Method for quick correction of verticality of laser cutting machine

Abstract

The present invention belongs to the technical field of laser cutting, and particularly relates to a method for quickly correcting the perpendicularity of a laser cutting machine. First, a vibration sensor collects signals. After transmitting them to the central processing unit, an improved time-frequency domain joint analysis method is used. First, through wavelet packet transform for multi-level time-frequency decomposition and adaptive spectrum estimation, features such as the main frequency and amplitude of each frequency band are extracted and the energy ratio is calculated, etc. Then, the perpendicularity deviation is detected by comparing the normal and current cutting vibration modes through cosine similarity. If there is a deviation, an improved incremental control method is adopted. First, the deviation value is calculated and the level is divided to determine the correction increment, and then the step size is optimized according to the error and historical data for correction, and continuous monitoring is carried out after correction. This method effectively overcomes the defects of traditional manual correction, improves the correction efficiency and accuracy, guarantees the cutting quality, and enhances the stability and reliability of the equipment.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser cutting, and particularly relates to a method for quickly correcting the perpendicularity of a laser cutting machine. Background Art

[0002] In the process of laser cutting, the perpendicularity accuracy between the cutting head and the workbench of a laser cutting machine plays a crucial role in cutting quality and precision. However, in the actual production environment, due to mechanical wear caused by long-term operation of the equipment, initial errors during equipment installation and debugging, vibration interference during work, and the influence of external environmental factors, etc., the perpendicularity between the cutting head and the workbench often deviates. This perpendicularity deviation will increase the roughness of the cutting surface and reduce the cutting dimension accuracy. Seriously, it may even lead to the scrapping of the cut workpiece, greatly affecting production efficiency and product quality, and increasing production costs. Traditional perpendicularity correction methods often rely on manual experience judgment and manual adjustment, which are not only inefficient but also difficult to ensure the accuracy and consistency of correction. Summary of the Invention

[0003] In view of the technical problem of perpendicularity deviation in the above background art, the present invention proposes a method for quickly correcting the perpendicularity of a laser cutting machine with reasonable design and strong theory.

[0004] To achieve the above object, the technical solution adopted by the present invention is as follows, including the following steps:

[0005] S1. First, install high-precision vibration sensors at key parts of the cutting head and the workbench of the laser cutting machine to collect and monitor the vibration signals generated during the cutting process;

[0006] S2. Transmit the signals collected by the vibration sensors to the central processing unit, analyze the vibration signals by using an improved time-frequency domain joint analysis method, extract the frequency and amplitude characteristics related to the perpendicularity change, and detect whether the perpendicularity deviates by comparing the vibration mode during the normal cutting process with the vibration mode during the current cutting process;

[0007] Among them, the specific implementation of analyzing the vibration signals by using the improved time-frequency domain joint analysis method and detecting whether the perpendicularity deviates in step S2 is as follows:

[0008] S21. First, apply wavelet packet transform to the collected vibration signals for multi-level time-frequency decomposition to extract signal components in different frequency bands: Among them, c k is the wavelet packet coefficient, ψ k (t) is the improved basis function of each level of wavelet packet, and K is the decomposition level;

[0009] S22. Then apply the adaptive spectral estimation method to each frequency band for local spectral adjustment: where \(S(f)\) is the power spectral density at frequency \(f\), \(T\) is the time window length, and \(e\) -2jπft is the complex exponential basis function for performing Fourier transform on the signal;

[0010] S23. Then, extract the dominant frequency and amplitude features from the time-frequency analysis results of each frequency band, calculate the energy ratio of each frequency band, identify the energy distribution of different frequency bands during vibration, and extract the time-domain waveform features of each frequency band. The calculation of the energy ratio is as follows: where \(X[n]\) is the sampling value of the time-frequency decomposition sample, and \(X\) k [n] is the sampling value of the sub-signal in the \(k\)-th frequency band, \(N\) is the number of sampling points, and \(\omega\) k is the weight coefficient of the \(k\)-th frequency band;

[0011] S24. Finally, compare the vibration characteristics of the normal cutting process with the characteristics of the current cutting process, and calculate the difference between the two sets of characteristics through cosine similarity;

[0012] S3. When the perpendicularity deviation is detected, introduce an improved incremental control method to correct the perpendicularity deviation;

[0013] S4. After the final correction, continue to monitor the vibration signal and the change of perpendicularity in real time to confirm the adjustment effect and improve the accuracy of the adjustment strategy.

[0014] Preferably, the specific form of the improved wavelet packet basis function \(\psi\) k (t) in step S21 is: where \(j(k)\) is the scale, where \(\varphi(t k ) is the instantaneous phase of the signal; \(\gamma(k)\) is the time-frequency modulation factor, \(\gamma(k)=\exp(-|f inst (t k ) - f0|), where \(f inst (t k ) is the instantaneous frequency of the signal at time \(t k , and \(f0\) is the desired frequency center.

[0015] Preferably, the specific form of the weight coefficient \(\omega\) k of the \(k\)-th frequency band in step S23 is: where \(\alpha\) is an adjustment factor, and the importance of each frequency band is controlled based on empirical values. \(f k is the center frequency band of the \(k\)-th frequency band, and \(f max is the maximum frequency.

[0016] Preferably, the specific implementation method of correcting the perpendicularity deviation by the improved incremental control method in step S3 is:

[0017] S31. First, by comparing the ideal state with the vibration mode during the current cutting process, calculate the current perpendicularity deviation c: c = c current - c ideal , where c current is the current perpendicularity, and c ideal is the ideal perpendicularity;

[0018] S32. According to the magnitude of the deviation c, divide it into different deviation levels to determine the correction increment;

[0019] S33. According to the current deviation level, calculate the correction amount Δθ;

[0020] S34. Finally, according to the magnitude of the current error and the historical correction data, gradually reduce the correction step size to avoid overcorrection.

[0021] Preferably, the different deviation levels divided in step S32 are: where K1, K2, K3 are gain constants, corresponding to the correction step sizes for large deviation, medium deviation, and small deviation respectively, and K1 > K2 > K3, λ, β are parameters for adjusting the sensitivity of the gain function. Specifically, λ controls the rate at which the gain function changes with the increase of the deviation, and β determines the degree to which the correction increment changes with the increase of the deviation.

[0022] Preferably, the correction reduction formula in step S34 is: where Δθ i is the correction amount for the i-th time.

[0023] Compared with the prior art, the advantages and positive effects of the present invention are as follows. By improving the time-frequency domain joint analysis method, accurately extract the perpendicularity-related features with the help of wavelet packet transform and adaptive spectral estimation, and accurately judge the deviation according to the cosine similarity, overcoming the disadvantages of strong subjectivity and poor consistency in traditional manual judgment. When correcting, an improved incremental control is adopted. First, accurately quantify the deviation, divide the level to determine the increment, and then optimize the step size according to the error and historical data, effectively avoiding overcorrection or undercorrection, and improving the correction efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0025] Figure 1 It is a schematic structural implementation flowchart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0026] To more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0027] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the present invention is not limited to the limitations of the specific embodiments disclosed in the following specification.

[0028] Embodiment. In the field of laser cutting processing, the perpendicularity deviation problem between the cutting head and the workbench has always been a key factor affecting cutting quality and efficiency. In order to effectively solve problems such as increased cutting surface roughness, reduced dimensional accuracy, and even workpiece scrapping caused by perpendicularity deviation, improve production efficiency and product quality, and reduce production costs, the present invention proposes an innovative method for quickly correcting the perpendicularity of a laser cutting machine. The implementation process of the present invention is as Figure 1 shown.

[0029] First, high-precision vibration sensors are installed at key parts of the cutting head and the workbench of the laser cutting machine. The sensors can detect the vibration caused by perpendicularity deviation. During the cutting process, once the perpendicularity deviates, the vibration characteristics of the equipment will change, and the sensors can capture these changes in real time and transmit the vibration signals to the central processing unit.

[0030] Next, considering that traditional techniques for detecting the perpendicularity deviation of a laser cutting machine usually rely on manual observation of the appearance of the cutting surface and measurement of the dimensional accuracy of the cut workpiece by experience to judge the perpendicularity situation. This method is highly subjective, and it is difficult to unify the judgment criteria of different workers, resulting in poor result consistency. The improved time-frequency domain joint analysis method adopted by the present invention has significant advantages. It collects signals with the help of high-precision vibration sensors installed at key parts, and uses advanced wavelet packet transform and adaptive spectral estimation means to accurately extract the frequency and amplitude characteristics closely related to perpendicularity. By scientifically comparing with the normal cutting vibration mode, it can quickly and accurately determine whether there is a perpendicularity deviation. First, apply wavelet packet transform to the collected vibration signals for multi-level time-frequency decomposition to extract signal components in different frequency bands: where c k is the wavelet packet coefficient, ψ k (t) is the improved basis function of each level of wavelet packet, where j(k) is the scale, where φ(t k ) is the instantaneous phase of the signal; γ(k) is the time-frequency modulation factor, γ(k) = exp(-|f inst (t k ) - f0|), where finst (t k ) is the instantaneous frequency of the signal at time t k , f0 is the desired frequency center, and K is the number of decomposition levels; then, an adaptive spectral estimation method is applied to each frequency band for local spectral adjustment: where S(f) is the power spectral density at frequency f, T is the time window length, and e -2jπft is the complex exponential basis function used for Fourier transform of the signal; then, the dominant frequency and amplitude features are extracted from the time-frequency analysis results of each frequency band, the energy ratio of each frequency band is calculated to identify the energy distribution of different frequency bands in vibration, and the time-domain waveform features of each frequency band are extracted. The calculation of the energy ratio is as follows: where X[n] is the sampling value of the time-frequency decomposition sample, and X k [n] is the sampling value of the sub-signal in the k-th frequency band, N is the number of sampling points, and ω k is the weight coefficient of the k-th frequency band, where α is an adjustment factor set based on empirical values to control the importance of each frequency band, f k is the center frequency band of the k-th frequency band, and f max is the maximum frequency. Finally, the vibration characteristics of the normal cutting process are compared with those of the current cutting process, and the difference between the two sets of characteristics is calculated by cosine similarity.

[0031] When a difference is found, considering that traditional correction methods often lack accurate deviation quantification and scientific adjustment strategies, which are prone to overcorrection or undercorrection, affecting equipment stability and cutting accuracy, and with low efficiency. The improved incremental control method first accurately compares the ideal and current vibration modes, accurately calculates the perpendicularity deviation value, and provides a reliable basis for subsequent correction. First, by comparing the ideal state with the vibration mode in the current cutting process, the current perpendicularity deviation c is calculated: c = c current -c ideal , where c current is the current perpendicularity and c ideal is the ideal perpendicularity; according to the magnitude of the deviation c, it is divided into different deviation levels to determine the correction increment. The divided different deviation levels are: where K1, K2, and K3 are gain constants corresponding to the correction step sizes for large, medium, and small deviations respectively, and K1 > K2 > K3. λ and β are parameters for adjusting the sensitivity of the gain function. Specifically, λ controls the rate of change of the gain function with the increase of the deviation, and β determines the degree of change of the correction increment with the increase of the deviation. According to the current deviation level, the correction amount Δθ is calculated; finally, according to the magnitude of the current error and historical correction data, the correction step size is gradually reduced to avoid overcorrection. The correction reduction formula is: where Δθ iis the correction amount for the ith time. This method can significantly improve the calibration efficiency and accuracy, reduce the equipment downtime, improve the quality of the cut products, and enhance the stability and reliability of the long-term operation of the laser cutting machine.

[0032] As described above, it is only the preferred embodiment of the present invention, and it is not a limitation to the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for quickly correcting the perpendicularity of a laser cutting machine, characterized in that, It includes the following steps: S1. First, install high-precision vibration sensors at the key parts of the cutting head and the workbench of the laser cutting machine to collect the vibration signals generated during the cutting process for monitoring; S2. Transmit the signals collected by the vibration sensors to the central processing unit, analyze the vibration signals using the improved time-frequency domain joint analysis method, extract the frequency and amplitude characteristics related to the perpendicularity change, and detect whether there is a deviation in the perpendicularity by comparing the vibration mode during the normal cutting process with the vibration mode during the current cutting process; Among them, the specific implementation of analyzing the vibration signals using the improved time-frequency domain joint analysis method and detecting whether there is a deviation in the perpendicularity in step S2 is as follows: S21. First, apply wavelet packet transform to the collected vibration signal for multi-level time-frequency decomposition to extract signal components in different frequency bands: where c k is the wavelet packet coefficient, ψ k (t) is the improved basis function of wavelet packets at each level, and K is the decomposition level; S22. Then, apply the adaptive spectral estimation method to each frequency band for local spectral adjustment: where S(f) is the power spectral density at frequency f, T is the time window length, and e -j2πft is the complex exponential basis function used for Fourier transform of the signal; S23. Then, extract the main frequency and amplitude characteristics from the time-frequency analysis results of each frequency band, calculate the energy ratio of each frequency band, identify the energy distribution of different frequency bands during vibration, and extract the time-domain waveform characteristics of each frequency band. The calculation of the energy ratio is as follows: where X[n] is the sampling value of the time-frequency decomposition sample, X k [n] is the sampling value of the sub-signal of the k-th frequency band, N is the number of sampling points, ω k is the weighting coefficient of the k-th frequency band; S24. Finally, compare the vibration characteristics of the normal cutting process with the characteristics of the current cutting process, and calculate the difference between the two groups of characteristics through cosine similarity; S3. When a perpendicularity deviation is detected, introduce the improved incremental control method to correct the perpendicularity deviation; S4. After the correction, continue to monitor the vibration signals and the perpendicularity change in real time to confirm the adjustment effect and improve the accuracy of the adjustment strategy.

2. The method for quickly correcting the perpendicularity of a laser cutting machine according to claim 1, characterized in that The improved basis function ψ of each level of wavelet packet in the step S21 k (t) has the following specific form: where j(k) is the scale, where φ(t k ) is the instantaneous phase of the signal; γ(k) is the time-frequency modulation factor, γ(k) = exp(-|f inst (t k ) - f0|), where f inst (t k ) is the instantaneous frequency of the signal at time t k , and f0 is the desired frequency center.

3. The method for rapid verticality correction of the laser cutting machine according to claim 1, characterized in that The weight coefficient ω of the k-th frequency band in the step S23 k has the specific form of: where α is an adjustment factor, which is set based on empirical values to control the importance of each frequency band, and f k is the central frequency band of the k-th frequency band, and f max is the maximum frequency.

4. The method for rapid verticality correction of a laser cutting machine according to claim 1, characterized in that, The specific implementation method of correcting the perpendicularity deviation through the improved incremental control method in step S3 is as follows: S31. First, by comparing the ideal state with the vibration mode during the current cutting process, calculate the current perpendicularity deviation c: c = c current - c ideal , where c current is the current perpendicularity, and c ideal is the ideal perpendicularity; S32. According to the magnitude of the deviation c, divide it into different deviation levels to determine the correction increment; S33. Calculate the correction amount Δθ according to the current deviation level; S34. Finally, according to the magnitude of the current error and the historical correction data, gradually reduce the correction step size to avoid overcorrection.

5. The method for rapid verticality correction of a laser cutting machine according to claim 4, characterized in that, The different deviation levels divided in the step S32 are as follows: Among them, K1, K2, and K3 are gain constants, corresponding to the correction step sizes for large deviation, medium deviation, and small deviation respectively, and K1 > K2 > K3. λ and β are parameters for adjusting the sensitivity of the gain function. Specifically, λ controls the rate at which the gain function changes with the increase in deviation, and β determines the degree to which the correction increment changes with the increase in deviation.

6. The method for rapid verticality correction of a laser cutting machine according to claim 4, characterized in that, The correction and reduction formula in step S34 is as follows: where Δθ i is the correction amount for the i-th time.

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