Fiber composite material laser curing infrared monitoring method and system

Abstract

The invention provides a fiber composite material laser curing infrared monitoring method and system, and relates to the technical field of laser curing monitoring. The method comprises the following steps: acquiring historical curing data of fiber composite materials of the same type, and performing curing characteristic analysis based on a curing result to form curing monitoring reference data; real-time curing information of the object fiber composite material is collected, real-time curing analysis is carried out in combination with the curing monitoring reference data, and real-time curing monitoring result data is formed; and performing defect calibration processing according to the real-time curing monitoring result data in combination with the curing monitoring reference data to form curing monitoring defect calibration information. According to the method, the curing effect is efficiently and accurately judged by using the curing process data acquired by infrared monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of laser curing monitoring, and more particularly, to an infrared monitoring method and system for laser curing of fiber composite materials. Background Art

[0002] Laser curing uses a laser beam to irradiate a specific material, causing it to undergo a curing reaction instantaneously. This technology has the advantages of high precision, high efficiency, and pollution-free, and is widely used in various material processing fields. As people's understanding of materials gradually deepens, the application of composite materials is also becoming more and more extensive, among which fiber composite materials are the most important type of composite materials. Fiber composite materials are mainly materials formed by mixing specific types of fibers with resin and undergoing a curing reaction.

[0003] Currently, the curing of fiber composite materials is carried out by laser curing to improve the efficiency of curing production. Since the temperature changes during the curing process, and the temperature change situation during the whole process reflects the curing state and directly affects the curing effect, monitoring the temperature change during the curing process is an important way for quality control and monitoring of the curing process. The non-contact infrared monitoring method collects the thermal radiation of the curing heat release through an infrared sensor to establish a corresponding temperature field, but further research is needed on how to accurately analyze the curing effect using the monitored data.

[0004] Therefore, designing an infrared monitoring method and system for laser curing of fiber composite materials, and efficiently and accurately determining the curing effect by using the curing process data collected by infrared monitoring, is an urgent problem to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to provide an infrared monitoring method for laser curing of fiber composite materials. By obtaining the historical curing data of the same type of fiber composite materials, analyzing the characteristics of the curing process for the curing effect, establishing the temperature change reference data for the curing process of this type of fiber composite materials, and then forming the reference data for the real-time curing information to be compared. During the real-time curing process, the real-time curing data can be compared and analyzed synchronously to determine whether the real-time curing temperature change at the curing position has reached the curing temperature change corresponding to a good curing effect, and then the curing effect of the curing position can be determined efficiently and accurately. Compared with the traditional method of evaluating the curing effect by other means after curing, the curing monitoring method of the present application is more efficient and accurate, and can also be used as reference data for guiding the control of real-time curing parameters.

[0006] The object of the present invention also lies in providing a fiber composite laser curing infrared monitoring system. This system obtains the basic big data for feature data extraction and analysis by the feature extraction unit through the data acquisition unit, uses the database unit to store and update the basic big data, and the real-time monitoring unit compares and analyzes the real-time curing data with the extracted feature data to determine the effect of real-time curing and calibrate the curing defects. The functions of each unit are independent of each other, but are closely related to form an overall for real-time infrared monitoring and analysis of curing, effectively ensuring the efficient and accurate implementation of real-time curing effect monitoring, and being an important material basis for realizing curing monitoring.

[0007] In the first aspect, the present invention provides a fiber composite laser curing infrared monitoring method, including: obtaining the historical curing data of the same type of fiber composite, performing curing feature analysis based on the curing result to form curing monitoring reference data; collecting the real-time curing information of the target fiber composite, and performing real-time curing analysis in combination with the curing monitoring reference data to form real-time curing monitoring result data; and performing defect calibration processing according to the real-time curing monitoring result data and in combination with the curing monitoring reference data to form curing monitoring defect calibration information.

[0008] In the present invention, this method obtains the historical curing data of the same type of fiber composite, performs feature analysis on the curing process aiming at the curing effect, establishes the reference comparison data of the temperature change in the curing process of this type of fiber composite, and further forms the reference data for real-time curing information comparison. During the real-time curing process, the real-time curing data can be compared and analyzed synchronously to determine whether the real-time curing temperature change at the curing position reaches the curing temperature change corresponding to a better curing effect, and then the curing effect of the curing position can be determined efficiently and accurately. Compared with the traditional method of evaluating the curing effect by other means after curing, the curing monitoring method of the present application is more efficient and accurate, and can also be used as reference data for guiding real-time curing parameter control.

[0009] As a possible implementation, historical curing data of the same type of fiber composite material is obtained, curing characteristic analysis based on the curing results is carried out, and curing monitoring reference data is formed, including: according to the historical curing data, the infrared monitoring data corresponding to different curing positions with qualified quality of the curing results is extracted to form a historical curing infrared monitoring qualified data set; according to the historical curing data, the infrared monitoring data corresponding to different curing positions with unqualified quality of the curing results is extracted to form a historical curing infrared monitoring unqualified data set; for the historical curing infrared monitoring qualified data set, infrared monitoring characteristic analysis based on the curing conditions is carried out to form curing quality qualified infrared monitoring characteristic data; for the historical curing infrared monitoring unqualified data set, infrared monitoring characteristic analysis for different defect types is carried out to form curing quality defect infrared monitoring characteristic data; the curing quality qualified infrared monitoring characteristic data and the curing quality defect infrared monitoring characteristic data are combined to form curing monitoring reference data.

[0010] In the present invention, the extraction of curing characteristics based on historical curing data aims to obtain characteristic data of the temperature change during the curing process of a certain type of fiber composite material, and further provide reference data for analysis and comparison for monitoring the curing effect starting from the temperature change data in real time. The extracted characteristic data considers the comprehensiveness of analysis and comparison, and includes not only the extraction of the temperature change characteristic data of the curing process at the curing positions with good curing effects in the historical curing data, but also the extraction of the temperature change characteristic data of the curing process at the curing positions with curing defects in the historical curing data. In this way, on the one hand, the accurate real-time curing effect comparison analysis is carried out using the temperature change characteristic data of the curing process with good curing effects, and on the other hand, the defect types of the curing defects that occur at the real-time curing positions can be determined based on the temperature change characteristic data corresponding to the curing defects. In addition, since not only the temperature change characteristic data of the curing process with good curing effects is obtained, but also the temperature change characteristic data corresponding to different curing defects is extracted, it can provide a guidance for the control reference data of the control parameters mapped based on the temperature change during the curing process for the subsequent curing of the same type of fiber composite material, ensuring the reasonable and accurate setting of the curing control parameters to improve the curing quality.

[0011] As a possible implementation, perform infrared monitoring feature analysis based on curing conditions on the historical solidified infrared monitoring qualified dataset to form infrared monitoring feature data for qualified curing quality, including: determining the infrared monitoring conditions for curing, extracting the qualified monitoring condition values of different infrared monitoring conditions in the infrared monitoring data corresponding to different curing positions in the infrared monitoring feature data for qualified curing quality; extracting the corresponding qualified curing process heat value change data based on the infrared monitoring data of different curing positions in the historical solidified infrared monitoring qualified dataset, establishing a continuous change function based on the time dimension and performing smoothing processing to form a qualified curing process heat value change function; performing relationship mapping on the qualified monitoring condition values and the qualified curing process heat value change function corresponding to the infrared monitoring data of different curing positions in the historical solidified infrared monitoring qualified dataset to form a qualified curing condition-curing reaction mapping relationship corresponding to the infrared monitoring data of different curing positions; combining all qualified curing condition-curing reaction mapping relationships, performing clustering feature extraction based on the infrared monitoring conditions for curing to form infrared monitoring feature data for qualified curing quality.

[0012] In the present invention, when extracting the characteristic data of the temperature change during the curing process with good curing effect, it is considered that even for fiber composite materials of the same type, the curing effect may vary due to the influence of important parameters such as ambient temperature, ambient humidity, laser curing power, curing speed, and the structure of the object to be cured. Therefore, in order to accurately achieve the accuracy and rationality of subsequent real-time curing effect monitoring and analysis, it is necessary to perform a relationship mapping of the temperature change during the curing process based on the influencing factors for historical curing data. On the one hand, it can accurately determine under what conditions affecting the curing effect the good curing effect occurs, that is, which corresponding parameter values of the curing infrared monitoring conditions affect the temperature change during the curing process, making the characteristics of the curing have preconditions and avoiding inaccurate subsequent analysis due to overly general extraction of curing characteristics. On the other hand, it also provides a reference for how to control the parameter values to achieve a good curing effect based on these condition factors in the future, ensuring that the controllable condition factors can be adjusted in real time during real-time curing to achieve more accurate control of the curing effect and improve the curing quality. For the smoothing process, a time span can be determined in the time dimension. Using this time span, different time periods are formed by traversing the entire duration in the order of the time dimension, and the average change rate in different time periods is determined. Then, based on the average change rate, a smooth change curve within the time period is formed with the heat value at the start of the time period as the reference. Of course, the size of the time span determines the accuracy of the smoothing process, so it needs to be set according to the actual situation or determined based on big data analysis of the fluctuation accuracy of the heat value change rate. In addition, the acquisition of the heat value change function during the curing process is to accurately obtain the heat value change data from the start of the curing of the material to the end of the curing reaction. The start time point of the curing of the material and the end time point of the curing reaction can be determined based on the infrared characteristic analysis when the fiber composite material cures. The analysis methods include but are not limited to big data analysis, machine learning, heat conduction model analysis, etc. As long as the data can be reasonably and accurately obtained, it is acceptable, fully ensuring the accuracy and rationality of the analysis and processing of the heat value data during the curing process in this application.

[0013] As a possible implementation, combining all qualified curing condition-curing reaction mapping relationships, clustering feature extraction based on curing infrared monitoring conditions is carried out to form qualified infrared monitoring feature data for curing quality, including: clustering different qualified curing condition-curing reaction mapping relationships with the same qualified monitoring condition values in all qualified curing condition-curing reaction mapping relationships to form different qualified clustering mapping relationship sets; for different qualified clustering mapping relationship sets, overlapping different qualified curing process heat value change functions based on the time dimension to form a qualified curing process heat value change range function, and mapping the relationship between the qualified curing process heat value change range function and the corresponding qualified monitoring condition value to form a qualified curing condition-curing reaction mapping range relationship corresponding to the qualified clustering mapping relationship set; aggregating the qualified curing condition-curing reaction mapping range relationships corresponding to different qualified clustering mapping relationship sets to form qualified infrared monitoring feature data for curing quality.

[0014] In the present invention, it should be noted that for the monitoring condition values, different curing positions can be different position points of the same target model in the same historical curing operation, or different position points of the target model in different historical curing operations. For different position points of the same target model in the same historical curing operation, it can be understood that for the monitoring conditions affecting the curing effect, the environmental conditions and construction conditions are kept consistent, and the difference lies in the structure of the target model itself. For different position points of the target model in different historical curing operations, there may be cases where the environmental conditions and construction conditions in the monitoring conditions are kept consistent. And for the model structure itself, there must be position points with the same structure conditions affecting the curing effect on the same model, and there may be position points with the same structure conditions affecting the curing effect for different models. Therefore, all curing condition-curing reaction mapping relationships can definitely be combined during clustering, and no individual data will be separated. Of course, clustering with the data corresponding to the position points avoids the situation where the feature data extracted subsequently cannot be compared and referenced due to different models, ensuring that the obtained feature data has strong applicability to achieve accurate and reasonable monitoring and analysis. The clustering based on the qualified monitoring condition values mainly synthesizes different qualified curing process heat value change functions with the same conditions to determine the heat value change range corresponding to different time points during the entire curing time. It can be understood that within this range, the change situation of the heat value can be regarded as the change situation for forming a good curing effect. In addition, using the qualified curing process heat value change range function as a characterization of the constant temperature during the curing process is on the one hand because the direct data obtained by infrared monitoring is the heat value change data, and on the other hand because the heat value is mapped to the power of the temperature value numerically. Therefore, reflecting the temperature change with the heat value change can magnify the temperature change situation to a certain extent to achieve more accurate data recording and analysis.

[0015] As a possible implementation, perform infrared monitoring feature analysis on different defect types for the historical solidified infrared monitoring unqualified data set to form infrared monitoring feature data for solidification quality defects, including: performing data clustering based on defect types on the infrared monitoring data in the historical solidified infrared monitoring unqualified data set to form different defect type infrared monitoring unqualified data sets; performing clustering feature extraction based on solidification infrared monitoring conditions on different defect type infrared monitoring unqualified data sets to form corresponding defect type infrared monitoring unqualified condition clustering feature data; collecting all the defect type infrared monitoring unqualified condition clustering feature data in the defect type infrared monitoring unqualified data set to form corresponding defect type infrared monitoring unqualified feature data; collecting different defect type infrared monitoring unqualified feature data to form infrared monitoring feature data for solidification quality defects.

[0016] In the present invention, for the solidification data with solidification defects, the main purpose of performing feature analysis on it is to calibrate the solidification defects. Therefore, when extracting feature data, the historical data is first distinguished based on defect types, such as distinguishing overheating defects, material non-uniformity defects, etc. Of course, these defect types are the results of judgments determined by means not limited to infrared analysis for the objects after solidification in the historical data. Data clustering is formed for different defects, and then the solidification process feature data for the defects is extracted, making the feature data more targeted at related defects.

[0017] As a possible implementation, perform clustering feature extraction based on solidification infrared monitoring conditions on different defect type infrared monitoring unqualified data sets to form corresponding defect type infrared monitoring unqualified condition clustering feature data, including: extracting the defect monitoring condition values corresponding to different solidification infrared monitoring conditions and the heat value change function of the defect solidification process for the infrared monitoring data corresponding to different solidification positions in the defect type infrared monitoring unqualified data set to form the defect solidification condition - solidification reaction mapping relationship corresponding to the infrared monitoring data; clustering different defect solidification condition - solidification reaction mapping relationships with the same defect monitoring condition values in all the defect solidification condition - solidification reaction mapping relationships in the defect type infrared monitoring unqualified data set to form different defect clustering mapping relationship sets; for different defect clustering mapping relationship sets, overlapping different defect solidification process heat value change functions based on the time dimension to form a defect solidification process heat value change range function, and mapping the relationship between the defect solidification process heat value change range function and the corresponding defect monitoring condition values to form a defect solidification condition - solidification reaction mapping range relationship corresponding to the defect clustering mapping relationship set; collecting the defect solidification condition - solidification reaction mapping range relationships corresponding to different defect clustering mapping relationship sets to form defect type infrared monitoring unqualified condition clustering feature data corresponding to the defect type infrared monitoring unqualified data set.

[0018] In the present invention, feature extraction is performed on the clustered defective data, which is similar to the feature extraction method for qualified infrared monitoring data. Both are based on the parameter values of the solidified infrared monitoring conditions to perform a comprehensive analysis of the corresponding calorific value change function during the solidification period on the solidification time period to form the temperature change range data defined by the generation of corresponding solidification defects. Of course, for one type of defect, there may be multiple calorific value change functions of defect solidification processes corresponding to different parameter values of solidified infrared monitoring conditions, and under big data, it can basically cover all situations of solidified infrared monitoring conditions. In addition, it should be reminded that when clustering based on the parameter values of solidified infrared monitoring conditions, although most of the environmental data corresponding to different positions, especially because it is the same historical solidification operation, will basically remain unchanged. For example, the environmental temperature and humidity are basically unchanged during the same historical solidification operation, while for non-same solidification operations, the environmental temperature and humidity may be different. Directly using the same original parameter values as the basis for clustering may cause a certain degree of unreasonableness. For example, a difference of about one degree in environmental temperature may have no impact on solidification. Therefore, by analyzing the allowable offset amount of the solidified infrared monitoring conditions for the solidification effect, the clustering range can be further expanded to make the data analysis more reasonable and efficient.

[0019] As a possible implementation method, real-time solidification information of the target fiber composite is collected, and real-time solidification analysis is performed in combination with the solidification monitoring reference data to form real-time solidification monitoring result data, including: according to the real-time solidification information, extracting the real-time monitoring condition values of different solidified infrared monitoring conditions and the real-time calorific value change function during the solidification process at different solidification positions; according to the real-time monitoring condition values, determining the relationship between the qualified solidification condition-solidification reaction mapping range closest to the real-time monitoring condition values in the qualified infrared monitoring feature data of solidification quality through cumulative difference; performing real-time solidification analysis on the real-time calorific value change function during the solidification process and the qualified calorific value change range function in the qualified solidification condition-solidification reaction mapping range relationship in the following way: corresponding the real-time calorific value change function during the solidification process and the qualified calorific value change range function in the time dimension; if the calorific value of the real-time calorific value change function at each time point belongs to the calorific value range of the qualified calorific value change range function at the corresponding time point, real-time solidification normal information is formed; if there is any time point on the real-time calorific value change function during the solidification process whose calorific value does not belong to the calorific value range of the qualified calorific value change range function at the corresponding time point, solidification abnormal information is formed.

[0020] In the present invention, the real-time curing effect is monitored and analyzed by using the curing monitoring reference data. First, it is determined that the real-time curing data can be mapped into the characteristic data corresponding to the good curing effect. The mapping method is to determine the qualified curing condition-curing reaction mapping range relationship that is closest to the real-time curing data in terms of the parameter values under the curing infrared monitoring conditions, and then determine whether the calorific value change data during the curing process belongs to the calorific value change range data corresponding to the qualified curing condition-curing reaction mapping range relationship. Here, it should be noted that the real-time curing monitoring and analysis is relative to the usual method of using other means to inspect the curing effect after curing. By comparing the calorific value change data of the entire real-time curing process with the reference benchmark data to judge the curing effect, although it is also an analysis after curing, it greatly improves the efficiency and accuracy of the analysis compared to the commonly used method. Of course, it is also possible to make a comparison and judgment during the curing process, but the real-time curing data obtained needs to be compared after being fully collected until the exothermic peak of the curing reaction is reached to effectively ensure the accuracy of the analysis. After all, to a certain extent, the exothermic peak determines the energy level of the curing reaction and is an embodiment of the internal chemical change effect of the curing reaction. For the calorific value change data during the curing process that does not belong to the calorific value change range data corresponding to the qualified curing condition-curing reaction mapping range relationship, it can be preliminarily determined that there are defects in the corresponding curing position. In addition, for the curing position, the size of the curing reaction influence range can be analyzed according to the material type to determine a reasonable curing position range, or of course, the size of the position range can be set according to the actual operation situation.

[0021] As a possible implementation manner, according to the real-time monitoring condition value, the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition value in the qualified infrared monitoring characteristic data of the curing quality is determined by cumulative difference, including: for different real-time monitoring condition values , where n represents the number of the determined different curing infrared monitoring conditions, traverse all the qualified monitoring condition values corresponding to the qualified curing condition-curing reaction mapping range relationships in the qualified infrared monitoring characteristic data of the curing quality , and obtain the corresponding cumulative difference , where k represents the number of different qualified curing condition-curing reaction mapping range relationships, ; the qualified curing condition-curing reaction mapping range relationship with the smallest cumulative difference among all the cumulative differences is used as the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition value.

[0022] In the present invention, characteristic data corresponding to good curing effects for real-time curing data is determined. In this application, a judgment method based on the cumulative size of the differences in curing infrared monitoring conditions is adopted. That is, the sum of the differences between the real-time parameter values of all curing infrared monitoring conditions and the parameter values corresponding to the mapping range relationship between all qualified curing conditions and curing reactions is used as the judgment basis. The smaller the sum of the differences, the closer the construction conditions are, and thus the closer the influence of these conditions on the curing effect is, and further the mapping range relationship between the qualified curing conditions and the curing reaction is the most matched.

[0023] As a possible implementation manner, defect calibration processing is performed based on the real-time curing monitoring result data and in combination with the curing monitoring reference data to form curing monitoring defect calibration information, including: obtaining different defect curing condition-curing reaction mapping range relationships in the clustering characteristic data of infrared monitoring unqualified conditions for different defect types where the defect monitoring conditions are the same as the real-time monitoring conditions; according to the real-time curing process heat value change function and the defect curing process heat value change range function of different defect curing condition-curing reaction mapping range relationships, performing defect calibration processing in the following manner: if there exists a defect curing process heat value change range function such that the heat value of the real-time curing process heat value change function at each time point belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, then calibrate the defect corresponding to the defect curing process heat value change range function at the curing position; if there does not exist a defect curing process heat value change range function such that the heat value of the real-time curing process heat value change function at each time point belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, then perform curing anomaly calibration on the curing position.

[0024] In the present invention, the judgment of defects is also carried out by determining the mapping range relationship of defect curing conditions that is close to the real-time heat value change data in terms of curing infrared monitoring conditions to determine the inclusion relationship of the corresponding defect curing process heat value change range. It should be noted that due to the defect positions of real-time curing, corresponding matching characteristic data extraction and comparison are performed for different types of defects. Finally, the judgment of the defect type is confirmed through the attribution of the heat value change data during the curing process. After all, only the matching defect type will have a characteristic range that includes the real-time curing heat value change data throughout the curing time.

[0025] In a second aspect, the present invention provides a fiber composite material laser curing infrared monitoring system, including: a data acquisition unit for acquiring the curing data of the same type of fiber composite material and the real-time curing information of the target fiber composite material; a database unit for storing the curing data of the same type of fiber composite material obtained by the data acquisition unit; a feature extraction unit for performing curing feature analysis on the curing data of the same type of fiber composite material in the database unit to form curing monitoring reference data; and a real-time monitoring unit for performing real-time curing analysis on the real-time curing information obtained by the data acquisition unit and combining the curing monitoring basic data formed by the feature extraction unit to form real-time curing monitoring result data, and performing defect calibration processing to form curing monitoring defect calibration information.

[0026] In the present invention, the system obtains the basic big data for feature data extraction and analysis by the feature extraction unit through the data acquisition unit, uses the database unit to store and update the basic big data, and the real-time monitoring unit compares and analyzes the real-time curing data with the extracted feature data to determine the effect of real-time curing and calibrate the curing defects. The functions of each unit are independent of each other, but are closely related to form an overall for real-time infrared monitoring and analysis of curing, effectively ensuring the efficient and accurate implementation of real-time curing effect monitoring, and being an important material basis for realizing curing monitoring.

[0027] The beneficial effects of the fiber composite material laser curing infrared monitoring method and system provided by the present invention are as follows: By obtaining the historical curing data of the same type of fiber composite material, performing feature analysis on the curing process for the curing effect, establishing the reference comparison data of the temperature change in the curing process of this type of fiber composite material, and then forming the reference data for comparing and analyzing the real-time curing information. During the real-time curing process, the real-time curing data can be compared and analyzed synchronously to determine whether the real-time curing temperature change at the curing position reaches the curing temperature change corresponding to a better curing effect, and then the curing effect at the curing position can be determined efficiently and accurately. Compared with the traditional method of evaluating the curing effect by other means after curing, the curing monitoring method of this application is more efficient and accurate, and can also be used as reference data for guiding the control of real-time curing parameters.

[0028] The system obtains the basic big data for feature data extraction and analysis by the feature extraction unit through the data acquisition unit, uses the database unit to store and update the basic big data, and the real-time monitoring unit compares and analyzes the real-time curing data with the extracted feature data to determine the effect of real-time curing and calibrate the curing defects. The functions of each unit are independent of each other, but are closely related to form an overall for real-time infrared monitoring and analysis of curing, effectively ensuring the efficient and accurate implementation of real-time curing effect monitoring, and being an important material basis for realizing curing monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0030] Figure 1 It is a step diagram of a method for laser curing infrared monitoring of a fiber composite material provided by an embodiment of the present invention; Figure 2 It is a schematic structural diagram of a system for laser curing infrared monitoring of a fiber composite material provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.

[0032] Laser curing irradiates a specific material with a laser beam to cause an instant curing reaction. This technology has the advantages of high precision, high efficiency, and no pollution, and is widely used in the processing fields of various materials. As people's understanding of materials gradually deepens, the application of composite materials is becoming more and more extensive, and fiber composite materials are the most important type of composite materials. Fiber composite materials are mainly materials formed by mixing specific types of fibers with resins through a curing reaction.

[0033] Currently, the curing of fiber composite materials is improved by laser curing to increase the efficiency of curing production. Since the temperature changes during the curing process, and the temperature change situation during the whole process reflects the curing state and directly affects the curing effect, monitoring the temperature change during the curing process is an important way for quality control and monitoring of the curing process. The non-contact infrared monitoring method collects the thermal radiation of the curing heat release through an infrared sensor to establish a corresponding temperature field, but further research is needed on how to accurately analyze the curing effect using the monitored data.

[0034] Reference Figure 1 - Figure 2, an embodiment of the present invention provides a method for laser curing infrared monitoring of fiber composite materials. This method obtains the historical curing data of the same type of fiber composite materials, conducts characteristic analysis of the curing process for the curing effect, establishes the reference comparison data of the temperature change in the curing process of this type of fiber composite materials, and then forms the reference data for real-time curing information comparison. During the real-time curing process, the real-time curing data can be synchronously compared and analyzed to determine whether the real-time curing temperature change at the curing position reaches the curing temperature change corresponding to a good curing effect, and then the curing effect of the curing position can be determined efficiently and accurately. Compared with the traditional method of evaluating the curing effect by other means after curing, the curing monitoring method of this application is more efficient and accurate, and can also be used as reference data for guiding real-time curing parameter control.

[0035] The method for laser curing infrared monitoring of fiber composite materials specifically includes the following steps: S1: Obtain the historical curing data of the same type of fiber composite materials, conduct curing characteristic analysis based on the curing results, and form curing monitoring reference data.

[0036] Obtaining the historical curing data of the same type of fiber composite materials, conducting curing characteristic analysis based on the curing results, and forming curing monitoring reference data includes: extracting the infrared monitoring data corresponding to different curing positions with qualified quality according to the historical curing data to form a historical curing infrared monitoring qualified data set; extracting the infrared monitoring data corresponding to different curing positions with unqualified quality according to the historical curing data to form a historical curing infrared monitoring unqualified data set; conducting infrared monitoring characteristic analysis based on the curing conditions for the historical curing infrared monitoring qualified data set to form curing quality qualified infrared monitoring characteristic data; conducting infrared monitoring characteristic analysis for different defect types for the historical curing infrared monitoring unqualified data set to form curing quality defect infrared monitoring characteristic data; combining the curing quality qualified infrared monitoring characteristic data and the curing quality defect infrared monitoring characteristic data to form curing monitoring reference data.

[0037] Extract the curing characteristics based on historical solidified data, aiming to obtain the characteristic data of the temperature change during the curing process of a certain type of fiber composite material, and then provide the reference data for analysis and comparison for monitoring the curing effect in real time starting from the temperature change data. The extracted characteristic data takes into account the comprehensiveness of analysis and comparison, including not only the extraction of the temperature change characteristic data of the curing process at the curing positions with good curing effects in the historical curing data, but also the extraction of the temperature change characteristic data of the curing process at the curing positions with curing defects in the historical curing data. In this way, on the one hand, the accurate real-time curing effect comparison analysis is carried out using the temperature change characteristic data of the curing process with good curing effects, and on the other hand, the type of curing defects that occur at the real-time curing position can be determined based on the temperature change characteristic data corresponding to the curing defects. In addition, since not only the temperature change characteristic data of the curing process with good curing effects are obtained, but also the temperature change characteristic data corresponding to different curing defects are extracted, it can provide the guidance of the control reference data based on the control parameters mapped by the temperature change during the curing process for the subsequent curing of the same type of fiber composite material, ensuring the reasonable and accurate setting of the curing control parameters to improve the curing quality.

[0038] For the qualified dataset of historical curing infrared monitoring, conduct the infrared monitoring characteristic analysis based on the curing conditions to form the qualified infrared monitoring characteristic data for curing quality, including: determining the curing infrared monitoring conditions, and extracting the qualified monitoring condition values of different curing infrared monitoring conditions in the infrared monitoring data corresponding to different curing positions in the qualified infrared monitoring characteristic data for curing quality; according to the infrared monitoring data of different curing positions in the qualified dataset of historical curing infrared monitoring, extract the corresponding qualified calorific value change data of the curing process, establish a continuous change function based on the time dimension and perform smoothing processing to form a qualified calorific value change function of the curing process; map the relationship between the qualified monitoring condition values and the qualified calorific value change function of the infrared monitoring data corresponding to different curing positions in the qualified dataset of historical curing infrared monitoring to form the qualified curing condition-curing reaction mapping relationship corresponding to the infrared monitoring data of different curing positions; combine all the qualified curing condition-curing reaction mapping relationships to conduct the clustering characteristic extraction based on the curing infrared monitoring conditions to form the qualified infrared monitoring characteristic data for curing quality.

[0039] When extracting the characteristic data of the temperature change during the curing process with good curing effect, it is considered that even for fiber composite materials of the same type, the curing effect may vary due to the influence of important parameters such as environmental temperature, environmental humidity, laser curing power, curing speed, and the structure of the curing object. Therefore, in order to accurately achieve the accuracy and rationality of subsequent real-time curing effect monitoring and analysis, it is necessary to perform a relationship mapping of the temperature change during the curing process based on the influencing factors for historical curing data. On the one hand, it can accurately determine under what conditions affecting the curing effect the good curing effect occurs, that is, which corresponding parameter values of the curing infrared monitoring conditions affect the temperature change during the curing process, making the characteristics of the curing have preconditions and avoiding inaccurate subsequent analysis due to overly general extraction of curing characteristics. On the other hand, it also provides a reference for how to control the parameter values to form a good curing effect based on these conditional factors in the future, ensuring that the controllable conditional factors can be adjusted in real time during real-time curing to achieve more accurate control of the curing effect and improve the curing quality. For the smoothing process, a time span can be determined in the time dimension. According to this time span, different time periods are formed by traversing the entire duration in the order of the time dimension, and the average change rate in different time periods is determined. Then, based on the average change rate, a smooth change curve within the time period is formed with the heat value at the start of the time period as the reference. Of course, the size of the time span determines the accuracy of the smoothing process, so it needs to be set according to the actual situation or determined based on big data analysis of the fluctuation accuracy of the heat value change rate. In addition, the acquisition of the heat value change function during the curing process is to accurately obtain the heat value change data from the start of the curing of the material to the end of the curing reaction. The start time point of the curing of the material and the end time point of the curing reaction can be determined based on the infrared characteristic analysis when the fiber composite material cures. The analysis methods include but are not limited to big data analysis, machine learning, heat conduction model analysis, etc. As long as the data can be obtained reasonably and accurately, it is acceptable, fully ensuring the accuracy and rationality of the analysis and processing of the heat value data during the curing process in this application.

[0040] In combination with all qualified curing condition-curing reaction mapping relationships, cluster feature extraction based on curing infrared monitoring conditions is performed to form qualified infrared monitoring feature data of curing quality, including: clustering different qualified curing condition-curing reaction mapping relationships with the same qualified monitoring condition values in all qualified curing condition-curing reaction mapping relationships to form different qualified cluster mapping relationship sets; for different qualified cluster mapping relationship sets, overlapping different qualified curing process calorific value change functions based on the time dimension to form a qualified curing process calorific value change range function, and mapping the qualified curing process calorific value change range function with the corresponding qualified monitoring condition value to form a qualified curing condition-curing reaction mapping range relationship corresponding to the qualified cluster mapping relationship set; and aggregating the qualified curing condition-curing reaction mapping range relationships corresponding to different qualified cluster mapping relationship sets to form qualified infrared monitoring feature data of curing quality.

[0041] It should be noted that, for the monitoring condition value, different solidification positions can be different position points of the same target model under the same historical solidification operation, or different position points of the target model on different historical solidification operations. For different position points of the same target model under the same historical solidification operation, it can be understood that the environmental conditions and construction conditions in the monitoring conditions that affect the solidification effect are consistent. The difference lies in the structure of the target model itself. For different position points of the target model on different historical solidification operations, there may be a situation where the environmental conditions and construction conditions in the monitoring conditions are consistent. For the model structure itself, there must be position points with the same structural conditions that affect the solidification effect on the same model, and there may be position points with the same structural conditions that affect the solidification effect for different models. Therefore, when clustering, all the solidification condition-solidification reaction mapping relationships can be combined, and no separate data will be segmented. Of course, clustering the data corresponding to the position points avoids the situation where the subsequent extracted feature data cannot be compared and referenced due to different models, and ensures that the acquired feature data has strong applicability to achieve accurate and reasonable monitoring and analysis. Clustering based on qualified monitoring condition values mainly involves synthesizing the calorific value change functions of different qualified curing processes with the same conditions to determine the calorific value change range corresponding to different time points in the entire curing time. It can be understood that within this range, the change in calorific value can be regarded as a change in the formation of a good curing effect. In addition, the use of the calorific value change range function of the qualified curing process as a representation of the unchanged temperature during the curing process is on the one hand because the direct data obtained by infrared monitoring is the calorific value change data, and on the other hand because the calorific value is numerically mapped to multiple powers of the temperature value. Therefore, using the calorific value change to reflect the temperature change can amplify the temperature change to a certain extent, so as to achieve more accurate data recording and analysis.

[0042] For the historical solidified infrared monitoring unqualified data set, conduct infrared monitoring feature analysis for different defect types to form infrared monitoring feature data for solidification quality defects, including: clustering the infrared monitoring data in the historical solidified infrared monitoring unqualified data set based on defect types to form unqualified data sets for different defect type infrared monitoring; for the unqualified data sets for different defect type infrared monitoring, extract clustering features based on solidification infrared monitoring conditions to form corresponding clustering feature data for unqualified conditions of different defect type infrared monitoring; aggregate all the clustering feature data for unqualified conditions of different defect type infrared monitoring in the unqualified data set for different defect types to form corresponding unqualified feature data for different defect type infrared monitoring; aggregate the unqualified feature data for different defect types to form infrared monitoring feature data for solidification quality defects.

[0043] For the solidification data with solidification defects, the main purpose of conducting feature analysis on it is to calibrate the solidification defects. Therefore, when extracting feature data, first distinguish the historical data based on defect types, such as distinguishing overheating defects, material non-uniformity defects, etc. Of course, these defect types are the results of judgments determined by means not limited to infrared analysis for the objects after solidification in the historical data. Form data clustering for different defects, and then extract the solidification process feature data for the defects, making the feature data more targeted to the associated defects.

[0044] For the unqualified data sets for different defect type infrared monitoring, extract clustering features based on solidification infrared monitoring conditions to form corresponding clustering feature data for unqualified conditions of different defect type infrared monitoring, including: for the infrared monitoring data corresponding to different solidification positions in the unqualified data set for different defect type infrared monitoring, extract the defect monitoring condition values corresponding to different solidification infrared monitoring conditions and the heat value change function of the defect solidification process to form the defect solidification condition - solidification reaction mapping relationship corresponding to the infrared monitoring data; cluster the different defect solidification condition - solidification reaction mapping relationships with the same defect monitoring condition values in all the defect solidification condition - solidification reaction mapping relationships in the unqualified data set for different defect type infrared monitoring to form different defect clustering mapping relationship sets; for different defect clustering mapping relationship sets, overlap the different heat value change functions of the defect solidification process based on the time dimension to form the heat value change range function of the defect solidification process, and map the relationship between the heat value change range function of the defect solidification process and the corresponding defect monitoring condition values to form the defect solidification condition - solidification reaction mapping range relationship corresponding to the defect clustering mapping relationship set; aggregate the defect solidification condition - solidification reaction mapping range relationships corresponding to different defect clustering mapping relationship sets to form the clustering feature data for unqualified conditions of different defect type infrared monitoring corresponding to the unqualified data set for different defect type infrared monitoring.

[0045] Feature extraction is performed on the defective data of clustering, which is similar to the feature extraction method for qualified infrared monitoring data. Both are based on the parameter values of the solidified infrared monitoring conditions to comprehensively analyze the calorific value change function of the corresponding solidification process on the solidification period to form the temperature change range data defined by the generation of corresponding solidification defects. Of course, for one type of defect, there may be multiple calorific value change functions of defect solidification processes corresponding to different parameter values of solidified infrared monitoring conditions, which can basically cover all situations of solidified infrared monitoring conditions under big data. In addition, it should be reminded that when clustering based on the parameter values of solidified infrared monitoring conditions, although most of the environmental data corresponding to different positions, especially those from the same historical solidification operation, will basically remain unchanged. For example, the environmental temperature and humidity are basically unchanged during the same historical solidification operation, while for different solidification operations, the environmental temperature and humidity may be different. Directly using the same original parameter values as the basis for clustering may cause some degree of unreasonableness. For example, a difference of about one degree in environmental temperature may have no impact on solidification. Therefore, by analyzing the allowable offset of the solidified infrared monitoring conditions for the solidification effect, the clustering range can be further expanded to make the data analysis more reasonable and efficient.

[0046] S2: Collect the real-time solidification information of the target fiber composite, and perform real-time solidification analysis in combination with the solidification monitoring reference data to form real-time solidification monitoring result data.

[0047] Collect the real-time solidification information of the target fiber composite, and perform real-time solidification analysis in combination with the solidification monitoring reference data to form real-time solidification monitoring result data, including: according to the real-time solidification information, extract the real-time monitoring condition values of different solidified infrared monitoring conditions and the real-time calorific value change function of the solidification process at different solidification positions; according to the real-time monitoring condition values, determine the qualified solidification condition-solidification reaction mapping range relationship closest to the real-time monitoring condition values in the qualified infrared monitoring feature data of solidification quality through cumulative difference; perform real-time solidification analysis on the real-time calorific value change function of the solidification process and the qualified calorific value change range function in the qualified solidification condition-solidification reaction mapping range relationship in the following way: correspond the real-time calorific value change function of the solidification process and the qualified calorific value change range function in the time dimension; if the calorific value of the real-time calorific value change function of the solidification process at each time point belongs to the calorific value range of the qualified calorific value change range function of the solidification process at the corresponding time point, then form real-time solidification normal information; if there is any time point on the real-time calorific value change function of the solidification process whose calorific value does not belong to the calorific value range of the qualified calorific value change range function of the solidification process at the corresponding time point, then form solidification abnormal information.

[0048] The real-time curing effect is monitored and analyzed using the cured monitoring reference data. First, it is determined that the real-time curing data can be mapped into the characteristic data corresponding to a good curing effect. The mapping method is to determine the qualified curing condition-curing reaction mapping range relationship that is closest to the real-time curing data in terms of the parameter values under the cured infrared monitoring conditions, and then check whether the calorific value change data during the curing process falls within the calorific value change range data corresponding to the qualified curing condition-curing reaction mapping range relationship. Here, it should be noted that the real-time curing monitoring and analysis is in contrast to the usual method of using other means to check the curing effect after curing. By comparing the calorific value change data throughout the real-time curing process with the reference benchmark data to judge the curing effect, although it is also an analysis after curing, it greatly improves the efficiency and accuracy of the analysis compared to the commonly used method. Of course, it is also possible to make a comparison and judgment during the curing process, but the real-time curing data obtained needs to be compared after completely collecting the data up to the exothermic peak of the curing reaction to effectively ensure the accuracy of the analysis. After all, to a certain extent, the exothermic peak determines the energy level of the curing reaction and is an indication of the internal chemical change effect of the curing reaction. For the calorific value change data during the curing process that does not fall within the calorific value change range data corresponding to the qualified curing condition-curing reaction mapping range relationship, it can be preliminarily determined that there are defects in the corresponding curing position. In addition, for the curing position, the range of the curing reaction influence can be analyzed according to the material type to determine a reasonable curing position range, or the range size can also be set according to the actual operation situation.

[0049] According to the real-time monitoring condition value, the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition value in the qualified infrared monitoring characteristic data of the curing quality is determined by cumulative difference, including: for different real-time monitoring condition values , where n represents the number of different determined cured infrared monitoring conditions, traverse all the qualified monitoring condition values corresponding to the qualified curing condition-curing reaction mapping range relationship in the qualified infrared monitoring characteristic data of the curing quality , and obtain the corresponding cumulative difference , where k represents the number of different qualified curing condition-curing reaction mapping range relationships, ; the qualified curing condition-curing reaction mapping range relationship with the smallest cumulative difference among all the cumulative differences is taken as the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition value.

[0050] Determine the characteristic data of good curing effect corresponding to the real-time curing data. In this application, a judgment method for the cumulative size of the differences in curing infrared monitoring conditions is adopted. That is, the sum of the differences between the real-time parameter values of all curing infrared monitoring conditions and the parameter values corresponding to the qualified curing condition-curing reaction mapping range relationship is used as the judgment basis. The smaller the sum of the differences, the closer the construction conditions are, and then the influence of these conditions on the curing effect is also the closest, and thus the qualified curing condition-curing reaction mapping range relationship is also the most matched.

[0051] S3: According to the real-time curing monitoring result data and combined with the curing monitoring reference data, perform defect calibration processing to form curing monitoring defect calibration information.

[0052] According to the real-time curing monitoring result data and combined with the curing monitoring reference data, perform defect calibration processing to form curing monitoring defect calibration information, including: obtaining different defect curing condition-curing reaction mapping range relationships with the same defect monitoring conditions and real-time monitoring conditions in the clustering characteristic data of unqualified conditions for infrared monitoring of different defect types; according to the real-time curing process heat value change function and the defect curing process heat value change range function of different defect curing condition-curing reaction mapping range relationships, perform defect calibration processing in the following way: if there exists a defect curing process heat value change range function such that the heat value of the real-time curing process heat value change function at each time point belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, then calibrate the defect corresponding to the defect curing process heat value change range function at the curing position; if there does not exist a defect curing process heat value change range function such that the heat value of the real-time curing process heat value change function at each time point belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, then perform abnormal curing calibration at the curing position.

[0053] The judgment of defects is also carried out by determining the inclusion relationship of the corresponding defect curing process heat value change range by determining the defect curing condition-curing reaction mapping range relationship that is close to the real-time heat value change data in terms of curing infrared monitoring conditions. It should be noted that due to the defect positions of real-time curing, corresponding matching characteristic data extraction and comparison are carried out for different types of defects. Finally, the judgment of the defect type is confirmed through the attribution of the curing process heat value change data. After all, only the matching defect types will have characteristic ranges that include the real-time curing heat value change data throughout the curing time.

[0054] The present invention also provides a laser curing infrared monitoring system for fiber composite materials, which includes: a data acquisition unit for acquiring the curing data of the same type of fiber composite materials and the real-time curing information of the target fiber composite materials; a database unit for storing the curing data of the same type of fiber composite materials obtained by the data acquisition unit; a feature extraction unit for performing curing feature analysis based on the curing data of the same type of fiber composite materials in the database unit to form curing monitoring reference data; and a real-time monitoring unit for performing real-time curing analysis based on the real-time curing information obtained by the data acquisition unit and combining with the curing monitoring basic data formed by the feature extraction unit to form real-time curing monitoring result data, and performing defect calibration processing to form curing monitoring defect calibration information.

[0055] The system obtains the basic big data for feature data extraction and analysis by the feature extraction unit through the data acquisition unit, uses the database unit to store and update the basic big data, and the real-time monitoring unit compares and analyzes the real-time curing data with the extracted feature data to determine the effect of real-time curing and calibrate the curing defects. The functions of each unit are independent of each other, but are closely related to form an overall for real-time infrared monitoring and analysis of curing, effectively ensuring the efficient and accurate implementation of real-time curing effect monitoring, and being an important material basis for realizing curing monitoring.

[0056] In summary, the beneficial effects of the laser curing infrared monitoring method and system for fiber composite materials provided by the embodiments of the present invention are as follows: By obtaining the historical curing data of the same type of fiber composite materials, the method performs feature analysis on the curing process for the curing effect, establishes the reference comparison data of the temperature change in the curing process of this type of fiber composite materials, and further forms the reference data for comparing and analyzing the real-time curing information. During the real-time curing process, the real-time curing data can be compared and analyzed synchronously to determine whether the real-time curing temperature change at the curing position reaches the curing temperature change corresponding to a better curing effect, and thus the curing effect at the curing position can be determined efficiently and accurately. Compared with the traditional method of evaluating the curing effect by other means after curing, the curing monitoring method of this application is more efficient and accurate, and can also be used as reference data for guiding the control of real-time curing parameters.

[0057] The system obtains the basic big data for feature data extraction and analysis by the feature extraction unit through the data acquisition unit, uses the database unit to store and update the basic big data, and the real-time monitoring unit compares and analyzes the real-time curing data with the extracted feature data to determine the effect of real-time curing and calibrate the curing defects. The functions of each unit are independent of each other, but are closely related to form an overall for real-time infrared monitoring and analysis of curing, effectively ensuring the efficient and accurate implementation of real-time curing effect monitoring, and being an important material basis for realizing curing monitoring.

[0058] In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. If the information indicated by a certain piece of information is called the information to be indicated, then in the specific implementation process, there are many ways to indicate the information to be indicated. For example, but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated, etc. The information to be indicated can also be indirectly indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated. It is also possible to only indicate a part of the information to be indicated, while the other parts of the information to be indicated are known or pre-agreed. For example, the indication of specific information can also be achieved by relying on the arrangement order of each piece of information pre-agreed (such as protocol regulations), thereby reducing the indication overhead to a certain extent. At the same time, the common part of each piece of information can be identified and indicated uniformly to reduce the indication overhead caused by separately indicating the same information.

[0059] In addition, the specific indication method can also be various existing indication methods, such as, but not limited to, the above-mentioned indication methods and their various combinations, etc. The specific details of various indication methods can refer to the prior art and will not be elaborated herein. As can be seen from the above, for example, when it is necessary to indicate multiple pieces of information of the same type, there may be a situation where the indication methods of different pieces of information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiments of the present application do not limit the selected indication method. In this way, the indication methods involved in the embodiments of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0060] It should be understood that the information to be indicated can be sent as a whole, or can be divided into multiple sub-informations and sent separately, and the sending periods and / or sending times of these sub-informations can be the same or different. The specific sending method is not limited in the embodiments of the present application. Among them, the sending periods and / or sending times of these sub-informations can be pre-defined, such as pre-defined according to the protocol, or can be configured by the sending device by sending configuration information to the receiving device.

[0061] "Pre - defined" or "pre - configured" can be implemented by pre - saving the corresponding code, table or other means that can be used to indicate relevant information in the device. The embodiments of the present application do not limit the specific implementation methods thereof. Among them, "saving" may refer to saving in one or more memories. The one or more memories may be separately provided, or may be integrated in an encoder or decoder, a processor, or a communication device. The one or more memories may also be partially separately provided and partially integrated in a decoder, a processor, or a communication device. The type of memory may be any form of storage medium, and the embodiments of the present application do not limit this.

[0062] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a frame structure similar to that of a protocol family, or a relevant protocol applied to future communication systems. The embodiments of the present application do not make specific limitations on this.

[0063] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if", and "when" all mean that the device will perform corresponding processing under certain objective circumstances, which does not limit time, and does not require the device to have a judgment action during implementation, nor does it mean the existence of other limitations.

[0064] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship. For example, A / B may represent A or B. The "and / or" in the embodiments of the present application is merely a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B may be singular or plural. Also, in the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more than two. "At least one (item)" or its similar expression refers to any combination of these items, including any combination of a single item or plural items. For example, at least one (item) of a, b, or c may represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c may be single or plural. Additionally, for the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as more preferred or more advantageous than other embodiments or design solutions. Exactly, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific way for easy understanding.

[0065] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general - purpose processors, digital signal processors (DSPs), application - specific integrated circuits (ASICs), field - programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general - purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0066] It should also be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM).

[0067] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0068] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context.

[0069] In the present application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or a similar expression refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0070] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0071] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0072] Those skilled in the art can clearly understand that for the sake of convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0073] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0074] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0075] In addition, the functional units in the various embodiments of this application can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0076] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0077] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for laser curing infrared monitoring of fiber composite materials, characterized in that, Including: Obtain historical curing data of the same type of fiber composite material, conduct curing characteristic analysis based on the curing results, and form curing monitoring reference data; Collect real-time curing information of the target fiber composite material, conduct real-time curing analysis in combination with the curing monitoring reference data, and form real-time curing monitoring result data; According to the real-time curing monitoring result data, and in combination with the curing monitoring reference data, conduct defect calibration processing to form curing monitoring defect calibration information.

2. The method for laser curing infrared monitoring of a fiber composite material according to claim 1, wherein The obtaining of historical curing data of the same type of fiber composite material, conducting curing characteristic analysis based on the curing results, and forming curing monitoring reference data includes: According to the historical curing data, extract the infrared monitoring data corresponding to different curing positions with qualified quality of the curing results to form a historical curing infrared monitoring qualified data set; According to the historical curing data, extract the infrared monitoring data corresponding to different curing positions with unqualified quality of the curing results to form a historical curing infrared monitoring unqualified data set; Conduct infrared monitoring characteristic analysis based on the curing conditions on the historical curing infrared monitoring qualified data set to form curing quality qualified infrared monitoring characteristic data; Conduct infrared monitoring characteristic analysis for different defect types on the historical curing infrared monitoring unqualified data set to form curing quality defect infrared monitoring characteristic data; Combine the curing quality qualified infrared monitoring characteristic data and the curing quality defect infrared monitoring characteristic data to form the curing monitoring reference data.

3. The method for laser curing infrared monitoring of a fiber composite material according to claim 2, wherein The conducting of infrared monitoring characteristic analysis based on the curing conditions on the historical curing infrared monitoring qualified data set to form curing quality qualified infrared monitoring characteristic data includes: Determine the curing infrared monitoring conditions, and extract the qualified monitoring condition values of different curing infrared monitoring conditions in the infrared monitoring data corresponding to different curing positions in the curing quality qualified infrared monitoring characteristic data; According to the infrared monitoring data of different curing positions in the historical curing infrared monitoring qualified data set, extract the corresponding qualified curing process heat value change data, establish a continuous change function based on the time dimension and conduct smoothing processing to form a qualified curing process heat value change function; Perform a relationship mapping on the qualified monitoring condition values and the qualified curing process heat value change function corresponding to the infrared monitoring data of different curing positions in the historical curing infrared monitoring qualified data set to form a qualified curing condition-curing reaction mapping relationship corresponding to the infrared monitoring data of different curing positions; Combine all the qualified curing condition-curing reaction mapping relationships, conduct clustering feature extraction based on the curing infrared monitoring conditions, and form the curing quality qualified infrared monitoring characteristic data.

4. The method for laser curing infrared monitoring of the fiber composite material according to claim 3, characterized in that, The combining of all the qualified curing condition-curing reaction mapping relationships, conducting clustering feature extraction based on the curing infrared monitoring conditions, and forming the curing quality qualified infrared monitoring characteristic data includes: Cluster different qualified curing condition-curing reaction mapping relationships with the same qualified monitoring condition values in all the qualified curing condition-curing reaction mapping relationships to form different qualified clustering mapping relationship sets; For different sets of the qualified clustering mapping relationships, overlap the different qualified solidification process heat value change functions based on the time dimension to form a qualified solidification process heat value change range function, and map the relationship between the qualified solidification process heat value change range function and the corresponding qualified monitoring condition values to form a qualified solidification condition-solidification reaction mapping range relationship corresponding to the set of qualified clustering mapping relationships; Aggregate the qualified solidification condition-solidification reaction mapping range relationships corresponding to different sets of the qualified clustering mapping relationships to form the qualified infrared monitoring characteristic data of the solidification quality.

5. The method for laser curing infrared monitoring of a fiber composite material according to claim 4, wherein Performing infrared monitoring characteristic analysis for different defect types on the historical unqualified infrared monitoring dataset of solidification to form infrared monitoring characteristic data of solidification quality defects, including: Cluster the infrared monitoring data in the historical unqualified infrared monitoring dataset of solidification based on the defect type to form different unqualified infrared monitoring datasets of defect types; Extract clustering characteristics based on the solidification infrared monitoring conditions for different unqualified infrared monitoring datasets of defect types to form corresponding clustering characteristic data of unqualified conditions for infrared monitoring of defect types; Aggregate all the clustering characteristic data of unqualified conditions for infrared monitoring of defect types in the unqualified infrared monitoring dataset of defect types to form corresponding unqualified characteristic data for infrared monitoring of defect types; Aggregate different unqualified characteristic data for infrared monitoring of defect types to form the infrared monitoring characteristic data of solidification quality defects.

6. The method for laser curing infrared monitoring of the fiber composite material according to claim 5, characterized in that, Performing clustering characteristic extraction based on the solidification infrared monitoring conditions for different unqualified infrared monitoring datasets of defect types to form corresponding clustering characteristic data of unqualified conditions for infrared monitoring of defect types, including: Extract the defect monitoring condition values and defect solidification process heat value change functions corresponding to different solidification infrared monitoring conditions for the infrared monitoring data corresponding to different solidification positions in the unqualified infrared monitoring dataset of defect types to form a defect solidification condition-solidification reaction mapping relationship corresponding to the infrared monitoring data; Cluster the different defect solidification condition-solidification reaction mapping relationships with the same defect monitoring condition values among all the defect solidification condition-solidification reaction mapping relationships in the unqualified infrared monitoring dataset of defect types to form different defect clustering mapping relationship sets; For different defect clustering mapping relationship sets, overlap the different defect solidification process heat value change functions based on the time dimension to form a defect solidification process heat value change range function, and map the relationship between the defect solidification process heat value change range function and the corresponding defect monitoring condition values to form a defect solidification condition-solidification reaction mapping range relationship corresponding to the defect clustering mapping relationship set; Aggregate the defect solidification condition-solidification reaction mapping range relationships corresponding to different defect clustering mapping relationship sets to form the clustering characteristic data of unqualified conditions for infrared monitoring of the unqualified infrared monitoring dataset of defect types.

7. The method for laser curing infrared monitoring of a fiber composite material according to claim 6, characterized in that Collect the real-time curing information of the fiber composite material of the collection object, and perform real-time curing analysis in combination with the curing monitoring reference data to form real-time curing monitoring result data, including: According to the real-time curing information, extract the real-time monitoring condition values of different curing infrared monitoring conditions and the real-time curing process heat value change function at different curing positions; According to the real-time monitoring condition values, determine the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition values in the qualified infrared monitoring characteristic data of curing quality through differential accumulation; Perform real-time curing analysis on the real-time curing process heat value change function and the qualified curing process heat value change range function in the qualified curing condition-curing reaction mapping range relationship in the following manner: Correspond the real-time curing process heat value change function and the qualified curing process heat value change range function in the time dimension; If the heat value at each time point of the real-time curing process heat value change function belongs to the heat value range of the qualified curing process heat value change range function at the corresponding time point, real-time curing normal information is formed; If there is a heat value at any time point on the real-time curing process heat value change function that does not belong to the heat value range of the qualified curing process heat value change range function at the corresponding time point, curing abnormal information is formed.

8. The method for laser curing infrared monitoring of a fiber composite material according to claim 7, wherein The determining the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition values in the qualified infrared monitoring characteristic data of curing quality through differential accumulation according to the real-time monitoring condition values includes: For different real-time monitoring condition values , where n represents the number of different determined curing infrared monitoring conditions, traverse all the qualified monitoring condition values corresponding to the qualified curing condition - curing reaction mapping range relationship in the qualified infrared monitoring characteristic data of the curing quality , and obtain the corresponding cumulative difference , where k represents the number of different qualified curing condition - curing reaction mapping range relationships ; Take all the cumulative differences The qualified curing condition-curing reaction mapping range relationship with the smallest value among them is used as the qualified curing condition-curing reaction mapping range relationship closest to the real-time monitoring condition value.

9. The method for laser curing infrared monitoring of fiber composite materials according to claim 8, wherein According to the real-time curing monitoring result data, and performing defect calibration processing in combination with the curing monitoring reference data to form curing monitoring defect calibration information, including: Obtain different defect curing condition-curing reaction mapping range relationships with the same defect monitoring conditions and real-time monitoring conditions in the clustering characteristic data of unqualified conditions for infrared monitoring of different defect types; According to the real-time curing process heat value change function and the defect curing process heat value change range functions of different defect curing condition-curing reaction mapping range relationships, perform defect calibration processing in the following manner: If there is a defect curing process heat value change range function that satisfies that the heat value at each time point of the real-time curing process heat value change function belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, calibrate the defect corresponding to the defect curing process heat value change range function at the curing position; If there is no defect curing process heat value change range function that satisfies that the heat value at each time point of the real-time curing process heat value change function belongs to the heat value range of the defect curing process heat value change range function at the corresponding time point, perform curing abnormal calibration on the curing position.

10. The fiber composite material laser curing infrared monitoring system adopts the fiber composite material laser curing infrared monitoring method described in any one of claims 1-9, and is characterized in that, Including: A data acquisition unit for acquiring the curing data of the same type of fiber composite material and the real-time curing information of the object fiber composite material; A database unit for storing the curing data of the same type of fiber composite material acquired by the data acquisition unit; A feature extraction unit, configured to perform curing feature analysis based on the curing data of the same type of fiber composite material in the database unit to form curing monitoring reference data; A real-time monitoring unit, configured to perform real-time curing analysis based on the real-time curing information obtained by the data acquisition unit and in combination with the curing monitoring basic data formed by the feature extraction unit to form real-time curing monitoring result data, and perform defect calibration processing to form curing monitoring defect calibration information.

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