Railway vehicle brake disc additive remanufacturing process optimization method and system

Abstract

The present application belongs to the field of additive remanufacturing technology, and in particular, relates to a kind of brake disc additive remanufacturing process optimization method and system for rail vehicle.The method obtains material characteristic data by analyzing the material characteristics of the brake disc base body for rail vehicle, real-time monitors the molten pool solidification front appearance feature data in the additive remanufacturing process, analyzes and reasons the difference between the base body and the molten pool solidification appearance based on the two kinds of data, and optimizes and adjusts the additive remanufacturing process parameters according to the reasoning result.Through the accurate identification of the base body material characteristics, combined with the real-time monitoring of the molten pool solidification front, the present application can deeply analyze the deep reason of the local thermal anomaly of the molten pool, can identify and correct specific problems such as insufficient laser energy, excess, uneven spot energy distribution or scanning path anomaly, so as to realize the accurate optimization and adjustment of the additive remanufacturing process parameters, and provide a reliable and efficient solution for the additive remanufacturing of rail vehicle brake disc.

Description

Technical Field

[0001] This application relates to the field of additive remanufacturing technology, and more specifically, to an optimization method and system for the additive remanufacturing process of brake discs for rail vehicles. Background Technology

[0002] During long-term use, the surface of rail vehicle brake discs can be damaged due to wear and thermal fatigue. To extend their lifespan, additive remanufacturing technology is widely used, repairing damage by laser cladding of metal powder. However, in practice, ensuring the stability of the repaired brake disc material properties, manufacturing precision, and energy consumption presents challenges. This is mainly because the optical path system of additive remanufacturing equipment, especially the reflectors, can experience uneven decreases in reflectivity due to long-term operation and impurity adhesion, leading to uneven laser energy distribution. Simultaneously, the brake disc substrate itself develops localized metallographic differences during service, and existing detection methods struggle to accurately identify these microscopic changes.

[0003] In a typical additive remanufacturing system, a high-power laser is one of the core components. The laser beam it emits is precisely guided and applied to the surface of the brake disc to be repaired through a series of optical elements, such as mirrors and focusing lenses. However, during long-term operation, the mirrors in the optical path system are continuously exposed to the repeated impact of high-temperature laser energy. Simultaneously, the protective gas used in the additive process, even after rigorous purification, may contain trace amounts of impurities, which slowly adhere to the mirror surface with the airflow. The cumulative effect of these factors leads to a slight and uneven decrease in the local reflectivity of the mirror. While this uneven reflectivity change is difficult to perceive with the naked eye, it directly affects the energy transmission characteristics of the laser beam.

[0004] When uneven laser energy distribution and differences in matrix structure spatially overlap, the local thermal history of the molten pool becomes abnormal, affecting the quality and energy consumption of the remanufactured layer. Existing molten pool temperature sensor data often "smooths" these microscopic fluctuations, making it difficult for the control system to identify and correct these deep-seated problems in a timely manner. This abnormality in the local molten pool thermal history directly affects the deposition behavior and solidification process of metal powder during additive remanufacturing. In these affected specific areas, the melting, flow, and solidification of metal powder no longer follow the expected path, leading to unexpected changes in the internal grain growth direction, abnormal grain boundary morphology, and uneven residual stress distribution. Ultimately, these microstructural defects and inhomogeneities directly cause material performance degradation in specific areas of the remanufactured brake disc, such as uneven local hardness, decreased fatigue resistance, and reduced wear resistance. At the same time, the instability of local heat input can also cause manufacturing precision deviations, such as local warping deformation, abnormally increased surface roughness, and even microcracks. Furthermore, due to local fluctuations in melting efficiency in different regions, the energy utilization rate of the entire additive manufacturing process becomes unstable, making overall energy consumption control difficult to predict and optimize. However, due to the "smoothing" of the aforementioned sensor data and the "fault tolerance range" of the control system, the system still considers itself to be operating "normally." These potential quality problems and energy consumption fluctuations often only become apparent during subsequent rigorous testing or actual service. Summary of the Invention

[0005] This application discloses an optimization method and system for the additive remanufacturing process of brake discs for rail vehicles, which aims to solve the problem that uneven laser energy distribution and differences in matrix structure lead to abnormal local thermal history of the molten pool during the additive remanufacturing process of brake discs for rail vehicles, thereby affecting the quality of the remanufactured layer, manufacturing precision and energy consumption stability.

[0006] This invention is achieved using the following technical solution: an optimized method for the additive remanufacturing process of brake discs for rail vehicles, comprising: Material property analysis was performed on the brake disc substrate for rail vehicles to obtain material property data of the brake disc substrate for rail vehicles. Additive remanufacturing of brake disc substrate for rail vehicles, and real-time monitoring of the morphological characteristics of the molten pool solidification front during the additive remanufacturing process of brake disc substrate for rail vehicles. Based on material property data and molten pool solidification front morphology data, the differences between the brake disc matrix for rail vehicles and the molten pool solidification morphology are analyzed and inferred. Based on the analysis and reasoning results, the additive remanufacturing process parameters of the brake disc substrate for rail vehicles were optimized and adjusted.

[0007] This technical solution enables real-time monitoring, analysis, and optimization of the additive remanufacturing process of brake discs for rail vehicles. It effectively solves the problem of local thermal anomalies in the molten pool caused by uneven laser energy distribution and differences in matrix structure in existing technologies, thereby improving the quality and manufacturing precision of the remanufactured layer and optimizing energy consumption.

[0008] Preferably, a material property analysis is performed on the brake disc substrate for rail vehicles to obtain material property data of the brake disc substrate for rail vehicles, including: Obtain the microstructure information of the brake disc substrate for rail vehicles, and determine the overall material properties data of the brake disc substrate for rail vehicles based on the microstructure information. The surface of the brake disc substrate for rail vehicles is divided into multiple material property regions. Based on the distribution of the overall material property data of the brake disc substrate for rail vehicles in each material property region, the material property data of each material property region is determined. The material property data of each material property region includes at least the local hardness data and fatigue damage data of the corresponding material property region.

[0009] This technical solution enables refined analysis of the properties of brake disc substrate materials, not only obtaining overall material properties but also identifying key data such as hardness and fatigue damage in local areas, providing more accurate substrate condition information for subsequent additive remanufacturing process optimization.

[0010] Preferably, obtaining the microstructure information of the brake disc substrate for rail vehicles includes: The laser-induced ultrasonic spectrum analysis device scans the brake disc substrate of the rail vehicle. The pulse laser of the laser-induced ultrasonic spectrum analysis device emits laser pulses to generate ultrasonic signals on the brake disc substrate of the rail vehicle. A piezoelectric sensor is installed on the light spot formed on the surface of the brake disc substrate of a rail vehicle to obtain the ultrasonic signal excited on the material surface by the laser pulse emitted by the pulse laser of the laser-induced ultrasonic spectrum analysis device. The acquired ultrasonic signals are subjected to spectral analysis using Fourier transform to extract the acoustic feature information of the ultrasonic signals; The acoustic feature information is compared with the preset acoustic feature information in the preset database of brake disc matrix material of rail vehicles to determine the microstructure information of the current scanning area.

[0011] This technical solution utilizes laser-induced ultrasonic spectroscopy to obtain the microstructure information of the brake disc substrate in a non-destructive and precise manner, overcoming the limitations of traditional detection methods in identifying microscopic changes and providing a reliable data source for material property analysis.

[0012] Preferably, the brake disc substrate for rail vehicles is additively remanufactured, and the morphological characteristics of the molten pool solidification front of the brake disc substrate during the additive remanufacturing process are monitored in real time, including: Image acquisition equipment is deployed above the molten pool in additive remanufacturing to acquire images of the solidification front morphology of the molten pool in real time. The image of the solidification front morphology of the molten pool is preprocessed, including grayscale conversion and contrast enhancement. Using edge detection algorithms, the solidification front contour of the molten pool is extracted based on the preprocessed image of the solidification front morphology. The extracted solidification front profile was analyzed to determine the morphological characteristics of the solidification front of the molten pool.

[0013] This technical solution enables real-time and precise monitoring of the morphology of the molten pool solidification front during additive remanufacturing. By using image processing and edge extraction techniques, key morphological feature data can be obtained, providing a direct basis for subsequent anomaly detection and process optimization.

[0014] Preferably, the types of morphological feature data of the solidification front of the molten pool include: normal morphological features and abnormal morphological features; wherein, when there are local depressions, protrusions or irregular serrated structures in the solidification front contour, when the grain growth on the surface of the solidification front contour is abnormal or the grain growth direction on the surface of the solidification front contour is deviated, the data type of morphological feature of the solidification front of the molten pool is abnormal morphological features. The extracted solidification front profile was analyzed to determine the morphological characteristics of the molten pool solidification front, including: Geometric feature analysis is performed on the extracted solidification front contour to calculate local curvature and roughness parameters and identify whether there are local depressions, protrusions or irregular serrated structures in the solidification front contour. By analyzing the local brightness gradient changes of the solidification front profile, we can infer whether the grain growth on the surface of the solidification front profile is abnormal and whether the growth direction has shifted.

[0015] This technical solution can precisely identify the abnormal morphological features of the solidification front of the molten pool, and infer the grain growth by analyzing geometric features and brightness gradient changes, thereby more accurately determining the solidification state of the molten pool and providing more refined input for subsequent analysis of the causes of anomalies.

[0016] Preferably, based on material property data and molten pool solidification front morphology data, the differences between the brake disc substrate for rail vehicles and the molten pool solidification morphology are analyzed and inferred, including: Based on the morphological feature data of the solidification front of the molten pool, determine whether the morphological feature data of the solidification front of the molten pool of the brake disc substrate for rail vehicles is an abnormal morphological feature. If it is determined that there is an abnormality in the morphology of the solidification front of the molten pool, then query the material property data corresponding to the area where the morphology of the solidification front of the molten pool is abnormal, and determine whether the area where the morphology of the solidification front of the molten pool is abnormal is an area with abnormal material properties. Specifically, if the local hardness data in the material property data of one of the material property abnormality areas is greater than the preset local hardness data threshold, then the abnormality type of the corresponding material property abnormality area is high hardness phase transition; if the fatigue damage data in the material property data of one of the material property abnormality areas is greater than the preset fatigue damage data, then the abnormality type of the corresponding material property abnormality area is fatigue damage. Based on the morphology of the solidification front of the molten pool in the brake disc substrate for rail vehicles and the abnormal conditions in the region where the solidification front of the molten pool is located, the cause of the local thermal anomaly in the molten pool is inferred.

[0017] This technical solution enables the correlation analysis between abnormal solidification morphology of the molten pool and abnormal properties of the matrix material. By determining the type of abnormality (such as high-hardness phase transformation or fatigue damage), the underlying causes of local thermal anomalies in the molten pool can be more accurately inferred, avoiding the limitations of traditional methods that rely solely on surface phenomena for judgment.

[0018] Preferably, based on the morphology of the molten pool solidification front of the brake disc substrate for rail vehicles and the anomalies in the region where the molten pool solidification front is located, the causes of local thermal anomalies in the molten pool are inferred, including: When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front contraction or sawtooth morphology, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormality type of the abnormal area is high hardness phase transformation, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the laser energy is insufficient to fully melt the high hardness phase transformation area. When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally coarse grains, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormality type of the abnormal area is fatigue damage, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: excessive laser energy leads to local overheating. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front contraction or sawtooth morphology, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the energy distribution of the laser spot is locally low. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally large grains, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the energy distribution of the laser spot is locally too high. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is the deviation of the grain growth direction, and there is no abnormality in the area where the solidification front of the molten pool is located, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: uneven distribution of laser spot energy or abnormal scanning path. Wherein, the first preset melt pool size threshold is less than the second preset melt pool size threshold, and the melt pool size between the first preset melt pool size threshold and the second preset melt pool size threshold is the normal melt pool size.

[0019] This technical solution enables refined and multi-scenario analysis and reasoning of the causes of local thermal anomalies in the molten pool based on multiple dimensions such as the morphology of the solidification front of the molten pool, the type of abnormality in the matrix material properties, and the size of the molten pool. This allows for accurate identification of specific problems such as insufficient or excessive laser energy, uneven distribution of laser spot energy, or abnormal scanning path, providing precise guidance for subsequent process parameter adjustments.

[0020] Preferably, based on the analysis and reasoning results, the additive remanufacturing process parameters of the brake disc substrate for rail vehicles are optimized and adjusted, including: The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is insufficient to fully melt the high-hardness phase transition region or the laser spot energy distribution is locally low, the laser energy is increased and the laser heat input is increased by increasing the emission power of the pulsed laser emitting laser to the current region and decreasing the scanning speed of the pulsed laser emitting laser to the current region. The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is excessive, causing local overheating, or when the laser spot energy distribution is locally too high, the laser energy is reduced and the laser heat input is reduced by decreasing the emission power of the pulsed laser emitting laser to the current area and increasing the scanning speed of the pulsed laser emitting laser to the current area. The analysis and reasoning for the cause of local thermal anomalies in the molten pool is that when the laser spot energy distribution is uneven or the scanning path is abnormal, the grain growth direction can be corrected by adjusting the local angle or overlap rate of the laser scanning path.

[0021] This technical solution enables targeted adjustment of additive remanufacturing process parameters, including laser emission power, scanning speed, scanning path angle, or overlap rate, based on the specific identified causes of localized thermal anomalies in the molten pool. This achieves closed-loop control and precise optimization of the additive remanufacturing process, effectively correcting molten pool anomalies and ensuring the quality of the remanufactured layer.

[0022] Preferably, the emission power adjustment amount of the pulsed laser emitting laser light into the current region. Calculated using the following formula: in, This refers to the proportional gain of the PID controller for the pulsed laser. The integral coefficient of the PID controller for the pulsed laser is... It is the target molten pool size. This is the current molten pool size; This indicates the current moment when the additive remanufacturing process for brake discs used in rail vehicles is being optimized. The scanning speed adjustment of a pulsed laser that emits laser light into the current area. Calculated using the following formula: in, represents the differential coefficient of the PID controller for the pulsed laser.

[0023] This technical solution introduces a PID control algorithm to accurately calculate the adjustment of laser emission power and scanning speed, achieving dynamic and precise control of the molten pool size. This further improves the intelligence and refinement of process parameter adjustment, ensuring the stability and consistency of the additive remanufacturing process.

[0024] This invention also discloses an optimization system for the additive remanufacturing process of brake discs for rail vehicles, comprising: The material property data acquisition module is used to analyze the material properties of the brake disc substrate for rail vehicles and acquire the material property data of the brake disc substrate for rail vehicles. The molten pool solidification front morphology feature data monitoring module is used to monitor the molten pool solidification front morphology feature data of the brake disc substrate for rail vehicles in real time during the additive remanufacturing process. The analysis and reasoning module is used to analyze and reason about the differences between the brake disc substrate for rail vehicles and the solidification morphology of the molten pool based on material property data and molten pool solidification front morphology data. The optimization and adjustment module is used to optimize and adjust the additive remanufacturing process parameters of the brake disc substrate for rail vehicles based on the analysis and reasoning results.

[0025] This technical solution provides a system that integrates material property analysis, molten pool solidification monitoring, difference analysis and reasoning, and process parameter optimization and adjustment. It enables comprehensive and intelligent control of the additive remanufacturing process of brake discs for rail vehicles, effectively solving the quality and energy consumption problems existing in the prior art and improving the overall efficiency and reliability of remanufacturing.

[0026] This technical solution provides a system that integrates data acquisition, active feature generation, raw material deviation judgment, and process parameter adjustment, enabling comprehensive and intelligent monitoring and optimization of the bicycle seat molding process. It effectively solves the limitations of manual experience judgment and significantly improves the level of automation and intelligence in production.

[0027] Compared with the prior art, the beneficial effects of the present invention are: This invention discloses an optimization method for the additive remanufacturing process of brake discs for rail vehicles. It analyzes the material properties of the brake disc substrate to obtain material property data and monitors the solidification front morphology of the molten pool in real time during the additive remanufacturing process. Based on this, it analyzes and infers the differences between the solidification morphology of the substrate and the molten pool using these two types of data, and optimizes and adjusts the additive remanufacturing process parameters according to the inference results. This method effectively solves the problem of localized thermal anomalies in the molten pool caused by uneven laser energy distribution and differences in substrate microstructure in existing technologies. By accurately identifying the material properties of the substrate and combining real-time monitoring of the solidification front of the molten pool, this application can deeply analyze the underlying causes of localized thermal anomalies in the molten pool, rather than relying solely on smoothed temperature sensor data. This refined analysis and inference mechanism enables the system to identify and correct specific problems such as insufficient or excessive laser energy, uneven spot energy distribution, or abnormal scanning paths, thereby achieving precise optimization and adjustment of the additive remanufacturing process parameters. Ultimately, this method can significantly improve the material properties and manufacturing precision of the remanufactured layer, and optimize overall energy consumption. It overcomes the shortcomings of existing technologies, such as unstable remanufacturing quality, large precision deviation, and difficulty in energy consumption control, and provides a reliable and efficient solution for additive remanufacturing of rail vehicle brake discs. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart illustrating an optimized method for additive remanufacturing of brake discs for rail vehicles provided by the present invention.

[0030] Figure 2 This is a schematic diagram of the structure of an additive remanufacturing process optimization system for brake discs of rail vehicles provided by the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Traditional additive remanufacturing technology for rail vehicle brake discs faces challenges in terms of material properties, manufacturing precision, and energy consumption stability when repairing damaged brake discs. This is mainly due to the uneven decrease in local reflectivity of mirrors in the optical path system of additive remanufacturing equipment, and the local metallographic differences in the brake disc substrate itself, leading to uneven laser energy distribution. When the uneven laser energy distribution and the differences in substrate microstructure overlap spatially, the local thermal history of the molten pool becomes abnormal, thus affecting the quality and energy consumption of the remanufactured layer. Existing molten pool temperature sensor data often "smooths" these microscopic fluctuations, making it difficult for the control system to identify and correct these underlying problems in a timely manner.

[0033] This invention provides an embodiment: such as Figure 1 As shown, the present invention provides an optimized method for the additive remanufacturing process of brake discs for rail vehicles, comprising: S110: Perform material property analysis on the brake disc substrate for rail vehicles and obtain material property data of the brake disc substrate for rail vehicles.

[0034] The method proposed in this application aims to solve the quality and energy consumption problems caused by uneven laser energy distribution and differences in matrix material properties in existing additive remanufacturing processes through refined data acquisition, analysis, and intelligent optimization. Among these, the brake disc for rail vehicles is a key component of the rail vehicle braking system, and its surface will experience wear and fatigue damage due to friction and thermal stress during long-term operation. Material property data describes the physical and chemical properties of the brake disc matrix, such as hardness, fatigue strength, and microstructure.

[0035] To implement the aforementioned optimization methods, it is first necessary to analyze the material properties of the brake disc substrate for rail vehicles to obtain its material property data. One approach is to manually sample different areas of the brake disc substrate and then use traditional metallographic microscopes, hardness testers, and other equipment to perform point-by-point inspections, recording information such as the microstructure and local hardness at each point, and summarizing this data to form material property data. Another approach is to use non-destructive testing equipment, such as ultrasonic flaw detectors or eddy current detectors, to scan the brake disc substrate. By analyzing changes in reflected waves or eddy current signals, internal defects or structural inhomogeneities in the material can be inferred, thereby indirectly obtaining material property data.

[0036] When analyzing the material properties of brake disc substrates for rail vehicles, obtaining only overall material property data may not fully reflect the differences in material performance within the substrate or in localized areas on its surface. This is especially true after long-term service, when different regions of the brake disc may exhibit varying degrees of damage or performance degradation. Such macroscopic data can lead to a lack of targeted optimization in subsequent additive remanufacturing processes, thereby affecting the quality and reliability of remanufacturing. Therefore, this application proposes a more specific method for analyzing the material properties of brake disc substrates for rail vehicles to obtain more refined material property data.

[0037] This application further proposes a method for analyzing the material properties of a brake disc substrate for rail vehicles and obtaining material property data for the brake disc substrate for rail vehicles, the steps of which include: Obtain the microstructure information of the brake disc substrate for rail vehicles, and determine the overall material properties data of the brake disc substrate for rail vehicles based on the microstructure information. The surface of the brake disc substrate for rail vehicles is divided into multiple material property regions. Based on the distribution of the overall material property data of the brake disc substrate for rail vehicles in each material property region, the material property data of each material property region is determined. The material property data of each material property region includes at least the local hardness data and fatigue damage data of the corresponding material property region.

[0038] Specifically, obtaining the microstructure information of the brake disc substrate for rail vehicles aims to comprehensively understand the internal structure and composition of the matrix material. Microstructure information can be understood as the size, shape, distribution, phase composition, and presence of defects within the material's grains; this information is fundamental to determining the material's macroscopic properties. By analyzing these microscopic features, macroscopic material properties such as the overall mechanical and thermal properties of the matrix material can be inferred. For example, scanning electron microscopes and optical microscopes can be used to observe and analyze the cross-section of the matrix material, combined with energy dispersive spectroscopy (EDS) analysis to obtain detailed microstructure information.

[0039] Furthermore, the surface of the brake disc substrate for rail vehicles is divided into multiple material property regions to achieve a refined and localized assessment of the substrate material properties. During service, different regions of the brake disc may experience varying stresses and thermal loads, leading to localized differences in material properties. By dividing the surface into regions, material property data for each region can be obtained specifically, thus more accurately reflecting the actual condition of the substrate surface. For example, the surface can be divided into several grid-like or irregularly shaped regions based on the brake disc's geometry, stress characteristics, or historical damage records.

[0040] The material property data for each material property region includes at least local hardness data and fatigue damage data for that region. Local hardness data is an important indicator of a material's resistance to plastic deformation; changes in local hardness may indicate phase transformation, strengthening, or softening of the material. Fatigue damage data reflects the degree of damage accumulated under cyclic loading and is a key parameter for assessing the material's remaining life and remanufacturing feasibility. By acquiring this local data, potential defect areas or weak points on the substrate surface can be accurately identified, providing precise input information for subsequent additive remanufacturing. For example, local hardness data can be measured using a microhardness tester, while fatigue damage data can be evaluated using non-destructive testing methods such as ultrasonic testing and eddy current testing combined with damage models.

[0041] This application's solution acquires the microstructure information of the brake disc substrate for rail vehicles, thereby enabling a comprehensive and systematic understanding of the overall performance of the substrate material. Based on this, the substrate surface is further divided into multiple material characteristic regions, and refined material characteristic data, including local hardness and fatigue damage data, are acquired for each region. This layered and localized data acquisition method allows the analysis of substrate material characteristics to extend beyond the macroscopic level, delving into the microstructure and performance differences in local areas. Consequently, the subsequent analysis and inference module can perform more precise matching and difference analysis based on more accurate and targeted material characteristic data and real-time monitored molten pool solidification front morphology data, thereby more accurately identifying the root cause of local thermal anomalies in the molten pool, such as whether it is due to a localized high-hardness phase transformation in the substrate or fatigue damage. This refined data input provides a solid foundation for the subsequent optimization and adjustment of additive remanufacturing process parameters, ensuring the accuracy and effectiveness of the optimization adjustments.

[0042] Specifically, obtaining the microstructure information of the brake disc substrate for the aforementioned rail vehicles may include the following steps: The laser-induced ultrasonic spectrum analysis device scans the brake disc substrate of the rail vehicle. The pulse laser of the laser-induced ultrasonic spectrum analysis device emits laser pulses to generate ultrasonic signals on the brake disc substrate of the rail vehicle. A piezoelectric sensor is installed on the light spot formed on the surface of the brake disc substrate of a rail vehicle to obtain the ultrasonic signal excited on the material surface by the laser pulse emitted by the pulse laser of the laser-induced ultrasonic spectrum analysis device. The acquired ultrasonic signals are subjected to spectral analysis using Fourier transform to extract the acoustic feature information of the ultrasonic signals; The acoustic feature information is compared with the preset acoustic feature information in the preset database of brake disc matrix material of rail vehicles to determine the microstructure information of the current scanning area.

[0043] The laser-induced ultrasonic spectrum analysis device is a non-contact detection equipment. Its core lies in using laser pulses to excite ultrasonic waves on the surface of materials and analyzing the characteristics of these ultrasonic waves to infer the internal structure and properties of the materials. A pulsed laser is used to emit high-energy, short-duration laser pulses. When these laser pulses act on the surface of the brake disc substrate for rail vehicles, they cause rapid local heating and expansion of the material, thereby generating broadband ultrasonic signals within the material. The generated ultrasonic signals propagate within the material, and their propagation speed, attenuation characteristics, and scattering behavior are affected by the material's microstructure (such as grain size, grain boundaries, and defects). A piezoelectric sensor is placed in the laser pulse's spot area near the point of application to receive and convert the laser-excited ultrasonic signals. This sensor can convert mechanical vibrations (ultrasonic waves) into measurable electrical signals. Performing a Fourier transform on the acquired ultrasonic signals converts them from the time domain to the frequency domain, revealing the frequency components and intensity distribution of the ultrasonic signals. This spectral analysis helps identify specific acoustic features associated with the material's microstructure. Acoustic characteristics can include parameters such as the center frequency, bandwidth, attenuation coefficient, and frequency shift of ultrasonic signals. These parameters directly reflect the microscopic properties of a material, such as its elastic modulus, density, grain size, and internal defects. A pre-stored database of microstructures for rail vehicle brake disc matrix materials contains standard acoustic characteristics for different microstructure types (e.g., pearlite, ferrite, martensite, etc.). By comparing the real-time extracted acoustic characteristics with the pre-stored information in the database, accurate determination of the microstructure of the currently scanned area can be achieved. Microstructure information refers to the grain structure, phase composition, grain boundary morphology, and defect distribution of a material at the microscale. This information is crucial for evaluating the material's mechanical properties, fatigue life, and suitability for additive remanufacturing.

[0044] S120: Additive remanufacturing of brake disc substrate for rail vehicles, and real-time monitoring of the solidification front morphology of the molten pool of the brake disc substrate during the additive remanufacturing process.

[0045] Additive remanufacturing is a technology that repairs or manufactures parts by depositing materials layer by layer. In this application, it specifically refers to the repair of damaged brake discs using technologies such as laser cladding. The solidification front morphology data of the molten pool refers to information such as the geometry and grain growth state of the molten pool formed by laser melting of powder at the solidification front during the additive remanufacturing process. Real-time monitoring and analysis of this data are crucial for understanding and controlling the additive manufacturing process.

[0046] In the additive remanufacturing process of brake disc substrates for rail vehicles, it is necessary to monitor the morphological characteristics of the solidification front in real time. One approach is to install a high-speed camera on the additive remanufacturing equipment to continuously capture video or image sequences of the solidification front. These images are then manually observed to identify the shape of the solidification front, the presence of any abnormal features such as depressions or protrusions, and these characteristic data are manually recorded. Another approach is to use an infrared thermal imager to monitor the molten pool and infer the morphological characteristics of the solidification front by analyzing the temperature distribution on the molten pool surface. For example, the temperature gradient change at the solidification front can reflect its geometry and grain growth.

[0047] In some embodiments of this application, the following steps are used to achieve real-time monitoring of the morphological characteristics of the molten pool solidification front during the additive remanufacturing process of the brake disc substrate for rail vehicles: Image acquisition equipment is deployed above the molten pool in additive remanufacturing to acquire real-time images of the morphology of the molten pool solidification front.

[0048] In the additive remanufacturing process, an image acquisition device is positioned above the molten pool. This device can be understood as a mechanism capable of capturing visual information about the molten pool area, such as a high-speed camera, infrared thermal imager, or CCD camera. Its purpose is to acquire dynamic images of the molten pool's solidification front in real time, providing raw data for subsequent morphological feature analysis. Real-time acquisition ensures effective capture of transient changes during the additive remanufacturing process.

[0049] The image of the solidification front morphology of the molten pool is preprocessed, including grayscale conversion and contrast enhancement.

[0050] Preprocessing aims to eliminate image noise and enhance image features for subsequent accurate analysis. Specifically, preprocessing methods include grayscale conversion and contrast enhancement. Grayscale conversion converts a color image to a grayscale image, simplifying image data, reducing computational complexity, and preserving the image's brightness information. Contrast enhancement adjusts the image's brightness range to make the grayscale differences between different regions of the image more pronounced, thereby highlighting the detailed features of the molten pool solidification front. This can be achieved through methods such as histogram equalization or gamma correction.

[0051] Using an edge algorithm, the solidification front contour of the molten pool is extracted based on the preprocessed image of the solidification front morphology.

[0052] After image preprocessing, edge detection algorithms are used to process the preprocessed image of the molten pool solidification front morphology to extract the molten pool solidification front contour. Edge detection algorithms can be understood as an image processing technique used to identify the boundaries of regions in an image where brightness or color changes significantly, such as the Canny operator, Sobel operator, or Prewitt operator. By applying these algorithms, the boundary line of the molten pool solidification front can be accurately delineated, separating it from the background and forming clear contour information.

[0053] The extracted solidification front profile was analyzed to determine the morphological characteristics of the solidification front of the molten pool.

[0054] This analysis aims to quantify the geometric and morphological characteristics of the solidification front. For example, the curvature, roughness, length, area, and presence of local depressions, protrusions, or irregular structures of the profile can be calculated and evaluated. These quantified data constitute the morphological characteristics of the molten pool solidification front, providing a basis for subsequent judgments on whether the molten pool solidification state is abnormal.

[0055] In embodiments of the present invention, the types of morphological feature data of the solidification front of the molten pool include normal morphological features and abnormal morphological features. Specifically, when there are local depressions, protrusions, or irregular serrated structures in the solidification front contour, or when the grain growth on the surface of the solidification front contour is abnormal or the grain growth direction on the surface of the solidification front contour is deviated, the data type of morphological feature of the solidification front of the molten pool is determined to be an abnormal morphological feature.

[0056] The extracted solidification front profile was analyzed to determine the morphological characteristics of the molten pool solidification front, specifically including: Geometric feature analysis is performed on the extracted solidification front contour to calculate local curvature and roughness parameters and identify whether there are local depressions, protrusions or irregular serrated structures in the solidification front contour. By analyzing the local brightness gradient changes of the solidification front profile, we can infer whether the grain growth on the surface of the solidification front profile is abnormal and whether the growth direction has shifted.

[0057] Normal morphological characteristics refer to a smooth, continuous morphology of the solidification front of the molten pool that conforms to the expected grain growth pattern, indicating a stable additive remanufacturing process and good material solidification quality. Abnormal morphological characteristics, on the other hand, indicate potential defects or instabilities during the solidification process, such as localized overheating, uneven cooling, or material inhomogeneity.

[0058] Specifically, local depressions, bulges, or irregular serrated structures refer to the irregular geometric shapes exhibited at the microscopic scale of the solidification front profile. These shapes are often related to flow instability within the molten pool, uneven heat distribution, or differences in local material properties. For example, local depressions may indicate local shrinkage or incomplete filling of the molten pool, bulges may be related to local overheating or material accumulation, while serrated structures may reflect uneven growth at the solidification interface.

[0059] Abnormal grain growth refers to a significant difference in the size, shape, or distribution of grains at the solidification front surface compared to normal conditions. Examples include abnormally large or small grains, or irregular grain morphology. A shift in grain growth direction means that the preferred growth direction of the grains deviates from the expected direction, which may affect the final mechanical properties of the material.

[0060] In practical applications, geometric feature analysis refers to the quantitative description of the geometry of the solidification front profile using mathematical methods, such as calculating local curvature and roughness parameters. Local curvature reflects the degree of curvature of the profile; high curvature regions may correspond to local stress concentrations or drastic changes in heat gradients. Roughness parameters quantify the unevenness of the profile surface; high roughness may indicate instability at the solidification interface.

[0061] Furthermore, local brightness gradient variation refers to the analysis of the intensity and direction of pixel brightness changes in a solidification front contour image using image processing techniques. Since grain growth and arrangement affect the optical reflection properties of the material surface, changes in brightness gradient can indirectly reflect the grain growth state and direction. For example, a uniform brightness gradient may correspond to regular grain growth, while abrupt brightness gradients may indicate abnormal grain growth or directional deviation.

[0062] This application's solution, through detailed classification and in-depth analysis of the morphological characteristics of the molten pool solidification front, enables more precise identification of the microscopic state of molten pool solidification during additive remanufacturing. Specifically, by analyzing geometric features and calculating local curvature and roughness parameters, the geometric irregularities of the solidification front profile can be quantified, thereby identifying potential local defects. Simultaneously, by analyzing the local brightness gradient changes of the solidification front profile, the growth state and direction of grains can be inferred, which is crucial for evaluating the microstructure and properties of materials. It is precisely this multi-dimensional and refined feature extraction and analysis that allows the monitoring of the molten pool solidification front morphology to move beyond the macroscopic level and delve into the key stages of microstructure formation, providing richer and more accurate data support for subsequent differential analysis and reasoning.

[0063] S130: Based on material property data and molten pool solidification front morphology data, the differences between the brake disc matrix for rail vehicles and the molten pool solidification morphology are analyzed and inferred.

[0064] After acquiring material property data and molten pool solidification front morphology data, it is necessary to analyze and infer the differences between the brake disc substrate for rail vehicles and the molten pool solidification morphology based on this data. One approach is to manually compare the collected material property data and molten pool solidification front morphology data. For example, when an abnormal morphology is observed at the molten pool solidification front, the corresponding material property data for that abnormal area is manually queried to determine whether there is a material anomaly in that area, such as excessively high local hardness or fatigue damage. Then, based on experience, the correlation between these anomalies is determined to infer the cause of the local thermal anomaly in the molten pool.

[0065] This step specifically includes: Based on the morphological feature data of the solidification front of the molten pool, determine whether the morphological feature data of the solidification front of the molten pool of the brake disc substrate for rail vehicles is an abnormal morphological feature. If it is determined that there is an abnormality in the morphology of the solidification front of the molten pool, then query the material property data corresponding to the area where the morphology of the solidification front of the molten pool is abnormal, and determine whether the area where the morphology of the solidification front of the molten pool is abnormal is an area with abnormal material properties. Specifically, if the local hardness data in the material property data of one of the material property abnormality areas is greater than the preset local hardness data threshold, then the abnormality type of the corresponding material property abnormality area is high hardness phase transition; if the fatigue damage data in the material property data of one of the material property abnormality areas is greater than the preset fatigue damage data, then the abnormality type of the corresponding material property abnormality area is fatigue damage. Based on the morphology of the solidification front of the molten pool in the brake disc substrate for rail vehicles and the abnormal conditions in the region where the solidification front of the molten pool is located, the cause of the local thermal anomaly in the molten pool is inferred.

[0066] Specifically, during the analysis and reasoning process, the first step is to determine whether the current morphology of the molten pool solidification front exhibits abnormal characteristics based on the real-time monitored morphological features. Abnormal morphological features can be understood as geometric shapes or grain growth patterns that deviate from the normal, ideal solidification state. For example, they may manifest as local depressions, protrusions, irregular serrated structures, or abnormal grain growth or a shift in growth direction. Once an abnormal morphology is identified at the molten pool solidification front, the system further queries the matrix material property data corresponding to the region with the abnormal morphology. This step aims to determine whether the abnormal region is also an abnormal region in terms of material properties. The criteria for judging abnormal material property regions are based on preset thresholds. For example, when the local hardness data of a certain abnormal material property region exceeds a preset local hardness data threshold, the abnormal type of that region is determined to be a high-hardness phase transition; when the fatigue damage data of that region exceeds a preset fatigue damage data, it is determined to be fatigue damage. By combining the abnormal morphology of the molten pool solidification front with the abnormal material properties of its region, the system can more accurately infer the specific causes of local thermal anomalies in the molten pool.

[0067] This application's solution overcomes the limitations of single-source data analysis by deeply integrating and cross-validating real-time monitoring data of the molten pool solidification front with pre-analyzed material property data of the matrix. When anomalies occur at the molten pool solidification front, the analysis goes beyond simply identifying the anomaly; it traces its correlation with the matrix material properties. For example, if the molten pool solidification front exhibits a contraction or serrated morphology, and the matrix material in that region displays a high-hardness phase transformation, it can be reasonably inferred that the laser energy is insufficient to fully melt this high-hardness region. Conversely, if the molten pool solidification front shows expansion or abnormally coarse grains, and fatigue damage exists in that region, it may indicate excessive laser energy leading to localized overheating. This analytical reasoning mechanism based on multi-source data correlation makes the diagnosis of localized thermal anomalies during additive remanufacturing more accurate and in-depth, providing a clear direction and basis for subsequent process parameter adjustments.

[0068] In some preferred embodiments, assuming that during additive remanufacturing of the brake disc substrate for rail vehicles, real-time monitoring reveals a significant contraction or serrated structure at the solidification front of the molten pool in a localized area, which is identified as an abnormal morphology. The system then queries the material property data corresponding to this abnormal area and finds that the local hardness data is significantly higher than a preset local hardness threshold, thus determining that a high-hardness phase transition is present in this area. Based on the contraction morphology of the molten pool solidification front and the high-hardness phase transition in the matrix, the system infers that the cause of the localized thermal anomaly in the molten pool is insufficient laser energy to fully melt the high-hardness phase transition region. As another specific implementation, if during additive remanufacturing, an expansion or abnormally coarse grain morphology is detected at the molten pool solidification front, and fatigue damage is found in the matrix material of that area, the system analyzes and infers that the cause of the localized thermal anomaly is excessive laser energy leading to localized overheating. These specific analytical and reasoning results will directly guide the optimization and adjustment of subsequent additive remanufacturing process parameters. For example, increasing laser power or decreasing scanning speed to increase heat input, or decreasing laser power or increasing scanning speed to reduce heat input, thereby achieving precise control of the additive remanufacturing process.

[0069] In some embodiments described above, this application proposes inferring the causes of localized thermal anomalies in the molten pool based on the morphology of the solidification front of the brake disc substrate for rail vehicles and anomalies in the region where the solidification front is located. However, in practical applications, the causes of localized thermal anomalies in the molten pool can be diverse, and their manifestations are closely related to factors such as the properties of the substrate material and the laser energy input. If only a general anomaly assessment is made, the specific root cause of the thermal anomaly may not be accurately identified, thus affecting the targetedness and effectiveness of subsequent process parameter optimization adjustments. For example, anomalies in the morphology of the solidification front may be caused by insufficient laser energy, excessive laser energy, or even by uneven laser spot energy distribution or abnormal scanning path. These different causes require different optimization strategies.

[0070] In response, this application further proposes, based on the morphology of the molten pool solidification front and the anomalies in the region where the molten pool solidification front is located in the aforementioned brake disc substrate for rail vehicles, inferring the causes of local thermal anomalies in the molten pool, specifically including: When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front contraction or sawtooth morphology, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormality type of the abnormal area is high hardness phase transformation, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the laser energy is insufficient to fully melt the high hardness phase transformation area. When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally coarse grains, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormality type of the abnormal area is fatigue damage, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: excessive laser energy leads to local overheating. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front contraction or sawtooth morphology, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the energy distribution of the laser spot is locally low. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally large grains, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: the energy distribution of the laser spot is locally too high. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is the deviation of the grain growth direction, and there is no abnormality in the area where the solidification front of the molten pool is located, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: uneven distribution of laser spot energy or abnormal scanning path. Wherein, the first preset melt pool size threshold is less than the second preset melt pool size threshold, and the melt pool size between the first preset melt pool size threshold and the second preset melt pool size threshold is the normal melt pool size.

[0071] Abnormalities in the morphology of the solidification front of the molten pool, such as contraction or serrated morphology, typically indicate insufficient melt fluidity or uneven solidification, possibly related to insufficient local heat input. Expansion of the solidification front or abnormally coarse grains may indicate excessive local heat input, leading to overheating of the molten pool or excessively slow cooling rates. Deviation in grain growth direction may be related to uneven laser spot energy distribution or improper scanning path planning, affecting the directional growth of grains. Abnormalities in the aforementioned regions, such as high-hardness phase transformation, refer to a phase transformation in the matrix material in that region, forming a harder structure, which may alter the absorption and melting characteristics of laser energy in that region. Fatigue damage indicates the presence of microcracks or structural deterioration in the matrix material in that region, and its thermophysical properties may differ from normal regions. The molten pool size is a key indicator for measuring the laser energy input and the degree of material melting; a size smaller than a first preset molten pool size threshold usually indicates insufficient energy, while a size larger than a second preset molten pool size threshold may indicate excessive energy. The molten pool size between the first preset molten pool size threshold and the second preset molten pool size threshold is defined as the normal molten pool size, providing a benchmark for judging whether the molten pool size is abnormal.

[0072] This application's solution comprehensively analyzes and matches information from three dimensions: the morphological characteristics of the molten pool solidification front, the abnormal material properties in the region where the molten pool solidification front is located, and the size of the molten pool. This constructs a more refined and accurate mechanism for analyzing and reasoning about the causes of local thermal anomalies. For example, when the molten pool solidification front contracts and the molten pool size is small, and a high-hardness phase transition exists in this region, the system can accurately infer that the laser energy is insufficient to fully melt the high-hardness phase transition region, rather than simply indicating insufficient energy. This multi-factor cross-validation and logical reasoning makes the judgment of the cause of thermal anomalies more specific and targeted, thereby avoiding optimization deviations caused by ambiguous cause judgments.

[0073] In an embodiment of the present invention, assuming that during additive remanufacturing of a brake disc substrate for rail vehicles, real-time monitoring reveals that the solidification front morphology of a certain local area exhibits significant shrinkage, and the measured melt pool size is 150 micrometers, which is less than a preset first preset melt pool size threshold (e.g., 180 micrometers). Simultaneously, preliminary material property analysis reveals that the matrix material in this local area undergoes a high-hardness phase transition, with its local hardness data far exceeding a preset local hardness data threshold. Based on the above information, the analysis and reasoning module of this application will comprehensively determine that the cause of this local thermal anomaly is insufficient laser energy to fully melt the high-hardness phase transition region. As another specific implementation, if abnormally coarse grains are detected in the solidification front morphology of another region, with a measured melt pool size of 300 micrometers, which is greater than a preset second preset melt pool size threshold (e.g., 250 micrometers), and no significant material property anomalies are found in the matrix material of this region, then the system will infer that the cause of the local thermal anomaly is a locally high laser spot energy distribution. These specific reasoning results will directly guide subsequent adjustments to process parameters. For example, in the first case, increase the laser emission power and decrease the scanning speed, and in the second case, decrease the laser emission power and increase the scanning speed, in order to achieve precise process optimization.

[0074] S140: Based on the analysis and reasoning results, the additive remanufacturing process parameters of the brake disc substrate for rail vehicles are optimized and adjusted.

[0075] Based on the analytical reasoning results, the additive remanufacturing process parameters for the brake disc substrate of rail vehicles are optimized and adjusted. One approach is for operators to manually adjust the process parameters of the additive remanufacturing equipment, such as laser power, scanning speed, and powder feeding rate, according to the reasons derived from manual analysis and reasoning. For example, if the reasoning results indicate that insufficient laser energy is causing incomplete melting in certain areas, the operator can manually increase the laser power or decrease the scanning speed.

[0076] This application proposes an optimization method for the additive remanufacturing process of brake discs for rail vehicles. By deeply analyzing the material properties of the brake disc substrate and combining this with real-time monitoring of the solidification front morphology of the molten pool during the additive remanufacturing process, it achieves refined control of the process. The method first acquires material property data of the brake disc substrate, providing fundamental information for subsequent additive remanufacturing. During the process, real-time monitoring of the solidification front morphology data of the molten pool enables timely detection of abnormal behavior. Subsequently, based on these two types of data, the differences between the solidification morphology of the substrate and the molten pool are analyzed and reasoned to accurately identify the causes of localized thermal anomalies in the molten pool. For example, when an abnormal morphology appears at the solidification front of the molten pool, by querying the material property data of the corresponding area, it can be determined whether the problem is caused by abnormal substrate material (such as high-hardness phase transformation or fatigue damage) or by uneven laser energy distribution. Finally, based on the analysis and reasoning results, the additive remanufacturing process parameters are specifically optimized and adjusted, such as adjusting laser power, scanning speed, or scanning path, to correct abnormal behavior of the molten pool and ensure the quality and performance of the remanufactured layer.

[0077] Specifically, this step includes: The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is insufficient to fully melt the high-hardness phase transition region or the laser spot energy distribution is locally low, the laser energy is increased and the laser heat input is increased by increasing the emission power of the pulsed laser emitting laser to the current region and decreasing the scanning speed of the pulsed laser emitting laser to the current region. The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is excessive, causing local overheating, or when the laser spot energy distribution is locally too high, the laser energy is reduced and the laser heat input is reduced by decreasing the emission power of the pulsed laser emitting laser to the current area and increasing the scanning speed of the pulsed laser emitting laser to the current area. The analysis and reasoning for the cause of local thermal anomalies in the molten pool is that when the laser spot energy distribution is uneven or the scanning path is abnormal, the grain growth direction can be corrected by adjusting the local angle or overlap rate of the laser scanning path.

[0078] Specifically, when analysis and reasoning indicate that localized thermal anomalies in the molten pool are due to insufficient laser energy to fully melt the high-hardness phase transition region, or because the laser spot energy distribution is low in a localized area, it is necessary to increase the laser heat input to that area to effectively solve the problem. This can be achieved by simultaneously increasing the emission power of the pulsed laser and decreasing its scanning speed. Increasing the emission power directly increases the energy carried by the laser beam per unit time, while decreasing the scanning speed prolongs the laser beam's interaction time in a specific area. The combination of these two measures can significantly improve the energy density and total heat input in the localized area, ensuring that the high-hardness phase transition region can be fully melted, or compensating for insufficient localized energy distribution.

[0079] When the analysis indicates that localized thermal anomalies in the molten pool are due to excessive laser energy causing localized overheating, or that the laser spot energy distribution is excessively high in a localized area, it is necessary to reduce the laser heat input to that area to avoid material overheating, excessive grain coarsening, or other thermal damage. This can be achieved by reducing the emission power of the pulsed laser and increasing its scanning speed. Reducing the emission power directly decreases the laser energy, while increasing the scanning speed shortens the laser beam's interaction time in a specific area. The synergistic effect of these two measures effectively reduces the energy density and total heat input in the localized area, thereby preventing localized overheating.

[0080] In practical applications, when analysis and reasoning indicate that localized thermal anomalies in the molten pool are due to uneven laser spot energy distribution or abnormal scanning paths, causing grain growth directions to deviate from expectations, fine adjustments to the laser scanning strategy are necessary to correct these microstructural defects. This specifically includes adjusting the local angle or overlap rate of the laser scanning path. By changing the scanning angle, the heat flux gradient can be redirected, guiding grain growth along the desired direction; by adjusting the overlap rate, the energy distribution between adjacent scan lines can be optimized, eliminating grain growth anomalies caused by uneven energy distribution, thereby ensuring that the microstructure of the additive remanufactured layer meets design requirements.

[0081] In some preferred embodiments, a specific example is given below. Suppose that during the additive remanufacturing of a brake disc substrate for rail vehicles, real-time monitoring reveals localized shrinkage at the solidification front of the molten pool, and the molten pool size is smaller than a first preset molten pool size threshold. Simultaneously, material property analysis reveals a high-hardness phase transition in this region. Based on this information, the analysis and inference module infers that the cause of the localized thermal anomaly in the molten pool is insufficient laser energy to fully melt the high-hardness phase transition region. At this point, the optimization and adjustment module immediately responds by increasing the emission power of the pulsed laser emitting the laser into the current region, for example, from 200W to 250W, while simultaneously reducing the scanning speed, for example, from 1000mm / s to 800mm / s. This coordinated adjustment increases the laser heat input to the region, ensuring that the high-hardness phase transition region can be fully melted, thereby correcting the abnormal morphology of the molten pool solidification front.

[0082] For example, if in another region, local expansion of the solidification front morphology of the molten pool is detected, and the molten pool size exceeds a second preset molten pool size threshold, and material property analysis indicates fatigue damage in this region, the analysis and inference module infers that the cause of the local thermal anomaly in the molten pool is excessive laser energy leading to local overheating. To address this issue, the optimization and adjustment module reduces the emission power of the pulsed laser emitting the laser into the current region, for example, from 200W to 180W, and increases the scanning speed, for example, from 1000mm / s to 1200mm / s. This adjustment effectively reduces local heat input, preventing material overheating and excessive grain coarsening.

[0083] Specifically, when a deviation in grain growth direction is detected at the solidification front of the molten pool, but the material properties data for that region show no abnormalities, the analysis and inference module deduces that the cause of the local thermal anomaly in the molten pool is uneven laser spot energy distribution or an abnormal scanning path. In this case, the optimization and adjustment module adjusts the local angle of the laser scanning path, for example, by a fine adjustment of 5 degrees, or adjusts the overlap rate, for example, from 50% to 55%. In this way, the grain growth direction can be effectively corrected, ensuring that the microstructure of the repair layer is uniform and meets expectations.

[0084] In some of the embodiments described above in this application, a scheme for optimizing and adjusting the additive remanufacturing process parameters of the brake disc substrate for rail vehicles based on analytical reasoning results was proposed. However, in its implementation, there is a lack of precise quantitative calculation methods for the specific adjustment amounts of laser emission power and scanning speed. If adjustments are made solely based on experience, the adjustment amounts may be too large or too small, thereby causing fluctuations in the molten pool size, overshoot, or oscillations, affecting the stability of the additive remanufacturing process and the quality of the final product.

[0085] In response, this application further proposes an adjustment amount of the emission power of a pulsed laser that emits laser light into the current region. Calculated using the following formula: in, This refers to the proportional gain of the PID controller for the pulsed laser. The integral coefficient of the PID controller for the pulsed laser is... It is the target molten pool size. This is the current molten pool size; This indicates the current moment when the additive remanufacturing process for brake discs used in rail vehicles is being optimized. The scanning speed adjustment of a pulsed laser that emits laser light into the current area. Calculated using the following formula: in, represents the differential coefficient of the PID controller for the pulsed laser.

[0086] Specifically, the aforementioned transmit power adjustment amount The calculation employs the PID (Proportional-Integral-Derivative) control principle. Among other things, It is a scaling factor used to reflect the current molten pool size. With the target molten pool size The immediate impact of the error between them is that the larger the error, the greater the contribution of the proportional term, thus providing a rapid adjustment response; It is the integral coefficient, used to eliminate the steady-state error of the system. It gradually reduces and eventually eliminates the residual error by accumulating historical errors, ensuring that the molten pool size can be stabilized near the target value. Represents the desired molten pool size. This represents the real-time monitored size of the molten pool. By calculating the absolute value of the difference between the two, the correctness of the adjustment direction can be ensured; that is, regardless of whether the current molten pool size is too large or too small, the adjustment amount will be directed in the direction of reducing the error.

[0087] Furthermore, the scanning speed adjustment amount The calculation also incorporates the PID control concept, in which... These are differential coefficients, used to reflect the impact of errors. They can predict the trend of error changes, thus allowing for early adjustments and improving the system's response speed and stability. By differentiating the error, system oscillations can be effectively suppressed, and overshoot can be avoided. These adjustment quantities... and The calculations provide a quantitative basis for the precise adjustment of additive remanufacturing process parameters, enabling the system to dynamically and intelligently adjust the laser power and scanning speed based on the real-time feedback of the molten pool size.

[0088] Compared with existing technologies, the core innovation of this application lies in combining matrix material property analysis with real-time monitoring of the morphology of the molten pool solidification front, and then performing intelligent analysis and reasoning and process parameter optimization based on this. Existing technologies often rely on molten pool temperature sensor data, but this data tends to "smooth out" microscopic fluctuations, making it difficult to identify deep-seated quality problems. This application, by obtaining more refined material property data and molten pool solidification front morphology feature data, can more accurately diagnose the causes of local thermal anomalies in the molten pool. For example, when local depressions or abnormal grain growth occur at the molten pool solidification front, this application can further analyze the matrix material properties in that area, thereby distinguishing whether the problem lies with the matrix itself or with the laser energy distribution. This refined diagnostic capability makes process parameter adjustments more targeted, avoiding the negative impact of blind adjustments. Through this optimization method, the problems of unstable remanufactured layer quality, manufacturing precision deviations, and difficulties in energy consumption control caused by uneven laser energy distribution and differences in matrix structure in existing technologies can be effectively solved, significantly improving the quality and efficiency of additive remanufacturing of brake discs for rail vehicles.

[0089] like Figure 2 As shown, the present invention also provides an optimization system for the additive remanufacturing process of brake discs for rail vehicles, comprising: The material property data acquisition module 210 is used to perform material property analysis on the brake disc substrate for rail vehicles and acquire the material property data of the brake disc substrate for rail vehicles. The molten pool solidification front morphology feature data monitoring module 220 is used to monitor the molten pool solidification front morphology feature data of the brake disc substrate for rail vehicles in real time during the additive remanufacturing process. The analysis and reasoning module 230 is used to analyze and reason about the differences between the brake disc substrate for rail vehicles and the solidification morphology of the molten pool based on material property data and molten pool solidification front morphology data. The optimization and adjustment module 240 is used to optimize and adjust the additive remanufacturing process parameters of the brake disc substrate for rail vehicles based on the analysis and reasoning results.

[0090] This application proposes an optimization system for the additive remanufacturing process of brake discs for rail vehicles. Through integrated modular design, it aims to solve problems such as unstable remanufactured layer quality, manufacturing precision deviations, and difficulties in energy consumption control caused by uneven laser energy distribution and differences in substrate material properties during traditional additive remanufacturing. The system uses a material property data acquisition module to comprehensively analyze the brake disc substrate, providing accurate substrate state information for subsequent additive remanufacturing. Simultaneously, a molten pool solidification front morphology monitoring module captures the dynamic changes of the molten pool in real time during the additive remanufacturing process. Subsequently, an analysis and reasoning module deeply integrates and intelligently analyzes these two key data sets to accurately diagnose the root causes of localized thermal anomalies in the molten pool. Finally, an optimization and adjustment module makes precise and real-time feedback adjustments to the additive remanufacturing process parameters based on the analysis and reasoning results, thereby ensuring the stability of the remanufacturing process and the repair quality, effectively improving the service performance and remanufacturing efficiency of the brake disc.

[0091] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An optimized method for the additive remanufacturing process of brake discs for rail vehicles, characterized in that, include: Material property analysis is performed on the brake disc substrate for rail vehicles to obtain material property data of the brake disc substrate for rail vehicles, including: Obtain the microstructure information of the brake disc substrate for rail vehicles, and determine the overall material properties data of the brake disc substrate for rail vehicles based on the microstructure information of the brake disc substrate for rail vehicles. The surface of the brake disc substrate for rail vehicles is divided into multiple material property regions, and the material property data of each material property region is determined based on the distribution of the overall material property data of the brake disc substrate for rail vehicles in each material property region; wherein, the material property data of each material property region includes at least the local hardness data and fatigue damage data of the corresponding material property region. The brake disc substrate for rail vehicles is subjected to additive remanufacturing, and the morphological characteristics of the molten pool solidification front of the brake disc substrate during the additive remanufacturing process are monitored in real time, including: Image acquisition equipment is deployed above the molten pool in additive remanufacturing to acquire images of the solidification front morphology of the molten pool in real time. The image of the solidification front morphology of the molten pool is preprocessed, wherein the preprocessing method includes grayscale conversion and contrast enhancement; Using edge detection algorithms, the solidification front contour of the molten pool is extracted based on the preprocessed image of the solidification front morphology. The extracted solidification front contour was analyzed to determine the morphological characteristics of the solidification front of the molten pool. Based on the material property data and the solidification front morphology data of the molten pool, the differences between the brake disc substrate for rail vehicles and the solidification front morphology of the molten pool are analyzed and inferred, including: Based on the morphological feature data of the solidification front of the molten pool, determine whether the morphological feature data of the solidification front of the molten pool of the brake disc substrate for rail vehicles is an abnormal morphological feature. If it is determined that there is an abnormality in the morphology of the solidification front of the molten pool, then query the material property data corresponding to the area where the morphology of the solidification front of the molten pool is abnormal, and determine whether the area where the morphology of the solidification front of the molten pool is abnormal is an area with abnormal material properties. Specifically, if the local hardness data in the material property data of one of the material property abnormal regions is greater than the preset local hardness data threshold, then the abnormality type of the corresponding material property abnormal region is high hardness phase transition; if the fatigue damage data in the material property data of one of the material property abnormal regions is greater than the preset fatigue damage data threshold, then the abnormality type of the corresponding material property abnormal region is fatigue damage. Based on the morphology of the solidification front of the molten pool in the brake disc substrate of the rail vehicle and the abnormal conditions in the area where the solidification front of the molten pool is located, the cause of the local thermal anomaly in the molten pool is inferred. Based on the analysis and reasoning results, the additive remanufacturing process parameters of the brake disc substrate for rail vehicles are optimized and adjusted.

2. The optimized method for additive remanufacturing of brake discs for rail vehicles according to claim 1, characterized in that, Obtaining the microstructure information of the brake disc substrate for the rail vehicle includes: The brake disc substrate of the rail vehicle is scanned by a laser-induced ultrasonic spectrum analysis device. The pulse laser of the laser-induced ultrasonic spectrum analysis device emits laser pulses to generate ultrasonic signals on the brake disc substrate of the rail vehicle. A piezoelectric sensor is installed on the light spot formed on the surface of the brake disc substrate of the rail vehicle to obtain the ultrasonic signal excited on the material surface by the laser pulse emitted by the pulse laser of the laser-induced ultrasonic spectrum analysis device. The acquired ultrasonic signals are subjected to spectral analysis using Fourier transform to extract the acoustic feature information of the ultrasonic signals; The acoustic feature information is compared with the preset acoustic feature information in the preset database of brake disc matrix material for rail vehicles to determine the microstructure information of the current scanning area.

3. The method for optimizing the additive remanufacturing process of brake discs for rail vehicles according to claim 1, characterized in that, The types of morphological feature data of the solidification front of the molten pool include: normal morphological features and abnormal morphological features; wherein, when there are local depressions, protrusions or irregular serrated structures in the solidification front contour, when the grain growth on the surface of the solidification front contour is abnormal or when the grain growth direction on the surface of the solidification front contour is deviated, the data type of the morphological feature data of the solidification front of the molten pool is abnormal morphological features. The extracted solidification front profile was analyzed to determine the morphological characteristics of the molten pool solidification front, including: Geometric feature analysis is performed on the extracted solidification front contour to calculate local curvature and roughness parameters, and to identify whether there are local depressions, protrusions or irregular serrated structures in the solidification front contour. By analyzing the local brightness gradient changes of the solidification front profile, it can be inferred whether the grain growth on the surface of the solidification front profile is abnormal and whether the growth direction has shifted.

4. The optimized method for additive remanufacturing of brake discs for rail vehicles according to claim 1, characterized in that, Based on the morphology of the solidification front of the molten pool in the brake disc substrate of the rail vehicle and the anomalies in the region where the solidification front is located, the causes of the local thermal anomalies in the molten pool are inferred, including: When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is an abnormal morphology, and the abnormal type of the abnormal morphology is solidification front contraction or sawtooth morphology, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormal type of the abnormal area is high hardness phase transformation, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: the laser energy is insufficient to fully melt the high hardness phase transformation area. When the solidification front morphology of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally coarse grains, the area where the solidification front of the molten pool is located is an abnormal area, and the abnormality type of the abnormal area is fatigue damage, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is: excessive laser energy leads to local overheating. When the solidification front morphology of the molten pool of the brake disc substrate for the rail vehicle is an abnormal morphology feature, and the abnormal type of the abnormal morphology feature is a shrinkage or sawtooth morphology of the solidification front, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is smaller than the first preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: the energy distribution of the laser spot is locally low. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is solidification front expansion or abnormally large grains, there is no abnormality in the area where the solidification front of the molten pool is located, and the size of the molten pool is greater than the second preset molten pool size threshold, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: the energy distribution of the laser spot is locally too high. When the morphology of the solidification front of the molten pool of the brake disc substrate for rail vehicles is abnormal, and the abnormality type of the abnormal morphology is the deviation of the grain growth direction, and there is no abnormality in the area where the solidification front of the molten pool is located, the reason for the local thermal anomaly of the molten pool is analyzed and reasoned as follows: uneven distribution of laser spot energy or abnormal scanning path. Wherein, the first preset molten pool size threshold is less than the second preset molten pool size threshold, and the molten pool size between the first preset molten pool size threshold and the second preset molten pool size threshold is the normal molten pool size.

5. The optimized method for additive remanufacturing of brake discs for rail vehicles according to claim 4, characterized in that, Based on the analysis and reasoning results, the additive remanufacturing process parameters of the brake disc substrate for rail vehicles are optimized and adjusted, including: The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is insufficient to fully melt the high-hardness phase transition region or the laser spot energy distribution is locally low, the laser energy is increased and the laser heat input is increased by increasing the emission power of the pulsed laser emitting laser to the current region and decreasing the scanning speed of the pulsed laser emitting laser to the current region. The reasoning for the local thermal anomaly in the molten pool is that when the laser energy is excessive, causing local overheating, or when the laser spot energy distribution is locally too high, the laser energy is reduced and the laser heat input is reduced by decreasing the emission power of the pulsed laser emitting laser to the current area and increasing the scanning speed of the pulsed laser emitting laser to the current area. The analysis and reasoning for the cause of local thermal anomalies in the molten pool is that when the laser spot energy distribution is uneven or the scanning path is abnormal, the grain growth direction can be corrected by adjusting the local angle or overlap rate of the laser scanning path.

6. The optimized method for additive remanufacturing of brake discs for rail vehicles according to claim 5, characterized in that, The amount of pulsed laser emission power adjustment that emits laser light into the current region. Calculated using the following formula: in, This refers to the proportional gain of the PID controller for the pulsed laser. The integral coefficient of the PID controller for the pulsed laser is... It is the target molten pool size. This is the current molten pool size; This indicates the current moment when the additive remanufacturing process for brake discs used in rail vehicles is being optimized. The scanning speed adjustment of a pulsed laser that emits laser light into the current area. Calculated using the following formula: in, represents the differential coefficient of the PID controller for the pulsed laser.

7. A system for optimizing the additive remanufacturing process of brake discs for rail vehicles, wherein the additive remanufacturing process of brake discs for rail vehicles is optimized by means of any one of claims 1-6, characterized in that, include: The material property data acquisition module is used to perform material property analysis on the brake disc substrate for rail vehicles and acquire the material property data of the brake disc substrate for rail vehicles, including: Obtain the microstructure information of the brake disc substrate for rail vehicles, and determine the overall material properties data of the brake disc substrate for rail vehicles based on the microstructure information of the brake disc substrate for rail vehicles. The surface of the brake disc substrate for rail vehicles is divided into multiple material property regions. Based on the distribution of the overall material property data of the brake disc substrate in each material property region, the material property data of each material property region is determined. The material property data of each material property region includes at least the local hardness data and fatigue damage data of the corresponding material property region. A molten pool solidification front morphology feature data monitoring module is used to perform additive remanufacturing of the brake disc substrate for rail vehicles, and to monitor the molten pool solidification front morphology feature data of the brake disc substrate for rail vehicles in real time during the additive remanufacturing process, including: Image acquisition equipment is deployed above the molten pool in additive remanufacturing to acquire images of the solidification front morphology of the molten pool in real time. The image of the solidification front morphology of the molten pool is preprocessed, wherein the preprocessing method includes grayscale conversion and contrast enhancement; Using edge detection algorithms, the solidification front contour of the molten pool is extracted based on the preprocessed image of the solidification front morphology. The extracted solidification front contour was analyzed to determine the morphological characteristics of the solidification front of the molten pool. The analysis and reasoning module is used to analyze and reason about the differences between the brake disc substrate for rail vehicles and the solidification front morphology of the molten pool based on the material property data and the solidification front morphology data of the molten pool, including: Based on the morphological feature data of the solidification front of the molten pool, determine whether the morphological feature data of the solidification front of the molten pool of the brake disc substrate for rail vehicles is an abnormal morphological feature. If it is determined that there is an abnormality in the morphology of the solidification front of the molten pool, then query the material property data corresponding to the area where the morphology of the solidification front of the molten pool is abnormal, and determine whether the area where the morphology of the solidification front of the molten pool is abnormal is an area with abnormal material properties. Specifically, if the local hardness data in the material property data of one of the material property abnormal regions is greater than the preset local hardness data threshold, then the abnormality type of the corresponding material property abnormal region is high hardness phase transition; if the fatigue damage data in the material property data of one of the material property abnormal regions is greater than the preset fatigue damage data threshold, then the abnormality type of the corresponding material property abnormal region is fatigue damage. Based on the morphology of the solidification front of the molten pool in the brake disc substrate of the rail vehicle and the abnormal conditions in the area where the solidification front of the molten pool is located, the cause of the local thermal anomaly in the molten pool is inferred. The optimization and adjustment module is used to optimize and adjust the additive remanufacturing process parameters of the brake disc substrate for rail vehicles based on the analysis and reasoning results.

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