Iot informatization laser cutting and welding integrated intelligent machining head

Abstract

The application discloses an Internet of Things informatization laser cutting and welding integrated intelligent machining head and belongs to the technical field of laser cutting and welding, comprising a laser generator, a laser cutting head and a laser welding head are arranged on the laser generator, an intelligent acquisition device is arranged on the laser cutting head and the laser welding head, and the intelligent acquisition device is connected with a cloud server through a wireless network; the intelligent acquisition device is used for collecting laser cutting and welding integrated intelligent machining real-time data; the cloud server is used for processing, analyzing and intelligently controlling the laser cutting and welding integrated intelligent machining real-time data. The application solves the problems that the existing laser cutting and welding integrated intelligent machining head cannot be monitored and managed intelligently in real time, the use effect of the laser cutting and welding integrated intelligent machining head is poor, and the laser cutting and welding efficiency is low. The application can realize real-time monitoring and intelligent management of the laser cutting and welding integrated intelligent machining head, and can improve the use effect of the laser cutting and welding integrated intelligent machining head and the laser cutting and welding efficiency.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of laser cutting and welding, and particularly relates to an Internet of Things information-based laser cutting and welding integrated intelligent machining head. BACKGROUND

[0002] At present, laser cutting and welding are steadily developing in industrial manufacturing. The emission angle of laser is extremely small, and the laser is almost a highly equalized collimated light beam, can realize directional and concentrated emission, and the high brightness characteristic of the laser is also a manifestation of the high concentration of energy. After focusing by a lens, a high temperature of thousands of degrees or even tens of thousands of degrees can be formed near the focal point. This characteristic enables the laser to process almost all materials.

[0003] A Chinese patent with the publication number CN117086486A discloses a metal woven mesh laser cutting and welding integrated device. The device comprises a base, and a displacement mechanism, a limiting mechanism and a cleaning mechanism are arranged on the top end of the base. The displacement mechanism comprises a fourth electric sliding rail fixed to the top end of the base, a fourth electric sliding block movably arranged on the fourth electric sliding rail, a third electric sliding rail fixed to the top end of the fourth electric sliding block, a third electric sliding block movably arranged on the third electric sliding rail, a second electric sliding rail fixed to the top end of the third electric sliding block, and a second electric sliding block movably arranged on the second electric sliding rail. The fourth electric sliding rail, the third electric sliding rail and the second electric sliding rail are arranged in X, Y and Z axial directions respectively. The device can realize automatic cutting and welding of the metal woven mesh while ensuring precision, and effectively improve work efficiency. However, the patent has the following defects:

[0004] In the prior art, the laser cutting and welding integrated intelligent machining head cannot be monitored and managed intelligently in real time during cutting and welding, resulting in poor use effect and low laser cutting and welding efficiency of the laser cutting and welding integrated intelligent machining head. SUMMARY

[0005] The application aims to provide an Internet of Things information-based laser cutting and welding integrated intelligent machining head, which can realize real-time monitoring and intelligent management of the laser cutting and welding integrated intelligent machining head, improve the use effect and laser cutting and welding efficiency of the laser cutting and welding integrated intelligent machining head, and solve the problems in the background art.

[0006] To achieve the above-mentioned purpose, the application provides the following technical scheme.

[0007] The Internet of Things information-based laser cutting and welding integrated intelligent machining head comprises a laser generator, a laser cutting head and a laser welding head arranged on the laser generator for laser cutting and welding, an intelligent acquisition device arranged on the laser cutting head and the laser welding head, and a cloud server connected to the intelligent acquisition device through a wireless network.

[0008] The intelligent acquisition device is used for acquiring real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informatization.

[0009] The cloud server is used for processing, analyzing and intelligently controlling the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informatization.

[0010] Preferably, the intelligent acquisition device comprises:

[0011] The running acquisition unit is used for real-time monitoring and continuous acquisition of the running state of the laser cutting head and the laser welding head based on computer vision technology, and obtaining laser cutting and welding integrated intelligent machining running data.

[0012] The production acquisition unit is used for real-time monitoring and continuous acquisition of the production state of the laser cutting head and the laser welding head based on computer vision technology, and obtaining laser cutting and welding integrated intelligent machining production data.

[0013] The environment acquisition unit is used for real-time monitoring and continuous acquisition of the working environment of the laser cutting head and the laser welding head based on sensors, and obtaining laser cutting and welding integrated intelligent machining environment data.

[0014] Based on the laser cutting and welding integrated intelligent machining running data, the laser cutting and welding integrated intelligent machining production data and the laser cutting and welding integrated intelligent machining environment data, the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informatization is determined.

[0015] Preferably, the cloud server comprises:

[0016] The data processing module is used for cleaning, converting, integrating and storing the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informatization, so that the standardized real-time data of the laser cutting and welding integrated intelligent machining is safely stored in the database.

[0017] The machining analysis module is used for comparing and analyzing the real-time data of the laser cutting and welding integrated intelligent machining based on the laser cutting and welding integrated intelligent machining standard data, and determining the analysis result of the laser cutting and welding integrated intelligent machining.

[0018] The intelligent control module is used for intelligently controlling the abnormal situation of the laser cutting and welding integrated intelligent machining.

[0019] The user interface module is used for displaying the human-computer interaction process in a visual form.

[0020] Preferably, the data processing module comprises:

[0021] The data cleaning unit is used for cleaning the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informatization based on the pandas library.

[0022] wherein the laser cutting and welding integrated intelligent processing real-time data based on Internet of Things informatization is checked, repeated data, missing values and abnormal values in the laser cutting and welding integrated intelligent processing real-time data based on Internet of Things informatization are identified, and the repeated data, missing values and abnormal values in the laser cutting and welding integrated intelligent processing real-time data based on Internet of Things informatization are processed;

[0023] For the identified repeated data, the repeated items are marked based on unique keys or primary keys and deleted;

[0024] For the identified missing values, the records containing the missing values are directly deleted, the missing values are filled with median values or estimated by interpolation method;

[0025] For the identified abnormal values, the records containing the abnormal values are directly deleted or the abnormal values are replaced with average values.

[0026] Preferably, the data processing module further comprises:

[0027] The data conversion unit is configured to convert the laser cutting and welding integrated intelligent processing real-time data based on Internet of Things informatization based on the Z-score standardization method, reduce the dimensional difference between the laser cutting and welding integrated intelligent processing real-time data based on Internet of Things informatization, and determine standardized laser cutting and welding integrated intelligent processing real-time data;

[0028] The data integration unit is configured to integrate the standardized laser cutting and welding integrated intelligent processing real-time data, integrate the standardized laser cutting and welding integrated intelligent processing real-time data from different sources into one unified view, and check the integrated standardized laser cutting and welding integrated intelligent processing real-time data;

[0029] The data storage unit is configured to store the checked standardized laser cutting and welding integrated intelligent processing real-time data, and store the standardized laser cutting and welding integrated intelligent processing real-time data safely into a database.

[0030] Preferably, the processing analysis module comprises:

[0031] The standard storage unit is configured to store the pre-set laser cutting and welding integrated intelligent processing standard data;

[0032] The comparative analysis unit is configured to compare and analyze the laser cutting and welding integrated intelligent processing real-time data;

[0033] The laser cutting and welding integrated intelligent processing standard data and the laser cutting and welding integrated intelligent processing real-time data are obtained, the laser cutting and welding integrated intelligent processing real-time data are compared and analyzed based on the laser cutting and welding integrated intelligent processing standard data, and the laser cutting and welding integrated intelligent processing analysis result is determined;

[0034] When the real-time data of the laser cutting and welding integrated intelligent machining is within the standard data range of the laser cutting and welding integrated intelligent machining, the analysis result of the laser cutting and welding integrated intelligent machining is that the laser cutting and welding integrated intelligent machining is normal.

[0035] When the real-time data of the laser cutting and welding integrated intelligent machining is not within the standard data range of the laser cutting and welding integrated intelligent machining, the analysis result of the laser cutting and welding integrated intelligent machining is that the laser cutting and welding integrated intelligent machining is abnormal.

[0036] Preferably, the intelligent management and control module comprises:

[0037] The abnormal analysis unit is configured to analyze the abnormal situation of the laser cutting and welding integrated intelligent machining, find the cause of the abnormal situation of the laser cutting and welding integrated intelligent machining, and develop a control scheme for the laser cutting and welding integrated intelligent machining based on the cause of the abnormal situation.

[0038] The intelligent control unit is configured to optimize the control of the laser cutting and welding integrated intelligent machining based on the control scheme for the laser cutting and welding integrated intelligent machining, wherein the laser cutting and welding parameters are automatically optimized, and the management personnel are timely notified to maintain and manage the laser cutting and welding in a timely manner.

[0039] Preferably, the user interface module comprises:

[0040] The man-machine interaction unit is configured to provide a touch screen operation interface and display the laser cutting and welding machining parameters and equipment state information in a visual form, so that the management personnel can set, monitor and switch the laser cutting and welding machining.

[0041] Preferably, the intelligent management and control module further comprises:

[0042] The residual stress prediction unit is configured to construct and train a residual stress prediction model based on the historical machining operation data and historical machining production data of the laser cutting and welding, use the real-time collected machining operation data and machining production data of the laser cutting and welding as input parameters of the residual stress prediction model, and predict the residual stress of the current machining by the residual stress prediction model.

[0043] The stress influence evaluation unit is configured to implement the laser cutting and welding and its residual stress experiment, construct and train a stress influence model according to the experimental data, combine the residual stress predicted by the residual stress prediction unit, evaluate and process the residual stress by the stress influence model, and obtain a stress influence coefficient.

[0044] The laser control parameter correction unit is configured to correct the laser control parameters according to the stress influence coefficient obtained by the stress influence evaluation unit, and obtain the corrected laser control parameters.

[0045] The laser control implementation unit is configured to generate a laser control instruction according to the corrected laser control parameter, and implement laser cutting and welding process control by using the laser control instruction.

[0046] Preferably, the production acquisition unit comprises:

[0047] Machine vision image processing and recognition: based on computer vision technology, a laser cutting and welding image is obtained; image pre-processing is performed on the laser cutting and welding image, and cutting and welding position recognition is performed on the image after image pre-processing;

[0048] Cutting and welding image spectral feature extraction: spectral feature extraction is performed on the cutting and welding position image after image pre-processing to obtain spectral feature data of the cutting and welding position image;

[0049] Surface roughness prediction model construction: a neural network model for surface roughness prediction is constructed by using a neural network machine learning algorithm, historical spectral feature data of cutting and welding position images extracted from historical laser cutting and welding images after image pre-processing are used as training samples, the model is trained and optimized, the relationship between historical spectral feature data and surface roughness is learned through the model, surface roughness prediction of each cutting and welding position corresponding to the historical laser cutting and welding image is realized, if the surface roughness prediction accuracy of each cutting and welding position meets the requirements, the model training is completed, and a surface roughness prediction model is obtained;

[0050] Surface roughness prediction: the spectral feature data of the cutting and welding position image collected in real time is input into the surface roughness prediction model to obtain a real-time surface roughness prediction result of laser cutting and welding;

[0051] Laser parameter: according to the prediction result, the following formula is used to calculate the adjusted control laser power:

[0052]

[0053] Wherein, is the adjusted laser power, is the current laser power, is the surface roughness adjustment coefficient, is the Dirac function, is the surface roughness of the material around the first point of the cutting and welding position, is the surface roughness of the material around the first point of the cutting and welding position, is the surface roughness critical value of the material, is the differential of the cutting and welding position of the material surface, is the maximum allowed surface roughness, and the laser is adjusted when the laser cutting and welding is performed according to the calculated laser power.

[0054] Compared with the prior art, the beneficial effects of the present application are:

[0055] The application is based on computer vision technology and real-time acquisition of laser cutting and welding integrated intelligent machining operation data, production data and environmental data by sensors, determines real-time data of laser cutting and welding integrated intelligent machining based on Internet of Things informationization, processes and analyzes the real-time data of laser cutting and welding integrated intelligent machining based on Internet of Things informationization, determines laser cutting and welding integrated intelligent machining analysis results, and intelligently optimizes and controls abnormal conditions of laser cutting and welding integrated intelligent machining, so as to realize real-time monitoring and intelligent management of the laser cutting and welding integrated intelligent machining head, and improve the use effect of the laser cutting and welding integrated intelligent machining head and the laser cutting and welding efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0056] Fig. 1 It is a structure diagram of the Internet of Things informationization laser cutting and welding integrated intelligent machining head of the application.

[0057] Fig. 2 It is a module block diagram of the Internet of Things informationization laser cutting and welding integrated intelligent machining head of the application.

[0058] Fig. 3 It is an algorithm flowchart of the Internet of Things informationization laser cutting and welding integrated intelligent machining head of the application.

[0059] In the figure: 1, laser generator; 11, laser cutting head; 12, laser welding head. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the application.

[0061] In order to solve the problem that the existing laser cutting and welding integrated intelligent machining head cannot be monitored and managed intelligently in real time during cutting and welding, resulting in poor use effect and low efficiency of the laser cutting and welding integrated intelligent machining head, please refer to Figs. 1-3 The embodiment provides the following technical solutions:

[0062] The Internet of Things informationization laser cutting and welding integrated intelligent machining head comprises a laser generator 1, and a laser cutting head 11 and a laser welding head 12 for laser cutting and welding integrated intelligent machining are arranged on the laser generator 1. Intelligent acquisition devices are arranged on the laser cutting head 11 and the laser welding head 12, and the intelligent acquisition devices are connected to a cloud server through a wireless network.

[0063] It should be noted that the laser cutting head 11 irradiates the cutting material with a high-power density laser beam, which quickly heats the material to the vaporization temperature, evaporates to form a hole, and as the beam moves on the material, the hole continuously forms a narrow cutting seam, completing the cutting of the material, thereby realizing precise and non-contact cutting process.

[0064] It should be noted that the laser welding head 12 uses a focused laser beam as an energy source to hit the welding part to generate heat for welding, which can tightly bond two or more workpieces together and transfer heat input to the joint to fuse the workpieces together, achieving high-quality welding effect.

[0065] Among them, the intelligent acquisition device is used to acquire real-time data of laser cutting and welding integrated intelligent machining based on Internet of Things informationization;

[0066] In this embodiment, the intelligent acquisition device comprises:

[0067] The running acquisition unit is used to monitor and continuously acquire the running status of the laser cutting head 11 and the laser welding head 12 based on computer vision technology, and obtain laser cutting and welding integrated intelligent machining running data;

[0068] The production acquisition unit is used to monitor and continuously acquire the production situation of the laser cutting head 11 and the laser welding head 12 based on computer vision technology, and obtain laser cutting and welding integrated intelligent machining production data;

[0069] The environment acquisition unit is used to monitor and continuously acquire the working environment of the laser cutting head 11 and the laser welding head 12 based on sensors, and obtain laser cutting and welding integrated intelligent machining environment data;

[0070] Among them, based on the laser cutting and welding integrated intelligent machining running data, the laser cutting and welding integrated intelligent machining production data and the laser cutting and welding integrated intelligent machining environment data, the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization is determined.

[0071] It should be noted that by acquiring the real-time data of laser cutting and welding integrated intelligent machining based on Internet of Things informationization, real-time monitoring of the laser cutting and welding integrated intelligent machining head can be realized, which helps to find problems in the production process in time and make adjustments to ensure the stability of production and product quality.

[0072] The cloud server is used to process, analyze and intelligently control the real-time data of laser cutting and welding integrated intelligent machining based on Internet of Things informationization.

[0073] In this embodiment, the cloud server comprises a data processing module, a machining analysis module, an intelligent control module and a user interface module.

[0074] The data processing module is configured to clean, convert, integrate, and store the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization, so as to store the standardized real-time data of the laser cutting and welding integrated intelligent machining into a database in a safe manner.

[0075] In the embodiment, the data processing module comprises:

[0076] The data cleaning unit is configured to clean the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization based on a pandas library.

[0077] The real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization is checked to identify repeated data, missing values, and abnormal values in the real-time data, and the repeated data, missing values, and abnormal values in the real-time data are processed.

[0078] The repeated data identified is marked and deleted based on a unique key or a primary key.

[0079] The missing values identified are directly deleted, filled with a median value, or estimated by an interpolation method.

[0080] The abnormal values identified are directly deleted or replaced with an average value.

[0081] It should be noted that the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization is cleaned, and the repeated data, missing values, and abnormal values in the real-time data are processed, so as to improve the processing accuracy and speed of the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization.

[0082] The data conversion unit is configured to convert the real-time data of the laser cutting and welding integrated intelligent machining based on Internet of Things informationization based on a Z-score standardization method, reduce the dimensional difference between the real-time data, and determine standardized real-time data of the laser cutting and welding integrated intelligent machining.

[0083] The data integration unit is configured to integrate the standardized real-time data of the laser cutting and welding integrated intelligent machining, integrate the standardized real-time data of the laser cutting and welding integrated intelligent machining from different sources into a unified view, and check the integrated standardized real-time data of the laser cutting and welding integrated intelligent machining.

[0084] A data storage unit is configured to store the qualified standardized laser cutting and welding integrated intelligent machining real-time data, so that the standardized laser cutting and welding integrated intelligent machining real-time data is safely stored in a database.

[0085] It should be noted that by cleaning, converting, integrating and storing the laser cutting and welding integrated intelligent machining real-time data based on the Internet of Things information, and safely storing the standardized laser cutting and welding integrated intelligent machining real-time data in the database, the laser cutting and welding integrated intelligent machining real-time data based on the Internet of Things information can be viewed, which facilitates subsequent analysis of the laser cutting and welding integrated intelligent machining real-time data based on the Internet of Things information. The process of laser cutting and welding can be monitored in real time, and the cutting and welding parameters can be automatically optimized to ensure the consistency of cutting and welding quality.

[0086] The processing analysis module is configured to compare and analyze the laser cutting and welding integrated intelligent machining real-time data based on the laser cutting and welding integrated intelligent machining standard data, and determine the laser cutting and welding integrated intelligent machining analysis result.

[0087] In this embodiment, the processing analysis module includes:

[0088] The standard storage unit is configured to store the pre-set laser cutting and welding integrated intelligent machining standard data.

[0089] The comparison and analysis unit is configured to compare and analyze the laser cutting and welding integrated intelligent machining real-time data.

[0090] The laser cutting and welding integrated intelligent machining standard data and the laser cutting and welding integrated intelligent machining real-time data are obtained, the laser cutting and welding integrated intelligent machining real-time data is compared and analyzed based on the laser cutting and welding integrated intelligent machining standard data, and the laser cutting and welding integrated intelligent machining analysis result is determined.

[0091] When the laser cutting and welding integrated intelligent machining real-time data is within the range of the laser cutting and welding integrated intelligent machining standard data, the laser cutting and welding integrated intelligent machining analysis result is normal.

[0092] When the laser cutting and welding integrated intelligent machining real-time data is not within the range of the laser cutting and welding integrated intelligent machining standard data, the laser cutting and welding integrated intelligent machining analysis result is abnormal.

[0093] It should be noted that by comparing and analyzing the laser cutting and welding integrated intelligent machining real-time data based on the laser cutting and welding integrated intelligent machining standard data, and determining the laser cutting and welding integrated intelligent machining analysis result, the laser cutting and welding integrated intelligent machining abnormal situation can be found in time, and the laser cutting and welding integrated intelligent machining abnormal situation can be controlled in time, which can improve the use effect of the laser cutting and welding integrated intelligent machining head and the laser cutting and welding efficiency.

[0094] The intelligent management and control module is configured to intelligently manage and control the abnormal situation of the laser cutting and welding integrated intelligent machining.

[0095] In this embodiment, the intelligent management and control module comprises:

[0096] The abnormality analysis unit is configured to analyze the abnormal situation of the laser cutting and welding integrated intelligent machining, find the cause of the abnormality of the laser cutting and welding integrated intelligent machining, and develop a control scheme for the laser cutting and welding integrated intelligent machining based on the cause of the abnormality.

[0097] The intelligent control unit is configured to optimize the control of the laser cutting and welding integrated intelligent machining based on the control scheme for the laser cutting and welding integrated intelligent machining, wherein the laser cutting and welding parameters are automatically optimized, and the management personnel are timely notified to maintain and manage the laser cutting and welding.

[0098] The user interface module is configured to display the human-computer interaction process in a visual form.

[0099] In this embodiment, the user interface module comprises:

[0100] The human-computer interaction unit is configured to provide a touch screen operation interface and display the laser cutting and welding machining parameters and equipment state information in a visual form, so that the management personnel can set, monitor and switch the laser cutting and welding machining, and facilitate the management personnel to real-time understand the laser cutting and welding integrated intelligent machining process.

[0101] In summary, by processing and analyzing the real-time data of the laser cutting and welding integrated intelligent machining based on the Internet of Things information, determining the analysis result of the laser cutting and welding integrated intelligent machining, and intelligently optimizing the control of the abnormal situation of the laser cutting and welding integrated intelligent machining, the real-time monitoring and intelligent management of the laser cutting and welding integrated intelligent machining head can be realized, and the use effect of the laser cutting and welding integrated intelligent machining head and the laser cutting and welding efficiency can be improved.

[0102] In this embodiment, the intelligent management and control module further comprises:

[0103] The residual stress prediction unit is configured to construct and train a residual stress prediction model based on the historical machining operation data and historical machining production data of the laser cutting and welding, use the real-time collected machining operation data and machining production data of the laser cutting and welding as input parameters of the residual stress prediction model, and predict the residual stress of the current machining by the residual stress prediction model.

[0104] The stress influence evaluation unit is configured to implement the laser cutting and welding and its residual stress experiment, construct and train a stress influence model according to the experimental data, combine the residual stress predicted by the residual stress prediction unit, evaluate and process the residual stress by the stress influence model, and obtain a stress influence coefficient.

[0105] a laser control parameter correction unit configured to correct the laser control parameter according to the stress influence coefficient obtained by the stress influence evaluation unit, to obtain a corrected laser control parameter;

[0106] a laser control implementation unit configured to generate a laser control instruction according to the corrected laser control parameter, and implement laser cutting and welding process control by using the laser control instruction.

[0107] Specifically, by using historical data, a residual stress prediction model is constructed and trained, which is used for model analysis on current data of laser cutting and welding, and outputs the residual stress value of the current processing. Then, based on the trained stress influence model, residual stress influence evaluation is performed to obtain a stress influence coefficient, which is used as the correction basis data of the laser control parameter, and a laser control instruction can be generated and obtained, which is used for controlling the laser. By introducing the residual stress real-time monitoring and control technology, the residual stress in the laser processing process can be significantly reduced or even completely eliminated, and through real-time feedback and dynamic adjustment, the processing process is optimized, and the laser processing precision and reliability are improved.

[0108] In the embodiment, the production acquisition unit comprises:

[0109] Machine vision image processing and recognition: based on computer vision technology, a laser cutting and welding image is obtained; the laser cutting and welding image is preprocessed, and the preprocessed image is subjected to cutting and welding position recognition;

[0110] Cutting and welding image spectrum feature extraction: spectrum feature extraction is performed on the cutting and welding position image after image preprocessing, to obtain spectrum feature data of the cutting and welding position image;

[0111] Surface roughness prediction model construction: a neural network model for surface roughness prediction is constructed by using a neural network machine learning algorithm, historical spectrum feature data of the cutting and welding position image extracted from the historical laser cutting and welding image after image preprocessing is used as a training sample, the model is trained and optimized, the relationship between the historical spectrum feature data and the surface roughness is learned through model learning, the surface roughness corresponding to each cutting and welding position of the historical laser cutting and welding image is predicted, if the surface roughness prediction accuracy of each cutting and welding position meets the requirements, the model training is completed, and a surface roughness prediction model is obtained;

[0112] Surface roughness prediction: the spectrum feature data of the cutting and welding position image collected in real time is input into the surface roughness prediction model, to obtain a real-time surface roughness prediction result of laser cutting and welding;

[0113] Laser parameter: according to the prediction result, the following formula is used to calculate the adjusted control laser power:

[0114]

[0115] in, The adjusted laser power, For the current laser power, This is the surface roughness adjustment coefficient. For the Dirac function, For the material at the welding position Surface roughness around the point This represents the critical value for the surface roughness of the material. For the differential of the weld position on the material surface, To achieve the maximum permissible surface roughness, the laser power during laser cutting and welding is adjusted based on the calculated laser power.

[0116] Specifically, laser cutting and welding images are obtained through machine vision, preprocessed, and then subjected to spectral feature extraction to obtain spectral feature data. A surface roughness prediction model reflecting the spectral feature data and surface roughness is established. The model performs prediction analysis based on the spectral feature data of the cutting and welding position image to obtain the surface roughness prediction result. Then, the optimized laser power is calculated using the above formula. The formula takes into account the relatively concentrated stress generation in laser cutting and welding, and includes an integral process for each cutting and welding position. The integral reflects the surface roughness difference at different positions, avoiding the limitation of using a single point as a representative. Based on the calculation results, the laser is adjusted during laser cutting and welding, with real-time feedback and dynamic adjustment. Through dynamic adjustment, the laser processing process is optimized and controlled, significantly improving the performance and function of the laser cutting and welding equipment, and has broad application prospects and market potential.

[0117] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0118] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An Internet of Things information laser cutting and welding integrated intelligent machining head, comprising a laser generator (1), characterized in that, The laser generator (1) is provided with a laser cutting and welding integrated intelligent machining laser cutting head (11) and a laser welding head (12), the laser cutting head (11) and the laser welding head (12) are provided with an intelligent acquisition device, and the intelligent acquisition device is connected to a cloud server through a wireless network; The intelligent acquisition device is used for collecting laser cutting and welding integrated intelligent machining real-time data based on Internet of Things informationization; The cloud server is used for processing, analyzing and intelligently controlling the laser cutting and welding integrated intelligent machining real-time data based on Internet of Things informationization; The intelligent acquisition device comprises: An operation acquisition unit is used for monitoring and continuously acquiring the operation state of the laser cutting head (11) and the laser welding head (12) based on computer vision technology, and obtaining laser cutting and welding integrated intelligent machining operation data; A production acquisition unit is used for monitoring and continuously acquiring the production state of the laser cutting head (11) and the laser welding head (12) based on computer vision technology, and obtaining laser cutting and welding integrated intelligent machining production data; An environment acquisition unit is used for monitoring and continuously acquiring the working environment of the laser cutting head (11) and the laser welding head (12) based on a sensor, and obtaining laser cutting and welding integrated intelligent machining environment data; The laser cutting and welding integrated intelligent machining real-time data based on Internet of Things informationization is determined based on the laser cutting and welding integrated intelligent machining operation data, the laser cutting and welding integrated intelligent machining production data and the laser cutting and welding integrated intelligent machining environment data; The production acquisition unit comprises: Machine vision image processing and identification: based on computer vision technology, a laser cutting and welding image is obtained; the laser cutting and welding image is preprocessed, and the preprocessed image is identified; Cutting and welding image spectrum feature extraction: for the cutting and welding position image after image preprocessing, spectrum feature extraction is implemented to obtain the spectrum feature data of the cutting and welding position image; Surface roughness prediction model construction: a neural network model for surface roughness prediction is constructed by using a neural network machine learning algorithm, historical spectrum feature data of the cutting and welding position image extracted from the historical laser cutting and welding image after image preprocessing is used as a training sample, the model is trained and optimized, the relationship between the historical spectrum feature data and the surface roughness is learned through the model, the surface roughness corresponding to each cutting and welding position of the historical laser cutting and welding image is predicted, if the surface roughness prediction accuracy of each cutting and welding position meets the requirements, the model training is completed, and a surface roughness prediction model is obtained; Surface roughness prediction: the spectrum feature data of the cutting and welding position image collected in real time is input into the surface roughness prediction model, and a real-time surface roughness prediction result of laser cutting and welding is obtained; Laser parameters: according to the prediction result, the following formula is used to calculate the adjusted control laser power: wherein, is the adjusted laser power, is the current laser power, is the surface roughness adjustment factor is the Dirac function, is the surface roughness of the material at the point of the keyhole, is the surface roughness of the material at the periphery of the point of the keyhole, is the critical value of the surface roughness of the material, is the differential of the surface of the material at the point of the keyhole, is the maximum allowable surface roughness, the laser is adjusted according to the calculated laser power when the laser is used for keyhole welding.

2. The IoT informatization laser cutting and welding integrated intelligent machining head of claim 1, wherein The cloud server comprises: A data processing module is used for cleaning, converting, integrating and storing the laser cutting and welding integrated intelligent machining real-time data based on Internet of Things informationization, so that the standardized laser cutting and welding integrated intelligent machining real-time data is safely stored in a database; The processing analysis module is configured to compare and analyze the real-time data of the laser cutting and welding integrated intelligent processing based on the laser cutting and welding integrated intelligent processing standard data, and determine the laser cutting and welding integrated intelligent processing analysis result. The intelligent management and control module is configured to intelligently manage and control the abnormal situation of the laser cutting and welding integrated intelligent processing. The user interface module is configured to display the human-computer interaction process in a visual form. 3.The IoT informatization laser cutting and welding integrated intelligent machining head of claim 2, characterized in that, The data processing module comprises: The data cleaning unit is configured to clean the real-time data of the laser cutting and welding integrated intelligent processing based on the Internet of Things informationization based on a pandas library. The real-time data of the laser cutting and welding integrated intelligent processing based on the Internet of Things informationization is checked to identify repeated data, missing values and abnormal values in the real-time data, and the repeated data, missing values and abnormal values in the real-time data are processed. For the identified repeated data, the repeated items are marked based on a unique key or a primary key and deleted. For the identified missing values, the records containing the missing values are directly deleted, the missing values are filled with a median value, or the missing values are estimated by an interpolation method. For the identified abnormal values, the records containing the abnormal values are directly deleted, or the abnormal values are replaced with an average value. 4.The IoT informatization laser cutting and welding integrated intelligent machining head of claim 3, characterized in that, The data processing module further comprises: The data conversion unit is configured to convert the real-time data of the laser cutting and welding integrated intelligent processing based on the Internet of Things informationization based on a Z-score standardization method, reduce the dimension difference between the real-time data, and determine the standardized real-time data of the laser cutting and welding integrated intelligent processing. The data integration unit is configured to integrate the standardized real-time data of the laser cutting and welding integrated intelligent processing, integrate the standardized real-time data of the laser cutting and welding integrated intelligent processing from different sources into a unified view, and verify the integrated standardized real-time data. The data storage unit is configured to store the verified standardized real-time data of the laser cutting and welding integrated intelligent processing, and store the standardized real-time data of the laser cutting and welding integrated intelligent processing safely in a database. 5.The IoT informatization laser cutting and welding integrated intelligent machining head of claim 4, characterized in that, The processing analysis module comprises: The standard storage unit is configured to store the pre-set laser cutting and welding integrated intelligent processing standard data. The comparative analysis unit is configured to compare and analyze the real-time data of the laser cutting and welding integrated intelligent processing. The laser cutting and welding integrated intelligent processing standard data and the real-time data of the laser cutting and welding integrated intelligent processing are obtained, the real-time data of the laser cutting and welding integrated intelligent processing is compared and analyzed based on the laser cutting and welding integrated intelligent processing standard data, and the laser cutting and welding integrated intelligent processing analysis result is determined. When the real-time data of the laser cutting and welding integrated intelligent processing is within the range of the laser cutting and welding integrated intelligent processing standard data, the laser cutting and welding integrated intelligent processing analysis result is normal. When the real-time data of the laser cutting and welding integrated intelligent processing is not within the range of the laser cutting and welding integrated intelligent processing standard data, the laser cutting and welding integrated intelligent processing analysis result is abnormal. 6.The IoT informatization laser cutting and welding integrated intelligent machining head of claim 5, characterized in that, The intelligent management and control module comprises: An abnormality analysis unit is configured to analyze abnormal conditions of the laser cutting and welding integrated intelligent machining, find out reasons for the abnormal conditions, and develop a control scheme for the laser cutting and welding integrated intelligent machining based on the reasons. An intelligent control unit is configured to optimize and control the laser cutting and welding integrated intelligent machining based on the control scheme, in which laser cutting and welding parameters are automatically optimized, and management personnel are timely informed to maintain and manage laser cutting and welding failures.

7. The IoT informatization laser cutting and welding integrated intelligent machining head of claim 6, wherein, The user interface module includes: A human-computer interaction unit is configured to provide a touch screen operation interface and display laser cutting and welding machining parameters and equipment state information in a visual form, so that management personnel can set, monitor and switch laser cutting and welding machining.

8. The IoT informatization laser cutting and welding integrated intelligent machining head of claim 7, wherein, The intelligent management and control module further includes: A residual stress prediction unit is configured to construct and train a residual stress prediction model based on historical machining operation data and historical machining production data of the laser cutting and welding, input real-time machining operation data and machining production data collected by the laser cutting and welding into the residual stress prediction model as input parameters, and predict residual stress of current machining by the residual stress prediction model. A stress influence evaluation unit is configured to implement laser cutting and welding and residual stress experiments, construct and train a stress influence model based on experimental data, combine the residual stress predicted by the residual stress prediction unit, evaluate residual stress by the stress influence model, and obtain a stress influence coefficient. A laser control parameter correction unit is configured to correct laser control parameters based on the stress influence coefficient obtained by the stress influence evaluation unit, and obtain corrected laser control parameters. A laser control implementation unit is configured to generate laser control instructions based on the corrected laser control parameters, and implement laser cutting and welding process control by using the laser control instructions.

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