. A short-time Fourier transform (STFT) is performed on the windowed signal, and the STFT results are averaged along the time axis to obtain the average amplitude-frequency response curve of the pin. The global maximum amplitude point is searched within the range of 20Hz to 5000Hz, and its corresponding frequency is the first bending resonance frequency f0. After obtaining the resonance peak value |H(f0)|, the amplitude |H(f0)| corresponding to the half-power point is calculated. ≈0.707∣H(f0)∣. On the amplitude-frequency curve, search for the frequency points f1 and f2 where the amplitude first drops to 0.707 times the peak value on the low-frequency and high-frequency sides respectively. Then the first half-power bandwidth Δf = f2−f1.

[0070] S130, based on the first bending resonance frequency and the first half-power bandwidth, calculate the resonance sharpness value that reflects the micro-defects and the original stress state.

[0071] For example, the resonance sharpness value can be obtained by dividing the first bending resonance frequency by the first half-power bandwidth.

[0072] S140 uses the resonance sharpness value and the aspect ratio of the sample pin as the batch feature vector.

[0073] For example, the resonance sharpness value and the aspect ratio of the sample pin can be combined into a two-dimensional feature vector, namely the batch feature vector.

[0074] Through steps S110 to S140 above, the laser vibration module, a standard configuration of the cryogenic processing device (used to monitor intracavitary temperature uniformity), can be reused for vibration acquisition without additional hardware investment. The median strategy using multiple samples helps eliminate the influence of outliers and also helps control acquisition costs.

[0075] In one possible implementation, please refer to Figure 3 S500 acquires the real-time resonance sharpness and real-time dynamic modulus of the ejector pins in the current batch at fixed intervals, including: S510 acquires the second vibration response signal through the vibration measurement module at fixed time intervals.

[0076] For example, the laser vibration module can acquire the second vibration response signal of the measuring point in the middle of the pin at a sampling rate of f=20kHz. Each acquisition lasts for T=0.05s (corresponding to 1000 sampling points). The 0.05s data window contains about 43 resonance cycles (at 850Hz), which is sufficient for reliable spectrum analysis.

[0077] S520, based on the second vibration response signal, obtains the current second bending resonance frequency and the second half-power bandwidth.

[0078] For example, a short-time Fourier analysis can be performed on the acquired amplitude-frequency response curve in the frequency domain. Within the expected range of the first-order bending resonance (e.g., 800Hz–900Hz), the global maximum amplitude point can be searched to obtain the second bending resonance frequency, and the half-power amplitude |H| can be calculated. hp |=|H avg (f curr )∣ / The search points to the left and right of fcurr respectively first showed the amplitude dropping to |H. hp The frequency points f1 and f2 of | are used. Since the amplitude-frequency response curve is approximately symmetrical near the resonance peak, linear interpolation can be used to refine the positions of f1 and f2, thus obtaining the second half-power bandwidth Δf. curr =f2−f1.

[0079] S530 calculates real-time resonance sharpness and real-time dynamic modulus based on the second bending resonance frequency and the second half-power bandwidth.

[0080] For example, the real-time resonance sharpness can be obtained by dividing the second bending resonance frequency by the second half-power bandwidth, and the real-time dynamic modulus E can be calculated using the relationship between the second bending resonance frequency and the dynamic elastic modulus. curr =(2πL 2 f curr / 1.875 2 ) 2 ρA / I, where I=πD 4 / 64 is the moment of inertia of the cross section, A=πD 2 / 4 represents the cross-sectional area, and ρ represents the material density. The reference modulus E is stored at a pre-stored reference temperature. ref E can be calculated from the relative change of the resonant frequency. curr Relative change: E curr / E ref =(f curr / f ref ) 2 .

[0081] Through the above steps S510 to S530, all calculations are based on fixed formulas and table lookups, eliminating the need for online modeling and multi-strategy parallelism, making real-time safety sensing of the thimble feasible in industrial economics.

[0082] In one possible implementation, please refer to Figure 3 The S700 transmits vibration signals based on real-time resonance sharpness, real-time dynamic modulus, and vibration threshold, including: S710 calculates the ratio of real-time resonance sharpness to the initial resonance sharpness value to obtain the resonance sharpness retention rate.

[0083] For example, the ratio of real-time resonance sharpness to the initial resonance sharpness value can be calculated, i.e., the resonance sharpness retention rate.

[0084] S720 calculates the ratio of the real-time dynamic modulus to the reference modulus at the same temperature to obtain the modulus retention rate.

[0085] For example, the ratio of the real-time dynamic modulus to the preset reference modulus at the same temperature, i.e., the modulus retention rate, can be calculated.

[0086] S730 sends a vibration signal when the resonance sharpness retention rate is less than or equal to the resonance sharpness threshold in the vibration threshold and the modulus retention rate is greater than or equal to the modulus threshold in the vibration threshold.

[0087] For example, a vibration signal may be sent when the resonance sharpness retention rate is less than or equal to a preset resonance sharpness threshold and the modulus retention rate is greater than or equal to a preset modulus threshold.

[0088] The same vibration parameters are safe when the material is healthy, but may be fatal when the material has suffered micro-damage. However, current technology cannot distinguish between these two situations. Through the above steps S710 to S730, vibration is only permitted when the stress has been fully released and the material is undamaged.

[0089] In one possible implementation, please refer to Figure 4 S600 determines the vibration threshold based on real-time dynamic modulus, including: S610, obtain the cumulative vibration time of the ejector pin.

[0090] For example, the cumulative vibration time experienced by the target pin being processed since entering the cryogenic treatment station can be obtained in real time.

[0091] S620, if it is determined from the real-time dynamic modulus and cumulative vibration time that the safety boundary condition has not been exceeded, then the first threshold corresponding to the first process mode is used as the current vibration threshold. Here, the safety boundary condition refers to a preset upper limit for cumulative vibration time or a preset upper limit for the magnitude reduction of the real-time dynamic modulus relative to the initial dynamic modulus at the start of processing.

[0092] For example, when neither the real-time dynamic modulus nor the cumulative vibration time triggers the preset safety boundary conditions, the ejector pin is still in the first process mode, and the first threshold corresponding to the first process mode is used as the current vibration threshold.

[0093] S630, if the vibration threshold is exceeded based on the real-time dynamic modulus and the cumulative vibration time, then the second threshold corresponding to the second process mode is used as the current vibration threshold.

[0094] For example, when either the real-time dynamic modulus or the cumulative vibration time exceeds a preset safety boundary condition, the second threshold corresponding to the more conservative second process mode can be used as the current vibration threshold.

[0095] Through the steps S610 to S630 described above, the dual threshold automatic switching mechanism enables the system to adaptively match the individual characteristics of each pin and ensure that pins that touch the boundary receive more conservative protection before the start of the next vibration cycle.

[0096] In one possible implementation, please refer to Figure 4 The methods also include: S001, when it is determined that the safety boundary conditions are exceeded, stop the subsequent vibration operation of the first process mode.

[0097] For example, when it is determined that the safety boundary conditions are exceeded, a digital value of 0 (corresponding to 0V output) is sent to the D / A converter of the exciter, and the power amplifier stage of the exciter is turned off, thereby stopping the subsequent vibration operation of the first process mode.

[0098] S002, perform subsequent vibration operation according to the process parameters of the second process mode.

[0099] For example, after stopping the vibration of the first process mode, the process parameters of the second process mode (including vibration threshold, amplitude limit, number of cycles, cumulative vibration time limit, and modulus reduction limit, etc.) can be loaded immediately to continue the remaining processing of the ejector pin with the new parameters.

[0100] Through the above steps S001 to S002, the execution mechanism of triggering and stopping, and stopping and switching, helps to ensure that each pin that touches the boundary can obtain a set of conservative processing parameters that perfectly match its current state within milliseconds.

[0101] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0102] Corresponding to the multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins described in the above embodiments, this application embodiment also provides a multi-cycle cryogenic vibration combined aging dimensional stabilization treatment device for mold ejector pins. Each module of this device can realize each step of the multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins. Figure 5 The diagram shows a structural block diagram of the multi-cycle cryogenic vibration composite aging dimensional stabilization process device for mold ejector pins provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0103] Reference Figure 5 The device includes: The first acquisition module is used to acquire the batch feature vector of the current batch of ejector pins; wherein, the batch feature vector is used to reflect the resonance characteristics and geometric features of the ejector pins; The weighting module is used to determine the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector. The batch target evaluation function module is used to generate a batch target evaluation function based on the processing security weight, the processing efficiency weight, and the robustness weight. The first process mode module is used to select the process mode with the lowest overall processing cost from a candidate mode set containing at least two process modes, based on the batch target evaluation function, as the first process mode for the current batch. The second acquisition module is used to acquire the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins at fixed intervals when vibration processing is performed according to the first process mode. The vibration threshold module is used to determine the corresponding vibration threshold based on the real-time dynamic modulus. The vibration signal module is used to send vibration signals based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold.

[0104] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0105] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0106] This application also provides an electronic device. Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the electronic device 6 to implement the steps in the above embodiments of the multi-cycle cryogenic vibration composite aging dimensional stabilization process for mold ejector pins, or to implement the functions of each module / unit in the above embodiments of the devices.

[0107] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0108] The electronic device 6 can be a computing device such as an embedded control system, an industrial computer, a programmable logic controller, or a distributed control system. This electronic device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0109] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0110] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0111] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0112] This application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the steps in any of the above method embodiments.

[0113] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0114] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0115] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0116] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A multi-cycle cryogenic vibration combined with aging process for dimensional stabilization of mold ejector pins, characterized in that, include: Obtain the batch feature vector of the current batch of ejector pins; wherein, the batch feature vector is used to reflect the resonance characteristics and geometric features of the ejector pins; Based on the batch feature vector, determine the processing security weight, processing efficiency weight, and robustness weight; A batch target evaluation function is generated based on the processing security weight, the processing efficiency weight, and the robustness weight; According to the batch target evaluation function, the process mode with the lowest overall processing cost is selected from the candidate mode set containing at least two process modes and is used as the first process mode of the current batch. When performing vibration treatment according to the first process mode, the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins are obtained at fixed intervals. The corresponding vibration threshold is determined based on the real-time dynamic modulus. Vibration signals are sent based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold.

2. The multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The determination of processing security weights, processing efficiency weights, and robustness weights based on the batch feature vectors includes: Based on the aspect ratio in the batch feature vector, the bending instability risk component is determined using a preset slender rod bending instability risk function. Based on the degree of deviation of the resonance sharpness value in the batch feature vector from the historical median data, the cumulative risk adjustment coefficient is determined. The result of correcting the bending instability risk component with the cumulative risk adjustment coefficient is used as the processing safety weight.

3. The multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The process of determining the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector further includes: Calculate the overall deviation between the batch feature vector and the preset standard reference vector; Based on the preset positive correlation mapping relationship, the robustness weight value corresponding to the comprehensive deviation is obtained.

4. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The process of determining the processing security weight, processing efficiency weight, and robustness weight based on the batch feature vector further includes: The processing efficiency weight is obtained by subtracting the sum of the processing security weight and the robustness weight from the preset total weight value.

5. The multi-cycle cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The step of selecting the process mode with the lowest overall processing cost from a candidate mode set containing at least two process modes, based on the batch target evaluation function, as the first process mode for the current batch, includes: For each candidate process mode in the preset candidate mode set, its pre-calibrated safety cost, efficiency cost, and robustness cost are obtained, and then substituted into the batch target evaluation function to calculate the comprehensive processing cost. The candidate process mode with the lowest overall processing cost is determined as the first process mode.

6. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The step of obtaining the batch feature vector of the current batch of pins includes: A sweep frequency excitation was applied to the sample pin to acquire the first vibration response signal; Extract the first bending resonant frequency and the first half-power bandwidth from the first vibration response signal; Based on the first bending resonance frequency and the first half-power bandwidth, calculate the resonance sharpness value that reflects the micro-defects and the original stress state. The resonance sharpness value and the aspect ratio of the sample pin are used as the batch feature vector.

7. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The method of acquiring the real-time resonance sharpness and real-time dynamic modulus of the current batch of ejector pins at fixed intervals includes: The second vibration response signal is acquired at fixed time intervals via the vibration measurement module; The current second bending resonance frequency and second half-power bandwidth are obtained based on the second vibration response signal; The real-time resonance sharpness and real-time dynamic modulus are calculated based on the second bending resonance frequency and the second half-power bandwidth.

8. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 6, characterized in that, The step of sending a vibration signal based on the real-time resonance sharpness, the real-time dynamic modulus, and the vibration threshold includes: The ratio of the real-time resonance sharpness to the initial resonance sharpness value is calculated to obtain the resonance sharpness retention rate; The ratio of the real-time dynamic modulus to the reference modulus at the same temperature is calculated to obtain the modulus retention rate; The vibration signal is sent when the resonance sharpness retention rate is less than or equal to the resonance sharpness threshold in the vibration threshold, and the modulus retention rate is greater than or equal to the modulus threshold in the vibration threshold.

9. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 1, characterized in that, The step of determining the vibration threshold based on the real-time dynamic modulus includes: Obtain the cumulative vibration time of the ejector pin; If it is determined that the safety boundary condition has not been exceeded based on the real-time dynamic modulus and the cumulative vibration time, then the first threshold corresponding to the first process mode is used as the current vibration threshold; wherein, the safety boundary condition refers to the preset upper limit of the cumulative vibration time or the preset upper limit of the modulus reduction of the real-time dynamic modulus relative to the initial dynamic modulus at the start of the processing. If the vibration exceeds the safety boundary condition based on the real-time dynamic modulus and the cumulative vibration time, then the second threshold corresponding to the second process mode is used as the current vibration threshold.

10. The multi-cycle deep cryogenic vibration combined aging dimensional stabilization treatment process for mold ejector pins as described in claim 9, characterized in that, The method further includes: When the safety boundary conditions are exceeded, the subsequent vibration operation of the first process mode is stopped; Subsequent vibration operations are performed according to the process parameters of the second process mode.

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