A smart adjustment and control system for aluminum profile cutting process

Abstract

This application relates to the technical field of aluminum profile cutting and discloses an intelligent adjustment and control system for the aluminum profile cutting process, comprising: an aluminum profile information input unit for acquiring the model information of the aluminum profile; a measurement unit for measuring the thickness value of the cross-section at different positions of the aluminum profile during cutting; an infrared imager for acquiring infrared image information of the aluminum profile cutting process; a real-time image acquisition module for acquiring real-time image information of the aluminum profile cutting process; a cooling system data interface terminal for interface acquisition of real-time operating parameters of the cooling system; and an adjustment control analysis module for determining an initial cutting control strategy based on the model information and the thickness value of the cross-section at different positions, adjusting the initial cutting control strategy in real time based on the infrared image information, real-time image information, and real-time operating parameters of the cooling system to obtain an adjusted cutting control strategy, and controlling the cutting according to the adjusted cutting control strategy.

Description

Technical Field

[0001] This application relates to the technical field of aluminum profile cutting, and in particular to an intelligent adjustment and control system for the aluminum profile cutting process. Background Technology

[0002] With the widespread application of intelligent manufacturing in the industrial field, the processing and manufacturing process can improve the quality of processing while ensuring efficiency. As a common type of profile, aluminum profiles are a basic and common operation when cut. However, due to the material characteristics of aluminum profiles, excessively fast cutting speeds can easily cause the saw blade to overheat, resulting in aluminum chips adhering to the saw teeth, causing a rough cut surface or even burns. On the other hand, excessively slow cutting speeds not only lead to lower cutting efficiency but also easily generate extrusion and burrs, which aggravates saw blade wear. Therefore, intelligent control of the aluminum profile cutting process is one of the issues that intelligent manufacturing aims to address.

[0003] In existing technologies, different cutting parameters are set for aluminum profiles of different models and specifications. Since the cutting parameters are set based on test data or experience data, they can basically meet the quality requirements of the cutting process. However, for irregularly shaped aluminum profiles, it is still difficult to control the cutting process. At the same time, the cutting speed may be too fast or too slow depending on the actual state of the aluminum profile and the actual processing, making it difficult to maintain a balance between cutting efficiency and cutting quality. Usually, cutting quality has a higher priority, which results in relatively low cutting efficiency. Therefore, how to maintain a balance between cutting efficiency and cutting quality in the aluminum profile processing is the fundamental problem that this invention aims to solve. Summary of the Invention

[0004] To maintain a balance between cutting efficiency and cutting quality during aluminum profile processing, this application provides an intelligent adjustment and control system for the aluminum profile cutting process, employing the following technical solution:

[0005] An intelligent adjustment and control system for aluminum profile cutting process includes:

[0006] An aluminum profile information input unit is used to obtain the model information of aluminum profiles;

[0007] The measuring unit is used to measure the thickness of cross-sections at different locations when cutting aluminum profiles.

[0008] Infrared imager, used to acquire infrared image information of the aluminum profile cutting process;

[0009] The real-time image acquisition module is used to acquire real-time image information of the aluminum profile cutting process;

[0010] The cooling system data interface is used to connect and obtain the real-time operating parameters of the cooling system;

[0011] The adjustment control analysis module is used to determine the initial cutting control strategy based on the model information and the thickness value of the cross section at different positions. The initial cutting control strategy is adjusted in real time based on infrared image information, real-time image information and real-time operating parameters of the cooling system to obtain the adjusted cutting control strategy. The cutting is controlled according to the adjusted cutting control strategy.

[0012] Optionally, the process of determining the initial cutting control strategy includes:

[0013] The cutting parameters for the preset standard thickness are obtained based on the model information of the aluminum profile.

[0014] The thickness variation curve with feed distance is obtained by fitting the thickness values ​​of cross sections at different positions. Based on the ratio of the thickness variation curve with feed distance to the standard thickness, the real-time cutting parameters under different feed distances are determined, and the real-time cutting parameters are used as the initial cutting control strategy.

[0015] Optionally, the process of adjusting the initial cutting control strategy in real time includes:

[0016] Infrared image information is extracted and analyzed to obtain temperature characteristic parameters;

[0017] After preprocessing the real-time operating parameters and temperature characteristic parameters of the cooling system, they are input into the cutting heat generation model to obtain the cutting heat index.

[0018] Based on the pre-trained model, real-time image information of the aluminum profile cutting process is identified to obtain the aluminum chip area. The characteristic parameters of the aluminum chip area are analyzed to obtain the abnormal state index of the cut aluminum chip.

[0019] Determine the reference temperature as a function of feed distance based on the thickness as a function of feed distance curve;

[0020] Calculate the correlation coefficients between the cutting heat index and the reference temperature curves as a function of feed distance at different feed positions;

[0021] The initial cutting control strategy is adjusted in real time based on the real-time difference between the cutting heat index and the reference temperature curve as a function of feed distance, the correlation coefficient, and the magnitude of the abnormality index of the cut aluminum chips.

[0022] When the real-time difference, the abnormality index of the cutting aluminum chip state, and the correlation coefficient are all within the corresponding threshold range, the adjustment scheme of the real-time cutting speed is determined according to the magnitude of the cutting heat index. The adjustment scheme includes increasing the real-time cutting speed and keeping the real-time cutting speed unchanged.

[0023] When one or more of the real-time difference, the abnormal state index of aluminum chips, and the correlation coefficient are outside the corresponding threshold range, the real-time cutting speed will be reduced.

[0024] Optionally, the process of obtaining the temperature characteristic parameters includes:

[0025] The infrared image information is divided into regions according to multiple preset temperature steps, and the area of ​​the region corresponding to each temperature step is obtained. The area of ​​the region corresponding to each temperature step and the average temperature are used as temperature feature parameters.

[0026] The process of obtaining the cutting heat index includes:

[0027] The temperature cooling parameters are obtained by superimposing the temperature characteristic parameters and temperature cooling parameters on the real-time flow rate and heat dissipation capacity index of the cooling system in the real-time operating parameters. The cutting heat generation model is used to obtain the cutting heat index by superimposing the temperature characteristic parameters and temperature cooling parameters.

[0028] Optionally, the overlay analysis process includes:

[0029] The temperature cooling value is determined based on the range of the highest average temperature in the temperature gradient of the temperature characteristic parameters and the temperature cooling parameters.

[0030] Add the average temperature value corresponding to each temperature step to the temperature cooling value to obtain the actual temperature value;

[0031] The area and actual temperature value of each temperature step are compared with the thermal model under the standard thickness. The thermal model includes the reference area and reference temperature under different temperature steps.

[0032] Obtain the area difference between the region and the reference area, and the temperature difference between the actual temperature value and the reference area;

[0033] The area difference and temperature difference are normalized separately, and the normalized values ​​of the area difference and temperature difference are weighted and summed to obtain the cutting temperature index under each temperature step.

[0034] The weight of each temperature step is determined based on the average temperature. The higher the average temperature, the higher the weight, and the sum of the weights of all temperature steps is 1.

[0035] The cutting heat index is obtained by summing the cutting temperature indices under each temperature step according to their corresponding weights.

[0036] Optionally, the process of obtaining the abnormality index of the cut aluminum chips includes:

[0037] Obtain the area of ​​the aluminum chip region in the real-time image information;

[0038] The real-time image information is converted from RGB color space to CIELab color space. Several points are selected in the aluminum chip area according to the preset dot matrix. The color difference ΔE between each point and the standard color corresponding to the aluminum profile model information is calculated. The top N points are selected in descending order of color difference ΔE.

[0039] Calculate the mean and variance of the color difference ΔE corresponding to the top N points. Determine the abnormality index of the cutting aluminum chip state based on the area of ​​the aluminum chip region, the mean and variance of the color difference ΔE. The more the area of ​​the aluminum chip region exceeds the reference value of the corresponding thickness, the greater the abnormality index of the cutting aluminum chip state. The greater the mean of the color difference ΔE, the greater the abnormality index of the cutting aluminum chip state. The greater the variance of the color difference ΔE, the greater the abnormality index of the cutting aluminum chip state.

[0040] Optionally, the process of determining the reference temperature versus feed distance curve includes:

[0041] Test and obtain cutting temperature data of aluminum profiles with the same model information in different thickness ranges, establish the correspondence between thickness range and cutting temperature, and obtain the reference temperature change curve with feed distance based on the feed distance change curve and the corresponding relationship.

[0042] Optionally, when it is determined that the real-time cutting speed needs to be reduced:

[0043] If only the correlation coefficient is outside the corresponding threshold range, the real-time cutting speed will be reduced by the preset number of units.

[0044] If the real-time difference is not within the corresponding threshold range and the abnormality index of the cut aluminum chip state is within the corresponding threshold range, then the amount of reduction in cutting speed is determined according to the range of the real-time difference.

[0045] If the abnormality index of the aluminum chip state is not within the corresponding threshold range and the real-time difference is within the corresponding threshold range, then the reduction in cutting speed is determined according to the range of the abnormality index of the aluminum chip state.

[0046] Otherwise, the reduction in cutting speed is determined by combining the range of the real-time difference and the range of the abnormality index of the cut aluminum chips.

[0047] In summary, this application includes at least one of the following beneficial technical effects:

[0048] This invention determines the corresponding cutting parameters by measuring the thickness at different cutting positions in real time. Since the cutting parameters are obtained by integrating verified data, the balance between cutting efficiency and cutting quality can be initially guaranteed according to this data. At the same time, by comprehensively considering the heat generation state and aluminum chip state during the cutting process, real-time anomalies in the cutting process can be judged. Then, the adjusted cutting control strategy is obtained by adjusting the control analysis module. The cutting is controlled according to the adjusted cutting control strategy, thus ensuring the balance between cutting efficiency and cutting quality during the cutting process. Attached Figure Description

[0049] Figure 1 This is the principle logic diagram of the intelligent adjustment and control system for the aluminum profile cutting process. Detailed Implementation

[0050] The embodiments of this application are described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0051] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0052] This application discloses an intelligent adjustment and control system for aluminum profile cutting process, referring to... Figure 1 The system includes an aluminum profile information input unit, a measurement unit, an infrared imager, a real-time image acquisition module, a cooling system data interface, and an adjustment control analysis module. In this embodiment, the aluminum profile information input unit and the measurement unit determine the basic cutting parameters to determine the initial cutting control strategy. First, the aluminum profile model information is obtained through the aluminum profile information input unit. Then, the thickness values ​​of the cross-sections at different cutting positions of the aluminum profile are measured by the measurement unit. This function can be achieved by integrating a laser thickness gauge into the cutting equipment. Afterward, the adjustment control analysis module determines the initial cutting control strategy based on the model information and the thickness values ​​of the cross-sections at different positions. Through this process, for aluminum profiles with complex structures, the corresponding cutting parameters can be determined by real-time thickness measurement at different cutting positions. Since the cutting parameters are obtained by integrating verified data, the balance between cutting efficiency and cutting quality can be initially guaranteed according to this data.

[0053] Furthermore, since the aluminum profile cutting process is affected by batch size and environmental factors, this embodiment also collects and analyzes the parameters of the cutting process through an infrared imager, a real-time image acquisition module, and a data interface with the cooling system. Then, the initial cutting control strategy is adjusted in real time through the adjustment control analysis module, further ensuring the cutting efficiency and quality. Specifically, the infrared imager acquires infrared image information of the aluminum profile cutting process, the cooling system data interface is used to acquire the real-time operating parameters of the cooling system, and the infrared image information and the real-time operating parameters of the cooling system reflect the heat generation status of the cutting process. The real-time image acquisition module acquires real-time image information of the aluminum profile cutting process. By analyzing the real-time image information, the aluminum chips generated during the cutting process can be judged. Therefore, by comprehensively considering the heat generation status and aluminum chip status of the cutting process, real-time anomalies in the cutting process can be judged, and then the adjusted cutting control strategy is obtained through the adjustment control analysis module. The cutting is controlled according to the adjusted cutting control strategy, ensuring the balance between cutting efficiency and cutting quality during the cutting process.

[0054] The process of determining the initial cutting control strategy includes: firstly, obtaining the cutting parameters under the preset standard thickness according to the model information of the aluminum profile. The preset standard thickness is set according to conventional selection, and the cutting parameters are set according to the verified test data or historical data. Therefore, by fitting the thickness value of the cross-section at different positions, a thickness variation curve with feed distance is obtained. Based on the ratio of the thickness variation curve with feed distance to the standard thickness, the real-time cutting parameters under different feed distances are determined. It should be noted here that the ratio and the real-time cutting parameters are not linearly related, but rather different thickness ranges are set according to the comparison relationship with the preset standard thickness based on the verified data. Using the real-time cutting parameters as the initial cutting control strategy can initially ensure the balance between cutting efficiency and cutting quality.

[0055] The process of real-time adjustment of the initial cutting control strategy includes: firstly, extracting and analyzing infrared image information to obtain temperature characteristic parameters; secondly, preprocessing the real-time operating parameters of the cooling system and the temperature characteristic parameters and inputting them into the cutting heat generation model to obtain the cutting heat index. Therefore, the cutting heat index reflects the actual heat generation status of the cutting process. Compared to directly judging through infrared image information, this embodiment uses the real-time operating parameters of the cooling system to infer the temperature reduction and comprehensively determines the cutting heat index based on the temperature characteristic parameters, which can maximize the judgment of abnormalities in the cutting process through temperature status. Furthermore, this embodiment uses a pre-trained model to identify real-time image information of the aluminum profile cutting process to obtain… A pre-trained model based on a convolutional neural network (CNN) is trained on standard images of the aluminum chip area during the cutting process. Then, the model is analyzed based on the characteristic parameters of the aluminum chip area. An abnormality index of the cutting aluminum chip state is obtained based on the size and color characteristics of the aluminum chip area. Next, a reference temperature curve is determined based on the thickness-feed distance variation curve. This process involves obtaining cutting temperature data for aluminum profiles of the same model at different thickness ranges through testing, establishing a correspondence between thickness ranges and cutting temperatures. Based on the feed distance variation curve and the corresponding relationship, a reference temperature curve is obtained based on the feed distance variation curve. Finally, the correlation coefficient between the cutting heat index at different feed positions and the reference temperature curve is calculated. The correlation coefficient is calculated using the cutting heat index and reference temperature at several equally spaced feed distance points, employing existing correlation formulas. This coefficient determines the consistency between the cutting heat index and reference temperature curves as a function of feed distance at different feed distance points. Finally, the initial cutting control strategy is adjusted in real-time based on the real-time difference between the cutting heat index and reference temperature curves as a function of feed distance, the correlation coefficient, and the magnitude of the abnormality index of the cut aluminum chip state. When the real-time difference, the abnormality index of the cut aluminum chip state, and the correlation coefficient are all within their respective threshold ranges, the current state is considered normal. At this point, an adjustment scheme for the real-time cutting speed is determined based on the magnitude of the cutting heat index. This adjustment scheme includes increasing the real-time cutting speed and maintaining the real-time cutting speed... The cutting speed remains constant. If the cutting heat index is low, the real-time cutting speed is increased; otherwise, the real-time cutting speed remains constant. If one or more of the real-time difference, the abnormal state index of the cutting aluminum chips, and the correlation coefficient are outside the corresponding threshold range, the real-time cutting speed is reduced. If only the correlation coefficient is outside the corresponding threshold range, the real-time cutting speed is reduced by a preset unit amount. If the real-time difference is outside the corresponding threshold range but the abnormal state index of the cutting aluminum chips is within the corresponding threshold range, the reduction in cutting speed is determined based on the range of the real-time difference. If the abnormal state index of the cutting aluminum chips is outside the corresponding threshold range but the real-time difference is within the corresponding threshold range, the reduction in cutting speed is determined based on the range of the abnormal state index of the cutting aluminum chips.Otherwise, the reduction in cutting speed is determined by comprehensively considering the range of the real-time difference and the range of the abnormality index of the aluminum chip state. The above adjustment strategy explains that the real-time difference between the abnormality index of the aluminum chip state, the cutting heat index, and the reference temperature versus feed distance curve is directly related to the cutting speed. Therefore, the reduction in cutting speed is adjusted based on the magnitude of both values ​​(if neither is within the corresponding threshold range, both values ​​are considered together; if one is not within the corresponding threshold range, the value of that value is used). The correlation coefficient is related to the overall cutting process; therefore, if only the correlation coefficient is not within the corresponding threshold range, the real-time cutting speed is reduced by a preset unit amount, i.e., fine-tuning is performed. Furthermore, the corresponding thresholds and preset unit amounts in the above scheme are set based on verified test data or historical data. The process of determining the real-time cutting speed and the reduction in cutting speed based on the magnitude of the cutting heat index involves fitting a corresponding relationship based on the verified data, and then determining the real-time cutting speed and the reduction in cutting speed based on this relationship.

[0056] Meanwhile, the process of acquiring temperature characteristic parameters includes: dividing the infrared image information into regions according to multiple preset temperature steps. The temperature steps are set based on temperature experience data from the cutting process. The area corresponding to each temperature step is obtained, and the area and average temperature of each temperature step are used as temperature characteristic parameters. The process of acquiring the cutting heat index includes: obtaining temperature cooling parameters based on the real-time flow rate and heat dissipation capacity index of the cooling system in the real-time operating parameters. The temperature characteristic parameters and temperature cooling parameters are superimposed and analyzed using a cutting heat generation model to obtain the cutting heat index. The superposition analysis process includes: determining the temperature cooling value based on the range of the highest average temperature in the temperature steps and the temperature cooling parameter. This process is based on the temperature decay data corresponding to different coolant flow rates in different temperature ranges of the cooling system in the test data. The average temperature corresponding to each temperature step is added to the temperature cooling value to obtain the actual temperature value. The actual temperature value is calculated; the area and actual temperature value corresponding to each temperature step are compared with the thermal model under the standard thickness. The thermal model includes reference area and reference temperature under different temperature steps, which is fitted and set according to the test data under the standard thickness. Then, the area difference between the area and the reference area and the temperature difference between the actual temperature value and the reference area are obtained. The area difference and temperature difference are normalized respectively. The normalized values ​​of the area difference and temperature difference are weighted and summed. The corresponding weights are set according to empirical data. Finally, the cutting temperature index under each temperature step is obtained. The weight corresponding to each temperature step is determined according to the temperature mean. The higher the temperature mean, the higher the weight, and the sum of the weights of all temperature steps is 1. The cutting temperature index under each temperature step is weighted and summed according to the corresponding weight to obtain the cutting heat index. Therefore, the cutting heat index comprehensively judges the temperature distribution range and magnitude, which improves the accuracy of judgment compared with the temperature judgment of a single point.

[0057] In addition, the process of obtaining the abnormality index of the cut aluminum chips in this embodiment includes: obtaining the area of ​​the aluminum chip region in the real-time image information; converting the real-time image information from RGB color space to CIELab color space; selecting a number of points in the aluminum chip region according to a preset dot matrix, the spacing of the preset dot matrix being set according to the size of the cutting area; calculating the color difference ΔE between each point and the standard color corresponding to the aluminum profile model information; the calculation formula for the color difference ΔE is obtained according to the CIE definition, which reflects the degree of color difference; the larger the color difference ΔE, the greater the difference. Select the top N points in descending order of E; calculate the mean and variance of the color difference ΔE corresponding to the top N points; determine the aluminum chip state anomaly index based on the area of ​​the aluminum chip region, the mean and variance of the color difference ΔE; the more the area of ​​the aluminum chip region exceeds the reference value of the corresponding thickness, the larger the aluminum chip state anomaly index; the larger the mean of the color difference ΔE, the larger the aluminum chip state anomaly index; the larger the variance of the color difference ΔE, the larger the aluminum chip state anomaly index. By measuring the magnitude of the aluminum chip state anomaly index, it is possible to judge abnormal temperature during the cutting process.

[0058] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An intelligent adjustment control system for an aluminum profile cutting process, characterized by, include: An aluminum profile information input unit is used to obtain the model information of aluminum profiles; The measuring unit is used to measure the thickness of cross-sections at different locations when cutting aluminum profiles. Infrared imager, used to acquire infrared image information of the aluminum profile cutting process; The real-time image acquisition module is used to acquire real-time image information of the aluminum profile cutting process; The cooling system data interface is used to connect and obtain the real-time operating parameters of the cooling system; The adjustment control analysis module is used to determine the initial cutting control strategy based on the model information and the thickness value of the cross section at different positions. The initial cutting control strategy is adjusted in real time based on infrared image information, real-time image information and real-time operating parameters of the cooling system to obtain the adjusted cutting control strategy. The cutting is controlled according to the adjusted cutting control strategy. The process of determining the initial cutting control strategy includes: The cutting parameters for the preset standard thickness are obtained based on the model information of the aluminum profile. The thickness variation curve with feed distance is obtained by fitting the thickness values ​​of cross sections at different positions. Based on the ratio of the thickness variation curve with feed distance to the standard thickness, the real-time cutting parameters under different feed distances are determined, and the real-time cutting parameters are used as the initial cutting control strategy. The process of adjusting the initial cutting control strategy in real time includes: Infrared image information is extracted and analyzed to obtain temperature characteristic parameters; After preprocessing the real-time operating parameters and temperature characteristic parameters of the cooling system, they are input into the cutting heat generation model to obtain the cutting heat index. Based on the pre-trained model, real-time image information of the aluminum profile cutting process is identified to obtain the aluminum chip area. The characteristic parameters of the aluminum chip area are analyzed to obtain the abnormal state index of the cut aluminum chip. Determine the reference temperature as a function of feed distance based on the thickness as a function of feed distance curve; Calculate the correlation coefficients between the cutting heat index and the reference temperature curves as a function of feed distance at different feed positions; The initial cutting control strategy is adjusted in real time based on the real-time difference between the cutting heat index and the reference temperature curve as a function of feed distance, the correlation coefficient, and the magnitude of the abnormality index of the cut aluminum chips. When the real-time difference, the abnormality index of the cutting aluminum chip state, and the correlation coefficient are all within the corresponding threshold range, the adjustment scheme of the real-time cutting speed is determined according to the magnitude of the cutting heat index. The adjustment scheme includes increasing the real-time cutting speed and keeping the real-time cutting speed unchanged. When one or more of the real-time difference, the abnormal state index of aluminum chips, and the correlation coefficient are outside the corresponding threshold range, the real-time cutting speed will be reduced.

2. The intelligent adjustment control system for aluminum profile cutting process according to claim 1, characterized in that, The process of obtaining the temperature characteristic parameters includes: The infrared image information is divided into regions according to multiple preset temperature steps, and the area of ​​the region corresponding to each temperature step is obtained. The area of ​​the region corresponding to each temperature step and the average temperature are used as temperature feature parameters. The process of obtaining the cutting heat index includes: The temperature cooling parameters are obtained by superimposing the temperature characteristic parameters and temperature cooling parameters on the real-time flow rate and heat dissipation capacity index of the cooling system in the real-time operating parameters. The cutting heat generation model is used to obtain the cutting heat index by superimposing the temperature characteristic parameters and temperature cooling parameters.

3. The intelligent adjustment control system for aluminum profile cutting process according to claim 2, characterized in that, The overlay analysis process includes: The temperature cooling value is determined based on the range of the highest average temperature in the temperature gradient of the temperature characteristic parameters and the temperature cooling parameters. Add the average temperature value corresponding to each temperature step to the temperature cooling value to obtain the actual temperature value; The area and actual temperature value of each temperature step are compared with the thermal model under the standard thickness. The thermal model includes the reference area and reference temperature under different temperature steps. Obtain the area difference between the region and the reference area, and the temperature difference between the actual temperature value and the reference area; The area difference and temperature difference are normalized separately, and the normalized values ​​of the area difference and temperature difference are weighted and summed to obtain the cutting temperature index under each temperature step. The weight of each temperature step is determined based on the average temperature. The higher the average temperature, the higher the weight, and the sum of the weights of all temperature steps is 1. The cutting heat index is obtained by summing the cutting temperature indices under each temperature step according to their corresponding weights.

4. The intelligent adjustment control system for aluminum profile cutting process according to claim 3, characterized in that, The process of obtaining the abnormal state index of the cut aluminum chips includes: Obtain the area of ​​the aluminum chip region in the real-time image information; The real-time image information is converted from RGB color space to CIELab color space. Several points are selected in the aluminum chip area according to the preset dot matrix. The color difference ΔE between each point and the standard color corresponding to the aluminum profile model information is calculated. The top N points are selected in descending order of color difference ΔE. Calculate the mean and variance of the color difference ΔE corresponding to the top N points. Determine the abnormality index of the cutting aluminum chip state based on the area of ​​the aluminum chip region, the mean and variance of the color difference ΔE. The more the area of ​​the aluminum chip region exceeds the reference value of the corresponding thickness, the greater the abnormality index of the cutting aluminum chip state. The greater the mean of the color difference ΔE, the greater the abnormality index of the cutting aluminum chip state. The greater the variance of the color difference ΔE, the greater the abnormality index of the cutting aluminum chip state.

5. The intelligent adjustment and control system for aluminum profile cutting process according to claim 1, characterized in that, The process of determining the reference temperature versus feed distance curve includes: Test and obtain cutting temperature data of aluminum profiles with the same model information in different thickness ranges, establish the correspondence between thickness range and cutting temperature, and obtain the reference temperature change curve with feed distance based on the feed distance change curve and the corresponding relationship.

6. The intelligent adjustment and control system for aluminum profile cutting process according to claim 1, characterized in that, When it is determined that the real-time cutting speed needs to be reduced: If only the correlation coefficient is outside the corresponding threshold range, the real-time cutting speed will be reduced by the preset number of units. If the real-time difference is not within the corresponding threshold range and the abnormality index of the cut aluminum chip state is within the corresponding threshold range, then the amount of reduction in cutting speed is determined according to the range of the real-time difference. If the abnormality index of the aluminum chip state is not within the corresponding threshold range and the real-time difference is within the corresponding threshold range, then the reduction in cutting speed is determined according to the range of the abnormality index of the aluminum chip state. Otherwise, the reduction in cutting speed is determined by combining the range of the real-time difference and the range of the abnormality index of the cut aluminum chips.

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