A quartz crystal laser cutting method and system based on multi-parameter fusion control

Abstract

This invention relates to the field of quartz crystal laser cutting technology, and discloses a quartz crystal laser cutting method and system based on multi-parameter fusion control. The system includes: a parameter receiving module for receiving real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process; a cutting stage determination module for determining the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters, and determining whether the cutting process has entered a penetration critical state based on the real-time cutting depth; a collaborative adjustment module for generating a penetration risk characterization quantity, adjusting the real-time cutting parameters based on the penetration risk characterization quantity, and obtaining target cutting parameters; and a control output module for driving the laser cutting actuator to perform cutting operations on the quartz crystal according to the target cutting parameters. This invention significantly improves the stability, accuracy, and yield of quartz crystal laser cutting.

Description

Technical Field

[0001] This invention relates to the field of quartz crystal laser cutting technology, and more specifically, to a quartz crystal laser cutting method and system based on multi-parameter fusion control. Background Technology

[0002] Quartz crystal, as an important piezoelectric material, is widely used in high-end fields such as electronics, communications, and aerospace due to its excellent electromechanical properties. Laser cutting technology, with its advantages of high precision, high speed, and small heat-affected zone, has become a key means of precision machining of quartz crystals. However, quartz crystals are brittle, have low thermal conductivity, and are sensitive to temperature changes. During laser cutting, the interaction between laser energy and the material produces complex physicochemical changes, which can easily lead to problems such as edge chipping, excessive heat-affected zone, decreased cutting accuracy, and even crystal fragmentation. Traditional laser cutting control methods mostly use single-parameter closed-loop control, which only adjusts the laser power or cutting speed to maintain the stability of the cutting process. However, this is difficult to fully reflect the dynamic changes during the cutting process, especially in the critical stage when the cutting is about to penetrate the quartz crystal. The internal stress release and heat accumulation effects of the material intensify, and single-parameter control often has a lag in response, failing to avoid the risk of uncontrolled penetration in time. This leads to a decrease in product yield and seriously restricts the development of quartz crystal devices towards higher precision and more complex structures.

[0003] Therefore, it is necessary to design a quartz crystal laser cutting method and system based on multi-parameter fusion control to solve the problems existing in the current technology. Summary of the Invention

[0004] In view of this, the present invention proposes a method and system for laser cutting of quartz crystals based on multi-parameter fusion control, which aims to solve the problems of slow response of single-parameter control in the current technology, inability to avoid the risk of runaway through penetration in time, reduced product yield, and restriction on the development of quartz crystal devices towards high precision and complex structures.

[0005] This invention proposes a quartz crystal laser cutting system based on multi-parameter fusion control, comprising: The parameter receiving module is used to receive real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process. The cutting stage determination module is used to determine the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters; when the cutting stage is determined to be the thermally controlled penetration stage, the real-time cutting depth is collected, and the cutting process is judged to have entered the critical penetration state based on the real-time cutting depth. The collaborative adjustment module, when it is determined that the cutting process has entered the critical state of penetration, collects the penetration runaway risk parameters related to the critical state of penetration, generates a penetration risk characterization quantity, adjusts the real-time cutting parameters based on the penetration risk characterization quantity, and obtains the target cutting parameters. The control output module is used to output the target cutting parameters to the laser cutting actuator to drive the laser cutting actuator to cut the quartz crystal according to the target cutting parameters.

[0006] Furthermore, the real-time cutting parameters include single-pulse energy, laser scanning speed, and focus offset; the thermally correlated feedback parameters include the cutting area temperature and temperature change rate; and the cutting stages include the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage.

[0007] Furthermore, when determining the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters, the following steps are included: Obtain the cutting-thermal correlation vectors corresponding to the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage, respectively; A cutting-thermal correlation feature vector is constructed based on the real-time cutting parameters and thermal correlation feedback parameters; Calculate the degree of correlation between the cutting-heat related feature vector and the correlation vector of each cutting-heat related stage; The cutting stage of the quartz crystal cutting process is determined based on the degree of correlation.

[0008] Furthermore, when determining whether the cutting process has entered the critical penetration state based on the real-time cutting depth, the following steps are included: Obtain the target cutting thickness of the quartz crystal; Obtain the difference between the target cutting thickness and the real-time cutting depth, and record it as the cutting difference; The cutting difference is compared with the cutting difference threshold, and the cutting process is determined to have entered the critical state of penetration based on the comparison result. When the cutting difference is greater than the cutting difference threshold, it is determined that the cutting process has not entered the critical state of penetration; When the cutting difference is less than or equal to the cutting difference threshold, the cutting process is determined to have entered the critical state of penetration.

[0009] Furthermore, when collecting penetration runaway risk parameters related to the penetration critical state and generating penetration risk characterization quantities, the following are included: Obtain the thermal correlation feedback parameters under the critical state of penetration; Based on the aforementioned thermally related feedback parameters, a runaway risk parameter for penetrating the cutting area is extracted to characterize the degree of thermal accumulation and the trend of thermal change in the cutting area. The penetration risk parameters are normalized or weighted to construct a penetration risk feature vector; Calculate the penetration risk assessment value based on the penetration risk feature vector; The penetration risk assessment value is used as a penetration risk characterization quantity.

[0010] Furthermore, when calculating the penetration risk assessment value based on the penetration risk feature vector, the following steps are included: Obtain the feature components corresponding to each penetration runaway risk parameter in the penetration risk feature vector; Time series analysis is performed on each of the aforementioned feature components to extract the magnitude, rate, and trend of change of each penetrating runaway risk parameter in the current cutting stage. Based on the change amplitude, change rate and change trend information of each of the aforementioned characteristic components, the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components are determined respectively; The instantaneous risk contribution value and the trend risk contribution value are fused together to obtain the intermediate level of stage risk. Based on the distribution of the intermediate risk amount in the stage within the preset risk range, the intermediate risk amount in the stage is normalized or mapped to obtain the comprehensive risk amount. The comprehensive risk level is determined as the end-risk assessment value.

[0011] Furthermore, when determining the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components based on the change amplitude, change rate, and change trend information of each characteristic component, the process includes: Obtain the feature components of each runaway risk parameter at the current time point and in the adjacent time period; The magnitude of change of each feature component is calculated based on the numerical changes of the feature components in adjacent time periods. Calculate the rate of change of each feature component based on the changes of the feature components in adjacent time periods; Trend analysis is performed on the magnitude and rate of change of the feature components over multiple consecutive time periods to obtain the trend information of each feature component. Based on the magnitude and rate of change, determine the instantaneous risk contribution value corresponding to each of the aforementioned feature components; Based on the changing trend information, determine the trend risk contribution value corresponding to each of the aforementioned feature components.

[0012] Furthermore, when fusing the instantaneous risk contribution value and the trend risk contribution value to obtain the intermediate level of stage risk, the process includes: Obtain the instantaneous risk contribution value and trend risk contribution value corresponding to each runaway risk parameter; Based on the thermal stability characteristics within the current cutting stage, determine the fusion weights corresponding to the instantaneous risk contribution value and the trend risk contribution value; Based on the fusion weight, the instantaneous risk contribution value and the trend risk contribution value are weighted and fused to obtain the initial stage risk amount; A continuity analysis is performed on the initial stage risk quantity to determine the consistency of its changes in adjacent time periods; When the initial stage risk quantity shows a sudden change trend, the initial stage risk quantity is suppressed or smoothed. The initial stage risk amount after suppression or smoothing is determined as the intermediate stage risk amount.

[0013] Further, when adjusting the real-time cutting parameters based on the penetration risk characterization quantity and obtaining the target cutting parameters, the process includes: The penetration risk characterization quantity is compared with the first penetration risk characterization quantity and the second penetration risk characterization quantity, and the adjustment strategy of the real-time cutting parameters is determined based on the comparison result; wherein, the first penetration risk characterization quantity is smaller than the second penetration risk characterization quantity; When the penetration risk characterization value is less than or equal to the first penetration risk characterization value, the adjustment strategy is determined to be the first adjustment strategy; When the penetration risk characterization value is greater than the first penetration risk characterization value and less than or equal to the second penetration risk characterization value, the adjustment strategy is determined to be the second adjustment strategy. When the penetration risk representation quantity is greater than the second penetration risk representation quantity, the adjustment strategy is determined to be the third adjustment strategy.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: The quartz crystal laser cutting system based on multi-parameter fusion control provided by this invention achieves accurate identification of the quartz crystal cutting stage by real-time acquisition of multi-dimensional parameters (real-time cutting parameters and thermally related feedback parameters) during the cutting process. Especially in the thermally controlled penetration stage, it can promptly determine whether the cutting has entered the critical penetration state by analyzing the difference between the real-time cutting depth and the target cutting thickness. When this state is entered, the system further acquires penetration runaway risk parameters. By extracting and fusing key information such as the degree of heat accumulation and the trend of thermal changes, a scientific penetration risk characterization quantity is generated. Based on this, real-time cutting parameters such as single-pulse energy, laser scanning speed, and focus offset are dynamically adjusted. This effectively avoids problems such as thermal damage to the cutting edge, edge chipping, or insufficient cutting accuracy caused by thermal runaway in traditional cutting methods, significantly improving the stability, accuracy, and yield of quartz crystal laser cutting, and providing reliable technical support for the large-scale production of high-precision quartz crystal components.

[0015] In another aspect, this invention also proposes a method for laser cutting of quartz crystals based on multi-parameter fusion control, comprising the following steps: Receive real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process; The cutting stage of the quartz crystal cutting process is determined based on the real-time cutting parameters and thermally related feedback parameters; when the cutting stage is determined to be the thermally controlled penetration stage, the real-time cutting depth is collected, and the cutting process is judged to have entered the critical penetration state based on the real-time cutting depth. When the cutting process is determined to have entered the critical state of penetration, the penetration runaway risk parameters related to the critical state of penetration are collected, and a penetration risk characterization quantity is generated. Based on the penetration risk characterization quantity, the real-time cutting parameters are adjusted, and the target cutting parameters are obtained. The target cutting parameters are output to the laser cutting actuator to drive the laser cutting actuator to cut the quartz crystal according to the target cutting parameters.

[0016] It is understandable that the above-mentioned quartz crystal laser cutting method and system based on multi-parameter fusion control have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0017] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1A structural block diagram of a quartz crystal laser cutting system based on multi-parameter fusion control provided in an embodiment of the present invention; Figure 2 A flowchart of a quartz crystal laser cutting method based on multi-parameter fusion control provided for embodiments of the present invention. Detailed Implementation

[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] See Figure 1 As shown in some embodiments of this application, this embodiment provides a quartz crystal laser cutting system based on multi-parameter fusion control, including: The parameter receiving module is used to receive real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process. The cutting stage determination module is used to determine the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters; when the cutting stage is determined to be the thermally controlled penetration stage, the real-time cutting depth is collected, and the cutting process is judged to have entered the critical penetration state based on the real-time cutting depth. The collaborative adjustment module, when it is determined that the cutting process has entered the critical state of penetration, collects the penetration runaway risk parameters related to the critical state of penetration, generates a penetration risk characterization quantity, adjusts the real-time cutting parameters based on the penetration risk characterization quantity, and obtains the target cutting parameters. The control output module is used to output the target cutting parameters to the laser cutting actuator to drive the laser cutting actuator to cut the quartz crystal according to the target cutting parameters.

[0020] It is understood that the quartz crystal laser cutting system based on multi-parameter fusion control provided in this embodiment achieves accurate identification of the quartz crystal cutting stage by real-time acquisition of multi-dimensional parameters (real-time cutting parameters and thermally related feedback parameters) during the cutting process. Especially in the thermally controlled penetration stage, it can promptly determine whether the cutting has entered the critical penetration state by analyzing the difference between the real-time cutting depth and the target cutting thickness. When this state is entered, the system further acquires penetration runaway risk parameters. By extracting and fusing key information such as the degree of heat accumulation and the trend of thermal changes, a scientific penetration risk characterization quantity is generated. Based on this, real-time cutting parameters such as single-pulse energy, laser scanning speed, and focus offset are dynamically adjusted. This effectively avoids problems such as thermal damage to the cutting edge, edge chipping, or insufficient cutting accuracy caused by thermal runaway in traditional cutting methods, significantly improving the stability, accuracy, and yield of quartz crystal laser cutting, and providing reliable technical support for the large-scale production of high-precision quartz crystal components.

[0021] Specifically, the real-time cutting parameters include single-pulse energy, laser scanning speed, and focus offset; the thermally correlated feedback parameters include the cutting area temperature and temperature change rate; and the cutting stages include the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage.

[0022] Understandably, the initial cutting stage corresponds to the period from when the laser first contacts the quartz crystal surface to when a preliminary cutting trajectory is formed. At this time, the single-pulse energy in the real-time cutting parameters is usually set to a low level, and the laser scanning speed is slow to ensure accurate positioning of the initial cutting point and avoid surface overheating. The main cutting stage is the primary process for cutting most of the thickness of the quartz crystal. During this stage, the single-pulse energy and laser scanning speed remain relatively stable according to the preset cutting strategy and material characteristics. The focal offset is also adaptively adjusted according to the increase in cutting depth to ensure a balance between cutting efficiency and cutting quality. The thermally controlled penetration stage is the critical stage in the cutting process as it approaches the lower surface of the quartz crystal. At this time, the heat accumulation effect in the cutting area gradually becomes significant. The temperature of the cutting area and the rate of temperature change in the thermally related feedback parameters become important bases for judging the cutting state. The system lays the foundation for subsequent judgment and parameter adjustment when entering the critical penetration state through real-time monitoring and analysis of these parameters.

[0023] Specifically, determining the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters includes: Obtain the cutting-thermal correlation vectors corresponding to the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage, respectively; A cutting-thermal correlation feature vector is constructed based on the real-time cutting parameters and thermal correlation feedback parameters; Calculate the degree of correlation between the cutting-heat related feature vector and the correlation vector of each cutting-heat related stage; The cutting stage of the quartz crystal cutting process is determined based on the degree of correlation.

[0024] Understandably, the cutting-thermal correlation vector corresponding to the maximum correlation is determined, and the cutting stage corresponding to this correlation vector is taken as the cutting stage in the quartz crystal cutting process. The correlation degree is calculated using a cosine similarity algorithm.

[0025] Specifically, determining whether the cutting process has entered the critical state of penetration based on the real-time cutting depth includes: Obtain the target cutting thickness of the quartz crystal; Obtain the difference between the target cutting thickness and the real-time cutting depth, and record it as the cutting difference; The cutting difference is compared with the cutting difference threshold, and the cutting process is determined to have entered the critical state of penetration based on the comparison result. When the cutting difference is greater than the cutting difference threshold, it is determined that the cutting process has not entered the critical state of penetration; When the cutting difference is less than or equal to the cutting difference threshold, the cutting process is determined to have entered the critical state of penetration.

[0026] Understandably, the cutting difference threshold refers to a critical value preset in advance during the laser cutting of quartz crystals to ensure the cutting quality during the thermally controlled penetration stage, based on the characteristics of the quartz crystal material, the target cutting accuracy requirements, and the range of laser cutting process parameters. The setting of this threshold needs to comprehensively consider factors such as the thickness uniformity of the quartz crystal, the thermal diffusion coefficient of the laser energy, and the quality standards of the cutting edge, and is usually determined through extensive experimental data fitting and process verification. For example, for a quartz crystal with a thickness of 1 mm and a required edge chipping amount of less than 5 μm, the cutting difference threshold can be set to 50 μm. That is, when the difference between the real-time cutting depth and the target cutting thickness decreases to 50 μm or less, the cutting process is determined to have entered the critical penetration state. At this time, the system needs to immediately initiate the subsequent penetration risk parameter acquisition and cutting parameter adjustment process to cope with the potential thermal runaway risk that may occur at the moment of penetration.

[0027] Specifically, when collecting penetration runaway risk parameters related to the penetration critical state and generating penetration risk characterization quantities, the following are included: Obtain the thermal correlation feedback parameters under the critical state of penetration; Based on the aforementioned thermally related feedback parameters, a runaway risk parameter for penetrating the cutting area is extracted to characterize the degree of thermal accumulation and the trend of thermal change in the cutting area. The penetration risk parameters are normalized or weighted to construct a penetration risk feature vector; Calculate the penetration risk assessment value based on the penetration risk feature vector; The penetration risk assessment value is used as a penetration risk characterization quantity.

[0028] Understandably, the parameters used to characterize the degree of heat accumulation and the trend of thermal change in the cutting area include the real-time maximum temperature of the cutting area, the rate of change of the temperature field gradient, the growth rate of the heat-affected zone area, and the thermal stress concentration factor. The real-time maximum temperature directly reflects the current level of heat accumulation in the cutting area; when the temperature exceeds the softening threshold of the quartz crystal, the material is highly susceptible to thermal deformation. The rate of change of the temperature field gradient reflects the speed and direction of heat diffusion around the cutting area; a larger gradient indicates a more severe local thermal shock, which may lead to microcracks at the cutting edge. The growth rate of the heat-affected zone area indirectly reflects the dynamic trend of heat accumulation by continuously monitoring the expansion speed of the heat-affected zone boundary; an excessively rapid growth rate indicates a rapidly increasing risk of thermal runaway. The thermal stress concentration factor is a comprehensive parameter calculated by combining the thermophysical properties of the quartz crystal (such as the coefficient of thermal expansion and the elastic modulus), used to assess the magnitude of internal stress caused by uneven temperature distribution. When this factor exceeds a critical value, edge chipping or delamination is highly likely to occur during the cutting process.

[0029] Specifically, calculating the penetration risk assessment value based on the penetration risk feature vector includes: Obtain the feature components corresponding to each penetration runaway risk parameter in the penetration risk feature vector; Time series analysis is performed on each of the aforementioned feature components to extract the magnitude, rate, and trend of change of each penetrating runaway risk parameter in the current cutting stage. Based on the change amplitude, change rate and change trend information of each of the aforementioned characteristic components, the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components are determined respectively; The instantaneous risk contribution value and the trend risk contribution value are fused together to obtain the intermediate level of stage risk. Based on the distribution of the intermediate risk amount in the stage within the preset risk range, the intermediate risk amount in the stage is normalized or mapped to obtain the comprehensive risk amount. The comprehensive risk level is determined as the end-risk assessment value.

[0030] Understandably, there is currently a penetration risk feature vector (X1, X2, X3, X4), where X1 is the normalized feature component of the real-time maximum temperature, X2 is the normalized feature component of the temperature field gradient change rate, X3 is the normalized feature component of the heat-affected zone area growth rate, and X4 is the normalized feature component of the thermal stress concentration factor. For example, in a certain penetration critical state, X1 is 0.72 (the real-time maximum temperature reaches 72% of the softening threshold), X2 is 0.65 (the temperature field gradient change rate is at a moderately high level), X3 is 0.58 (the heat-affected zone area grows at a critical rate of 58%), and X4 is 0.69 (the thermal stress concentration factor is close to the microcrack initiation threshold of the material). Time series analysis of each feature component revealed that X1 increased from 0.60 to 0.72 over the past 5 sampling periods, with a change range of 0.12 and a change rate of 0.024 / period, showing a continuous upward trend; X2 changed with a change range of 0.08 and a change rate of 0.016 / period, showing a steady upward trend; X3 changed with a change range of 0.15 and a change rate of 0.03 / period, showing a clear upward trend; and X4 changed with a change range of 0.11 and a change rate of 0.022 / period, showing a slow upward trend. Based on this, the instantaneous risk contribution value of X1 is set to 0.72 × 0.3 (weighting coefficient) = 0.216, and the trend risk contribution value is set to (0.12 × 0.4 + 0.024 × 0.3 + 0.8 × 0.3) × 0.3 = 0.2016 (where 0.8 is the trend assessment coefficient, representing the risk level of an upward trend). After combining the two, the intermediate stage risk of X1 is 0.216 + 0.2016 = 0.4176; similarly, the intermediate stage risks of X2, X3, and X4 are calculated to be 0.382, 0.459, and 0.432, respectively. The summation of the intermediate risk values ​​at each stage yields a total intermediate risk value of 1.6906. The preset risk range is [0,2]. After normalization, the comprehensive risk value is 1.6906 / 2 = 0.8453. This means that the penetration risk assessment value in this scenario is 0.8453, indicating that there is a high risk of thermal runaway in the current penetration critical state, and the real-time cutting parameters need to be significantly adjusted.

[0031] Specifically, when determining the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components based on their change magnitude, change rate, and change trend information, the following steps are included: Obtain the feature components of each runaway risk parameter at the current time point and in the adjacent time period; The magnitude of change of each feature component is calculated based on the numerical changes of the feature components in adjacent time periods. Calculate the rate of change of each feature component based on the changes of the feature components in adjacent time periods; Trend analysis is performed on the magnitude and rate of change of the feature components over multiple consecutive time periods to obtain the trend information of each feature component. Based on the magnitude and rate of change, determine the instantaneous risk contribution value corresponding to each of the aforementioned feature components; Based on the changing trend information, determine the trend risk contribution value corresponding to each of the aforementioned feature components.

[0032] Understandably, the magnitude of change is obtained by subtracting the value of the current feature component from the value of the feature component at the beginning of the adjacent time period. Its absolute value reflects the intensity of the parameter's fluctuation in the short term. For example, if a feature component rises from 0.5 to 0.7 in 1 second, the magnitude of change is 0.2. The rate of change is obtained by dividing the magnitude of change by the duration of the adjacent time period. If the aforementioned magnitude of change of 0.2 is completed within 1 second, the rate of change is 0.2 / second. This indicator can intuitively reflect how fast the parameter changes. The trend information is obtained by linearly fitting or moving average processing the magnitude and rate of change in multiple consecutive time periods (such as the past 3 or 5 time periods) to determine whether the parameter as a whole shows an upward, downward, or stable trend. For example, if the rates of change in 3 consecutive time periods are 0.1 / second, 0.15 / second, and 0.2 / second, respectively, then the trend can be determined to be an accelerating upward trend. The instantaneous risk contribution value is usually determined by multiplying the current value of the characteristic component by a preset weighting coefficient. The weighting coefficient is preset according to the degree of influence of the parameter on the cutting quality. For example, the real-time maximum temperature has the greatest impact on thermal runaway, so its weighting coefficient can be set to 0.35, while the weighting coefficient of the temperature field gradient change rate is set to 0.25. The trend risk contribution value is obtained by combining the change trend information, assigning different weights to the change amplitude and change rate, summing them, multiplying by a trend evaluation coefficient (e.g., 1.0 for an upward trend, 0.5 for a stable trend, and 0.2 for a downward trend), and finally multiplying it by the weighting coefficient of the parameter. For example, if a parameter has a change amplitude of 0.3 (weight 0.4), a change rate of 0.15 / second (weight 0.3), an upward trend (trend evaluation coefficient 1.0), and a weighting coefficient of 0.3, then the trend risk contribution value is (0.3×0.4+0.15×0.3)×1.0×0.3=0.0495.

[0033] Specifically, when fusing the instantaneous risk contribution value and the trend risk contribution value to obtain the intermediate level of stage risk, the following steps are included: Obtain the instantaneous risk contribution value and trend risk contribution value corresponding to each runaway risk parameter; Based on the thermal stability characteristics within the current cutting stage, determine the fusion weights corresponding to the instantaneous risk contribution value and the trend risk contribution value; Based on the fusion weight, the instantaneous risk contribution value and the trend risk contribution value are weighted and fused to obtain the initial stage risk amount; A continuity analysis is performed on the initial stage risk quantity to determine the consistency of its changes in adjacent time periods; When the initial stage risk quantity shows a sudden change trend, the initial stage risk quantity is suppressed or smoothed. The initial stage risk amount after suppression or smoothing is determined as the intermediate stage risk amount.

[0034] Understandably, assuming a critical penetration state, the instantaneous risk contribution value of X1 (the real-time maximum temperature characteristic component) is 0.28, and the trend risk contribution value is 0.22. At this point, real-time monitoring reveals that the thermal stability characteristics of the cutting area exhibit small temperature fluctuations and a stable expansion of the heat-affected zone boundary, indicating a relatively stable current thermal state. Therefore, a fusion weight of 0.6 is assigned to the instantaneous risk contribution value, and a fusion weight of 0.4 is assigned to the trend risk contribution value. The initial stage risk, calculated through weighted fusion, is 0.28 × 0.6 + 0.22 × 0.4 = 0.168 + 0.088 = 0.256. Subsequently, a continuity analysis was performed on the initial stage risk quantity. Comparing the initial stage risk quantities of the previous three sampling periods (0.245, 0.251, and 0.253), it was found that the current value of 0.256 is continuous with the previous values, without any abrupt changes (e.g., previous values ​​were all around 0.25, and the current value suddenly jumps to above 0.3). Therefore, no suppression or smoothing is needed, and 0.256 is directly determined as the intermediate stage risk quantity for X1. For example, if the instantaneous risk contribution value of X3 (the characteristic component of the growth rate of the heat-affected zone area) is 0.32 and the trend risk contribution value is 0.38, and the current thermal stability characteristics of the cut area show that the area of ​​the heat-affected zone has suddenly accelerated its growth in the past two periods, indicating poor thermal stability, then a weight of 0.4 is assigned to the instantaneous risk contribution value, and a weight of 0.6 is assigned to the trend risk contribution value. The initial stage risk quantity is 0.32 × 0.4 + 0.38 × 0.6 = 0.128 + 0.228 = 0.356. Continuity analysis revealed that the initial stage risk values ​​for the first three periods were 0.210, 0.230, and 0.250, respectively. The current value of 0.356 represents an increase of over 40% compared to the previous maximum value of 0.250, indicating a significant abrupt change. At this point, the system activates a smoothing mechanism, employing a moving average method to correct the risk. For example, the initial stage risk values ​​of the current period and the previous two periods (0.250 and 0.356) are averaged (assuming the previous period was 0.230, then (0.230 + 0.250 + 0.356) / 3 ≈ 0.279). The corrected value of 0.279 is used as the intermediate stage risk value for X3 to avoid deviations in subsequent risk assessments due to sudden fluctuations in a single parameter.

[0035] Specifically, when adjusting the real-time cutting parameters based on the penetration risk characterization quantity and obtaining the target cutting parameters, the process includes: The penetration risk characterization quantity is compared with the first penetration risk characterization quantity and the second penetration risk characterization quantity, and the adjustment strategy of the real-time cutting parameters is determined based on the comparison result; wherein, the first penetration risk characterization quantity is smaller than the second penetration risk characterization quantity; When the penetration risk characterization value is less than or equal to the first penetration risk characterization value, the adjustment strategy is determined to be the first adjustment strategy; When the penetration risk characterization value is greater than the first penetration risk characterization value and less than or equal to the second penetration risk characterization value, the adjustment strategy is determined to be the second adjustment strategy. When the penetration risk representation quantity is greater than the second penetration risk representation quantity, the adjustment strategy is determined to be the third adjustment strategy.

[0036] It is understood that real-time cutting parameters include single-pulse energy, laser scanning speed, and focus offset. Therefore, the preferred first adjustment strategy is to keep the current real-time cutting parameters unchanged, only monitoring and recording the parameter change trends in real time. The preferred second adjustment strategy is to fine-tune the real-time cutting parameters, such as appropriately reducing the single-pulse energy by 5%-10% or increasing the laser scanning speed by 3%-5%, while keeping the focus offset unchanged. The reduction in single-pulse energy needs to be dynamically determined based on the changing trend of the heat-affected zone area growth rate. If the heat-affected zone area growth rate shows a slow upward trend, a 5% reduction can be selected; if the growth rate is close to the critical value, a 10% reduction can be selected to more effectively suppress heat accumulation. Increasing the laser scanning speed reduces heat input by shortening the laser's action time in the unit cutting area. The adjustment range must ensure that the cutting depth meets the process requirements and avoid incomplete cutting due to excessive speed. The preferred third adjustment strategy is to immediately implement significant parameter adjustment measures, including reducing the single-pulse energy by 15%-20%, increasing the laser scanning speed by 8%-12%, and fine-tuning the focus offset by 0.02mm-0.05mm away from the material surface. The significant reduction in single-pulse energy aims to rapidly decrease the total heat input, while the substantial increase in laser scanning speed further reduces the thermal interaction time. Adjustment of the focus offset, by altering the distribution of laser energy within the material, reduces the energy density in the cutting area, thereby mitigating thermal stress concentration. Simultaneously with this third adjustment strategy, the system activates a high-frequency monitoring mode, acquiring thermally relevant feedback parameters every 0.5 seconds to track changes in the risk characterization value in real time. If the risk assessment value does not show a downward trend within three consecutive sampling periods, an emergency pause mechanism is triggered, and operations resume only after manual confirmation of the cutting status.

[0037] See Figure 2As shown in some embodiments of this application, this embodiment provides a quartz crystal laser cutting method based on multi-parameter fusion control, including the following steps: S100: Receives real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process; S200: Determine the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters; when the cutting stage is determined to be the thermally controlled penetration stage, collect the real-time cutting depth, and determine whether the cutting process has entered the critical penetration state based on the real-time cutting depth. S300: When it is determined that the cutting process has entered the critical state of penetration, the penetration runaway risk parameters related to the critical state of penetration are collected, and a penetration risk characterization quantity is generated. Based on the penetration risk characterization quantity, the real-time cutting parameters are adjusted, and the target cutting parameters are obtained. S400: Output the target cutting parameters to the laser cutting actuator to drive the laser cutting actuator to perform cutting operations on the quartz crystal according to the target cutting parameters.

[0038] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0039] This application is described with flowcharts and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowcharts and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0040] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A quartz crystal laser cutting system based on multi-parameter fusion control, characterized in that, include: The parameter receiving module is used to receive real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process. The cutting stage determination module is used to determine the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters. When the cutting stage is determined to be a heat-controlled penetration stage, the real-time cutting depth is collected, and the cutting process is judged to have entered the critical penetration state based on the real-time cutting depth. The collaborative adjustment module, when it is determined that the cutting process has entered the critical state of penetration, collects the penetration runaway risk parameters related to the critical state of penetration, generates a penetration risk characterization quantity, adjusts the real-time cutting parameters based on the penetration risk characterization quantity, and obtains the target cutting parameters. The control output module is used to output the target cutting parameters to the laser cutting actuator to drive the laser cutting actuator to cut the quartz crystal according to the target cutting parameters.

2. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 1, characterized in that, The real-time cutting parameters include single-pulse energy, laser scanning speed, and focus offset; the thermally correlated feedback parameters include the cutting area temperature and temperature change rate; the cutting stages include the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage.

3. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 2, characterized in that, When determining the cutting stage of the quartz crystal cutting process based on the real-time cutting parameters and thermally related feedback parameters, the following are included: Obtain the cutting-thermal correlation vectors corresponding to the initial cutting stage, the main cutting stage, and the thermally controlled penetration stage, respectively; A cutting-thermal correlation feature vector is constructed based on the real-time cutting parameters and thermal correlation feedback parameters; Calculate the degree of correlation between the cutting-heat related feature vector and the correlation vector of each cutting-heat related stage; The cutting stage of the quartz crystal cutting process is determined based on the degree of correlation.

4. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 3, characterized in that, When determining whether the cutting process has entered the critical state of penetration based on the real-time cutting depth, the following are included: Obtain the target cutting thickness of the quartz crystal; Obtain the difference between the target cutting thickness and the real-time cutting depth, and record it as the cutting difference; The cutting difference is compared with the cutting difference threshold, and the cutting process is determined to have entered the critical state of penetration based on the comparison result. When the cutting difference is greater than the cutting difference threshold, it is determined that the cutting process has not entered the critical state of penetration; When the cutting difference is less than or equal to the cutting difference threshold, the cutting process is determined to have entered the critical state of penetration.

5. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 4, characterized in that, When collecting penetration runaway risk parameters related to the penetration critical state and generating penetration risk characterization quantities, the following are included: Obtain the thermal correlation feedback parameters under the critical state of penetration; Based on the aforementioned thermally related feedback parameters, a runaway risk parameter for penetrating the cutting area is extracted to characterize the degree of thermal accumulation and the trend of thermal change in the cutting area. The penetration risk parameters are normalized or weighted to construct a penetration risk feature vector; Calculate the penetration risk assessment value based on the penetration risk feature vector; The penetration risk assessment value is used as a penetration risk characterization quantity.

6. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 5, characterized in that, When calculating the penetration risk assessment value based on the penetration risk feature vector, the following steps are included: Obtain the feature components corresponding to each penetration runaway risk parameter in the penetration risk feature vector; Time series analysis is performed on each of the aforementioned feature components to extract the magnitude, rate, and trend of change of each penetrating runaway risk parameter in the current cutting stage. Based on the change amplitude, change rate and change trend information of each of the aforementioned characteristic components, the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components are determined respectively; The instantaneous risk contribution value and the trend risk contribution value are fused to obtain the intermediate level of stage risk. Based on the distribution of the intermediate risk amount in the stage within the preset risk range, the intermediate risk amount in the stage is normalized or mapped to obtain the comprehensive risk amount. The comprehensive risk level is determined as the end-risk assessment value.

7. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 6, characterized in that, When determining the instantaneous risk contribution value and trend risk contribution value corresponding to each of the aforementioned characteristic components based on their change amplitude, change rate, and change trend information, the following steps are included: Obtain the feature components of each runaway risk parameter at the current time point and in the adjacent time period; The magnitude of change of each feature component is calculated based on the numerical changes of the feature components in adjacent time periods. Calculate the rate of change of each feature component based on the changes of the feature components in adjacent time periods; Trend analysis is performed on the magnitude and rate of change of the feature components over multiple consecutive time periods to obtain the trend information of each feature component. Based on the magnitude and rate of change, determine the instantaneous risk contribution value corresponding to each of the aforementioned feature components; Based on the changing trend information, determine the trend risk contribution value corresponding to each of the aforementioned feature components.

8. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 7, characterized in that, When fusing the instantaneous risk contribution value and the trend risk contribution value to obtain the intermediate level of stage risk, the following steps are included: Obtain the instantaneous risk contribution value and trend risk contribution value corresponding to each runaway risk parameter; Based on the thermal stability characteristics within the current cutting stage, determine the fusion weights corresponding to the instantaneous risk contribution value and the trend risk contribution value; Based on the fusion weight, the instantaneous risk contribution value and the trend risk contribution value are weighted and fused to obtain the initial stage risk amount; A continuity analysis is performed on the initial stage risk quantity to determine the consistency of its changes in adjacent time periods; When the initial stage risk quantity shows a sudden change trend, the initial stage risk quantity is suppressed or smoothed. The initial stage risk amount after suppression or smoothing is determined as the intermediate stage risk amount.

9. The quartz crystal laser cutting system based on multi-parameter fusion control according to claim 8, characterized in that, When adjusting the real-time cutting parameters based on the penetration risk characterization quantity and obtaining the target cutting parameters, the process includes: The penetration risk characterization quantity is compared with the first penetration risk characterization quantity and the second penetration risk characterization quantity, and the adjustment strategy of the real-time cutting parameters is determined based on the comparison result; wherein, the first penetration risk characterization quantity is smaller than the second penetration risk characterization quantity; When the penetration risk characterization value is less than or equal to the first penetration risk characterization value, the adjustment strategy is determined to be the first adjustment strategy; When the penetration risk characterization value is greater than the first penetration risk characterization value and less than or equal to the second penetration risk characterization value, the adjustment strategy is determined to be the second adjustment strategy. When the penetration risk representation quantity is greater than the second penetration risk representation quantity, the adjustment strategy is determined to be the third adjustment strategy.

10. A method for laser cutting of quartz crystals based on multi-parameter fusion control, applied to the quartz crystal laser cutting system based on multi-parameter fusion control as described in any one of claims 1-9, characterized in that, include: Receive real-time cutting parameters and thermally related feedback parameters generated during the quartz crystal cutting process; The cutting stage of the quartz crystal cutting process is determined based on the real-time cutting parameters and thermally related feedback parameters. When the cutting stage is determined to be a heat-controlled penetration stage, the real-time cutting depth is collected, and the cutting process is judged to have entered the critical penetration state based on the real-time cutting depth. When the cutting process is determined to have entered the critical state of penetration, the penetration runaway risk parameters related to the critical state of penetration are collected, and a penetration risk characterization quantity is generated. Based on the penetration risk characterization quantity, the real-time cutting parameters are adjusted, and the target cutting parameters are obtained. The target cutting parameters are output to the laser cutting actuator to drive the laser cutting actuator to cut the quartz crystal according to the target cutting parameters.

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