A control method and system for a laser heating apparatus

Abstract

The application relates to the technical field of laser heating control, and discloses a control method and system for a laser heating device, which comprises the following steps: respectively comparing a laser influence parameter set and a material environment parameter set with historical data, and comparing influence similarity and material similarity with corresponding threshold values; if a matching first strategy is executed, determining a laser based on the comparison results of the laser influence parameter set and the material environment parameter set and the historical data; if a matching second strategy is executed, determining the laser influence parameter set based on a clustering algorithm, and / or determining a similar data set of the material environment parameter set and the historical data; establishing a running database, wherein the running database comprises a laser normal running library and a laser deviation running library; constructing a running data set based on the laser and screening to determine abnormal data; and performing self-adjusting control on the laser according to the comparison results. The application ensures the reliability of laser heating device control and self-adjusting.

Description

Technical Field

[0001] This invention relates to the field of laser heating control technology, and more specifically, to a control method and system for laser heating equipment. Background Technology

[0002] Laser heating is a non-contact, high-energy-density thermal processing technology widely used in high-end manufacturing fields such as semiconductor packaging, precision material annealing, microelectronic interconnects, and optical device fabrication. As industrial products evolve towards higher precision, the types of materials, thermophysical properties, and process requirements of the materials to be processed continue to diversify, placing stringent demands on the adaptability of laser heating equipment to different scenarios, the stability of its operation, and the efficiency of process parameter adjustment. Currently, laser heating can achieve heating efficiency and temperature control for specific materials and specific process scenarios. However, when the processed material changes, the existing equipment requires a replacement of the laser itself. Matching laser heating equipment relies heavily on operator experience, necessitating repeated manual adjustments to adapt to process requirements. This not only results in long adjustment cycles but also narrows the equipment's process window. Furthermore, the feedback mechanism of existing laser heating equipment is simplistic, lacking intelligent parameter self-tuning capabilities, making parameter correction difficult and reducing product yield and long-term equipment reliability.

[0003] Therefore, it is necessary to design a control method and system for laser heating equipment to solve the problems existing in the current technology. Summary of the Invention

[0004] In view of this, the present invention proposes a control method and system for laser heating equipment, aiming to solve the above-mentioned problems.

[0005] This invention proposes a control method for laser heating equipment, comprising: The laser influence parameter set and material environment parameter set of the material to be processed are obtained. The laser influence parameter set and the material environment parameter set are compared with historical data respectively. The influence similarity and material similarity are compared with the corresponding thresholds. Based on the threshold comparison results, it is determined whether to execute the first matching strategy or the second matching strategy. If the first matching strategy is executed, the laser is determined based on the comparison results between the laser influence parameter set and the material environment parameter set and the historical data. If the second matching strategy is executed, the laser influence parameter set is determined based on the clustering algorithm, and / or the similar datasets of the material environment parameter set and the historical data, and the laser is determined based on the overlap results of the similar datasets. An operational database is established, which includes a normal laser operation database and a laser deviation operation database. The operational database includes control commands, sensor monitoring data, and operational data, and the control commands, operational data, and sensor monitoring data correspond to each other. A running dataset is constructed based on the laser and abnormal data is identified through screening. The abnormal data is compared with the running database, and the laser is self-tuned based on the comparison results.

[0006] Furthermore, when acquiring the laser influence parameter set and material environment parameter set of the material to be processed, the following are included: The laser influence parameter set includes the reflectivity, transmittance, and absorptivity of the material to be processed; The set of material environmental parameters includes the moisture content and coating thickness of the material to be processed, as well as the transmittance of the protective gas used on the material to be processed.

[0007] Furthermore, when comparing the similarity and material similarity with corresponding thresholds, and determining whether to implement the first matching strategy or the second matching strategy based on the threshold comparison results, the following steps are included: Acquire historical laser impact database and historical material environment parameter library; The historical laser influence database includes several historical laser influence parameter sets and several historical lasers, with each historical laser influence parameter set corresponding to a historical laser. The historical material environment parameter library includes several historical material environment parameter sets and several historical lasers, and each historical material environment parameter set corresponds to a historical laser. The laser influence parameter set and the historical laser influence database are compared to determine the influence similarity; the material environment parameter set and the historical material environment parameter database are compared to determine the material similarity. If the influence similarity is greater than the influence similarity threshold, and the material similarity is greater than the material similarity threshold, then the first matching strategy is executed; otherwise, the second matching strategy is executed.

[0008] Furthermore, when the first matching strategy is executed, it includes: When the historical laser influence parameter set with influence similarity greater than the influence similarity threshold is unique, and the historical material environment parameter set with material similarity greater than the material similarity threshold is not unique, or when the historical laser influence parameter set with influence similarity greater than the influence similarity threshold is not unique, and the historical material environment parameter set with material similarity greater than the material similarity threshold is unique, then the historical laser corresponding to the historical laser influence parameter set with the maximum influence similarity or the historical material environment parameter set with the maximum material similarity is selected as the first candidate laser, and the historical laser corresponding to the unique historical laser influence parameter set or the historical material environment parameter set is selected as the second candidate laser. If the first candidate laser and the second candidate laser are the same, then the first candidate laser or the second candidate laser shall be used as the laser; otherwise, the second candidate laser shall be used as the laser.

[0009] Furthermore, when executing the first matching strategy, it also includes: When the set of historical laser influence parameters with influence similarity greater than the influence similarity threshold is unique, and the set of historical material environment parameters with material similarity greater than the material similarity threshold is unique, if the historical lasers corresponding to the set of historical laser influence parameters and the set of historical material environment parameters are the same, then the historical laser is taken as the laser; if the historical lasers corresponding to the set of historical laser influence parameters and the set of historical material environment parameters are not the same, then the historical lasers corresponding to the set of historical laser influence parameters are taken as the laser. When the set of historical laser influence parameters with influence similarity greater than the influence similarity threshold is not unique, and the set of historical material environment parameters with material similarity greater than the material similarity threshold is not unique, if the maximum influence similarity is greater than or equal to the maximum material similarity, then the historical laser corresponding to the maximum influence similarity is taken as the laser; if the maximum influence similarity is less than the maximum material similarity, then the historical laser corresponding to the maximum material similarity is taken as the laser.

[0010] Furthermore, when the second matching strategy is executed, it includes: When there exists an influence similarity greater than the influence similarity threshold, and there is no material similarity greater than the material similarity threshold, then a similar dataset between the laser influence parameter set and the historical laser influence database is determined based on a clustering algorithm, and the laser is identified in the similar dataset; When there is a material similarity greater than the material similarity threshold and there is no influence similarity greater than the influence similarity threshold, then a similar dataset between the material environment parameter set and the historical material environment parameter library is determined based on the clustering algorithm, and the laser is determined in the similar dataset; When there is no influence similarity greater than the influence similarity threshold, and there is no material similarity greater than the material similarity threshold, then a first similar dataset of the laser influence parameter set and the historical laser influence database, and a second similar dataset of the material environment parameter set and the historical material environment parameter database are determined based on the clustering algorithm.

[0011] Furthermore, when executing the second matching strategy, it also includes: If the historical lasers in the first similar dataset and the second similar dataset are the same, then the historical laser is used as the laser. If the historical lasers in the first similar dataset and the second similar dataset are not the same, then the historical laser in either the first similar dataset or the second similar dataset shall be used as the laser.

[0012] Furthermore, in identifying outlier data, the following should be considered: The data in the running dataset are compared with the corresponding operating condition ranges, and the data that is not within the operating condition range is identified as abnormal data.

[0013] Furthermore, the self-tuning control of the laser includes: The abnormal data is compared with the operating database, and the control instructions corresponding to the data in the operating database that are the same as the abnormal data are used to perform self-tuning control on the laser.

[0014] Compared with existing technologies, the advantages of this invention are as follows: By acquiring laser influence parameter sets and material environment parameter sets, the material to be processed can be comprehensively characterized from two dimensions: laser energy coupling characteristics and actual processing environment. This avoids matching deviations caused by selecting a laser solely based on single material information. Furthermore, by comparing the two parameter sets with historical laser influence databases and historical material environment parameter databases, and selecting either a first or second matching strategy based on influence similarity, material similarity, and corresponding thresholds, different laser determination methods can be adopted according to the degree of matching of historical data, improving the reliability of controlling the laser heating equipment. An operational database is established, including a normal laser operation database and a laser deviation operation database. Control commands, sensor monitoring data, and operational data are stored accordingly, preserving the operating patterns of the laser in normal and deviation states. Abnormal data is matched with the operational database, and corresponding control commands are invoked to implement self-tuning control of the laser. This achieves fully automated laser heating and reduces the time consumption and control errors caused by repeated manual adjustments. It realizes a closed-loop control system from material parameter acquisition, laser matching, operational status monitoring, anomaly identification to self-tuning control, improving the reliability of controlling the laser heating equipment.

[0015] On the other hand, this application also provides a control system for a laser heating device, for applying the above-described control method for a laser heating device, including: The acquisition and analysis unit is configured to acquire the laser influence parameter set and material environment parameter set of the material to be processed, compare the laser influence parameter set and the material environment parameter set with historical data respectively, and perform threshold comparison between the influence similarity and material similarity and the corresponding threshold, and determine whether to execute the first matching strategy or the second matching strategy based on the threshold comparison result. A first control unit is configured to, if the first matching strategy is executed, determine the laser based on the comparison results of the laser influence parameter set and the material environment parameter set with the historical data; if the second matching strategy is executed, determine the laser influence parameter set based on a clustering algorithm, and / or the similar dataset of the material environment parameter set and the historical data, and determine the laser based on the overlap results of the similar datasets. The storage control unit is configured to establish an operating database, which includes a normal laser operation database and a laser deviation operation database. The operating database includes control commands, sensor monitoring data, and operating data, and the control commands, the operating data, and the sensor monitoring data correspond to each other. The second control unit is configured to construct an operating dataset based on the laser and filter it to identify abnormal data, compare the abnormal data with the operating database, and perform self-tuning control on the laser based on the comparison results.

[0016] It is understandable that the control method and system described above for laser heating equipment have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart of a control method for a laser heating device provided in an embodiment of the present invention; Figure 2 A flowchart illustrating the execution of the second matching strategy provided in this embodiment of the invention; Figure 3 This is a functional block diagram of a control system for a laser heating device provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] See Figure 1-2 As shown in some embodiments of this application, a control method for a laser heating device includes: S100: Obtain the laser influence parameter set and material environment parameter set of the material to be processed, compare the laser influence parameter set and material environment parameter set with historical data respectively, and compare the influence similarity and material similarity with the corresponding thresholds. Based on the threshold comparison results, determine whether to execute the first matching strategy or the second matching strategy. S200: If the first matching strategy is executed, the laser is determined based on the comparison results of the laser influence parameter set and the material environment parameter set with historical data. If the second matching strategy is executed, the laser influence parameter set is determined based on the clustering algorithm, and / or the material environment parameter set is determined based on the similar dataset of historical data, and the laser is determined based on the overlap results of the similar dataset. S300: Establish an operation database, which includes a normal laser operation database and a laser deviation operation database. The operation database includes control commands, sensor monitoring data, and operation data, and the control commands, operation data, and sensor monitoring data correspond to each other. S400: Based on the laser, a running dataset is constructed and filtered to identify abnormal data. The abnormal data is compared with the running database, and the laser is self-tuned according to the comparison results.

[0022] Specifically, in S100, the laser influence parameter set and material environment parameter set of the material to be processed are first obtained. The material to be processed is the object that needs to be heated by a laser heating device. Different materials to be processed have different reflection, transmission, and absorption of laser energy when irradiated by laser. At the same time, the water content of the material itself, the state of the surface coating, and the influence of the protective gas on laser propagation may also be different. Therefore, this embodiment establishes two types of parameter sets from the perspectives of laser-material interaction and material and processing environment, respectively, so as to determine the laser suitable for the current material to be processed based on historical matching results from different dimensions. By integrating lasers of different wavelengths into the laser heating device, it is possible to adapt to different materials and application scenarios. Based on historical data, a suitable wavelength of laser can be quickly matched for heating, thereby improving processing efficiency.

[0023] The laser influence parameter set includes the reflectivity, transmittance, and absorptivity of the material to be processed. Reflectivity represents the proportion of laser energy incident on the surface of the material that is reflected by the surface; transmittance represents the proportion of laser energy that passes through the material or its heated area; and absorptivity represents the proportion of laser energy that the material can absorb and use to generate heat. These three parameters together reflect the interaction between the material and the laser energy. By simultaneously acquiring reflectivity, transmittance, and absorptivity, the influence of reflection or transmission can be avoided when selecting a laser based solely on a single absorption parameter, thereby improving the controllability of the laser heating equipment and expanding the process window.

[0024] The material environment parameter set includes the moisture content and coating thickness of the material to be processed, as well as the transmittance of the protective gas used to process the material. Moisture content reflects the degree of moisture contained within or on the surface of the material; coating thickness reflects the size and shape of the coating covering the surface of the material; and the transmittance of the protective gas reflects the extent to which the laser can continue to reach the material after passing through the protective gas. These three parameters complement the laser matching in terms of material condition and processing environment. That is, even if two materials to be processed have relatively similar laser influence parameters, their moisture content, coating thickness, or protective gas transmittance may still differ. Therefore, by using the material environment parameter set to determine whether the processing conditions are close to historical processing conditions, the reliability of the laser heating equipment in adapting and controlling different materials and application scenarios is ensured.

[0025] Obtain a historical laser effect database and a historical material environment parameter database. The historical laser effect database includes several historical laser effect parameter sets and several historical lasers, with each historical laser effect parameter set corresponding to a specific historical laser. The historical material environment parameter database includes several historical material environment parameter sets and several historical lasers, with each historical material environment parameter set corresponding to a specific historical laser. The historical lasers are those actually identified or used during historical processing. The correspondence in the historical laser effect database and the historical material environment parameter database indicates which laser was used under the corresponding historical parameter conditions, enabling the current material to be processed to achieve laser matching based on existing processing records. The historical laser effect database and the historical material environment parameter database can be constructed based on previously verified and successful experience, and can be accumulated and improved through subsequent data.

[0026] When comparing the current set of laser influence parameters with the historical laser influence database, the current set of laser influence parameters is compared sequentially with each historical set of laser influence parameters in the database. The similarity between the current set of laser influence parameters and the historical set of laser influence parameters is determined based on the closeness between the corresponding parameters. Similarly, when comparing the set of material environment parameters with the historical material environment parameter database, the material environment parameter set is compared sequentially with each historical set of material environment parameters in the database. The material similarity is determined based on the closeness of moisture content, coating thickness, and protective gas transmittance. Influence similarity and material similarity can be determined using methods such as Euclidean distance and cosine similarity.

[0027] The similarity of influence parameters is compared with the similarity threshold, and the similarity of materials is compared with the similarity threshold. The similarity threshold is used to determine whether the historical laser influence parameter set can be used as direct matching data for the current material to be processed. Similarly, the similarity threshold is used to determine whether the historical material environment parameter set can be used as direct matching data for the current material to be processed. The two thresholds can be set according to the distribution of historical data and the matching requirements of the laser heating equipment, and there are no specific limitations. When there is at least one historical laser influence parameter set in the historical laser influence database with an influence similarity greater than the influence similarity threshold, and there is at least one historical material environment parameter set in the historical material environment parameter database with a material similarity greater than the material similarity threshold, it means that the current material to be processed can find historical data that meets the direct matching requirements in both the laser effect dimension and the material environment dimension, and the first matching strategy is executed. Conversely, if there is no historical parameter set exceeding the corresponding threshold in either of the two dimensions, the second matching strategy is executed.

[0028] In S200, either the first matching strategy or the second matching strategy is executed based on the obtained threshold comparison results, and the laser used for the current material to be processed is determined. The laser is the device selected from historical lasers corresponding to historical data that matches the laser influence parameter set and the material environment parameter set; this is the irradiation body of the laser heating equipment and the object of subsequent self-tuning control. When the first matching strategy is executed, classification is performed based on the number of historical parameter sets (historical laser influence parameter set and historical material environment parameter set) exceeding the corresponding similarity threshold and the historical lasers corresponding to those historical parameter sets. Historical parameter sets exceeding the threshold may be unique or not. Uniqueness means that only one historical parameter set in the corresponding database has a similarity greater than the corresponding similarity threshold; not uniqueness means that two or more historical parameter sets have a similarity greater than the corresponding similarity threshold. The purpose of judging uniqueness is to distinguish whether the historical matching results can directly point to a single historical record, and to determine the final laser by comparison when the matching results of the two parameter dimensions are inconsistent, thereby adapting to different materials and application scenarios and ensuring the reliability of controlling the laser heating equipment.

[0029] The first scenario is where the set of historical laser influence parameters with an influence similarity greater than the influence similarity threshold is unique, while the set of historical material environment parameters with a material similarity greater than the material similarity threshold is not unique. In this case, multiple sets of historical material environment parameters that meet the material similarity threshold are compared according to material similarity. The set of historical material environment parameters with the highest material similarity is determined, and the historical laser corresponding to this set is selected as the first candidate laser. Simultaneously, the historical laser corresponding to the unique set of historical laser influence parameters that meets the influence similarity threshold is selected as the second candidate laser.

[0030] The second scenario is where the set of historical laser influence parameters with an impact similarity greater than the impact similarity threshold is not unique, while the set of historical material environment parameters with a material similarity greater than the material similarity threshold is unique. In this case, multiple sets of historical laser influence parameters that meet the impact similarity threshold are compared according to their impact similarity. The set of historical laser influence parameters with the highest impact similarity is determined, and its corresponding historical laser is selected as the first candidate laser. Simultaneously, the historical laser corresponding to the unique set of historical material environment parameters that meets the material similarity threshold is selected as the second candidate laser.

[0031] In both of the above scenarios, if the first candidate laser and the second candidate laser are the same, it means that the record with the highest similarity selected from the non-unique parameter dimension and the record in the other unique parameter dimension both point to the same historical laser. Therefore, this historical laser is used as the current laser. The "same" here refers to the situation where the first candidate laser and the second candidate laser are the same. For example, when the set of historical laser influence parameters with an influence similarity greater than the influence similarity threshold is not unique, the set of historical laser influence parameters corresponding to the highest influence similarity is determined, and the corresponding historical laser is used as the first candidate laser. If there are multiple identical highest influence similarities, then all of these corresponding historical lasers are used as the first candidate laser. As long as there is a first candidate laser and a unique second candidate laser that are the same, then the identical historical laser is used as the current laser. If the first candidate laser is different from the second candidate laser, that is, when there is only one historical record exceeding the threshold in one parameter dimension, while there are multiple historical records exceeding the threshold in another parameter dimension, the historical laser pointed to by the unique historical record is given priority. This avoids interference from multiple candidate records in non-unique dimensions on the determination result, and at the same time ensures the adaptability and reliability of controlling the laser heating equipment.

[0032] The third scenario is where the historical laser influence parameter set with an influence similarity greater than the influence similarity threshold is unique, and the historical material environment parameter set with a material similarity greater than the material similarity threshold is also unique. In this case, the historical lasers corresponding to the two unique historical parameter sets are extracted separately. If the two historical lasers are the same, they are directly used as the current laser; if they are different, the historical laser corresponding to the unique historical laser influence parameter set is used as the current laser. When both dimensions form a unique match but the corresponding results conflict, the historical laser corresponding to the laser influence parameter set is prioritized. This is mainly because reflectivity, transmittance, and absorptivity directly represent the energy coupling relationship between the material to be processed and the laser. These parameters are directly related to whether the laser output can be effectively utilized by the material to be processed, and are also the basic conditions for judging whether the laser is suitable for the material to be processed. In contrast, moisture content, coating thickness, and protective gas transmittance are mainly used to reflect the additional effects of the current state of the material to be processed and the processing environment on laser propagation and heating processes. Therefore, when the unique matching results of the two dimensions conflict, the laser's reflectivity, transmittance, and absorptivity are first ensured to be compatible with the material.

[0033] The fourth scenario is where the set of historical laser influence parameters with an influence similarity greater than the influence similarity threshold is not unique, and the set of historical material environment parameters with a material similarity greater than the material similarity threshold is also not unique. In this case, the maximum influence similarity is determined from multiple sets of historical laser influence parameters, and the maximum material similarity is determined from multiple sets of historical material environment parameters. If the maximum influence similarity is greater than or equal to the maximum material similarity, the historical laser corresponding to the maximum influence similarity is used as the current laser; otherwise, if the maximum influence similarity is less than the maximum material similarity, the historical laser corresponding to the maximum material similarity is used as the current laser. Thus, when multiple candidate records exist in both parameter dimensions, the historical laser corresponding to the highest similarity in both dimensions is compared to determine which dimension to use, ensuring the reliability of controlling the laser heating equipment.

[0034] When the second matching strategy is executed, it indicates that no historical parameter set with a similarity exceeding the corresponding threshold was found in at least one of the laser influence parameter dimension and the material environment parameter dimension. In this case, a clustering algorithm is used to determine similar datasets between the current laser influence parameter set and / or the material environment parameter set and the historical data. Similar datasets are those that, after clustering, belong to similar data categories to the current laser influence parameter set and / or the current material environment parameter set. The clustering process does not change the current laser influence parameter set and the material environment parameter set; rather, it utilizes the distribution relationships between historical parameters to group data with similar parameter characteristics into corresponding datasets and identify historical lasers that can be used for current processing.

[0035] When a historical laser influence parameter set exists with an influence similarity greater than the influence similarity threshold, but a historical material environment parameter set with a material similarity greater than the material similarity threshold does not exist, it indicates that the laser influence parameter dimension already has historical data that meets the direct matching condition, while the material environment parameter dimension lacks records that meet the threshold condition. Based on a clustering algorithm, a similar dataset is determined between the current laser influence parameter set and the historical laser influence database, and the laser is identified within this similar dataset. Taking this clustering case as an example, the subsequent processing method is the same and will not be repeated. The laser influence parameter set and the historical laser influence database are used as the dataset to be clustered. The historical lasers corresponding to each data point in the dataset to be clustered are extracted, and the expected cluster size is determined to be 2. The probability of each data point in the dataset to be clustered belonging to each Gaussian distribution is calculated to determine the responsibility value. Based on the responsibility value, a similar dataset corresponding to the laser influence parameter set is obtained, and the historical lasers in the similar dataset are used as the lasers.

[0036] When a historical set of material environment parameters with a material similarity greater than the material similarity threshold exists, but a historical set of laser influence parameters with an influence similarity greater than the influence similarity threshold does not exist, it indicates that the material environment parameter dimension already has historical data that meets the direct matching condition, while the laser influence parameter dimension lacks records that meet the threshold condition. In this case, a clustering algorithm is used to determine the similar dataset between the current material environment parameter set and the historical material environment parameter database, and the laser is identified within this similar dataset.

[0037] When there is no historical laser influence parameter set with an influence similarity greater than the influence similarity threshold, and there is no historical material environment parameter set with a material similarity greater than the material similarity threshold, it indicates that neither parameter dimension can be directly matched using historical records exceeding the threshold. In this case, two clustering processes are performed: a first similarity dataset is determined based on the clustering algorithm between the laser influence parameter set and the historical laser influence database; a second similarity dataset is determined based on the clustering algorithm between the material environment parameter set and the historical material environment parameter database. The first similarity dataset contains historical laser influence parameter sets and corresponding historical lasers with characteristics similar to reflectivity, transmittance, and absorptivity. The second similarity dataset contains historical material environment parameter sets and corresponding historical lasers with characteristics similar to water content, coating thickness, and protective gas transmittance. If the historical lasers in the first and second similarity datasets are different, meaning there are no common historical lasers between the two similar datasets, then the historical laser is determined from either the first or second similarity dataset. If the same historical laser exists in the first and second similar datasets, then the same historical laser is used as the current laser. The historical laser that points to the same direction is extracted from the two independent clustering results, so that the control results have both similarity of laser influence parameters and adaptability of material and environmental parameters.

[0038] In the S300, an operational database is established for anomaly data comparison and self-tuning control. This operational database includes a normal laser operation database and a laser deviation operation database. Each data record in the operational database includes control commands, sensor monitoring data, and operational data. Control commands indicate the execution of the corresponding self-tuning process; for example, if the spot light power is low, the laser drive light power is increased; if the spot center shifts, the motor position is adjusted to align with the spot position. Sensor monitoring data includes the spot contour and center shift data collected by the light intensity sensor, while operational data is the laser's operating time. The normal laser operation database stores historical data records generated when the laser heating equipment is in normal operating condition, while the laser deviation operation database stores data records generated when the operational data deviates from the corresponding operating condition range during the operation of the laser heating equipment.

[0039] The operational database allows for the accumulation of data from pre-operation tests, trial processing tests, and subsequent actual operation of different lasers before the laser heating equipment is put into formal processing. Several materials compatible with the laser are selected and heated, and the sensor monitoring data output and laser operating data are recorded. Corresponding control commands are established through manual or experimental verification, thus forming a complete set of operational samples. During the pre-operation test, control commands under heating conditions can be obtained from the laser manufacturer's technical manuals and documents.

[0040] In S400, an operational dataset is constructed based on a defined laser. This dataset represents sensor monitoring data, such as the current laser spot profile and center offset. The operational dataset is then filtered to identify abnormal data. Each data point in the operational dataset has a corresponding operating range. The operating range refers to the allowable numerical interval for the corresponding data during normal laser operation, used to determine whether the operational data has deviated. The operating range can be comprehensively set based on the laser's rated operating parameters and the processing requirements of the material to be processed. In other words, the basic range that cannot be exceeded is determined according to the laser's equipment manual, avoiding setting values ​​that exceed the conditions under which the laser can stably operate. Subsequently, under conditions of reflectivity, transmittance, absorptivity, moisture content, coating thickness, and protective gas transmittance corresponding to the material to be processed, multiple sets of operational data are collected through pre-operation tests or trial processing tests. Samples with stable processing, normal sensor monitoring data, and processing results meeting requirements are then selected. The maximum, minimum, and main distribution intervals of various operational data in the normal samples are statistically analyzed to form the corresponding operating range. Furthermore, the operating range can also consider sensor detection accuracy and allowable fluctuations during normal operation. Furthermore, a certain detection margin is reserved on the basis of forming the corresponding working condition range to prevent normal data from being misjudged as abnormal due to sensor errors or short-term fluctuations.

[0041] The data in the operational dataset is compared with its corresponding operating range. If a piece of operational data falls within its corresponding operating range, it is not considered abnormal. If a piece of operational data is below the lower limit or above the upper limit of its corresponding operating range (i.e., it does not fall within the corresponding operating range), it is identified as abnormal. If multiple pieces of data in the operational dataset exceed the range simultaneously, each piece of data is identified as abnormal. After identifying abnormal data, it is compared with the operational database. Based on the data type of the abnormal data, data of the same data type (e.g., spot contour, center offset) is searched in the operational database. When data identical to the abnormal data exists in the operational database, the laser is self-tuned according to the corresponding control command. Self-tuning control, upon identifying abnormal data, does not rely on the operator to reselect control content from scratch. Instead, it retrieves the control command corresponding to the same historical situation from the operational database. The laser adjusts its operating state according to the control command, thereby restoring the current data to the corresponding operating range.

[0042] In summary, by acquiring laser influence parameter sets and material environment parameter sets, the material to be processed can be comprehensively characterized from two dimensions: laser energy coupling characteristics and the actual processing environment. This avoids matching deviations caused by selecting a laser solely based on single material information. Furthermore, by comparing the two parameter sets with historical laser influence databases and historical material environment parameter databases, and selecting either a first or second matching strategy based on influence similarity, material similarity, and corresponding thresholds, different laser selection methods can be adopted according to the degree of matching of historical data, improving the reliability of laser heating equipment control. An operational database, including a normal laser operation database and a laser deviation operation database, is established. Control commands, sensor monitoring data, and operational data are stored accordingly, preserving the laser's operating patterns under normal and deviation states. Abnormal data is matched with the operational database, and corresponding control commands are invoked to implement self-tuning control of the laser. This achieves fully automated laser heating and reduces the time consumption and control errors caused by repeated manual adjustments. A closed-loop control system is realized, from material parameter acquisition, laser matching, operational status monitoring, anomaly identification to self-tuning control, further improving the reliability of laser heating equipment control.

[0043] Based on another preferred embodiment described above, see [link to preferred embodiment]. Figure 3 As shown, this embodiment provides a control system for a laser heating device, used to apply the above-described control method for a laser heating device, including: The acquisition and analysis unit is configured to acquire the laser influence parameter set and material environment parameter set of the material to be processed, compare the laser influence parameter set and material environment parameter set with historical data, and compare the influence similarity and material similarity with the corresponding thresholds. Based on the threshold comparison results, it determines whether to execute the first matching strategy or the second matching strategy. The first control unit is configured to determine the laser based on the comparison results of the laser influence parameter set and the material environment parameter set with historical data if the first matching strategy is executed, and to determine the laser influence parameter set based on the clustering algorithm and / or the similar dataset of the material environment parameter set and historical data based on the overlap results of the similar datasets if the second matching strategy is executed. The storage control unit is configured to establish an operating database, which includes a normal laser operation database and a laser deviation operation database. The operating database includes control commands, sensor monitoring data, and operating data, and the control commands, operating data, and sensor monitoring data correspond to each other. The second control unit is configured to build an operational dataset based on the laser, filter and identify abnormal data, compare the abnormal data with the operational database, and perform self-tuning control on the laser based on the comparison results.

[0044] It is understandable that the control method and system described above for laser heating equipment have the same beneficial effects, and will not be elaborated further here.

[0045] 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 control method for a laser heating device, characterized in that, include: The laser influence parameter set and material environment parameter set of the material to be processed are obtained. The laser influence parameter set and the material environment parameter set are compared with historical data respectively. The influence similarity and material similarity are compared with the corresponding thresholds. Based on the threshold comparison results, it is determined whether to execute the first matching strategy or the second matching strategy. If the first matching strategy is executed, the laser is determined based on the comparison results between the laser influence parameter set and the material environment parameter set and the historical data. If the second matching strategy is executed, the laser influence parameter set is determined based on the clustering algorithm, and / or the similar datasets of the material environment parameter set and the historical data, and the laser is determined based on the overlap results of the similar datasets. An operational database is established, which includes a normal laser operation database and a laser deviation operation database. The operational database includes control commands, sensor monitoring data, and operational data, and the control commands, operational data, and sensor monitoring data correspond to each other. A running dataset is constructed based on the laser and abnormal data is identified through screening. The abnormal data is compared with the running database, and the laser is self-tuned based on the comparison results.

2. The control method for laser heating equipment according to claim 1, characterized in that, When obtaining the laser influence parameter set and material environment parameter set of the material to be processed, the following are included: The laser influence parameter set includes the reflectivity, transmittance, and absorptivity of the material to be processed; The set of material environmental parameters includes the moisture content and coating thickness of the material to be processed, as well as the transmittance of the protective gas used on the material to be processed.

3. The control method for laser heating equipment according to claim 2, characterized in that, When comparing the similarity and material similarity with corresponding thresholds, and determining whether to implement the first matching strategy or the second matching strategy based on the threshold comparison results, the following steps are included: Acquire historical laser impact database and historical material environment parameter library; The historical laser influence database includes several historical laser influence parameter sets and several historical lasers, with each historical laser influence parameter set corresponding to a historical laser. The historical material environment parameter library includes several historical material environment parameter sets and several historical lasers, and each historical material environment parameter set corresponds to a historical laser. The laser influence parameter set and the historical laser influence database are compared to determine the influence similarity; the material environment parameter set and the historical material environment parameter database are compared to determine the material similarity. If the influence similarity is greater than the influence similarity threshold, and the material similarity is greater than the material similarity threshold, then the first matching strategy is executed; otherwise, the second matching strategy is executed.

4. The control method for laser heating equipment according to claim 3, characterized in that, If the first matching strategy is executed, it includes: When the historical laser influence parameter set with influence similarity greater than the influence similarity threshold is unique, and the historical material environment parameter set with material similarity greater than the material similarity threshold is not unique, or when the historical laser influence parameter set with influence similarity greater than the influence similarity threshold is not unique, and the historical material environment parameter set with material similarity greater than the material similarity threshold is unique, then the historical laser corresponding to the historical laser influence parameter set with the maximum influence similarity or the historical material environment parameter set with the maximum material similarity is selected as the first candidate laser, and the historical laser corresponding to the unique historical laser influence parameter set or the historical material environment parameter set is selected as the second candidate laser. If the first candidate laser and the second candidate laser are the same, then the first candidate laser or the second candidate laser shall be used as the laser; otherwise, the second candidate laser shall be used as the laser.

5. The control method for a laser heating device according to claim 4, characterized in that, If the first matching strategy is executed, it also includes: When the set of historical laser influence parameters with influence similarity greater than the influence similarity threshold is unique, and the set of historical material environment parameters with material similarity greater than the material similarity threshold is unique, if the historical lasers corresponding to the set of historical laser influence parameters and the set of historical material environment parameters are the same, then the historical laser is taken as the laser; if the historical lasers corresponding to the set of historical laser influence parameters and the set of historical material environment parameters are not the same, then the historical lasers corresponding to the set of historical laser influence parameters are taken as the laser. When the set of historical laser influence parameters with influence similarity greater than the influence similarity threshold is not unique, and the set of historical material environment parameters with material similarity greater than the material similarity threshold is not unique, if the maximum influence similarity is greater than or equal to the maximum material similarity, then the historical laser corresponding to the maximum influence similarity is taken as the laser; if the maximum influence similarity is less than the maximum material similarity, then the historical laser corresponding to the maximum material similarity is taken as the laser.

6. The control method for a laser heating device according to claim 5, characterized in that, When the second matching strategy is executed, it includes: When there exists an influence similarity greater than the influence similarity threshold, and there is no material similarity greater than the material similarity threshold, then a similar dataset between the laser influence parameter set and the historical laser influence database is determined based on a clustering algorithm, and the laser is identified in the similar dataset; When there is a material similarity greater than the material similarity threshold and there is no influence similarity greater than the influence similarity threshold, then a similar dataset between the material environment parameter set and the historical material environment parameter library is determined based on the clustering algorithm, and the laser is determined in the similar dataset; When there is no influence similarity greater than the influence similarity threshold, and there is no material similarity greater than the material similarity threshold, then a first similar dataset of the laser influence parameter set and the historical laser influence database, and a second similar dataset of the material environment parameter set and the historical material environment parameter database are determined based on the clustering algorithm.

7. The control method for a laser heating device according to claim 6, characterized in that, If the second matching strategy is executed, it also includes: If the historical lasers in the first similar dataset and the second similar dataset are the same, then the historical laser is used as the laser. If the historical lasers in the first similar dataset and the second similar dataset are not the same, then the historical laser in either the first similar dataset or the second similar dataset shall be used as the laser.

8. The control method for a laser heating device according to claim 7, characterized in that, When identifying outlier data, the following should be included: The data in the running dataset are compared with the corresponding operating condition ranges, and the data that is not within the operating condition range is identified as abnormal data.

9. The control method for a laser heating device according to claim 8, characterized in that, When performing self-tuning control on the laser, the following are included: The abnormal data is compared with the operating database, and the control instructions corresponding to the data in the operating database that are the same as the abnormal data are used to perform self-tuning control on the laser.

10. A control system for a laser heating device, used for applying the control method for a laser heating device as described in any one of claims 1-9, characterized in that, include: The acquisition and analysis unit is configured to acquire the laser influence parameter set and material environment parameter set of the material to be processed, compare the laser influence parameter set and the material environment parameter set with historical data respectively, and compare the influence similarity and material similarity with the corresponding thresholds. Based on the threshold comparison results, it determines whether to execute the first matching strategy or the second matching strategy. A first control unit is configured to, if the first matching strategy is executed, determine the laser based on the comparison results of the laser influence parameter set and the material environment parameter set with the historical data; if the second matching strategy is executed, determine the laser influence parameter set based on a clustering algorithm, and / or the similar dataset of the material environment parameter set and the historical data, and determine the laser based on the overlap results of the similar datasets. The storage control unit is configured to establish an operating database, which includes a normal laser operation database and a laser deviation operation database. The operating database includes control commands, sensor monitoring data, and operating data, and the control commands, the operating data, and the sensor monitoring data correspond to each other. The second control unit is configured to construct an operating dataset based on the laser and filter it to identify abnormal data, compare the abnormal data with the operating database, and perform self-tuning control on the laser based on the comparison results.

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