Method, system and apparatus for anomaly monitoring of additive manufacturing beams

Abstract

The application relates to an abnormality monitoring method, system and device for additive manufacturing beams. The method synchronously collects trigger parameters sent to at least one beam generator during the execution of a scanning task, beam control parameters after the beam generator receives the trigger signal, and actual emission parameters obtained based on operation signals, and obtains corresponding beam monitoring parameters by using a paraxial monitoring system; the trigger parameters, the control parameters and the actual emission parameters are compared, if any parameter deviates from a preset tolerance threshold, it is determined that there is a beam emission abnormality; further, abnormal beam parameters are constructed according to the abnormal trigger, control and actual emission parameters, and are spatially registered with the beam monitoring parameters, and finally, a feedback result containing abnormal point position information is generated. The application can realize the alignment identification between the actual emission of the beam and the trigger control, and further realize the accurate identification and positioning of the abnormal beam.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of additive manufacturing, and more particularly to an abnormality monitoring method, system and device for additive manufacturing beams. BACKGROUND

[0002] Additive manufacturing technology is a manufacturing process that realizes rapid shaping of complex three-dimensional components based on layer-by-layer accumulation of materials, and has advantages such as high design freedom, high material utilization rate, and integrated shaping of components, and has been widely applied in manufacturing fields such as aerospace, medical devices, and automobile industry. With the in-depth application of high-energy laser beams, electron beams and other beam energy sources in additive manufacturing equipment, high precision and high dynamic response control have become key factors to ensure stable molten pool, continuous organization and uniform performance of components.

[0003] In the beam-driven additive manufacturing process, control instructions are usually generated according to preset scanning paths and process parameters, trigger signals are sent to the beam generator through intermediate devices such as control cards to drive it to emit energy at the set power and waveband at the precise time point, and the instantaneous melting and accumulation of materials are realized. However, in the actual manufacturing process, affected by multiple factors such as control system, hardware response, energy transmission efficiency or environmental disturbance, the beam generator may exhibit abnormal behaviors such as response delay, emission intensity deviation, waveband drift, non-response or false triggering. Such abnormalities directly affect the energy coupling relationship between the beam and the material, easily leading to molten pool fluctuations, accumulation defects, metallurgical discontinuity, and even causing structural deformation or functional failure, which seriously affects the manufacturing quality of three-dimensional components.

[0004] At present, existing beam abnormality monitoring methods mostly rely on indirect visual signals such as molten pool images, splash characteristics, and temperature field changes for post-analysis, which can reflect manufacturing abnormalities to some extent, but lack real-time diagnostic monitoring means for the key issue of whether the beam is accurately emitted, making it difficult to meet the real-time control needs of high-precision manufacturing processes. SUMMARY

[0005] The present application provides an abnormality monitoring method, system and device for additive manufacturing beams, which can comprehensively monitor the whole process from beam trigger signal sending, control signal execution to beam actual output, thereby realizing multi-parameter comparison and abnormality diagnosis of the whole beam emission process, and accurately identifying beam abnormalities and realizing spatial positioning of abnormal points in combination with image monitoring.

[0006] In a first aspect, the application provides an abnormality monitoring method for additive manufacturing beams, comprising: collecting trigger parameters of trigger signals sent to at least one beam generator for performing a scanning task, collecting beam control parameters of the trigger signals received by the at least one beam generator, collecting actual beam emission parameters according to operation signals of the at least one beam generator, and collecting beam monitoring parameters of the beams performing the scanning task by using a side-axis monitoring device; comparing the trigger parameters, the beam control parameters and the actual beam emission parameters, and determining parameters deviating from a preset tolerance threshold as beam emission abnormalities according to a comparison result; constructing abnormal beam parameters according to the trigger parameters, the beam control parameters and the actual beam emission parameters determined as the emission abnormalities, and registering the abnormal beam parameters with the beam monitoring parameters to generate and feedback corresponding abnormal point positions.

[0007] In an optional solution of the first aspect, when determining the beam emission abnormalities, the method comprises: extracting trigger time stamps of the trigger signals, beam control time stamps of the beam control parameters and actual emission time stamps of the actual emission parameters respectively; constructing time difference parameters of the beam emission process according to the trigger time stamps, the beam control time stamps and the actual emission time stamps; comparing the time difference parameters with a time tolerance threshold, and determining time difference parameters exceeding the time tolerance threshold as the beam emission abnormalities according to a comparison result.

[0008] In an optional solution of the first aspect, when constructing the time difference parameters of the beam emission process, the method comprises: constructing a trigger-to-control delay time difference, a control-to-actual emission delay time difference, an actual emission-to-energy action area activation delay time difference and a total response delay time difference in the beam emission process.

[0009] In an optional solution of the first aspect, when determining the beam emission abnormalities, the method further comprises: comparing the trigger-to-control delay time difference, the control-to-actual emission delay time difference and the total response delay time difference with the time tolerance threshold in sequence, and determining the beam emission abnormalities when any time difference exceeds the time tolerance threshold.

[0010] In an optional solution of the first aspect, when determining the beam emission abnormalities, the method further comprises: extracting beam trigger data of the trigger signals, beam control data of the beam control parameters and beam actual emission data of the actual emission parameters respectively; constructing beam characteristic difference parameters of the beam emission process according to the beam trigger data, the beam control data and the beam actual emission data; comparing the beam characteristic difference parameters with a characteristic tolerance threshold, and determining beam characteristic difference parameters deviating from the characteristic tolerance threshold as the emission abnormalities according to a comparison result.

[0011] In an optional implementation of the first aspect, in the extracting of the beam control data and the beam actual emission data, the method comprises: extracting the beam trigger intensity and / or wavelength of the trigger signal, the beam control intensity and / or wavelength of the beam control parameter, and the beam actual emission intensity and / or wavelength of the actual emission parameter, respectively; and constructing the trigger-to-control intensity and / or wavelength difference, the control-to-actual emission intensity and / or wavelength difference, and the trigger-to-actual emission intensity and / or wavelength difference during the beam emission process.

[0012] In an optional implementation of the first aspect, in the generating and feeding back of the corresponding abnormal point position, the method comprises: associating the abnormal beam parameter with the corresponding scanning path of the scanning task and matching the spatial coordinates of the actual target component according to the scanning path index; generating the abnormal point position by using the image frame pairing of the beam monitoring parameter and the period when the beam emission abnormality occurs and combining the spatial coordinates of the actual target component; and transmitting the beam abnormality information comprising at least the timestamp, the abnormal control parameter, the error amplitude, and the abnormal point position to the target terminal.

[0013] In an optional implementation of the first aspect, in the generating of the abnormal point position, the method comprises: intercepting the abnormal timestamp when the abnormal beam occurs and obtaining the scanning path segment number corresponding to the abnormality in the scanning task according to the abnormal timestamp; obtaining the spatial coordinates of the scanning path segment in the three-dimensional model of the target component according to the path index information and the geometry mapping in the three-dimensional model of the target component, and performing Z-axis interpolation or calibration on the spatial coordinates in combination with the construction layer thickness and layer sequence number of the scanning path segment; according to the abnormal timestamp, finding the matching frame in the image data of the beam monitoring parameter and extracting the intersection region of the scanning path segment in the matching frame image, so as to convert the intersection region into a physical coordinate system through image calibration; and registering the spatial coordinates of the intersection region semantics to generate the abnormal point position.

[0014] In an optional implementation of the first aspect, in the determining of the beam emission abnormality, the method further comprises: synchronously collecting the trigger parameter, the beam control parameter, and the beam actual emission parameter of a plurality of beams under the scanning task, constructing the time difference parameter and / or the beam characteristic difference parameter of each beam independently, and sequentially aligning the time difference parameter and / or the beam characteristic difference parameter on the time axis; comparing the time difference parameter and / or the beam characteristic difference parameter with the tolerance threshold, and according to the comparison result, determining the time difference parameter and / or the beam characteristic difference parameter deviating from the tolerance threshold as the beam emission abnormality; when at least two beams produce the beam emission abnormality in the preset time interval and / or in the same scanning path, marking the beam emission abnormality as a regional beam abnormality, so as to trigger the preset control strategy according to the regional beam abnormality.

[0015] In an optional solution of the first aspect, when determining the abnormality of the beam emission, the method further comprises: synchronously collecting the trigger parameters, the beam control parameters and the actual emission parameters of the beams in any scanning path, and constructing time difference parameters and / or beam characteristic difference parameters of each beam; sequentially aligning the time difference parameters and / or the beam characteristic difference parameters on a time axis, and constructing a corresponding beam parameter matrix; when any diagonal element in the beam parameter matrix deviates from a cooperative tolerance threshold, determining that the synchronization beam emission is abnormal, and triggering a preset control strategy according to the abnormality of the synchronization beam emission.

[0016] In an optional solution of the first aspect, in the multi-beam comparison and abnormality determination process, the method comprises: setting a corresponding characteristic tolerance threshold for different beam types, and comparing the time difference parameters and / or the beam characteristic difference parameters of each beam with the characteristic tolerance threshold matched with the beam type.

[0017] In the second aspect, the application provides an abnormality monitoring method for additive manufacturing beams. Before parameter collection, the method comprises: irradiating at least one visible light to a plurality of calibration points in at least one region of a calibration substrate, and collecting visible light irradiation signals of the calibration points; registering the visible light reflection signals of the calibration points with the calibration substrate, and constructing a visible light calibration matrix; applying the visible light calibration matrix to the spatial mapping and deviation correction of the beam monitoring parameters collected in the subsequent beam monitoring process and the positions of abnormal points, and completing data calibration.

[0018] In an optional solution of the second aspect, when irradiating a plurality of calibration points in at least one region of the calibration substrate with a plurality of beams of visible light, the method comprises: simultaneously or alternately irradiating a plurality of beams of visible light with the same parameters and different positions and / or angles to a plurality of calibration points in at least one region of the calibration substrate, and periodically turning on and off the irradiation of the plurality of beams of visible light according to a preset switching frequency, to form an irradiation frame sequence with time segmentation control; using the boundary difference between a plurality of shadow regions and bright areas formed during the irradiation of the plurality of beams of visible light, constructing a mapping matrix between the plurality of beams of visible light and image coordinates, and using the mapping matrix to assist data calibration in the subsequent beam monitoring process.

[0019] In the third aspect, the application provides an abnormality monitoring method for additive manufacturing beams. Before parameter collection, the method further comprises: providing heating for a plurality of calibration points in at least one region of a calibration substrate, and collecting infrared light signals formed by the calibration points; registering the infrared light signals of the calibration points with the calibration substrate, and constructing an infrared light calibration matrix; applying the infrared light calibration matrix to the spatial mapping and deviation correction of the beam monitoring parameters collected in the subsequent beam monitoring process and the positions of abnormal points, and completing data calibration.

[0020] In a fourth aspect, the present application provides an abnormality monitoring system for additive manufacturing beams, comprising: a beam generator for generating and emitting beams; a galvanometer control unit connected with the galvanometer and the beam generator respectively, for triggering and adjusting the beam parameters generated and emitted by the beam generator; a coaxial monitoring unit for collecting signal parameters during the execution of a scanning task by the galvanometer; an off-axis monitoring unit for collecting timestamp parameters, image data, spectral data and thermal imaging data of the beams acting on the surface of the target component during the execution of at least one scanning task; and a control device connected with and controlling the beam generator, the galvanometer control unit, the coaxial monitoring unit and the off-axis monitoring unit to execute the method of any one of the first aspect.

[0021] In a fifth aspect, the present application provides an abnormality monitoring system for additive manufacturing beams, comprising: a beam generator for generating and emitting beams; a galvanometer control unit connected with the galvanometer and the beam generator respectively, for triggering and adjusting the beam parameters generated and emitted by the beam generator; a coaxial monitoring unit for collecting signal parameters during the execution of a scanning task by the galvanometer; an off-axis monitoring unit for collecting timestamp parameters, image data, spectral data and thermal imaging data of the beams acting on the surface of the target component during the execution of at least one scanning task; at least one calibration substrate provided in the forming area and provided with a plurality of calibration points with unique spatial encoding, for providing data calibration; a light source provided in the forming chamber for generating visible light of a predetermined waveband; and a control device connected with and controlling the beam generator, the galvanometer control unit, the coaxial monitoring unit, the off-axis monitoring unit and the light source to execute the method of any one of the second aspect.

[0022] In a sixth aspect, the present application provides an abnormality monitoring system for additive manufacturing beams, comprising: a beam generator for generating and emitting beams; a galvanometer control unit connected with the galvanometer and the beam generator respectively, for triggering and adjusting the beam parameters generated and emitted by the beam generator; a coaxial monitoring unit for collecting signal parameters during the execution of a scanning task by the galvanometer; an off-axis monitoring unit for collecting timestamp parameters, image data, spectral data and thermal imaging data of the beams acting on the surface of the target component during the execution of at least one scanning task; at least one calibration substrate provided in the forming area and provided with a plurality of calibration points with unique spatial encoding, for providing data calibration; a heating unit provided at the calibration points of the calibration substrate for providing independent heating for the calibration points; and a control device connected with and controlling the beam generator, the galvanometer control unit, the coaxial monitoring unit, the off-axis monitoring unit and the at least one heating unit to execute the method of the third aspect.

[0023] In a seventh aspect, the present application provides an additive manufacturing device comprising the anomaly monitoring system of any one of the second aspect to the fourth aspect.

[0024] In an eighth aspect, the present application provides an electronic device comprising: at least one processor; at least one memory; the at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions, when executed by the at least one processor, causing the electronic device to perform the method according to any one of the first aspect, the second aspect and the third aspect.

[0025] In a ninth aspect, the present application provides a computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program, the computer program, when executed by a processor, implements the method according to any one of the first aspect, the second aspect and the third aspect.

[0026] It should be understood that the general description above and the following detailed description are only exemplary and are not limiting on the present application. BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate one or more embodiments of the present application and, together with the description, explain the principles of the present application and serve to make and use the present application.

[0028] Figure 1 is a structural connection diagram of an exemplary anomaly monitoring system according to some embodiments of the present application.

[0029] Figure 2 is a flow diagram of an exemplary anomaly monitoring method according to some embodiments of the present application.

[0030] Figure 3 is a timing diagram of an exemplary anomaly monitoring method according to some embodiments of the present application.

[0031] Figure 4 is a flow diagram of an exemplary anomaly point location generation method according to some embodiments of the present application.

[0032] Figure 5 is a flow diagram of an exemplary time difference delay determination method according to some embodiments of the present application.

[0033] Figure 6 is a flow diagram of an exemplary characteristic difference deviation determination method according to some embodiments of the present application.

[0034] Figure 7is a flowchart of an exemplary multi-beam parameter deviation determination method according to some embodiments of the present application.

[0035] Figure 8 is a flowchart of an exemplary multi-beam parameter deviation determination method according to some embodiments of the present application.

[0036] Figure 9 is a flowchart of an exemplary beam type threshold assignment method according to some embodiments of the present application.

[0037] Figure 10 is a structural diagram of an exemplary calibration substrate, light source and off-axis monitoring unit according to some embodiments of the present application.

[0038] Figure 11 is a flowchart of an exemplary light source irradiation data calibration method according to some embodiments of the present application.

[0039] Figure 12 is a structural diagram of an exemplary calibration substrate, multi-light source and off-axis monitoring according to some embodiments of the present application.

[0040] Figure 13 is a flowchart of an exemplary multi-light source periodic on-off data calibration method according to some embodiments of the present application.

[0041] Figure 14 is a structural diagram of an exemplary calibration substrate, heating unit and off-axis monitoring according to some embodiments of the present application.

[0042] Figure 15 is a flowchart of an exemplary calibration point heating data calibration method according to some embodiments of the present application.

[0043] Figure 16 is a connection diagram of an exemplary electronic device according to some embodiments of the present application. DETAILED DESCRIPTION

[0044] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0045] In the additive manufacturing technology system, laser beams and electron beams, as high-energy-density beam forms, are widely used in the melting and deposition of materials, representing the mainstream technology path of high-performance additive manufacturing. These energy beams concentrate energy in a very small area to achieve rapid melting and cooling solidification of materials, thereby constructing complex three-dimensional components layer by layer. Among them, additive manufacturing materials include, but are not limited to, metal powder materials and non-metal powder materials. In this application, metal powder materials are used as an example.

[0046] Laser beam additive manufacturing typically includes selective laser melting (SLM), laser powder bed fusion (LPBF), and laser direct energy deposition (L-DED). In SLM and LPBF, a laser beam irradiates a pre-laid material substrate point-by-point or line-by-line along a scanning path, locally melting the material, which then rapidly solidifies to form a solid structure. These layers are stacked to create a three-dimensional component. In L-DED, the laser beam melts and deposits the material in real time and bonds it to the substrate through synchronous material feeding, offering high deposition efficiency and controllability.

[0047] Electron beam additive manufacturing is mainly represented by electron beam melting (EBM). This additive manufacturing process uses a high-speed electron beam to bombard materials in a high vacuum environment, causing them to melt and be deposited layer by layer to form parts. Unlike lasers, electron beams have higher energy density and stronger penetration capabilities, making them suitable for processing high-melting-point alloys (such as titanium-based, nickel-based, tantalum, etc.). They also have fast forming speeds and lower internal residual stress.

[0048] Currently, existing beam anomaly monitoring systems suffer from poor real-time performance, delayed anomaly detection, and inaccurate spatial positioning. They lack real-time diagnostic methods for the crucial issue of whether the beam is outputting the correct power at the correct time and location.

[0049] Therefore, for reference Figure 1 As shown, Figure 1 This illustration shows a structural connection diagram of an exemplary anomaly monitoring system according to some embodiments of this application. To address the aforementioned technical problems of beams, this application relates to an anomaly monitoring system 1 for additive manufacturing beams, comprising:

[0050] The beam generator 100 is used to generate and emit an energy beam with a set intensity, wavelength and duration based on the received trigger signal. In this application, the energy beam is described as a laser beam, but in actual applications, the energy beam can also be an electron beam, plasma beam or other energy beams. The beam generator 100 outputs an operation feedback signal containing the actual emission power, voltage, current, wavelength and emission timestamp while emitting.

[0051] The galvanometer control unit 101 is connected to the beam generator 100 on one hand, sending trigger signals and beam control parameters (including power, voltage, current, band, switching time and other set values) to it. On the other hand, it is connected to the galvanometer 105 for synchronous control of the scanning path, deflection angle and scanning speed. The galvanometer control unit 101 has timing accuracy control function and can output trigger timestamp and control parameter timestamp.

[0052] The coaxial monitoring unit 102 is connected to the galvanometer control unit 101 and is set in the coaxial path of the beam. It is used to collect feedback information on triggering, beam control and actual beam emission.

[0053] The off-axis monitoring unit 103 is located in the forming chamber of the additive manufacturing equipment. It includes, but is not limited to, an industrial camera, a multispectral imaging device, and a thermal imaging device. It is used to collect image data, spectral data, thermal imaging data, and response timestamps of the beam acting on the surface of the target component 401 during the scanning task. The industrial camera is used to collect image data during the beam action process, the multispectral imaging device is used to collect spectral data during the beam action process, and the thermal imaging device is used to collect thermal imaging data during the beam action process.

[0054] The control device 104 connects to and controls the beam generator 100, the galvanometer control unit 101, the coaxial monitoring unit 102, and the off-axis monitoring unit 103 to perform abnormal beam monitoring operations.

[0055] Specifically, during the beam emission process, the galvanometer control unit 101 first sends a trigger signal containing trigger parameters to the beam generator 100. After receiving the trigger signal, the beam generator 100 generates beam control parameters according to the trigger signal and simultaneously emits a beam towards the target point in the forming area. At the same time as the beam is emitted, an operating signal containing the actual beam emission parameters is fed back. Then, the off-axis monitoring unit 103 set at the off-axis position of the beam path records the response image or spot characteristics of the beam acting on the surface of the target component 401.

[0056] Therefore, for reference Figure 2 and Figure 3 As shown, Figure 2 The diagram illustrates a flowchart of an exemplary anomaly monitoring method according to some embodiments of this application.Figure 3 A timing diagram of an exemplary abnormality monitoring method of some embodiments of the present application is shown. The present application also relates to an abnormality monitoring method 2 for a beam for additive manufacturing using the above-mentioned abnormality monitoring system 1, the method comprising the following steps:

[0057] 201: Collecting trigger parameters of a trigger signal sent to at least one beam generator 100 for performing a scanning task, collecting beam control parameters received by the at least one beam generator 100 after receiving the trigger signal, and collecting actual beam emission parameters according to operation signals of the at least one beam generator 100, while simultaneously collecting beam monitoring parameters of the scanning task performed by the side-axis monitoring unit.

[0058] Specifically, in step 201, the trigger signal is a TTL trigger signal from the galvanometer control unit 101, which usually includes the set values of the power, voltage, current, wavelength, switching time, etc. of the beam and the corresponding trigger time stamp. After the beam generator 100 receives the trigger signal, it generates corresponding control parameters according to the power set value, wavelength, switching time, etc. of the beam and corresponding beam control time stamps. The operation signal is the internal sampling power feedback signal of the beam generator 100, which usually contains the actual emission power, voltage, current, wavelength, and corresponding actual emission time stamp of the beam. At the same time, through the side-axis monitoring unit 103 arranged in the forming chamber of the additive manufacturing device, the monitoring images, spectral responses, and thermal imaging data of the beam acting on the surface of the target component 401 are collected and the monitoring time stamps are recorded simultaneously, i.e. the side-axis monitoring unit 103 can not only synchronously monitor the monitoring images, spectral responses, and thermal imaging data between the trigger signal and the operation signal, but also synchronously record the monitoring time stamp information between the trigger signal and the operation signal, so as to facilitate the registration of the corresponding abnormal point position when an abnormal beam is generated in the subsequent steps.

[0059] 202: Comparing the trigger parameters, beam control parameters, and actual beam emission parameters, and according to the comparison results, determining the parameters deviating from the preset tolerance threshold as beam emission abnormalities.

[0060] Specifically, in step 202, the comparison of beam emission abnormalities includes but is not limited to emission time difference comparison, beam intensity difference comparison, and beam wavelength difference comparison, so as to determine the beam with abnormal behavior according to at least one of the above comparison methods.

[0061] The preset tolerance threshold includes but is not limited to time tolerance threshold, intensity tolerance threshold, and wavelength tolerance threshold, which is the maximum tolerance range of each time difference, intensity difference, and wavelength difference preset by the debugging personnel according to the factory static tolerance, process debugging experience value based on different materials or scanning paths, etc.

[0062] 203: constructing abnormal beam parameters according to the trigger parameters, beam control parameters and actual beam emission parameters determined as abnormal, and registering the abnormal beam parameters with the beam monitoring parameters, to generate and feedback corresponding abnormal point positions.

[0063] Specifically, in step 203, for the emission event determined as abnormal, the corresponding trigger parameters, control parameters and actual emission parameters are extracted and abnormal beam parameter sets are constructed, and then the abnormal beam parameters are registered with at least one of the image data, spectral data and thermal imaging data collected by the off-axis monitoring unit 103. The registration process includes: matching the off-axis monitoring data according to the abnormal corresponding monitoring time stamp, extracting the beam state at the corresponding time, then querying the geometric mapping of the three-dimensional model of the target member 401 according to the scan path index, obtaining the spatial coordinates corresponding to the abnormal scan point of the scan path, and converting the abnormal point during beam scanning into physical space coordinates consistent with the coordinate system of the actual target member 401 using the calibration parameters, and finally determining the abnormal point position. By adopting the above technical solution, the synchronous acquisition and comparison of the whole process data of the beam emission can be realized, the parameter deviation of the beam power, waveband, response timing and the like caused during the emission process can be accurately identified, and through the abnormal point registration, the spatial position corresponding to the abnormal beam can be located, so as to enhance the real-time perception of the additive manufacturing beam.

[0064] In some embodiments of the present application, the method of the present application can be integrated into an artificial intelligence system, and the intelligent data acquisition, parameter comparison, abnormal registration and abnormal identification of related processes and objects can be realized by the artificial intelligence system, so as to improve the overall application efficiency.

[0065] Reference Figure 4 As shown, Figure 4 A flowchart of an exemplary abnormal point position generation method of some embodiments of the present application is shown. In some embodiments of the present application, when generating and feeding back the corresponding abnormal point position, the method (specifically step 203) includes the following steps 2031-2033.

[0066] 2031: associating the abnormal beam parameters to the corresponding scan path of the scan task and matching the spatial coordinates of the actual target member 401 according to the scan path index.

[0067] Specifically, in step 2031, the abnormal beam parameter corresponding to the beam emission abnormality is determined to be bound to the scan path segment corresponding to the scan task, which is provided by the scan task file in the additive manufacturing equipment, and usually includes path number, path point sequence, path layer number and layer thickness, etc. information; further, in order to realize abnormal positioning, according to the time stamp corresponding to the determination of the beam emission abnormality, the scan path number corresponding to the time when the beam emission abnormality is determined is matched by combining the execution time index of the scan path segment in the scan task, and then the geometric entity information corresponding to the above-mentioned scan path number is extracted from the target component 401 three-dimensional CAD model associated with the scan task. According to the index information of the scan path segment, the projection trajectory thereof in the target component 401 three-dimensional CAD model is queried, and Z-axis interpolation or calibration is performed in combination with layer thickness information and layer sequence number, so as to obtain the complete spatial coordinates (X, Y, Z) of the path in the three-dimensional physical space.

[0068] 2032: Image frame pairing is performed using the beam monitoring parameter and the period when the beam emission abnormality occurs, and the abnormal point position is generated in combination with the spatial coordinates of the actual target component 401.

[0069] Specifically, in step 2032, while determining the beam emission abnormality, the corresponding image frame sequence is synchronously extracted from the image data of the beam monitoring parameter according to the time stamp corresponding to the determination of the beam emission abnormality, and the image data is usually equipped with calibrated internal and external parameter matrices. Then, by accurately pairing the abnormal time stamp and the image frame time axis, the image frame closest to the abnormal event is extracted, and the area intersected with the above-mentioned scan path segment is searched in the image frame. Further, based on the calibration parameters (such as camera internal parameters, distortion coefficients, pose matrix) between the image and the forming platform, the pixel coordinates of the image intersection area are back-projected to the physical coordinate system, realizing the coordinate mapping from the image domain to the three-dimensional space of the target component 401. Then, the generated path spatial coordinates are registered with the physical coordinates after projection transformation, and the least square method or the iterative closest point (ICP) algorithm is used for coordinate alignment to identify the abnormal point set in the intersection area. Finally, taking the center point or the pixel intensity maximum point of the registration area as a representative, the three-dimensional coordinates thereof are extracted, which are recorded as the abnormal point position.

[0070] Wherein, the projection transformation can be based on the following model: , wherein is the mapped physical coordinate point, is the pose matrix, is the camera internal parameter matrix, is the image pixel point.

[0071] 2033: The beam abnormality information including at least the time stamp, the abnormal control parameter, the error amplitude and the abnormal point position is transmitted to the target terminal.

[0072] Specifically, in step 2033, the abnormal timestamp, abnormal control parameter, abnormal error amplitude, abnormal point position, abnormal image frame, abnormal state code, and response suggestion and other information are packaged to form a complete beam abnormal information data packet and sent to the target terminal such as the host computer or the manufacturing terminal, which is used for subsequent process tracing, defect prediction, compensation reconstruction, or quality evaluation, etc.

[0073] By adopting the above technical solutions, the present application realizes accurate positioning of beam abnormalities and spatial coordinate calibration of abnormal points. Compared with the traditional abnormality detection method based on image or control parameter, the present application has stronger spatial mapping capability and time sequence consistency, which can effectively avoid abnormal position misjudgment or omission. At the same time, the registration of the intersection area of the image frame and the path segment can improve the resolution and accuracy of the abnormal point extraction.

[0074] Reference Figure 5 As shown, Figure 5 A flowchart of an exemplary time difference delay determination method of some embodiments of the present application is shown. In some embodiments of the present application, when determining beam emission abnormalities, the method (specifically step 202) includes the following steps 2021-2023.

[0075] 2021: Extract the trigger timestamp of the trigger signal, the beam control timestamp of the beam control parameter, and the actual emission timestamp of the actual emission parameter, respectively.

[0076] Specifically, in step 2021, the trigger timestamp recorded when the galvanometer control unit 101 sends the TTL trigger signal to the beam generator 100, the beam control timestamp recorded when the beam generator 100 receives the trigger signal and completes the control parameter generation process, and the actual emission timestamp recorded when the beam is actually emitted are extracted in turn.

[0077] 2022: Construct the time difference parameter of the beam emission process according to the trigger timestamp, the beam control timestamp, and the actual emission timestamp.

[0078] Specifically, in step 2022, the recorded trigger timestamp is set as T1, the beam control timestamp is set as T2, and the actual emission timestamp or monitoring timestamp is set as T3. Then, the trigger-to-control delay time difference (i.e., the time difference between T1 and T2), the control-to-actual emission delay time difference (i.e., the time difference between T2 and T3), and the total response delay time difference (i.e., the time difference between T1 and T3) in the beam emission process are constructed, specifically the trigger-to-control delay time difference , the control-to-actual emission delay time difference , and the total response delay time difference .

[0079] 2023: compare the time difference parameter with a time tolerance threshold, and according to the comparison result, determine the time difference parameter exceeding the time tolerance threshold as a beam emission abnormality.

[0080] Specifically, in step 2023, the time tolerance threshold can be set as a single threshold, i.e. 、 and are compared with the threshold , and if any condition (e.g. , , ) is met, it is determined that the beam emission is abnormal.

[0081] Different thresholds can also be set for each stage, i.e. is compared with the threshold , and is compared with the threshold , and is compared with the threshold , and if any condition (e.g. , , ) is met, it is determined that the beam emission is abnormal.

[0082] Thus, when any of the time differences exceeds the time tolerance threshold range, the current scanning path, abnormal time point, and beam parameter data are immediately recorded, and the abnormal position registration mechanism is triggered.

[0083] In this application, to ensure the accuracy of the time difference calculation, a unified high-precision clock source (e.g. synchronized with the clock module of the galvanometer control unit 101 and the beam generator 100) is used, and a high-speed communication protocol is adopted to reduce data sampling and transmission errors.

[0084] By using the above technical solution, the time difference parameter of the entire emission process is constructed, which can accurately identify the slight delay deviation in the trigger to control, control to emission, and overall response process, and then by comparing with the preset time tolerance threshold, the beam emission abnormality event caused by signal response abnormality, control delay or emission failure can be effectively judged.

[0085] In practical implementation, a monitoring timestamp can be added when the energy action zone of the beam is activated, identified by the off-axis monitoring. The recorded trigger timestamp is set to T1, the beam control timestamp to T2, the actual launch timestamp to T3, and the monitoring timestamp to T4. This constructs the time difference between trigger and control delays during beam launch (i.e., the time difference between T1 and T2), the time difference between control delays and actual launch delays (i.e., the time difference between T2 and T3), and the time difference between actual launch delays and energy action zone activation delays (i.e., the time difference between T3 and T4). Specifically, the trigger-to-control delay time difference... Controlled to the actual launch delay time difference Actual launch to the energy action zone activation delay time difference Total response delay time difference If any of the following conditions are met ( , , , If the signal is abnormal, then the beam emission is determined to be abnormal.

[0086] By adopting the above technical solution and introducing a side-axis monitoring system to obtain the monitoring timestamp of the activated beam action area, various anomalies in the signal response link can be comprehensively quantified. By comparing and judging with the corresponding time tolerance threshold, a high-sensitivity identification of micro-hour time offset can be achieved, thereby improving the ability of additive manufacturing equipment to perceive problems such as energy transmission failure, optical path misalignment, and abnormal controller response.

[0087] refer to Figure 6 As shown, Figure 6 A flowchart illustrating an exemplary characteristic deviation determination method according to some embodiments of this application is shown. In some embodiments of this application, when determining a beam emission anomaly, the method (specifically step 202) includes the following steps 2024-2026.

[0088] 2024: Extract the beam trigger data of the trigger signal, the beam control data of the beam control parameters, and the actual beam transmission data of the actual transmission parameters, respectively.

[0089] Specifically, in step 2024, the beam trigger data typically includes preset beam power values, voltage, current, band, and other information. The beam control data consists of control parameters generated by the beam generator 100 in response to the trigger signal, which includes beam control power values, voltage, current, band, and other information. The actual beam transmission data is the sampling result of the operating signal, reflecting the actual power values, voltage, current, band, and other information when the beam is actually transmitted.

[0090] 2025: Construct beam characteristic difference parameters for the beam emission process based on the beam triggering data, beam control data, and actual beam emission data.

[0091] Specifically, in step 2025, the characteristic difference parameters of the beam emission process are constructed, if the difference is judged in the aspect of intensity, the constructed parameters include but are not limited to trigger-to-control intensity difference (i.e. the difference between trigger power and control power), control-to-actual emission intensity difference (i.e. the difference between control power and actual emission power), and total response intensity difference (i.e. the difference between actual emission power and trigger power); if the difference is judged in the aspect of wavelength band, the constructed parameters include but are not limited to trigger-to-control wavelength band difference (i.e. the difference between trigger wavelength band and control wavelength band), control-to-actual emission wavelength band difference (i.e. the difference between control wavelength band and actual emission wavelength band), and total response wavelength band difference (i.e. the difference between actual emission wavelength band and trigger wavelength band); or the difference can be judged in the combined aspect of intensity and wavelength band, the constructed parameters include but are not limited to trigger-to-control intensity difference, control-to-actual emission intensity difference, total response intensity difference, trigger-to-control wavelength band difference, control-to-actual emission wavelength band difference, and total response wavelength band difference.

[0092] 2026: comparing the beam characteristic difference parameters with the characteristic tolerance threshold, and according to the comparison result, judging the beam characteristic difference parameters deviating from the characteristic tolerance threshold as emission abnormality.

[0093] Specifically, in step 2026, the above-constructed intensity difference is compared with the set intensity tolerance threshold, or the above-constructed wavelength band difference is compared with the set wavelength band tolerance threshold, or the above-constructed intensity difference is compared with the set intensity tolerance threshold and the above-constructed wavelength band difference is compared with the wavelength band tolerance threshold, so that if any difference value exceeds the corresponding tolerance range, it is judged that the beam emission has abnormality, otherwise it is considered that the beam emission process characteristic is normal; for example, the intensity deviation exceeds ±5%, and the wavelength band deviation exceeds the set range.

[0094] By adopting the above technical solution, the whole process tracking and abnormal identification of the beam energy output characteristic can be realized, and the emission intensity abnormality or wavelength band drift problem caused by equipment fluctuation, control delay, unstable energy beam, etc. can be identified in time.

[0095] Reference Figure 7 As shown, Figure 7 A flowchart of an exemplary multi-beam parameter deviation judgment method is shown, which shows some embodiments of the present application. In some embodiments of the present application, when judging beam emission abnormality, the method (specifically step 202) further includes steps 2001-2003.

[0096] 2001: synchronously collecting trigger parameters, beam control parameters and beam actual emission parameters of multiple beams under the scanning task, and constructing time difference parameters and / or beam characteristic difference parameters of each beam independently, and sequentially aligning each time difference parameter and / or beam characteristic difference parameter on the time axis.

[0097] Specifically, in step 2001, during the execution of the additive manufacturing scanning task, the trigger parameters, beam control parameters and actual beam emission parameters corresponding to multiple beams (such as a laser array, an electron beam group, etc.) are synchronously collected, and then at least one of the time difference parameters and the beam characteristic difference parameters is constructed according to each beam, and then the time difference parameters and / or the beam characteristic difference parameters are aligned on a unified time axis (for example, taking the scanning task start time as a reference timestamp); wherein the characteristic difference parameters include at least one of intensity difference and waveband difference.

[0098] 2002: Compare each time difference parameter and / or beam characteristic difference parameter with a tolerance threshold, and according to the comparison result, determine the time difference parameter and / or the beam characteristic difference parameter deviating from the tolerance threshold as beam emission abnormality.

[0099] Specifically, in step 2002, the constructed time difference is compared with a set time tolerance threshold, or the constructed characteristic difference is compared with a set characteristic tolerance threshold, or the constructed time difference is compared with a set time tolerance threshold and the constructed characteristic difference is compared with a set characteristic tolerance threshold, so that if any difference value exceeds the corresponding tolerance range, it is determined that the beam emission has abnormality, otherwise it is considered that the beam emission process is normal.

[0100] 2003: When at least two beams are detected to have beam emission abnormality in a preset time interval and / or in the same scanning path, the beam emission abnormality is marked as regional beam abnormality, and a preset control strategy is triggered according to the regional beam abnormality.

[0101] Specifically, in step 2003, the regional beam abnormality judgment is divided into time clustering judgment and path clustering judgment. For example, if at least two different beams are detected to have emission abnormality in the same preset time window (such as Δt≤50 ms), the beam emission abnormality of this type is upgraded to regional beam abnormality; for example, if multiple beams have emission abnormality in different time periods in the same or adjacent scanning path segment, the beam emission abnormality of this type is upgraded to regional beam abnormality; the preset control strategy includes at least one of suspending the scanning task of the current construction layer, warning the target terminal, identifying the registration abnormal point position, performing repeated scanning or power compensation on the abnormal point position.

[0102] By adopting the technical scheme, compared with the abnormal monitoring mode of single-beam feedback, the multi-beam regional beam abnormality identification mode can identify potential regional abnormal problems in time when multiple beams continuously emit abnormally in the same time period or the same scanning path, and prevent multiple local abnormalities from accumulating and evolving into serious construction defects, such as incomplete sintering, forming holes or discontinuous organization.

[0103] Reference Figure 8 As shown, Figure 8 A flowchart of an exemplary multi-beam collaborative parameter deviation determination method of some embodiments of the application is shown. In some embodiments of the application, when determining beam emission abnormality, the method (specifically step 202) further includes steps 2004-2006.

[0104] 2004: Synchronously collect the trigger parameters, beam control parameters and actual beam emission parameters of multiple beams in any scanning path and construct time difference parameters and / or beam characteristic difference parameters for each beam independently.

[0105] Specifically, in step 2004, during the execution of the additive manufacturing scanning task, the corresponding trigger parameters, beam control parameters and actual beam emission parameters of multiple beams (such as laser arrays, electron beam groups, etc.) are synchronously collected, and then at least one of the corresponding time difference parameters and beam characteristic difference parameters is constructed according to each beam; wherein the characteristic difference parameters include at least one of intensity difference and wavelength difference.

[0106] 2005: Align each time difference parameter and / or beam characteristic difference parameter on the time axis in turn and construct a corresponding beam parameter matrix.

[0107] Specifically, in step 2005, the time difference parameters and / or beam characteristic difference parameters constructed above are aligned on a unified time axis (for example, the starting time of the scanning task is taken as a reference timestamp), and then a beam parameter matrix is constructed according to the constructed time difference parameters and / or beam characteristic difference parameters, which at least includes time difference, intensity difference and wavelength difference.

[0108] 2006: When any group of diagonal elements in the beam parameter matrix deviates from the collaborative tolerance threshold, it is determined that the synchronous beam emission is abnormal, and a preset control strategy is triggered according to the synchronous beam emission abnormality.

[0109] Specifically, in step 2006, the synchronization beam emission anomaly generally indicates that there is a synchronization deviation problem in the multi-beam when performing the scanning task of the unified path, which can be caused by common control link failure, scanning path interference or device misadjustment. Through the synchronization beam emission anomaly identification method, when there is a small but consistent trend abnormal fluctuation among multiple beams, the potential cooperative deviation characteristics can be captured in time; and the preset control strategy includes at least one of suspending the scanning task of the current construction layer, warning the target terminal, identifying the registration abnormal point position, performing repeated scanning or power compensation on the abnormal point position.

[0110] By adopting the above technical solution, the cooperative working state of multiple beams under the same scanning path can be comprehensively reflected, and the abnormal recognition blind area caused by the dependence on a single beam parameter is avoided. At the same time, by introducing the diagonal element deviation identification method, that is, extracting the time difference parameter or characteristic difference parameter matrix of multiple beams after aligning them on the time axis, and analyzing the consistency and deviation degree between the diagonal elements, the cooperative deviation characteristics in the synchronization beam emission process are identified, so that early warning of synchronization misadjustment or local mismatch is realized, and the monitoring ability of multiple beam emission consistency under complex working conditions is further enhanced.

[0111] Reference Figure 9 As shown in the drawings, Figure 9 A flowchart of an exemplary beam type threshold allocation method of some embodiments of the present application is shown. In some embodiments of the present application, the method (specifically step 202) further includes the following step 2008 in the multi-beam comparison and abnormality determination process of any of the above embodiments.

[0112] 2008: Set the corresponding characteristic tolerance threshold according to different beam types, and compare the constructed time difference parameter and / or beam characteristic difference parameter of each beam independently with the characteristic tolerance threshold matched with the beam type.

[0113] Specifically, in step 2008, the different beam types include but are not limited to laser beams with different powers, electron beams, etc. The beam type information corresponding to each beam channel is read or identified in the scanning task configuration stage, and the characteristic tolerance threshold matched with the beam type is set according to different types of beams. Therefore, after constructing the time difference parameter and / or characteristic difference parameter of each beam, the corresponding beam type information is found according to the number of beam types, and the characteristic tolerance threshold under the beam type is loaded according to the type information, and then the constructed time difference parameter and / or beam characteristic difference parameter of each beam independently is compared with the characteristic tolerance threshold matched with the beam type.

[0114] By adopting the technical scheme, the beam abnormality judgment result is more sensitive to types, and the accuracy of abnormality identification is increased. Compared with the identification method using a unified tolerance standard (such as a unified intensity tolerance threshold, a waveband tolerance threshold, and a time tolerance threshold), the embodiment can set a judgment boundary that is more in line with the physical characteristics of beams of different functions, powers, and control modes, thereby avoiding false alarms caused by too narrow a range or abnormality omissions caused by too wide a range.

[0115] Reference Figure 10 As shown in the figure, Figure 10 An exemplary structure diagram of a correction substrate 106, a light source 107, and a paraxial monitoring unit is shown to illustrate some embodiments of the present application. In some embodiments of the present application, the abnormality monitoring system 1 disclosed herein also includes at least one correction substrate 106 and a light source 107. The at least one correction substrate 106 is arranged in a forming area and is provided with a plurality of correction points 1061 having unique spatial codes for providing data calibration. The light source 107 is arranged in a forming bin for generating visible light of a predetermined waveband.

[0116] Specifically, each correction point 1061 of the at least one correction substrate 106 is provided with unique spatial identification information, including a point number and physical coordinates. The correction points 1061 are arranged on the correction substrate 106 in a predetermined pattern, such as a grid, a cross, or a spiral, for example. The three-dimensional spatial coordinates of each correction point 1061 are recorded in the abnormality monitoring system 1. Each correction point 1061 of the at least one correction substrate 106 can be arranged to reflect different visible light wavebands. In addition, the at least one correction substrate 106 can be divided into regions, each region containing a plurality of correction points 1061. Each region of correction points 1061 is arranged to reflect different visible light wavebands, thereby improving the correction effect.

[0117] Specifically, the light source 107 is arranged at any position in the forming bin without interfering with the energy beam. Preferably, the light source 107 is arranged on a bracket at an angle to the industrial camera to ensure that the illumination range of the visible light can uniformly cover the area of the correction substrate 106. The light source 107 is an LED array or a linear laser that generates visible light of a predetermined waveband (such as 500-1100 nm) to balance the imaging contrast and environmental adaptability. If there are multiple light sources 107, each light source 107 is arranged in a certain spacing and incident angle. Each light source 107 can use the same or different power and waveband.

[0118] Reference Figure 11 As shown in the figure, Figure 11An exemplary light source 107 irradiation data calibration method is shown in the flowchart. In some embodiments of the present application, before the parameter acquisition, the method (specifically step 201) includes the following steps 2111-2113.

[0119] 2111: At least one visible light is used to irradiate a plurality of correction points 1061 in at least one region of the correction substrate 106, and the visible light irradiation signals of each correction point 1061 are collected.

[0120] Specifically, in step 2111, at least one visible light source 107 is started, which emits visible light of a set waveband to irradiate a plurality of correction points 1061 in at least one region of the correction substrate 106. The correction substrate 106 has a plurality of correction points 1061 with unique spatial encoding on its surface. Under the action of light, the correction points 1061 reflect characteristic visible light signals, and then the image acquisition device (such as an industrial camera) in the off-axis monitoring collects the image frame in the light state, identifies and records the visible light reflection image features of each correction point 1061 and its pixel coordinates in the image plane.

[0121] 2112: According to the visible light reflection signals of each correction point 1061 and the correction substrate 106, a visible light correction matrix is constructed.

[0122] Specifically, in step 2112, an image processing algorithm is used to extract the position coordinates of each correction point 1061 in the image data, i.e. the pixel coordinates in the image data, wherein the image processing algorithm includes but is not limited to image threshold segmentation, code recognition, and sub-pixel fitting method; further, the extracted image pixel coordinates are one-to-one matched with the three-dimensional space coordinates of each correction point 1061 calibrated in advance to form a mapping pair of the correction point 1061. Based on at least four mapping pairs, a polynomial method based on least squares fitting is used to solve the projection transformation relationship between the image domain and the actual space coordinates, thereby establishing a visible light correction matrix, i.e. realizing the mapping relationship between the two-dimensional image pixel coordinates and the three-dimensional space physical coordinates.

[0123] 2113: The visible light correction matrix is applied to the spatial mapping and deviation correction of the beam monitoring parameters and abnormal point positions collected in the subsequent beam monitoring process, and the data calibration is completed.

[0124] Specifically, in step 2113, the constructed visible light correction matrix is applied as a transformation reference to the spatial mapping and deviation correction of the beam parameters and abnormal point positions in the subsequent monitoring process, that is, when a potential abnormal point is identified, the image pixel coordinates matching the abnormal point in the beam image data collected by the off-axis monitoring are extracted, and then the constructed visible light correction matrix is used to map these pixel coordinates to the corresponding three-dimensional spatial coordinates, realizing the restoration of the actual physical position, and then the spatial error correction and real position confirmation of the abnormal point are realized based on the spatial mapping result.

[0125] By adopting the above technical solution, that is, by introducing the correction substrate 106 with unique spatial coding and the visible light source 107, combining image processing and spatial registration algorithm, the visible light correction matrix is constructed, the accurate mapping of pixel coordinates to constructed spatial coordinates in off-axis image monitoring is realized, the spatial positioning error caused by image distortion, imaging angle deviation and system assembly error can be effectively corrected, and the spatial positioning accuracy of abnormal points is improved.

[0126] Reference Figure 12 and Figure 13 As shown in Figure 12 An exemplary flowchart of a multi-light source 107 periodic on-off data calibration method is shown, which is used to calibrate the multi-light source 107 periodic on-off data in some embodiments of the present application, Figure 13 An exemplary flowchart of a multi-light source 107 periodic on-off data calibration method is shown, which is used to calibrate the multi-light source 107 periodic on-off data in some embodiments of the present application; wherein, in Figure 12 The light source is set to multiple positions, the light source at the first position is set as the first light source 107-1, the light source at the second position is set as the second light source 107-2, the light source at the third position is set as the third light source, and the light source at the fourth position is set as the fourth light source. The number of the first light source 107-1, the second light source 107-2, the third light source and the fourth light source can be single or multiple, which is set by the debugging personnel according to the actual demand. In some embodiments of the present application, when multiple beams of visible light are used to irradiate the multiple correction points 1061 of at least a part of the region of the correction substrate 106, the method (specifically step 201) comprises the following steps 2121-2122.

[0127] 2121: multiple beams of visible light with the same parameters and different positions and / or angles are simultaneously or alternately irradiated to the multiple correction points 1061 of at least a part of the region of the correction substrate 106, and the multiple beams of visible light are periodically turned on and off according to a preset switching frequency to form a time-segmented controllable irradiation frame sequence.

[0128] Specifically, in step 2121, the multi-beam visible light source (i.e., the first light source 107-1, the second light source 107-2, the third light source, and the fourth light source) is arranged with the same parameters but different positions and / or angles, for example, distributed on a spherical, ring, or planar array above the correction substrate 106 with different polar and azimuth angles; the multi-beam visible light source 107 is periodically controlled to turn on and off at a set switching frequency, which can be in a synchronous mode or an alternating mode, where the synchronous mode is to switch all light sources synchronously to form a whole-frame illumination and whole-frame extinction sequence; the alternating mode is to turn on and off each first light source 107-1, second light source 107-2, third light source, and fourth light source in turn or in groups, and only one light source 107 or one group of light sources is in the on state in each frame; in this way, in the periodic irradiation process, part of the correction points 1061 are illuminated by different light beams to form overlapping bright areas, and the unilluminated areas form regularly distributed shadow areas, that is, a sequence of alternating bright and dark frames is formed on the surface of the correction substrate 106, where each frame corresponds to the shadow projection boundary and bright area boundary image under illumination from different directions.

[0129] 2122: Using the boundary difference between the multiple shadow areas and bright areas formed in the multi-beam visible light irradiation process, a mapping matrix between the multi-beam visible light and the image coordinates is constructed, and the mapping matrix is used to assist data calibration in the subsequent beam monitoring process.

[0130] Specifically, in step 2122, in each frame image sequence, the Sobel edge detection or Canny algorithm is used to extract the gray level jump boundary from light to dark or from dark to light in each correction point 1061 area and to calibrate the boundary direction, position, and change speed of each correction point 1061 from light to dark when illuminated by different light sources in each frame. Then, according to the known spatial geometric layout of the correction points 1061, the shadow direction vector and the light spot distribution area generated by each beam of visible light, the gray level jump area of the correction points 1061 from the bright area to the shadow area on the image plane, and the illumination response of the same correction point 1061 under the action of different light sources in the time sequence are calculated. Then, the mapping relationship between the correction point 1061 coordinates in the image plane and the direction vector or position coordinates of each beam of visible light is constructed through the above boundary response data, and the mapping matrix between the image coordinate system and the physical light space is established by the least square fitting method.

[0131] Therefore, the mapping matrix can be used to correct image distortion, improve the spatial registration accuracy of subsequent abnormal points, and provide auxiliary reference in the decoupling and spatial positioning process of multi-beam abnormal monitoring images.

[0132] By adopting the above technical scheme, the differentiability of responses of different light spots in an image frame is enhanced and the registration accuracy between image coordinates and three-dimensional space coordinates is improved by adopting multiple visible light sources and periodically irradiating the calibration substrate to form a shadow area at a preset frequency.

[0133] Reference Figure 14 as shown, Figure 14 An exemplary schematic diagram of a correction substrate 106, a heating unit 108 and a paraxial monitoring is shown to illustrate some embodiments of the present application. In some embodiments of the present application, the abnormal monitoring system 1 related to the present application further comprises: a heating unit 108 arranged at a correction point 1061 of the correction substrate 106, for providing independent heating for the correction point 1061.

[0134] Specifically, the heating unit 108 provides controllable independent heating excitation for the correction point 1061, so that the correction point 1061 forms an infrared signal after being heated, so as to present a clear thermal response image.

[0135] For example, a micro-resistance heating sheet or a MEMS heating element is pre-embedded or attached at each correction point 1061 position, and temperature rise and drop are achieved by controlling the on-off and on-off time of the current.

[0136] Reference Figure 15 as shown, Figure 15 An exemplary flowchart of a correction point 1061 heating data calibration method is shown to illustrate some embodiments of the present application. In some embodiments of the present application, before parameter collection, the method (specifically step 201) further comprises the following steps 2131-2133.

[0137] 2131: providing heating for multiple correction points 1061 in at least a part of the correction substrate 106 and collecting infrared light signals formed by each correction point 1061.

[0138] Specifically, in step 2131, the heating unit 108 is controlled to heat the correction points 1061 one by one or in groups according to a set power and time curve, and then the infrared image during the heating process is collected in real time using the thermal imaging device in the paraxial monitoring unit 103, while the brightness center, edge profile and gray scale distribution of the infrared hot spot area in each infrared image are extracted as the infrared response characteristics of the correction point 1061.

[0139] 2132: registering the infrared light signals of each correction point 1061 with the correction substrate 106 to construct an infrared light correction matrix.

[0140] Specifically, in step 2132, based on identifying the hot spot region corresponding to the correction point 1061 in the infrared image according to the infrared response characteristics, and then according to the image coordinates of the hot spot center or the high gray region gravity center, the actual three-dimensional space coordinates are matched, and then the least square method, affine transformation or other methods are applied to solve the mapping transformation relationship between the infrared image coordinates and the position of the correction point 1061, and the infrared light correction matrix is generated.

[0141] 2133: Apply the infrared light correction matrix to the spatial mapping and deviation correction of the beam monitoring parameters and abnormal point positions collected in the subsequent beam monitoring process, and complete the data calibration.

[0142] Specifically, in step 2133, the constructed infrared light correction matrix can be used to compare the actual forming path, device calibration trajectory or expected beam energy distribution center to accurately extract the spatial deviation amount; or, the constructed infrared light correction matrix is used to correct the beam pointing and adjust the energy distribution using the deviation data; or, in the execution of a multi-beam scanning task, the constructed infrared light correction matrix is used to distinguish the response characteristics of different beam channels under infrared imaging, and to realize independent calibration of the beams.

[0143] By adopting the above technical solutions, measurement errors caused by environmental reflection, multi-path beam interference and optical shielding in the visible light calibration process can be avoided, and stable and high-precision spatial registration and calibration operations can be realized under complex lighting conditions and shielding environments.

[0144] In some embodiments, the present application also relates to an additive manufacturing device comprising the abnormal monitoring system 1 of any of the above embodiments.

[0145] In some embodiments, with reference to Figure 16 as shown, Figure 16 A connection diagram of an exemplary electronic device according to some embodiments of the present application is shown. The electronic device 3 comprises a memory 301 and a processor 302, and the memory 301 stores a computer program executable on the processor 302. The processor 302 implements the method in the above embodiments when executing the computer program. The number of memories 301 and processors 302 can be one or more.

[0146] The electronic device 3 further comprises a communication interface 303 for communicating with external devices and performing data transmission.

[0147] If the memory 301, the processor 302 and the communication interface 303 are implemented independently, the memory 301, the processor 302 and the communication interface 303 can be connected to each other through a bus and complete communication between each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 16 Only one thick line is used to represent the bus in the figure, but it does not mean that there is only one bus or only one type of bus.

[0148] Optionally, in a specific implementation, if the memory 301, the processor 302 and the communication interface 303 are integrated on a chip, the memory 301, the processor 302 and the communication interface 303 can complete communication between each other through an internal interface.

[0149] The embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by the processor 302 to implement the method provided in the embodiment of the present application.

[0150] The embodiment of the present application further provides a chip, which includes the processor 302, is used for calling and running instructions stored in the memory 301, so that a communication device installed with the chip executes the method provided in the embodiment of the present application.

[0151] The embodiment of the present application further provides a chip, which includes an input interface, an output interface, a processor 302 and a memory 301, the input interface, the output interface, the processor 302 and the memory 301 are connected through an internal connection path, and the processor 302 is used for executing code in the memory 301, when the code is executed, the processor 302 is used for executing the method provided in the embodiment of the present application.

[0152] It is to be understood that the above-described processor 302 can be a central processing unit (CPU), but can also be other general purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. The general purpose processor can be a microprocessor or any conventional processor, etc. It is to be noted that the processor 302 can be a processor 302 supporting an advanced RISC machine (ARM) architecture.

[0153] Further, the above-described memory 301 can include read-only memory and random access memory, and can also include non-volatile random access memory. The memory can be volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. Among them, the non-volatile memory can include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory can include random access memory (RAM) used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM).

[0154] In the above embodiments, all or part can be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part generates the flow or function according to the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium.

[0155] The above description is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for anomaly monitoring of a beam used in additive manufacturing, characterized in that, The method includes: The system collects trigger parameters of the trigger signal sent to at least one beam generator to perform the scanning task, and simultaneously collects beam control parameters of the at least one beam generator when it receives the trigger signal. The system also collects actual beam emission parameters based on the operating signals of the at least one beam generator, and uses a parietal axis to monitor the beam monitoring parameters used to perform the scanning task. Extract the beam trigger timestamp and / or intensity and / or band of the trigger parameters, the beam control timestamp and / or intensity and / or band of the beam control parameters, and the actual beam emission timestamp and / or intensity and / or band of the actual beam emission parameters, respectively. The time difference and / or intensity difference and / or band difference from the trigger to the control delay, the time difference and / or intensity difference and / or band difference from the control to the actual transmission delay, and the time difference and / or intensity difference and / or band difference from the trigger to the actual transmission delay are compared with the preset tolerance thresholds. Based on the comparison results, parameters that deviate from the preset tolerance thresholds are judged as transmission anomalies. Based on the trigger parameters, beam control parameters, and actual beam emission parameters that indicate a transmission anomaly, abnormal beam parameters are constructed and registered with beam monitoring parameters to generate and feed back the corresponding anomaly point locations.

2. The method according to claim 1, characterized in that, When determining beam emission anomalies, the method includes: Extract the trigger timestamp of the trigger signal, the beam control timestamp of the beam control parameters, and the actual transmission timestamp of the actual transmission parameters, respectively. The time difference parameters of the beam emission process are constructed based on the trigger timestamp, beam control timestamp, and actual emission timestamp. The time difference parameter is compared with the time tolerance threshold, and based on the comparison result, the time difference parameter exceeding the time tolerance threshold is determined to be an abnormal beam emission.

3. The method according to claim 2, characterized in that, When constructing the time difference parameters of the beam emission process based on the trigger timestamp, beam control timestamp, and actual emission timestamp, the method includes: Construct the time difference between triggering and control, control and actual launch, actual launch and energy activation zone activation, and total response delay during beam launch.

4. The method according to claim 3, characterized in that, When determining beam emission anomalies, the method further includes: The time difference between triggering and control delay, the time difference between control and actual launch delay, the time difference between actual launch and beam operation area activation delay, and the total response delay are compared with the time tolerance threshold in sequence. When any time difference exceeds the time tolerance threshold, it is determined that the beam launch is abnormal.

5. The method according to claim 1 or 2, characterized in that, When determining beam emission anomalies, the method further includes: The beam triggering data of the trigger signal, the beam control data of the beam control parameters, and the actual beam emission data of the actual emission parameters are extracted respectively. The beam characteristic difference parameters of the beam emission process are constructed based on the beam triggering data, beam control data, and actual beam emission data. The beam characteristic difference parameter is compared with the characteristic tolerance threshold, and based on the comparison result, the beam characteristic difference parameter that deviates from the characteristic tolerance threshold is determined to be an emission anomaly.

6. The method according to claim 5, characterized in that, The method for extracting the beam control data and the actual beam emission data includes: The beam triggering intensity and / or band of the trigger signal, the beam control intensity and / or band of the beam control parameters, and the actual beam transmission intensity and / or band of the actual transmission parameters are extracted respectively. Constructing the beam transmission process triggering to control strength and / or band difference, control to actual transmission strength and / or band difference, and triggering to actual transmission strength and / or band difference.

7. The method according to claim 1, 4, or 6, characterized in that, When generating and reporting the corresponding anomaly locations, the method includes: Associate the abnormal beam parameters with the corresponding scanning path of the scanning task and match the spatial coordinates of the actual target component according to the scanning path index; By matching the beam monitoring parameters with the time period of beam emission anomaly occurrence and combining them with the spatial coordinates of the actual target component, the location of the anomaly point is generated. The beam anomaly information, including at least a timestamp, anomaly control parameters, error amplitude, and anomaly location, will be transmitted to the target terminal.

8. The method according to claim 7, characterized in that, When generating outlier locations, the method includes: Extract the abnormal timestamp of the abnormal beam occurrence and obtain the scan path segment number corresponding to the abnormality in the scan task based on the abnormal timestamp; Based on the path index information, query the geometric mapping in the 3D model of the target component and obtain the spatial coordinates of the scanned path segment in the 3D model of the target component. Then, combine the spatial coordinates with the construction layer thickness and layer sequence number of the scanned path segment to perform Z-axis interpolation or calibration. Based on the abnormal timestamp, a matching frame is found in the image data of the beam monitoring parameters, and the intersection area between the matching frame image and the scanning path segment is extracted. In this way, the intersection area is converted into a physical coordinate system through image calibration. The spatial coordinates of the intersecting regions are registered to generate the locations of outliers.

9. The method according to claim 6, characterized in that, When determining beam emission anomalies, the method further includes: Simultaneously acquire the corresponding trigger parameters, beam control parameters and actual beam emission parameters of multiple beams under the scanning task, and construct independent time difference parameters and / or beam characteristic difference parameters for each beam, and align each time difference parameter and / or beam characteristic difference parameter on the time axis in sequence; Each time difference parameter and / or beam characteristic difference parameter is compared with the tolerance threshold, and based on the comparison results, the time difference parameters and / or beam characteristic difference parameters that deviate from the tolerance threshold are judged as beam emission anomalies. When at least two beams are detected to emit beams abnormally within a preset time interval and / or in the same scanning path, the beam emission abnormality is marked as a regional beam abnormality, and a preset control strategy is triggered based on the regional beam abnormality.

10. The method according to claim 6, characterized in that, When determining beam emission anomalies, the method further includes: Simultaneously acquire the corresponding trigger parameters, beam control parameters and actual beam emission parameters of multiple beams under any scanning path, and construct independent time difference parameters and / or beam characteristic difference parameters for each beam; Align each time difference parameter and / or beam characteristic difference parameter sequentially on the time axis and construct the corresponding beam parameter matrix; When any set of diagonal elements in the beam parameter matrix deviates from the cooperative tolerance threshold, it is determined to be a synchronous beam emission anomaly, and a preset control strategy is triggered based on the synchronous beam emission anomaly.

11. The method according to claim 9 or 10, characterized in that, In the process of multi-beam comparison and anomaly detection, the method includes: Set corresponding characteristic tolerance thresholds for different beam types and compare the independent time difference parameters and / or beam characteristic difference parameters of each constructed beam with the characteristic tolerance thresholds that match the beam type.

12. The method according to claim 1, characterized in that, Before collecting parameters, the method includes: At least one visible light is used to illuminate at least a portion of a calibration substrate at multiple calibration points, and the visible light illumination signal of each calibration point is collected. A visible light correction matrix is ​​constructed by registering the visible light reflection signals of each correction point with the correction substrate. The visible light correction matrix is ​​applied to the spatial mapping and deviation correction of the beam monitoring parameters and anomaly locations collected during subsequent beam monitoring, thereby completing data calibration.

13. The method according to claim 12, characterized in that, When illuminating at least a portion of a correction point on a correction substrate with multiple beams of visible light, the method includes: Multiple beams of visible light with the same parameters and different positions and / or angles are simultaneously or alternately irradiated onto multiple correction points in at least a portion of the correction substrate, and the multiple beams of visible light are periodically switched on and off according to a preset switching frequency to form a time-segmented controllable irradiation frame sequence. By utilizing the boundary differences between multiple shadow areas and bright areas formed during the illumination of multiple visible light beams, a mapping matrix between the multiple visible light beams and image coordinates is constructed, and the mapping matrix is ​​used to assist in data calibration during subsequent beam monitoring.

14. The method according to claim 12 or 13, characterized in that, Before collecting parameters, the method further includes: Heating is provided to multiple correction points in at least a portion of the correction substrate, and infrared light signals generated by each correction point are acquired. An infrared light correction matrix is ​​constructed by registering the infrared light signals of each correction point with the correction substrate. The infrared light correction matrix is ​​applied to the spatial mapping and deviation correction of the beam monitoring parameters and anomaly point locations collected during subsequent beam monitoring, thereby completing the data calibration.

15. An anomaly monitoring system for an additive manufacturing beam, characterized in that, The anomaly monitoring system includes: A beam generator is used to generate and emit beams; The galvanometer control unit is used to connect to the galvanometer and the beam generator respectively, and is used to trigger and adjust the beam parameters generated and emitted by the beam generator; The coaxial monitoring unit is used to acquire signal parameters during the scanning process of the galvanometer. The off-axis monitoring unit is used to acquire timestamp parameters, image data, spectral data, and thermal imaging data of the beam acting on the surface of the target component during at least one scanning task; A control device is connected to and controls the beam generator, galvanometer control unit, coaxial monitoring unit, and paraxial monitoring unit to perform the method according to any one of claims 1 to 11.

16. An anomaly monitoring system for an additive manufacturing beam, characterized in that, The anomaly monitoring system includes: A beam generator is used to generate and emit beams; The galvanometer control unit is connected to both the galvanometer and the beam generator, and is used to trigger and adjust the beam parameters generated and emitted by the beam generator. The coaxial monitoring unit is used to acquire signal parameters during the scanning process of the galvanometer. The off-axis monitoring unit is used to acquire timestamp parameters, image data, spectral data, and thermal imaging data of the beam acting on the surface of the target component during at least one scanning task; At least one calibration substrate is disposed in the forming area and has multiple calibration points with unique spatial codes for providing data calibration; The light source, located inside the forming chamber, is used to generate visible light of a preset wavelength. A control device, connected to and controlling the beam generator, galvanometer control unit, coaxial monitoring unit, paraxial monitoring unit, and light source, to perform the method according to any one of claims 12 to 13.

17. An anomaly monitoring system for an additive manufacturing beam, characterized in that, The anomaly monitoring system includes: A beam generator is used to generate and emit beams; The galvanometer control unit is connected to both the galvanometer and the beam generator, and is used to trigger and adjust the beam parameters generated and emitted by the beam generator. The coaxial monitoring unit is used to acquire signal parameters during the scanning process of the galvanometer. The off-axis monitoring unit is used to acquire timestamp parameters, image data, spectral data, and thermal imaging data of the beam acting on the surface of the target component during at least one scanning task; At least one calibration substrate is disposed in the forming area and has multiple calibration points with unique spatial codes for providing data calibration; A heating unit, which is disposed at the correction point of the correction substrate, is used to provide independent heating for the correction point; A control device is connected to and controls the beam generator, galvanometer control unit, coaxial monitoring unit, off-axis monitoring unit, and at least one heating unit to perform the method of claim 14.

18. An additive manufacturing apparatus, characterized in that, Includes the anomaly monitoring system as described in any one of claims 15 to 17.

19. An electronic device, characterized in that, include: At least one processor; At least one memory; The at least one memory is coupled to the at least one processor and is used to store instructions executed by the at least one processor, which, when executed by the at least one processor, cause the electronic device to perform the method according to any one of claims 1 to 14.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 14.

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