Closed-loop control method, device and system for laser cladding and storage medium

Abstract

The invention discloses a closed-loop control method, device and system for laser cladding and a storage medium. In the method, the first center temperature and the first width of a molten pool are monitored, and the first laser power and the first powder feeding rate of a laser are adjusted through a fuzzy control algorithm based on the monitoring result; and the precision and the quality of laser cladding are further improved. The method comprises the following steps: controlling powder spraying equipment to spray a cladding material on a substrate; a laser is controlled to emit laser to the cladding material, so that the cladding material and the base body making contact with the cladding material form a molten pool; the first center temperature and the first width of the molten pool are obtained; and according to the first center temperature of the molten pool and the first width of the molten pool, a fuzzy control algorithm is used for adjusting the first laser power and the first powder feeding rate of the laser device, and the first powder feeding rate is the rate of spraying the cladding material by the powder spraying equipment.

Description

Technical Field

[0001] The present application relates to the field of additive manufacturing technology, and in particular to a closed-loop control method, device, system and storage medium for laser cladding. Background Art

[0002] Laser cladding technology is a new surface modification technology that uses a high-energy laser beam to simultaneously radiate and heat the cladding material and the substrate to form a good metallurgical bonding interface between the two. It can effectively improve the material's corrosion resistance, corrosion resistance, and high-temperature oxidation resistance, and can even change the material's optical, electromagnetic and other physical properties. It has the characteristics of high bonding strength, low dilution, small thermal deformation, and uniform and dense coating. It is currently widely used in aerospace, automotive, mold, biomedicine and other industries.

[0003] However, due to the complex coupling of multiple physical fields such as mass transfer, heat transfer and convection during the metal laser melting and deposition process, the reliability and repeatability of processing quality are low, adaptive control is difficult, and defects are uncontrollable, which have always been important problems faced by this technology. Therefore, how to ensure the accuracy and quality of laser cladding has become a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0004] In view of this, the present application provides a closed-loop control method, device, system and storage medium for laser cladding. In this method, the first center temperature and the first width of the molten pool are monitored, and based on the monitoring results, a fuzzy control algorithm is used to adjust the first laser power and the first powder feeding rate of the laser, thereby improving the accuracy and quality of laser cladding.

[0005] According to one aspect of the present application, a closed-loop control method for laser cladding is provided, comprising:

[0006] Control the powder spraying equipment to spray the cladding material on the substrate;

[0007] Controlling the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool;

[0008] Acquire a first center temperature and a first width of the molten pool;

[0009] According to the first center temperature and the first width of the molten pool, the first laser power and the first powder feeding rate of the laser are adjusted using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0010] In some embodiments, the method further comprises:

[0011] Determine the proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool;

[0012] According to all fuzzy languages ​​in the fuzzy language set corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool, a fuzzy relationship is determined, wherein the fuzzy relationship includes a first fuzzy relationship and a second fuzzy relationship, the first fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second laser power, and the second fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second powder feeding rate.

[0013] In some embodiments, the step of determining the proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool comprises:

[0014] Setting attribute information for a second center temperature of the molten pool, a second width of the molten pool, a second laser power, and a second powder feeding rate, wherein the attribute information includes an input quantity and an output quantity, the attribute information of the second center temperature of the molten pool and the second width of the molten pool are both input quantities, and the attribute information of the second laser power and the second powder feeding rate are both output quantities;

[0015] Obtaining fuzzy control information corresponding to a second center temperature of the molten pool, a second width of the molten pool, a second laser power, and a second powder feeding rate, respectively, wherein the fuzzy control information includes an actual variation range and a preset fuzzy set range;

[0016] Determine proportional factors corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool, respectively, according to the fuzzy control information and the attribute information;

[0017] According to the preset fuzzy set ranges corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool, the membership function corresponding to each fuzzy language in the fuzzy language set corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool is determined.

[0018] In some embodiments, the process of determining the actual variation range of the second center temperature of the molten pool includes:

[0019] Determine the variation range of the second center temperature of the molten pool;

[0020] Determine a central value of a variation range of a second central temperature of the molten pool;

[0021] Subtracting the center value from the minimum value of the variation range to obtain a first result, and subtracting the center value from the maximum value of the variation range to obtain a second result;

[0022] The actual variation range of the second center temperature of the molten pool is determined by using the first result and the second result.

[0023] In some embodiments, the step of adjusting the first laser power and the first powder feeding rate of the laser by using a fuzzy control algorithm according to the first center temperature and the first width of the molten pool includes:

[0024] Determine the fuzzy languages ​​corresponding to the first center temperature and the first width of the molten pool respectively;

[0025] According to the fuzzy languages ​​corresponding to the first center temperature and the first width of the molten pool, respectively, the fuzzy language corresponding to the first laser power of the laser is determined based on the first fuzzy relationship, and the fuzzy language corresponding to the first powder feeding rate is determined based on the second fuzzy relationship;

[0026] Using the membership function corresponding to the second laser power, screening out a first fuzzy value with the highest probability in the fuzzy language corresponding to the first laser power;

[0027] Using the membership function corresponding to the second powder feeding rate, a second fuzzy value with the highest probability is screened out from the fuzzy language corresponding to the first powder feeding rate;

[0028] Determining a control change amount of the first laser power according to the first fuzzy value with the highest probability; and adjusting the current first laser power according to the control change amount of the first laser power;

[0029] According to the second fuzzy value with the highest probability, a control change amount of the first powder feeding rate is determined; and according to the control change amount of the first powder feeding rate, a current first powder feeding rate is adjusted.

[0030] In some embodiments, the step of determining the fuzzy language corresponding to the first center temperature of the molten pool includes:

[0031] Calculating a difference between a first center temperature of the molten pool and the center value;

[0032] multiplying the difference by a proportionality factor corresponding to the second center temperature of the molten pool;

[0033] The fuzzy language corresponding to the first center temperature of the molten pool is determined using the result obtained by multiplication.

[0034] In some embodiments, the step of determining the control change amount of the first laser power according to the first fuzzy value with the highest probability includes:

[0035] The first fuzzy value is multiplied by a proportional factor corresponding to the second laser power to obtain a control change amount of the first laser power.

[0036] In some embodiments, after the step of adjusting the first laser power and the first powder feeding rate of the laser by using a fuzzy control algorithm according to the first center temperature and the first width of the molten pool, the method further includes:

[0037] Repeat the steps of obtaining the first center temperature and the first width of the molten pool and adjusting the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm until it is detected that the powder spraying equipment and the laser are turned off.

[0038] According to another aspect of the present application, a closed-loop control system for laser cladding is provided, comprising a powder spraying device, a laser, a temperature meter, a camera and an industrial computer;

[0039] The industrial computer is used to control the powder spraying equipment to spray the cladding material on the substrate;

[0040] Controlling the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool;

[0041] Acquire a first central temperature of the molten pool measured by a thermometer and a first width of the molten pool determined by a camera;

[0042] According to the first center temperature and the first width of the molten pool, the first laser power and the first powder feeding rate of the laser are adjusted using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0043] According to another aspect of the present application, a closed-loop control device for laser cladding is provided, comprising:

[0044] A first control unit is used to control the powder spraying device to spray the cladding material on the substrate;

[0045] A second control unit is used to control the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool;

[0046] an acquisition unit, configured to acquire a first central temperature and a first width of the molten pool;

[0047] The adjustment unit is used to adjust the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0048] According to another aspect of the present application, a storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the method described above is implemented.

[0049] Through the above technical scheme, the present application provides a closed-loop control method, device, system and storage medium for laser cladding. In this method, the first center temperature and the first width of the molten pool are monitored, and based on the monitoring results, a fuzzy control algorithm is used to adjust the first laser power and the first powder feeding rate of the laser, thereby improving the accuracy and quality of laser cladding.

[0050] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0052] Figure 1 A schematic structural diagram of a closed-loop control system for laser cladding provided according to some embodiments is exemplarily shown;

[0053] Figure 2 A flowchart of a closed-loop control method for laser cladding provided according to some embodiments is exemplarily shown;

[0054] Figure 3 The following is a schematic diagram showing an installation of a thermometer and a camera according to some embodiments;

[0055] Figure 4 A schematic diagram showing, by way of example, membership functions corresponding to five fuzzy languages ​​in a fuzzy language set provided according to some embodiments;

[0056] Figure 5 A schematic diagram showing the structure of another closed-loop control system for laser cladding according to some embodiments is shown.

[0057] Figure 6A schematic structural diagram of a closed-loop control device for laser cladding provided according to some embodiments is exemplarily shown;

[0058] Figure 7 A schematic diagram of the device structure of a computer device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0059] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0060] Laser cladding technology is a new surface modification technology that uses a high-energy laser beam to simultaneously radiate and heat the cladding material and the substrate to form a good metallurgical bonding interface between the two. It can effectively improve the material's corrosion resistance, corrosion resistance, and high-temperature oxidation resistance, and can even change the material's optical, electromagnetic and other physical properties. It has the characteristics of high bonding strength, low dilution, small thermal deformation, and uniform and dense coating. It is currently widely used in aerospace, automotive, mold, biomedicine and other industries.

[0061] However, due to the complex coupling of multiple physical fields such as mass transfer, heat transfer and convection during the metal laser melting and deposition process, the reliability and repeatability of processing quality are low, adaptive control is difficult, and defects are uncontrollable, which have always been important problems faced by this technology. Therefore, how to ensure the accuracy and quality of laser cladding has become a technical problem that technicians in this field need to solve urgently.

[0062] In order to solve the above technical problems, an embodiment of the present application provides a closed-loop control method for laser cladding, in which the first center temperature and the first width of the molten pool are monitored, and based on the monitoring results, a fuzzy control algorithm is used to adjust the first laser power and the first powder feeding rate of the laser, thereby improving the accuracy and quality of laser cladding.

[0063] Before introducing the method in the embodiment of the present application, a system for executing the method is introduced. Figure 1 The schematic diagram of the structure of a closed-loop control system for laser cladding provided according to some embodiments is exemplified. The system includes an industrial computer, a camera, an IO module, a thermometer, a laser, and a powder spraying device. The control system adopts a bus structure and communicates based on real-time industrial Ethernet. The industrial computer serves as the master station of the real-time industrial Ethernet and is connected to the IO module. The IO module serves as a slave station and directly controls the thermometer, laser, and powder spraying device and exchanges data with them. The camera is directly connected to the industrial computer.

[0064] Among them, the industrial computer is Nano N18, with Intel Core i5 onboard, 8G memory, 128G solid-state drive, and 6 RJ45 Gigabit network ports. The control system is developed based on Windows and real-time expansion kits to meet industrial-grade real-time requirements, support C++ and C# secondary development programming, support visual libraries OpenCV and Halcon, and meet the acquisition and processing of real-time vision at the kernel layer. Specifically, the industrial computer collects images in real time through the GIGE interface (camera interface standard developed by Gigabit Ethernet communication protocol) to complete image processing; communicates with the IO module through real-time industrial Ethernet to obtain the temperature data of the thermometer collected by the IO module, and controls the IO module to issue laser control instructions and other IO signals.

[0065] In the embodiment of the present application, reasonable configuration of relevant hardware and software is adopted to realize real-time collection of multi-sensor signals, which can monitor and record the laser cladding process in situ without loss.

[0066] Figure 2 The flowchart of a closed-loop control method for laser cladding provided according to some embodiments is exemplarily shown. The embodiment of the present application provides a closed-loop control method for laser cladding, including S100-S400.

[0067] S100, controlling the powder spraying equipment to spray the cladding material on the substrate.

[0068] In this embodiment, the powder spraying equipment is usually equipped with a precise powder conveying system, which can spray the cladding powder evenly onto the surface of the substrate to be processed according to a predetermined powder feeding rate.

[0069] S200, controlling a laser to emit laser light onto a cladding material, so that the cladding material and a substrate in contact with the cladding material form a molten pool.

[0070] While executing step S100, it is necessary to control the laser to emit laser light onto the cladding material, and utilize the high energy density of the laser beam to heat the cladding material and the substrate, so that both are in a molten state and form a molten pool.

[0071] S300, obtaining a first central temperature and a first width of the molten pool;

[0072] In this embodiment, the first center temperature of the molten pool is measured by a temperature meter in the system. The first width of the molten pool is determined by an image taken by a camera (CCD camera). In this embodiment, the first center temperature and the first width of the molten pool are used to more comprehensively characterize the complex process of multi-physical field coupling such as mass transfer, heat transfer and convection, and the information of the molten pool is fully understood, which can improve the accuracy and quality of laser cladding.

[0073] Figure 3The following is a schematic diagram of the installation of a thermometer and a camera according to some embodiments. In some embodiments, the thermometer can be a two-color infrared thermometer with an electric focusing function, and is composed of an optical system, a filter, an infrared detector, a signal processor, and an output part. The response band channels of the two filters are 1.65-1.8μm and 1.45-1.65μm, respectively, with a response time of less than 1ms and a temperature measurement range of 300-2600℃, which can meet the measurement requirements of the molten pool temperature.

[0074] The two-color infrared thermometer 1 and the laser 2 are integrated on the laser cladding head 3. A reflector 4 and a light-transmitting mirror 5 are installed inside the laser cladding head 3. The laser emitted by the laser 2 can be adjusted through the light-transmitting mirror 5 so that the laser is emitted to the center of the molten pool. The light reflected from the center of the molten pool can enter the two-color infrared thermometer 1 through the reflector 4, so that the two-color infrared thermometer 1 can achieve the effect of temperature measurement. In addition, the reflector is a special lens, and a special film is provided on the front and back surfaces of the reflector to ensure that the laser can reach the center of the molten pool through the reflector. It should be noted that the laser optical path of the laser 2 is coaxial with the optical path of the two-color infrared thermometer 1, and the thermometer can measure the center temperature of the laser cladding molten pool.

[0075] In this embodiment, the molten pool can be ensured to be within the optimal effective range of the two-color infrared thermometer by adjusting the focal length of the two-color infrared thermometer 1. In some embodiments, the two-color infrared thermometer 1 is installed perpendicular to the laser cladding head and moves synchronously with the cladding head. The reflector 4 is used to realize that the laser optical path of the laser 2 and the optical path of the two-color infrared thermometer 1 are coaxial.

[0076] In a two-color infrared thermometer, two sets of different monochromatic filters with very narrow bandwidths are used to collect radiation energy in two similar bands. The radiation energy is received by two independent infrared detectors and converted into electrical signals. Because the ratio of the radiation energy changes with the temperature when the two spectra and bandwidths are clear, the signal processor calculates the ratio of the two signals and outputs the temperature data after ambient temperature compensation, as shown in the following formula:

[0077]

[0078] Where T is the target temperature, e1 and e2 are the emissivity of the target in the two bands, E1 and E2 are the energy of the target in the two bands, and A and B are constants.

[0079] Compared with the single-color thermometer, the temperature measured by the two-color infrared thermometer will not change with the state of the surface of the object. Different surface roughness or different surface chemical state will not affect the accuracy of temperature measurement. In addition, the two-color infrared thermometer can measure objects smaller than the field of view.

[0080] In some embodiments, the step of obtaining the width of the molten pool includes:

[0081] A molten pool image captured by a camera is acquired, and a size relationship between the molten pool image and the molten pool is determined.

[0082] In this embodiment, the camera may be an industrial camera, specifically a black and white CCD camera. In some embodiments, the black and white CCD camera is equipped with a filter and an attenuation plate, has a resolution of 672×512, a maximum frame rate of real-time image acquisition of 250Hz, supports GIGE and USB3.0 camera interfaces, and can realize real-time visual acquisition and real-time image processing.

[0083] In this embodiment, Figure 3 As shown, a paraxial black-and-white CCD camera 6 is integrated on the laser cladding head, which can move synchronously with the cladding head, adjust the parameters and shooting angle of the black-and-white CCD camera, ensure that the molten pool is in the best effective field of view of the CCD camera, and the collected molten pool image is clear and less disturbed, and outputs a grayscale image, that is, the molten pool image is a grayscale image. Figure 3 In the process, the black and white CCD camera is installed at a certain angle to the laser cladding head and moves synchronously with the cladding head, so it can directly shoot the molten pool.

[0084] In this embodiment, the process of determining the size relationship between the molten pool image and the molten pool includes: simulating the laser cladding process, physically calibrating the black and white CCD camera, and determining the size relationship between the pixels in the molten pool image and the actual molten pool. Specifically, the Zhang calibration method can be used, that is, using a black and white plane array panel for calibration, collecting different posture pictures of the calibration plate, extracting the pixel coordinates of the corner points in the molten pool picture, calculating the initial values ​​of the internal and external parameters of the camera through the homography matrix, estimating the distortion coefficient using the nonlinear least squares method, and finally optimizing the parameters using the maximum likelihood estimation method. By optimizing the parameters, the camera imaging model can be made closer to the actual situation, thereby more accurately reflecting the size relationship between the molten pool image and the actual molten pool.

[0085] A melt pool edge point set is extracted from the melt pool image, and the size of a circumscribed rectangle formed by the melt pool edge point set is calculated.

[0086] In some embodiments, the steps of extracting a melt pool edge point set from the melt pool image and calculating the size of a circumscribed rectangle formed by the melt pool edge point set include: processing the melt pool image using a threshold segmentation and contour detection algorithm to extract the melt pool edge point set, and then calculating the circumscribed rectangle of the melt pool edge point set to obtain the rectangle coordinates and size.

[0087] In some embodiments, the threshold segmentation uses triangulation to establish an image grayscale value histogram based on the molten pool image. If the maximum peak of the histogram is on the side close to the brightest, the maximum straight-line distance is obtained through the triangle, and the histogram grayscale level corresponding to the maximum straight-line distance is the segmentation threshold. The triangulation method is based on a pure geometric method to find the optimal threshold, which is suitable for extracting bright targets in the background. It can automatically determine the threshold and convert the image into a binary image. Contour detection uses the Suzuki contour detection algorithm to obtain the molten pool contour in the molten pool image, and determines the molten pool contour information based on the characteristics that the pixel value of the edge point is different from the pixel value of its adjacent points. First, a raster scan is performed on the input binary image to find the starting point of boundary tracking, and then boundary tracking is performed to find the complete boundary.

[0088] The calculation of the circumscribed rectangle of the molten pool edge point set and the acquisition of the rectangular coordinates and size can be completed by an algorithm for calculating the circumscribed rectangle. The algorithm for calculating the circumscribed rectangle is developed based on the OpenCV visual algorithm library. After obtaining the minx, maxx, miny and maxy of the point cluster, the circumscribed rectangle is determined and appropriately rotated to adapt to the current laser scanning direction.

[0089] In some embodiments, before the step of extracting a melt pool edge point set from the melt pool image, the method further includes: filtering, enhancing and removing noise from the melt pool image to update the melt pool image.

[0090] In this embodiment, the molten pool image is collected in real time by a camera, and the molten pool image is filtered and enhanced to remove noise, and the processed molten pool image is transmitted to the industrial computer. The presence of image noise seriously interferes with the extraction of molten pool features (i.e., extraction of molten pool edge point sets). In order to improve the signal-to-noise ratio of the molten pool image and accurately extract the molten pool size features, a nonlinear median filter is used here to replace the pixel value of each point in the molten pool image with the median of the grayscale values ​​of the adjacent points of the point. While being able to effectively remove the interference of spatter, powder and smoke, it can also protect the details of the molten pool edge. The enhancement process can improve the contrast between the target and the background, highlight the molten pool area, and ensure the accuracy of the acquired molten pool information.

[0091] A first width of the molten pool is calculated according to the size relationship and the size of the circumscribed rectangle.

[0092] In this embodiment, the first width, length and area information of the molten pool are calculated according to the size of the circumscribed rectangle and in combination with the size relationship between the molten pool image and the molten pool.

[0093] In the embodiments of the present application, the molten pool morphology and temperature characteristic information are collected in real time by means of cameras and thermometers, including molten pool size information, shape characteristics, temperature trends and other characteristics, thereby realizing the extraction of various process characteristics based on multi-sensor information fusion, and more comprehensively characterizing the complex processes of multi-physical field coupling such as mass transfer, heat transfer and convection, thereby improving the comprehensiveness of the molten pool information.

[0094] S400. According to the first center temperature and the first width of the molten pool, a fuzzy control algorithm is used to adjust the first laser power and the first powder feeding rate of the laser, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0095] In this embodiment, a fuzzy control algorithm is used to adjust the first laser power and the first powder feeding rate of the laser. Instead of directly using numerical values, the system is described using linguistic fuzzy variables. It is not necessary to establish a complete mathematical model for the controlled object. Therefore, the complexity of system design can be simplified. It is particularly suitable for the control of nonlinear, time-varying, lagging, and incomplete model systems, and has better robustness, adaptability, and better fault tolerance.

[0096] In some embodiments, the method further comprises:

[0097] The proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool are determined.

[0098] Exemplarily, the fuzzy language set includes five fuzzy languages, which are negative large (NL), negative small (NS), zero (ZO), positive small (PS) and positive large (PL). The membership functions are all continuous membership functions with triangular characteristics.

[0099] In some embodiments, the step of determining the proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool comprises:

[0100] Attribute information is set for the second center temperature of the molten pool, the second width of the molten pool, the second laser power, and the second powder feeding rate. The attribute information includes input quantity and output quantity. The attribute information of the second center temperature of the molten pool and the second width of the molten pool are both input quantities, and the attribute information of the second laser power and the second powder feeding rate are both output quantities.

[0101] In this embodiment, the first center temperature and the first width of the molten pool are used to adjust the first laser power and the first powder feeding rate, so the attribute information of the second center temperature and the second width of the molten pool are set as input quantities, and the attribute information of the second laser power and the second powder feeding rate are set as output quantities.

[0102] Obtain fuzzy control information corresponding to a second center temperature of the molten pool, a second width of the molten pool, a second laser power, and a second powder feeding rate, respectively, wherein the fuzzy control information includes an actual variation range and a preset fuzzy set range.

[0103] In this embodiment, the process of determining the actual range of variation of the second center temperature of the molten pool includes: the first step is to determine the range of variation of the second center temperature of the molten pool. The first step can be obtained by multiple tests according to actual conditions. Exemplarily, the second center temperature of the molten pool is 1500-2000°C. The second step is to determine the center value of the range of variation of the second center temperature of the molten pool. Exemplarily, the center value is (1500+2000)÷2=1750°C. The third step is to subtract the center value from the minimum value of the variation range to obtain the first result, exemplarily 1500-1750, that is, -250°C. The second result is obtained by subtracting the center value from the maximum value of the variation range, exemplarily 2000-1750, that is, 250°C. The fourth step is to use the first result and the second result to determine the actual range of variation of the second center temperature of the molten pool, that is, [-250°C, +250°C]. The process of determining the actual range of variation of the second width of the molten pool, the second laser power, and the second powder feeding rate is the same as the process of determining the actual range of variation of the second center temperature of the molten pool, and will not be repeated.

[0104] The actual range of variation in the fuzzy control information corresponding to the second center temperature of the molten pool can be expressed as [-ΔT, +ΔT]. The actual range of variation in the fuzzy control information corresponding to the second width of the molten pool can be expressed as [-Δd, +Δd]. The actual range of variation in the fuzzy control information corresponding to the second laser power can be expressed as [-ΔP, +ΔP]. The actual range of variation in the fuzzy control information corresponding to the second powder feeding rate can be expressed as [-ΔS, +ΔS]. In an example, if the range of variation in the molten pool width is 2-3mm, the molten pool temperature is 1500-2000℃, the laser power is 2000-3000W, the powder feeding rate is 10-15g / min, and the intermediate values ​​are 2.5mm, 1750℃, 2500W, and 12.5g / min, respectively, then the actual ranges of variation are [-0.5mm, +0.5mm], [-250℃, +250℃], [-500W, +500W], [-2.5g / min,

[0105] +2.5g / min].

[0106] In one example, the preset fuzzy language ranges in the fuzzy control information corresponding to the second center temperature of the molten pool, the second width of the molten pool, the second laser power, and the second powder feeding rate are all [-1, +1].

[0107] According to the fuzzy control information and the attribute information, proportional factors corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool are determined respectively.

[0108] In this embodiment, different attribute information corresponds to different methods of calculating proportional factors. The method of calculating the proportional factor of the input quantity is to divide the maximum value in the preset fuzzy language range by the maximum value in the actual variation range. Exemplarily, the actual variation range in the fuzzy control information corresponding to the second center temperature of the molten pool is [-ΔT, +ΔT]. The actual variation range in the fuzzy control information corresponding to the second width of the molten pool is [-Δd, +Δd]. The preset fuzzy language ranges in the fuzzy control information corresponding to the second center temperature of the molten pool and the second width of the molten pool are both [-1, +1]. Then the proportional factor corresponding to the second center temperature of the molten pool is 1 / ΔT, and the proportional factor corresponding to the second width of the molten pool is 1 / Δd.

[0109] The method for calculating the proportional factor of the output is to divide the maximum value in the actual variation range by the maximum value in the preset fuzzy language range. Exemplarily, the actual variation range in the fuzzy control information corresponding to the second laser power is [-ΔP, +ΔP]. The actual variation range in the fuzzy control information corresponding to the second powder feeding rate is [-ΔS, +ΔS]. The preset fuzzy language ranges in the fuzzy control information corresponding to the second laser power and the second powder feeding rate are both [-1, +1]. Then the proportional factor corresponding to the second laser power is ΔP, and the proportional factor corresponding to the second powder feeding rate is ΔS.

[0110] According to the preset fuzzy language ranges corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool, the fuzzy language sets corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool and the membership function corresponding to each fuzzy language in the fuzzy language sets are determined.

[0111] In one example, the fuzzy language sets corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool include five fuzzy languages, and the five fuzzy languages ​​are respectively represented by negative large (NL), negative small (NS), zero (ZO), positive small (PS) and positive large (PL). Each fuzzy language has a corresponding membership function. The fuzzy language set of the second width of the molten pool also includes five fuzzy languages, and the fuzzy languages ​​in each fuzzy language have a corresponding membership function. Similarly, the second laser power and the second powder feeding rate are the same.

[0112] Figure 4 The following is a schematic diagram showing the membership functions corresponding to five fuzzy languages ​​in a fuzzy language set provided according to some embodiments. Figure 4 In , the horizontal axis is the preset fuzzy language range, and the vertical axis is the probability corresponding to the fuzzy language in the preset fuzzy language range. Figure 4 The figure is a schematic diagram of the membership function corresponding to the five fuzzy languages ​​in the fuzzy language set of the second center temperature of the molten pool. When the preset fuzzy language range is less than or equal to -1, the value of the fuzzy language NL is 100%, and when the preset fuzzy language range is -0.5, the probability of the fuzzy language NL linearly changes to 0. When the preset fuzzy language range is from -1 to -0.5, the probability of the fuzzy language NS value increases linearly from 0 to 1, and when it reaches 0, the probability of the fuzzy language NS decreases to 0. When the preset fuzzy language range is from -0.5 to 0, the probability of the fuzzy language ZO value increases linearly from 0 to 1, and when it reaches 0.5, the probability of the fuzzy language ZO value decreases to 0. When the preset fuzzy language range is from 0 to 0.5, the probability of the fuzzy language PS value increases linearly from 0 to 1, and when it reaches 1, the probability of the fuzzy language PS decreases to 0. When the preset fuzzy language range is from 0.5 to 1, the probability of the fuzzy language PL value increases linearly from 0 to 1, and when it is greater than or equal to 1, the probability of the fuzzy language PL decreases to 0.

[0113] According to all fuzzy languages ​​in the fuzzy language set corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool, a fuzzy relationship is determined, wherein the fuzzy relationship includes a first fuzzy relationship and a second fuzzy relationship, the first fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second laser power, and the second fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second powder feeding rate. In this embodiment, the fuzzy relationship can be set according to actual conditions.

[0114] In one example, the fuzzy language set of the second center temperature of the molten pool includes five fuzzy languages, and the fuzzy language set of the width of the molten pool includes five fuzzy languages. The first fuzzy relationship is shown in Table 1. In Table 1, when the fuzzy language corresponding to the second center temperature of the molten pool and the fuzzy language corresponding to the second width of the molten pool are determined, the fuzzy language corresponding to the second laser power can be determined. In one example, the fuzzy language corresponding to the second center temperature of the molten pool is NL, the fuzzy language corresponding to the second width of the molten pool is NL, and the fuzzy language corresponding to the second laser power is PL. In another example, the fuzzy language corresponding to the second center temperature of the molten pool is ZO, the fuzzy language corresponding to the second width of the molten pool is PS, and the fuzzy language corresponding to the second laser power is NS.

[0115] Table 1 Control rules of molten pool width and molten pool temperature on laser power

[0116]

[0117] In addition, the first fuzzy relationship can also be expressed by a formula. Assuming that the fuzzy languages ​​of the second width of the molten pool, the second center temperature, and the second laser power are A, B, and C, respectively, the first fuzzy relationship can be expressed by the following formula:

[0118]

[0119] Among them, the fuzzy language sets of the second width of the molten pool, the second center temperature, and the second laser power each include five fuzzy languages. The fuzzy language representing the second width of the molten pool, The fuzzy language representing the second center temperature of the molten pool, Representatives in and The fuzzy language corresponding to the second laser power under joint participation, μ R (d, T, P) represents the first fuzzy rule. The maximum values ​​of i and j are 5 because the fuzzy language set of the second center temperature of the molten pool and the fuzzy language set of the second width of the molten pool each include five fuzzy languages.

[0120] The second fuzzy relationship is shown in Table 2. In Table 2, when the fuzzy language corresponding to the second center temperature of the molten pool and the fuzzy language corresponding to the second width of the molten pool are determined, the fuzzy language corresponding to the second powder feeding rate can be determined. In one example, the fuzzy language corresponding to the second center temperature of the molten pool is NL, the fuzzy language corresponding to the second width of the molten pool is NL, and the fuzzy language corresponding to the second laser power is ZO. The second fuzzy relationship can also be expressed by a formula, and the formula corresponding to the second fuzzy relationship can be adaptively modified by the formula corresponding to the first fuzzy relationship.

[0121] Table 2 Control rules of molten pool width and molten pool temperature on powder feeding rate

[0122]

[0123] In some embodiments, Figure 5 A flowchart of another closed-loop control method for laser cladding provided according to some embodiments is exemplified. The step of adjusting the first laser power and the first powder feeding rate of the laser using a fuzzy control algorithm according to the first center temperature and the first width of the molten pool comprises:

[0124] S401, determining the fuzzy language corresponding to the first center temperature and the first width of the molten pool. In this embodiment, the first center temperature and the first width of the molten pool are data measured in real time. After the first center temperature and the first width of the molten pool are obtained in real time, they are converted into fuzzy language.

[0125] In some embodiments, the step of determining the fuzzy language corresponding to the first center temperature of the molten pool includes:

[0126] The difference between the first center temperature of the molten pool and the center value is calculated.

[0127] The difference is multiplied by a proportionality factor corresponding to the second center temperature of the molten pool.

[0128] Exemplarily, the difference is 5, and the proportional factor corresponding to the second center temperature of the molten pool is 0.1, and the result of multiplying the two is 0.5.

[0129] The fuzzy language corresponding to the first center temperature of the molten pool is determined using the result obtained by multiplication.

[0130] For example, the fuzzy language corresponding to the first center temperature of the molten pool is determined based on the multiplication result, i.e., 0.5. Specifically, the membership function corresponding to each fuzzy language in the fuzzy language set corresponding to the second center temperature of the molten pool is again referred to as Figure 4 , it can be seen that when the preset fuzzy language range is 0.5, the corresponding fuzzy language is PS. If the multiplication result is 0.25, then when the preset fuzzy language range is 0.25, the probability of the corresponding fuzzy language ZO and PS is 50% each, and a fuzzy language can be randomly selected at this time. If the multiplication result is 0.1, then when the preset fuzzy language range is 0.1, the probability of the corresponding fuzzy language ZO is 80%, and the probability of PS is 20%, and the fuzzy language can be selected according to the probability.

[0131] The step of determining the fuzzy language corresponding to the first width of the molten pool is similar to the step of determining the fuzzy language corresponding to the first center temperature of the molten pool. The only difference is that the data to be executed is different, so it will not be repeated here.

[0132] The monitored first center temperature and first width of the molten pool are compared with the corresponding preset values ​​(i.e., the corresponding center values), and the obtained temperature error and width error are used as input. The controlled laser power and powder feeding rate are used as output. The adjusted changes of the process parameters are transmitted to the industrial computer in real time to realize closed-loop control of the process parameters of the cladding process and improve the accuracy and quality of laser cladding.

[0133] S402. According to the fuzzy languages ​​corresponding to the first center temperature and the first width of the molten pool, respectively, determine the fuzzy language corresponding to the first laser power of the laser based on the first fuzzy relationship, and determine the fuzzy language corresponding to the first powder feeding rate based on the second fuzzy relationship.

[0134] After determining the fuzzy language corresponding to the first center temperature of the molten pool and the fuzzy language corresponding to the first width of the molten pool, the fuzzy language corresponding to the first laser power of the laser can be determined by table lookup. For example, referring to Table 1, the fuzzy language corresponding to the first center temperature of the molten pool is NS, and the fuzzy language corresponding to the first width of the molten pool is ZO. The fuzzy language corresponding to the first laser power of the laser is determined to be ZO.

[0135] S403 , using the membership function corresponding to the second laser power, screening out a first fuzzy value with the highest probability from the fuzzy language in which the fuzzy language corresponding to the first laser power is located.

[0136] In this embodiment, refer to Figure 3 When the fuzzy language corresponding to the first laser power is ZO, the first fuzzy value with the highest probability (ie, 1) selected from the fuzzy language is 0.

[0137] S404: Using the membership function corresponding to the second powder feeding rate, select a second fuzzy value with the highest probability from the fuzzy language in which the fuzzy language corresponding to the first powder feeding rate is located.

[0138] The execution process of step S404 is the same as that of step S403 and will not be described in detail.

[0139] S405 , determining a control change amount of the first laser power according to the first fuzzy value with the highest probability; and adjusting the current first laser power according to the control change amount of the first laser power.

[0140] In some embodiments, the step of determining the control change amount of the first laser power according to the first fuzzy value with the highest probability includes:

[0141] The first fuzzy value is multiplied by a proportional factor corresponding to the second laser power to obtain a control variation of the first laser power. The current first laser power is adjusted according to the control variation of the first laser power.

[0142] Exemplarily, if the first fuzzy value is 0.5, 0.5 is multiplied by the proportional factor corresponding to the second laser power to obtain the control change amount of the first laser power.

[0143] In some embodiments, the step of adjusting the current first laser power according to the control change amount of the first laser power includes adding the control change amount of the first laser power to the original laser power data.

[0144] S406: Determine a control change amount of the first powder feeding rate according to the second fuzzy value with the highest probability; and adjust the current first powder feeding rate according to the control change amount of the first powder feeding rate.

[0145] In some embodiments, the step of determining the control change amount of the first powder feeding rate according to the second fuzzy value with the highest probability includes:

[0146] The second fuzzy value is multiplied by a proportional factor corresponding to the second powder feeding rate to obtain a controlled change amount of the first powder feeding rate.

[0147] The execution process of step S406 is the same as that of step S405, which will not be described again.

[0148] In this embodiment, the first center temperature and the first width of the molten pool are first fuzzified, and the fuzzy language corresponding to the first laser power and the fuzzy language corresponding to the first powder feeding rate are determined using the first fuzzy relationship and the second fuzzy relationship, respectively. Then, the first fuzzy value is determined using the membership function corresponding to the predetermined second laser power. The second fuzzy value is determined using the membership function corresponding to the predetermined second powder feeding rate. Subsequently, the first fuzzy value and the second fuzzy value are both defuzzified to obtain the control change of the first laser power and the control change of the first powder feeding rate, respectively. Finally, the current first laser power and the current first powder feeding rate are adjusted to close the loop and control the laser cladding process to improve accuracy and quality.

[0149] In some embodiments, after the step of adjusting the first laser power and the first powder feeding rate of the laser by using a fuzzy control algorithm according to the first center temperature and the first width of the molten pool, the method further includes:

[0150] Repeat the steps of obtaining the first center temperature and the first width of the molten pool and adjusting the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm until it is detected that the powder spraying equipment and the laser are turned off.

[0151] The method in the embodiment of the present application is a closed-loop control, which uses the first center temperature of the molten pool and the first width of the molten pool obtained in real time to adjust the powder spraying equipment and the laser to achieve closed-loop control of laser cladding, thereby improving the accuracy and quality of the cladding process.

[0152] In the embodiment of the present application, monitoring the center temperature and width of the molten pool can detect the characteristics of the dynamic process of molten pool melting, melting and solidification, identify defects and other factors affecting the cladding quality, and clarify the mechanism of the influence of the molten pool characteristics on the forming quality. While providing a reliable monitoring object for online monitoring of laser cladding, it also helps to quickly design process parameters and propose optimization methods, and perform closed-loop control of process parameters, thereby improving the accuracy and quality of laser cladding.

[0153] By means of the above technical scheme, the present application provides a closed-loop control method, device, system and storage medium for laser cladding, in which the first center temperature and the first width of the molten pool are monitored, and the first laser power and the first powder feeding rate of the laser are adjusted based on the monitoring results by a fuzzy control algorithm, thereby improving the accuracy and quality of laser cladding. The method includes: controlling the powder spraying equipment to spray the cladding material on the substrate; controlling the laser to emit laser light onto the cladding material so that the cladding material and the substrate in contact with the cladding material form a molten pool; obtaining the first center temperature and the first width of the molten pool; according to the first center temperature and the first width of the molten pool, using a fuzzy control algorithm, adjusting the first laser power and the first powder feeding rate of the laser, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material. .

[0154] It should be noted that the description of the structure in the system involved in the closed-loop control method of laser cladding provided in an embodiment of the present application can refer to the corresponding description of the system above, and will not be repeated here.

[0155] Furthermore, the embodiment of the present application provides a closed-loop control device for laser cladding. Figure 6 A schematic structural diagram of a closed-loop control device for laser cladding provided according to some embodiments is exemplarily shown; the device comprises: a first control unit 601 , a second control unit 602 , an acquisition unit 603 and an adjustment unit 604 .

[0156] A first control unit is used to control the powder spraying device to spray the cladding material on the substrate;

[0157] A second control unit is used to control the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool;

[0158] an acquisition unit, configured to acquire a first central temperature and a first width of the molten pool;

[0159] The adjustment unit is used to adjust the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0160] It should be noted that for other corresponding descriptions of the functional units involved in a closed-loop control device for laser cladding provided in an embodiment of the present application, reference can be made to the corresponding descriptions of the system above, which will not be repeated here.

[0161] The embodiment of the present application also provides a closed-loop control system for laser cladding, including a powder spraying device, a laser, a temperature meter, a camera and an industrial computer;

[0162] The industrial computer is used to control the powder spraying equipment to spray the cladding material on the substrate;

[0163] Controlling the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool;

[0164] Acquire a first central temperature of the molten pool measured by a thermometer and a first width of the molten pool determined by a camera;

[0165] According to the first center temperature and the first width of the molten pool, the first laser power and the first powder feeding rate of the laser are adjusted using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

[0166] The present application also provides a computer device, which may be a personal computer, a server, a network device, etc. Figure 7 As shown, the computer device includes a bus, a processor, a memory and a communication interface, and may also include an input and output interface and a display device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store location information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in each method embodiment are implemented.

[0167] Those skilled in the art will understand that Figure 7The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0168] In one embodiment, a computer-readable storage medium is provided. The computer-readable storage medium may be non-volatile or volatile, and stores a computer program thereon. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0169] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0170] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0171] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0172] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0173] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A closed-loop control method for laser cladding, characterized in that: include: Control the powder spraying equipment to spray the cladding material on the substrate; Controlling the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool; Acquire a first center temperature and a first width of the molten pool; According to the first center temperature and the first width of the molten pool, the first laser power and the first powder feeding rate of the laser are adjusted using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

2. The method according to claim 1, characterized in that Also includes: Determine the proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool; According to all fuzzy languages ​​in the fuzzy language set corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool, a fuzzy relationship is determined, wherein the fuzzy relationship includes a first fuzzy relationship and a second fuzzy relationship, the first fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second laser power, and the second fuzzy relationship being the relationship between the fuzzy language corresponding to the second center temperature of the molten pool, the fuzzy language corresponding to the second width of the molten pool and the fuzzy language corresponding to the second powder feeding rate.

3. The method according to claim 2, characterized in that The step of determining the proportional factors, fuzzy language sets and the membership function corresponding to each fuzzy language in the fuzzy language sets respectively corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool comprises: Setting attribute information for a second center temperature of the molten pool, a second width of the molten pool, a second laser power, and a second powder feeding rate, wherein the attribute information includes an input quantity and an output quantity, the attribute information of the second center temperature of the molten pool and the second width of the molten pool are both input quantities, and the attribute information of the second laser power and the second powder feeding rate are both output quantities; Obtaining fuzzy control information corresponding to a second center temperature of the molten pool, a second width of the molten pool, a second laser power, and a second powder feeding rate, respectively, wherein the fuzzy control information includes an actual variation range and a preset fuzzy set range; Determine proportional factors corresponding to the second center temperature, the second width, the second laser power and the second powder feeding rate of the molten pool, respectively, according to the fuzzy control information and the attribute information; According to the preset fuzzy set ranges corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool, the membership function corresponding to each fuzzy language in the fuzzy language set corresponding to the second center temperature, second width, second laser power and second powder feeding rate of the molten pool is determined.

4. The method according to claim 3, characterized in that The process of determining the actual variation range of the second center temperature of the molten pool includes: Determine the variation range of the second center temperature of the molten pool; Determine a central value of a variation range of a second central temperature of the molten pool; Subtracting the center value from the minimum value of the variation range to obtain a first result, and subtracting the center value from the maximum value of the variation range to obtain a second result; The actual variation range of the second center temperature of the molten pool is determined by using the first result and the second result.

5. The method according to claim 4, characterized in that The step of adjusting the first laser power and the first powder feeding rate of the laser by using a fuzzy control algorithm according to the first center temperature and the first width of the molten pool comprises: Determine the fuzzy languages ​​corresponding to the first center temperature and the first width of the molten pool respectively; According to the fuzzy languages ​​corresponding to the first center temperature and the first width of the molten pool, respectively, the fuzzy language corresponding to the first laser power of the laser is determined based on the first fuzzy relationship, and the fuzzy language corresponding to the first powder feeding rate is determined based on the second fuzzy relationship; Using the membership function corresponding to the second laser power, screening out a first fuzzy value with the highest probability in the fuzzy language corresponding to the first laser power; Using the membership function corresponding to the second powder feeding rate, a second fuzzy value with the highest probability is screened out from the fuzzy language corresponding to the first powder feeding rate; Determining a control change amount of the first laser power according to the first fuzzy value with the highest probability; and adjusting the current first laser power according to the control change amount of the first laser power; determining a control change amount of the first powder feeding rate according to the second fuzzy value with the highest probability; and adjusting the current first powder feeding rate according to the control change amount of the first powder feeding rate; Wherein, the step of determining the control change amount of the first laser power according to the first fuzzy value with the highest probability comprises: The first fuzzy value is multiplied by a proportional factor corresponding to the second laser power to obtain a control change amount of the first laser power.

6. The method according to claim 5, characterized in that The step of determining the fuzzy language corresponding to the first center temperature of the molten pool comprises: Calculating a difference between a first center temperature of the molten pool and the center value; multiplying the difference by a proportionality factor corresponding to the second center temperature of the molten pool; The fuzzy language corresponding to the first center temperature of the molten pool is determined using the result obtained by multiplication.

7. The method according to claim 1, characterized in that After the step of adjusting the first laser power and the first powder feeding rate of the laser by using a fuzzy control algorithm according to the first central temperature and the first width of the molten pool, the method further includes: Repeat the steps of obtaining the first center temperature and the first width of the molten pool and adjusting the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm until it is detected that the powder spraying equipment and the laser are turned off.

8. A closed-loop control device for laser cladding, characterized in that: include: A first control unit is used to control the powder spraying device to spray the cladding material on the substrate; A second control unit is used to control the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool; an acquisition unit, configured to acquire a first central temperature and a first width of the molten pool; The adjustment unit is used to adjust the first laser power and the first powder feeding rate of the laser according to the first center temperature and the first width of the molten pool by using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

9. A closed-loop control system for laser cladding, characterized in that: Including powder spraying equipment, lasers, thermometers, cameras and industrial computers; The industrial computer is used to control the powder spraying equipment to spray the cladding material on the substrate; Controlling the laser to emit laser light onto the cladding material so that the cladding material and a substrate in contact with the cladding material form a molten pool; Acquire a first central temperature of the molten pool measured by a thermometer and a first width of the molten pool determined by a camera; According to the first center temperature and the first width of the molten pool, the first laser power and the first powder feeding rate of the laser are adjusted using a fuzzy control algorithm, wherein the first powder feeding rate is the rate at which the powder spraying equipment sprays the cladding material.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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