Method for quick correction of verticality of laser cutting machine

Abstract

The present invention belongs to the field of laser cutting technology, and in particular to a method for rapid correction of the verticality of a laser cutting machine. First, the vibration sensor collects the signal, and after transmitting it to the central processing unit, an improved time-frequency domain joint analysis method is used. First, the main frequency, amplitude and other characteristics of each frequency band are extracted by multi-level time-frequency decomposition and adaptive spectrum estimation through wavelet packet transform, and the energy ratio is calculated. Then, the normal and current cutting vibration modes are compared by cosine similarity to detect the verticality deviation. If there is a deviation, an improved incremental control method is used to first calculate the deviation value and divide the level 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 performed after correction. This method effectively overcomes the defects of traditional manual correction, improves correction efficiency and accuracy, ensures cutting quality, and enhances equipment stability and reliability.

Description

Method for quick correction of verticality of laser cutting machine Technical Field

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

[0002] During the laser cutting process, the verticality accuracy between the cutting head and the worktable of the laser cutting machine plays a key role in the cutting quality and accuracy. However, in the actual production environment, due to the mechanical wear caused by long-term operation of the equipment, the initial error during the installation and commissioning of the equipment, the vibration interference during operation, and the influence of external environmental factors, the verticality between the cutting head and the worktable often deviates. This verticality deviation will increase the roughness of the cutting surface and reduce the cutting size accuracy. In severe cases, it may even cause the cut workpiece to be scrapped, greatly affecting the production efficiency and product quality, and increasing the production cost. Traditional verticality correction methods often rely on manual experience judgment and manual adjustment, which is not only inefficient, but also difficult to ensure the accuracy and consistency of the correction. Summary of the invention

[0003] In view of the technical problem of verticality deviation existing in the above-mentioned background technology, the present invention proposes a method for rapid verticality correction of a laser cutting machine with reasonable design and strong theoretical basis.

[0004] In order to achieve the above object, the technical solution adopted by the present invention comprises the following steps:

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

[0006] S2, transmitting the signal collected by the vibration sensor to the central processing unit, analyzing the vibration signal using an improved time-frequency domain joint analysis method, extracting the frequency and amplitude characteristics related to the verticality change, and detecting whether the verticality deviates by comparing the vibration mode in the normal cutting process with the vibration mode in the current cutting process;

[0007] The specific implementation of analyzing the vibration signal and detecting whether the verticality has a deviation by using the improved time-frequency domain joint analysis method in step S2 is as follows:

[0008] S21. First, wavelet packet transform is applied to the collected vibration signal to perform multi-level time-frequency decomposition and extract signal components of 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 number of decomposition levels;

[0009] S22, then apply the adaptive spectrum estimation method to each frequency band to perform local spectrum adjustment: Where S(f) is the power spectrum density at frequency f, T is the time window length, e -2jπft is a complex exponential basis function used to perform Fourier transform on the signal;

[0010] 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 in vibration, and extract the time domain waveform characteristics of each frequency band, wherein the energy ratio is calculated as: Where X[n] is the sampling value of the time-frequency decomposition sample, X k [n] is the sampling value of the sub-signal in the kth frequency band, N is the number of sampling points, ω k is the weight coefficient of the kth frequency band;

[0011] S24, finally, comparing the vibration characteristics of the normal cutting process with the characteristics of the current cutting process, and calculating the difference between the two sets of characteristics by cosine similarity;

[0012] S3, verticality deviation is detected, and an improved incremental control method is introduced to correct the verticality deviation;

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

[0014] Preferably, the wavelet packet improved basis functions ψ at each level in step S21 are k The specific form of (t) is: 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 signal at time t k is the instantaneous frequency, and f0 is the desired frequency center.

[0015] Preferably, the weight coefficient ω of the kth frequency band in step S23 is k The specific form is: Where α is the adjustment factor, which is set based on the empirical value to control the importance of each frequency band, and f k is the center frequency of the kth frequency band, f max is the maximum frequency.

[0016] Preferably, the specific implementation method of correcting the verticality deviation in step S3 by improving the incremental control method is as follows:

[0017] S31, firstly, by comparing the ideal state with the vibration mode in the current cutting process, calculate the current verticality deviation c: c = c current -c ideal , where c current is the current verticality, c ideal is the ideal verticality;

[0018] S32, dividing the deviation c into different deviation levels according to its size to determine the correction increment;

[0019] S33, calculating a correction amount Δθ according to the current deviation level;

[0020] S34. Finally, according to the current error size and historical correction data, the correction step size is gradually reduced to avoid over-correction.

[0021] Preferably, the different deviation levels in step S32 are: Among them, K1, K2, K3 are gain constants, corresponding to the correction step sizes of large deviations, medium deviations 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 at which the gain function changes with the increase of deviation, and β determines the degree to which the correction increment changes with the increase of deviation.

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

[0023] Compared with the prior art, the advantages and positive effects of the present invention are that, through the improved time-frequency domain joint analysis method, the verticality-related features are accurately extracted by means of wavelet packet transform and adaptive spectrum estimation, and the deviation is accurately judged according to cosine similarity, overcoming the disadvantages of strong subjectivity and poor consistency of traditional manual judgment. During correction, improved incremental control is adopted, firstly accurately quantifying the deviation, dividing the level to determine the increment, and then optimizing the step size according to the error and historical data, effectively avoiding excessive or insufficient correction, 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 briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] FIG1 is a schematic diagram of a structural implementation flow of the present invention. DETAILED DESCRIPTION

[0026] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0027] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways than those described herein. Therefore, the present invention is not limited to the specific embodiments of the following disclosure.

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

[0029] First, high-precision vibration sensors are installed at key locations of the laser cutting machine’s cutting head and worktable. The sensors can detect vibrations caused by verticality deviations. During the cutting process, once verticality deviations occur, the vibration characteristics of the equipment will change. The sensors can capture these changes in real time and transmit vibration signals to the central processing unit.

[0030] Next, consider that traditional technology usually relies on manual experience to observe the appearance of the cutting surface and measure the dimensional accuracy of the cut workpiece to judge the verticality in detecting the verticality deviation of the laser cutting machine. This method is highly subjective, and it is difficult to unify the judgment standards of different workers, resulting in poor consistency of results. 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 in key positions, and uses advanced wavelet packet transform and adaptive spectrum estimation methods to accurately extract frequency and amplitude characteristics that are closely related to verticality. Through scientific comparison with normal cutting vibration modes, it can quickly and accurately determine whether the verticality has deviations. First, the collected vibration signal is subjected to multi-level time-frequency decomposition by applying wavelet packet transform 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 all levels, 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 signal at time t k The instantaneous frequency of f0 is the desired frequency center, and K is the number of decomposition layers. Then the adaptive spectrum estimation method is applied to each frequency band to adjust the local spectrum: Where S(f) is the power spectrum density at frequency f, T is the time window length, e -2jπft is a complex exponential basis function, which is used to perform Fourier transform on the signal. Then, the main frequency and amplitude characteristics are extracted from the time-frequency analysis results of each frequency band, the energy ratio of each frequency band is calculated, the energy distribution of different frequency bands in vibration is identified, and the time domain waveform characteristics of each frequency band are extracted. The calculation of the energy ratio is: Where X[n] is the sampling value of the time-frequency decomposition sample, X k [n] is the sampling value of the sub-signal in the kth frequency band, N is the number of sampling points, ω k is the weight coefficient of the kth frequency band, Where α is the adjustment factor, which is set based on the empirical value to control the importance of each frequency band, and f k is the center frequency of the kth frequency band, f max is the maximum frequency. Finally, the vibration characteristics of the normal cutting process are compared with the characteristics of the current cutting process, and the difference between the two sets of characteristics is calculated by cosine similarity.

[0031] When the difference is found, considering that traditional correction methods often lack accurate deviation quantification and scientific adjustment strategies, it is easy to cause over-correction or under-correction, affecting equipment stability and cutting accuracy, and inefficiency. The improved incremental control method first accurately calculates the verticality deviation value by accurately comparing the ideal and current vibration modes, providing a reliable basis for subsequent correction. First, by comparing the ideal state with the vibration mode during the current cutting process, the current verticality deviation c is calculated: c = c current -c ideal , where c current is the current verticality, c ideal is the ideal verticality; according to the size of the deviation c, it is divided into different deviation levels to determine the correction increment, and the different deviation levels are: Among them, K1, K2, K3 are gain constants, corresponding to the correction step sizes of 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 deviation, and β determines the degree to which the correction increment changes with the increase of deviation. According to the current deviation level, calculate the correction amount Δθ; finally, according to the current error size and historical correction data, gradually reduce the correction step size to avoid over-correction. The correction reduction formula is: where Δθ iis the i-th correction amount. This method can greatly improve the correction efficiency and accuracy, reduce equipment downtime, improve the quality of cutting products, and enhance the stability and reliability of long-term operation of laser cutting machines.

[0032] The above description is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for quickly correcting the verticality of a laser cutting machine, characterized in that: The following steps are involved: S1. First, install high-precision vibration sensors at key positions of the cutting head and workbench of the laser cutting machine to collect and monitor the vibration signals generated during the cutting process; S2. Transmit the signals collected by the vibration sensor to the central processing unit, analyze the vibration signals using an improved time-frequency domain joint analysis method, extract the frequency and amplitude characteristics related to the verticality change, and detect whether the verticality deviates by comparing the vibration mode in the normal cutting process with the vibration mode in the current cutting process; wherein, the specific implementation of using the improved time-frequency domain joint analysis method to analyze the vibration signal and detect whether the verticality deviates 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 all levels, and K is the number of decomposition layers; S22, then the adaptive spectrum estimation method is applied to each frequency band to perform local spectrum adjustment: Where S(f) is the power spectrum density at frequency f, T is the time window length, e -j2πft is a complex exponential basis function used to perform Fourier transform on 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 in vibration, and extract the time domain waveform characteristics of each frequency band, where the energy ratio is calculated as: Where X[n] is the sampling value of the time-frequency decomposition sample, X k [n] is the sampling value of the sub-signal in the kth frequency band, N is the number of sampling points, ω k is the weight coefficient of the kth frequency band; S24, finally, the vibration characteristics of the normal cutting process are compared with the characteristics of the current cutting process, and the difference between the two sets of characteristics is calculated by cosine similarity; S3, the verticality deviation is detected, and an improved incremental control method is introduced to correct the verticality deviation; S4, after the final correction, the vibration signal and verticality changes are continued to be monitored in real time to confirm the adjustment effect and improve the accuracy of the adjustment strategy.

2. The method for rapid correction of verticality of a laser cutting machine according to claim 1, characterized in that: In step S21, the wavelet packet improved basis function ψ at each level k The specific form of (t) is: 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 signal at time t k is the instantaneous frequency, and f0 is the desired frequency center.

3. The method for rapid verticality correction of a laser cutting machine according to claim 1, characterized in that: The weight coefficient ω of the kth frequency band in step S23 k The specific form is: Where α is the adjustment factor, which is set based on the empirical value to control the importance of each frequency band, and f k is the center frequency of the kth frequency band, 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 verticality deviation by improving the incremental control method in step S3 is as follows: S31, firstly, by comparing the ideal state with the vibration mode in the current cutting process, the current verticality deviation c is calculated: c = c current -c ideal , where c current is the current verticality, c ideal is the ideal verticality; S32, according to the size of the deviation c, it is divided into different deviation levels to determine the correction increment; S33, according to the current deviation level, the correction amount Δθ is calculated; S34, finally, according to the size of the current error and the historical correction data, the correction step size is gradually reduced to avoid over-correction.

5. The method for rapid verticality correction of a laser cutting machine according to claim 4, characterized in that: The different deviation levels in step S32 are: Among them, K1, K2, K3 are gain constants, corresponding to the correction step sizes of large deviations, medium deviations 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 at which the gain function changes with the increase of deviation, and β determines the degree to which the correction increment changes with the increase of deviation.

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

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