Rail laser additive defect detection method and system

Abstract

The present application relates to the technical field of steel rail repair, and provides a steel rail laser additive defect detection method and system, the method comprising: before laser additive repair is carried out on the damaged area of the steel rail, the local area of the steel rail base body is instantaneously heated to form an instantaneous hot spot in the corresponding local area; the thermal radiation attenuation information of the instantaneous hot spot is collected; according to the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated to realize the detection of the damaged area of the steel rail; according to the actual heat dissipation rate, the repair process parameters used for laser additive repair are selected from the pre-stored process parameter combinations; and the repair process parameters are used to perform laser additive repair on the damaged area of the steel rail. The present application has the effect of improving the quality and reliability of the laser additive repair of the steel rail.

Description

Technical Field

[0001] This invention relates to the technical field of rail repair, specifically to a method and system for detecting defects in rail laser additive manufacturing. Background Technology

[0002] In the routine maintenance of railway infrastructure, rails, subjected to heavy train loads and impacts over long periods, commonly suffer from surface damage such as fatigue cracks and wear pits. To efficiently and economically repair this damage, laser additive repair technology, also known as laser cladding, is widely used. This technology restores the integrity of the rail by fusing a new layer of metal onto the damaged area. However, laser cladding is a rapid heating and cooling process, especially in complex field environments where factors such as ambient temperature and wind speed significantly affect the cooling rate of the repaired area. Excessive cooling can lead to the formation of hard and brittle microstructures within the repair layer, generating significant residual stress. These internal defects are undetectable by existing surface optical inspection methods, thus creating a safety hazard of "surface compliance, internal failure."

[0003] Existing online inspection systems can only see the surface of the cladding layer. They are adept at detecting pores or tiny surface cracks because they can directly see these geometric discontinuities. However, they are completely blind to excessive residual stress within the repaired area and undesirable brittle phase structures resulting from rapid cooling. From the monitoring system's images, the repaired surface appears smooth and flawless, leading the system to conclude that the repair quality is acceptable. But in reality, this seemingly perfect repaired area may be filled with unseen internal stresses, like tempered glass, and its microstructure may have become brittle. When the first train passes through this repair point with tremendous impact, these unseen internal defects could instantly expand, causing the repair layer to peel off in large sections, potentially leading to even more serious safety accidents.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] This application discloses a method and system for detecting defects in laser additive manufacturing of rails, aiming to solve the safety hazard problem of "surface qualified, internal failure" caused by the difficulty in effectively detecting internal defects in the repair area and the difficulty in dynamically adjusting the repair process parameters according to the actual situation during the existing laser additive repair process of rails.

[0006] The technical solution of this application is as follows:

[0007] In a first aspect, this application discloses a method for detecting defects in rail laser additive manufacturing, including:

[0008] Before performing laser additive repair on the damaged area of ​​the rail, a local area of ​​the rail substrate is instantaneously heated to create an instantaneous hot spot in the corresponding local area;

[0009] Collect information on the thermal radiation attenuation of instantaneous hotspots;

[0010] Based on the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated to enable the detection of rail damage areas;

[0011] Based on the actual heat dissipation rate, select the repair process parameters for laser additive repair from the pre-stored process parameter combinations;

[0012] Laser additive repair was performed on the damaged areas of the rail using repair process parameters.

[0013] This application, through its technical solution, achieves effective detection of damaged areas in the rail by instantaneously heating a localized area of ​​the rail substrate and collecting information on thermal radiation attenuation before laser additive repair. This allows for the calculation of the actual heat dissipation rate. Based on the detection results, appropriate repair process parameters can be selected, thus avoiding the problem of "surface compliance but internal failure" caused by the inability to detect internal defects in traditional methods, significantly improving repair quality and safety.

[0014] Furthermore, after the step of using repair process parameters to perform laser additive repair on the damaged area of ​​the rail, the procedure also includes:

[0015] During the laser additive repair process, the thermal response of the solidified region behind the molten pool was detected;

[0016] Calculate the instantaneous cooling rate of the solidification zone behind the molten pool based on the thermal response;

[0017] The instantaneous cooling rate is compared with the preset target cooling rate range to obtain the cooling rate deviation;

[0018] Based on the cooling rate deviation, the repair process parameters corresponding to the unrepaired forward path during the laser additive repair process are adjusted to guide the instantaneous cooling rate of the unrepaired forward path back to the target cooling rate range.

[0019] Through this technical solution, this application introduces a real-time cooling rate monitoring and feedback adjustment mechanism in the laser additive repair process, which can dynamically control the cooling rate within the target range, effectively avoiding the formation of brittle tissue and excessive residual stress caused by excessively rapid cooling, and further improving the internal quality and reliability of the repair layer.

[0020] More specifically, in some implementation schemes, the step of detecting the thermal response of the solidified region behind the molten pool during laser additive repair includes:

[0021] During the laser additive repair process, a narrowband filter is set on a high-speed camera to receive thermal radiation signals of a preset specific wavelength.

[0022] By adjusting the exposure time, the high-speed camera's operating state can be adapted to the wide temperature variations in the solidification region behind the molten pool.

[0023] Based on the received thermal radiation signal of a preset specific wavelength and the exposure data of a high-speed camera adapted to a wide range of temperature changes, the thermal response of the solidification region behind the molten pool is detected in real time.

[0024] Through this technical solution, this application achieves accurate and real-time detection of the thermal response of the solidification region behind the molten pool by combining a high-speed camera with a narrow-band filter and exposure time adjustment. This ensures the accuracy of data acquisition under a wide range of temperature variations and provides a reliable data foundation for the accurate calculation of the subsequent cooling rate and the fine adjustment of process parameters.

[0025] Based on the above, this application further proposes a step for detecting rail damage areas by calculating the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot based on thermal radiation attenuation information:

[0026] Linear scanning heating is performed on a local area of ​​the rail substrate to form an instantaneous heat line;

[0027] Collect information on the thermal radiation attenuation of instantaneous hot wires;

[0028] The thermal radiation attenuation information is averaged over a region to obtain the corresponding actual heat dissipation rate.

[0029] Through this technical solution, the present application forms an instantaneous heat line by linear scanning heating and performs regional averaging processing, which can obtain the heat dissipation characteristics of the local area more comprehensively and accurately, improving the accuracy and reliability of rail damage area detection, and is especially suitable for the assessment of large or irregular damage areas.

[0030] Preferably, this application also discloses a method for detecting defects in rail laser additive manufacturing, wherein the steps of using repair process parameters to perform laser additive repair on the damaged area of ​​the rail include:

[0031] During the laser additive repair process, the current position information of the laser additive equipment on the rail substrate is obtained;

[0032] Based on the current location information, obtain the local difference information corresponding to the current location;

[0033] Based on the information on local differences, the repair process parameters were adjusted;

[0034] Using the adjusted repair process parameters, laser additive repair was performed on the current location of the rail damage area.

[0035] Through this technical solution, this application introduces a dynamic adjustment mechanism for process parameters based on local difference information in the laser additive repair process. This mechanism can optimize repair parameters in real time according to the specific conditions of different locations in the rail damage area, thereby significantly improving the adaptability and uniformity of the repair and ensuring the repair quality of complex damage areas.

[0036] Based on the above, this application further proposes that the steps for adjusting the repair process parameters according to local difference information include:

[0037] Based on local difference information, determine the material properties and geometric features of the current repair area;

[0038] Calculate the heat dissipation efficiency of the current repair area based on material properties and geometric characteristics;

[0039] Based on the heat dissipation efficiency, the adjustment amounts for laser power, scanning speed, and powder feeding rate are determined to obtain parameter adjustment information.

[0040] The parameter adjustment information is applied to the repair process parameters to obtain the adjusted repair process parameters.

[0041] Through this technical solution, this application achieves precise and quantitative adjustment of the repair process parameters by accurately determining the material properties, geometric features, and heat dissipation efficiency, and accordingly calculating the adjustment amount of laser power, scanning speed, and powder feeding rate. This greatly improves the control accuracy of the repair process and the stability of the repair quality.

[0042] In some preferred embodiments, after determining the adjustment amounts for laser power, scanning speed, and powder feed rate based on heat dissipation efficiency to obtain parameter adjustment information, the method further includes:

[0043] Obtain real-time environmental parameters for the current repair area;

[0044] Obtain the actual output parameters of the laser additive manufacturing equipment under the current operating conditions;

[0045] The parameter adjustment information is corrected based on heat loss efficiency, real-time environmental parameters, and actual output parameters.

[0046] Through this technical solution, this application, based on parameter adjustment, further considers the influence of real-time environmental parameters and actual equipment output parameters, and corrects the parameter adjustment information, making the adjustment of repair process parameters closer to actual working conditions. This effectively addresses the complexity and uncertainty of the field operation environment, and further improves the robustness and success rate of the repair.

[0047] Based on the above, this application further proposes a step for determining the adjustment amounts of laser power, scanning speed, and powder feeding rate according to heat dissipation efficiency, and obtaining parameter adjustment information, including:

[0048] Based on the heat dissipation efficiency, obtain real-time temperature and stress state information of the current repair area;

[0049] Adjust the corresponding thermophysical parameters based on real-time temperature and stress state information;

[0050] Based on the heat dissipation efficiency and the adjusted thermophysical parameters, the instantaneous mapping relationship between the heat dissipation efficiency and the adjustment amounts of laser power, scanning speed, and powder feeding rate is calculated.

[0051] Based on the instantaneous mapping relationship, the adjustment amounts for laser power, scanning speed, and powder feeding rate are determined to obtain parameter adjustment information.

[0052] Through this technical solution, this application obtains real-time temperature and stress state information, adjusts thermophysical parameters accordingly, and calculates the instantaneous mapping relationship between heat loss efficiency and process parameter adjustment, thereby realizing intelligent and adaptive adjustment of repair process parameters, which greatly improves the accuracy of the repair process and its adaptability to complex working conditions.

[0053] More specifically, in some implementation schemes, the steps for obtaining real-time temperature and stress state information of the current repair area based on heat dissipation efficiency include:

[0054] Collect temperature information for the currently repaired area;

[0055] By selecting thermal radiation signals within several specific wavelength ranges and calculating the real-time temperature information of the current repair area based on the intensity ratio of each specific wavelength thermal radiation signal;

[0056] Collect stress state information for the current repair area;

[0057] Ultrasonic waves are generated inside the rail by emitting laser pulses;

[0058] Receive the echo signal after the ultrasonic wave propagates inside the rail;

[0059] Based on the propagation time, attenuation, and frequency shift of the echo signal, calculate the real-time stress state information of the current repair area.

[0060] Through this technical solution, this application accurately measures real-time temperature using the multi-wavelength thermal radiation signal ratio method and utilizes laser ultrasonic technology for non-destructive testing of real-time stress state, providing high-precision, real-time internal state data for adjusting the thermophysical parameters of the repair area, significantly improving the intelligence and precision of the repair process.

[0061] Secondly, this application also discloses a rail laser additive defect detection system for performing rail laser additive defect detection, including:

[0062] The instantaneous hotspot formation module is used to instantaneously heat a local area of ​​the rail substrate before laser additive repair of the damaged area of ​​the rail, so as to form an instantaneous hotspot in the corresponding local area;

[0063] The attenuation information acquisition module is used to collect thermal radiation attenuation information of instantaneous hotspots;

[0064] The heat dissipation rate calculation module is used to calculate the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot based on the thermal radiation attenuation information, so as to realize the detection of the rail damage area.

[0065] The process parameter selection module is used to select the repair process parameters for laser additive repair from the pre-stored process parameter combinations based on the actual heat dissipation rate.

[0066] The damaged area repair module is used to perform laser additive repair on the damaged areas of the rail using repair process parameters.

[0067] This application provides a rail laser additive defect detection system. Through modular design, it realizes the automation and integration of pre-repair detection of rail damage areas, intelligent selection of process parameters, and repair execution, effectively solving the limitations of manual experience judgment and improving repair efficiency and quality stability.

[0068] Beneficial Effects: This application provides a method for detecting defects in rail laser additive manufacturing. Before laser additive repair, a localized area of ​​the rail substrate is instantaneously heated to create a hot spot, and its thermal radiation attenuation information is collected. Based on the attenuation information, the actual heat dissipation rate of the localized area is calculated, thereby enabling the detection of damaged areas in the rail. This method can effectively identify differences in the heat dissipation characteristics within the rail, thus determining whether fatigue cracks, wear pits, or other damage exist, overcoming the limitation of existing surface optical inspection methods that cannot detect internal defects. Based on this, the most suitable repair process parameters are selected from a pre-stored combination of process parameters according to the actual heat dissipation rate, and laser additive repair is performed using these parameters. This scheme can dynamically adjust the repair process according to the actual condition of the damaged area of ​​the rail, avoiding the formation of hard and brittle microstructures and large residual stresses inside the repair layer due to excessively rapid cooling, thus effectively solving the safety hazard of "surface compliance, internal failure." This method significantly improves the quality and reliability of rail laser additive repair, extends the service life of the rail, and ensures railway transportation safety. Attached Figure Description

[0069] Figure 1 This is a flowchart of a method for detecting defects in rail laser additive manufacturing, as described in one embodiment of the present invention.

[0070] Figure 2 This is a flowchart of the sub-steps of a method for detecting defects in laser additive manufacturing of steel rails according to another embodiment of the present invention;

[0071] Figure 3 This is a system block diagram of a rail laser additive defect detection system according to another embodiment of the present invention;

[0072] Explanation of reference numerals in the attached figures:

[0073] 1. Rail laser additive manufacturing defect detection system; 11. Instantaneous hot spot formation module; 12. Attenuation information acquisition module; 13. Heat dissipation rate calculation module; 14. Process parameter selection module; 15. Damaged area repair module. Detailed Implementation

[0074] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0075] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0076] This application discloses a method for detecting defects in laser additive manufacturing of steel rails, combined with... Figure 1 As shown, it includes:

[0077] S1. Before performing laser additive repair on the damaged area of ​​the rail, a local area of ​​the rail substrate is instantaneously heated to form an instantaneous hot spot in the corresponding local area.

[0078] S2, collects information on the thermal radiation attenuation of instantaneous hotspots;

[0079] S3, based on the thermal radiation attenuation information, calculates the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot, so as to realize the detection of the rail damage area;

[0080] S4. Based on the actual heat dissipation rate, select the repair process parameters for laser additive repair from the pre-stored process parameter combinations.

[0081] S5 uses repair process parameters to perform laser additive repair on the damaged areas of the rail.

[0082] Specifically, before performing laser additive repair on damaged areas of the rail, it is necessary to momentarily heat a localized area of ​​the rail substrate to create a momentary hotspot. This momentary heating can be achieved in several ways. For example, a high-energy pulsed laser beam can be used to irradiate the localized area for a short period, rapidly raising its surface temperature to form a hotspot; alternatively, a high-intensity light source such as a flash lamp or xenon lamp can be used to radiate heat the target area for an extremely short time; or, a localized induction heating coil can be used to generate eddy currents in the localized area through high-frequency current, thereby achieving rapid temperature rise. All these heating methods can enable the localized area to reach a high temperature in a very short time, forming a momentary hotspot suitable for subsequent inspection.

[0083] Subsequently, it is necessary to collect information on the thermal radiation attenuation of the instantaneous hotspot. This information can be acquired using non-contact temperature measurement devices. For example, an infrared thermometer or thermal imager can be used to continuously monitor the instantaneous hotspot and record its temperature change curve over time. These devices can capture the changes in thermal radiation intensity throughout the entire process of the hotspot gradually cooling down as heat is conducted to the surrounding substrate after heating stops, thus obtaining information on thermal radiation attenuation.

[0084] Based on thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated to detect damaged areas of the rail. The calculation of the actual heat dissipation rate can be based on a heat conduction theory model. For example, the collected thermal radiation attenuation curve can be fitted with a preset theoretical cooling model to deduce the local thermal diffusivity or heat dissipation coefficient, thereby obtaining the actual heat dissipation rate. Alternatively, the heat dissipation rate can be indirectly assessed by analyzing the time required for the hot spot to drop from its peak temperature to a specific temperature, or the temperature drop rate within a specific time period. Anomalies in the heat dissipation rate, such as excessively fast or slow heat dissipation, usually indicate defects inside the rail, such as cracks, voids, or uneven structure, because these defects alter the heat conduction path and efficiency.

[0085] Furthermore, based on the actual heat dissipation rate, the repair process parameters for laser additive repair are selected from a pre-stored combination of process parameters. The selection process can be based on a pre-established database or mapping relationship. For example, multiple combinations of repair process parameters such as laser power, scanning speed, and powder feeding rate can be preset according to different heat dissipation rate ranges. When a certain actual heat dissipation rate is detected, the system automatically matches or searches the database for the closest or most suitable combination of process parameters. This selection can be a simple table lookup or a judgment based on empirical rules.

[0086] Finally, laser additive repair is performed on the damaged areas of the rail using the selected repair process parameters. After obtaining the selected repair process parameters, the laser additive equipment operates according to these parameters. For example, the laser outputs laser light at a set power, the scanning head moves at a set speed, and the powder feeder delivers metal powder at a set rate. The entire repair process strictly follows these parameters to achieve the best repair effect based on the currently detected condition of the rail substrate. In some implementations, the repair process parameters may remain fixed throughout the repair process, or may be preset and adjusted only based on macroscopic area divisions, without real-time, microscopic dynamic adjustments.

[0087] This application proposes a forward-looking solution to the problem of ineffective detection of internal defects after laser additive repair of rails in existing technologies. Traditional methods often rely on surface inspection after repair, failing to reveal the internal brittle structure and residual stress caused by rapid cooling. This application calculates the actual heat dissipation rate reflecting the internal structure and defects by locally and instantaneously heating the rail substrate before repair and analyzing its thermal radiation attenuation information. This thermophysical-based detection method can effectively identify internal defects that traditional optical inspection methods cannot detect, such as microcracks, voids, or uneven structure. By combining the detected heat dissipation rate with the selection of repair process parameters, adaptive adjustment of repair parameters is achieved, thereby predicting and avoiding the risk of reduced repair quality due to substrate defects before repair. Compared with the passive inspection and rework mode after repair in existing technologies, this application's solution achieves defect prediction and process parameter optimization before repair, significantly improving the success rate and reliability of repair, fundamentally solving the safety hazard of "surface qualified, internal failure," and demonstrating significant progress.

[0088] Optionally, after the step of performing laser additive repair on the damaged area of ​​the rail using repair process parameters, the following steps may also be included:

[0089] During the laser additive repair process, the thermal response of the solidified region behind the molten pool was detected;

[0090] Calculate the instantaneous cooling rate of the solidification zone behind the molten pool based on the thermal response;

[0091] The instantaneous cooling rate is compared with the preset target cooling rate range to obtain the cooling rate deviation;

[0092] Based on the cooling rate deviation, the repair process parameters corresponding to the unrepaired forward path during the laser additive repair process are adjusted to guide the instantaneous cooling rate of the unrepaired forward path back to the target cooling rate range.

[0093] Specifically, during laser additive repair, it is necessary to monitor the thermal response of the solidified region behind the molten pool in real time. The thermal response can be understood as information such as temperature changes, thermal radiation intensity, or cooling curves in the region, directly reflecting the thermal behavior of the material during solidification. The solidified region behind the molten pool refers to the area where the metallic material behind the laser molten pool transforms from a liquid to a solid state during its movement. The cooling rate of this region has a decisive influence on the microstructure and mechanical properties of the final repair layer. Monitoring the thermal response of this region aims to obtain its instantaneous thermal state during the actual repair process.

[0094] Based on the detected thermal response, the instantaneous cooling rate of the solidified region behind the molten pool can be calculated. The instantaneous cooling rate refers to the rate of temperature decrease per unit time and is a key parameter for evaluating the material solidification process. For example, the instantaneous cooling rate can be calculated by analyzing the slope of the thermal response curve. The calculated instantaneous cooling rate is compared with a preset target cooling rate range to obtain the cooling rate deviation. The preset target cooling rate range is an ideal cooling rate interval predetermined based on the required microstructure and mechanical properties of the repair layer. The cooling rate deviation quantifies the degree of deviation between the actual cooling rate and the target range.

[0095] Based on the cooling rate deviation, the repair process parameters corresponding to the unrepaired preceding path can be adjusted during laser additive repair. This means that the system predicts and adjusts the process parameters of subsequent repair areas, such as laser power, scanning speed, or powder feeding rate, based on the actual cooling status of the currently repaired area. The purpose of the adjustment is to guide the instantaneous cooling rate of the unrepaired preceding path back to the preset target cooling rate range, thereby achieving real-time adaptive control of the entire repair process.

[0096] In some preferred embodiments, a specific example is given below. Suppose that during laser additive repair of a damaged section of rail, the initially selected repair process parameters, in the initial repair section, result in a slightly higher instantaneous cooling rate in the solidified region behind the molten pool due to localized stress concentration or minor fluctuations in material composition within the rail. In this case, the system uses an infrared thermal imager or high-speed narrowband radiometer positioned behind the repair head to monitor the thermal response of the solidified region in real time, acquiring, for example, its temperature distribution and its time-varying curve. Based on this thermal response data, the actual instantaneous cooling rate is calculated. If the calculation shows a cooling rate of 150 K / s, while the preset target cooling rate range is 100-120 K / s, the system identifies a cooling rate deviation of 30-50 K / s. Based on this deviation, the control system immediately adjusts the repair process parameters for the subsequent, unrepaired sections. For example, to reduce the cooling rate, the system may automatically reduce the laser power output, appropriately increase the scanning speed, or adjust the powder feed rate to reduce the energy input per unit area, thereby guiding the instantaneous cooling rate of the subsequent repair area back to the target range of 100-120 K / s. Through this real-time feedback and proactive adjustment, even if local uncertainties are encountered during the repair process, the quality consistency and performance stability of the entire repair path can be ensured.

[0097] Optionally, during laser additive repair, the steps for detecting the thermal response of the solidified region behind the molten pool include:

[0098] During the laser additive repair process, a narrowband filter is set on a high-speed camera to receive thermal radiation signals of a preset specific wavelength.

[0099] By adjusting the exposure time, the high-speed camera's operating state can be adapted to the wide temperature variations in the solidification region behind the molten pool.

[0100] Based on the received thermal radiation signal of a preset specific wavelength and the exposure data of a high-speed camera adapted to a wide range of temperature changes, the thermal response of the solidification region behind the molten pool is detected in real time.

[0101] Specifically, during laser additive repair, the temperature of the solidification zone behind the molten pool undergoes a rapid cooling process from a high-temperature liquid state to a solid state, and this temperature change range can be very wide. To accurately capture the thermal response during this dynamic process, a high-speed camera can be used for data acquisition. This high-speed camera is equipped with a narrow-band filter, which allows only thermal radiation signals of a preset specific wavelength to pass through and be received. The selection of this specific wavelength can be based on the thermal radiation characteristics of the rail material to be repaired; for example, a wavelength range with strong radiation intensity at high temperatures and minimal environmental interference can be chosen.

[0102] Furthermore, to ensure that the high-speed camera can still operate effectively and acquire accurate thermal response data under a wide range of temperature variations, its exposure time needs to be dynamically adjusted. For example, when the solidified region behind the molten pool is at an extremely high temperature, the exposure time can be shortened to avoid overexposure; when the temperature is relatively low, the exposure time can be appropriately extended to ensure sufficient signal strength. This adaptive adjustment of the exposure time allows the high-speed camera to always be in optimal working condition, thereby accurately capturing the thermal radiation information of the solidified region behind the molten pool throughout the cooling process.

[0103] Therefore, based on the received thermal radiation signal of a preset specific wavelength and the exposure data of a high-speed camera adapted to a wide range of temperature variations, the thermal response of the solidified region behind the molten pool can be calculated or derived in real time. The thermal response can be expressed as parameters such as temperature and radiation intensity, which can directly reflect the instantaneous thermal state and cooling behavior of the region.

[0104] This application's solution addresses the challenge of accurately detecting the real-time thermal response of the solidified region behind the molten pool during laser additive repair by introducing a high-speed camera, narrow-band filters, and an adaptive exposure time adjustment mechanism. Specifically, the narrow-band filter ensures the purity of the acquired thermal radiation signal, eliminating interference from stray light of other wavelengths and making the reception of specific wavelength thermal radiation signals more accurate. Simultaneously, by dynamically adjusting the exposure time of the high-speed camera, it adapts to a wide temperature range from high to low in the solidified region behind the molten pool, avoiding overexposure or underexposure problems that may occur with traditional fixed exposure times at extreme temperatures. This ensures the integrity and accuracy of the thermal response data throughout the cooling process. It is precisely these synergistic effects that enable the accurate detection of the real-time thermal response of the solidified region behind the molten pool, providing a reliable data foundation for subsequent instantaneous cooling rate calculations and precise adjustment of repair process parameters.

[0105] Optionally, the step of calculating the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot based on the thermal radiation attenuation information to detect the rail damage area may include the following methods:

[0106] Linear scanning heating is performed on a local area of ​​the rail substrate to form an instantaneous heat line;

[0107] Collect information on the thermal radiation attenuation of instantaneous hot wires;

[0108] The thermal radiation attenuation information is averaged over a region to obtain the corresponding actual heat dissipation rate.

[0109] Linear scanning heating of a localized area of ​​the rail substrate refers to rapidly heating a specific localized area of ​​the rail substrate using a laser or other instantaneous heating source, creating a momentary high-temperature linear region, or instantaneous hot spot. This linear scanning heating method aims to cover a larger detection range than the instantaneous hot spot, in order to more comprehensively assess the heat dissipation characteristics of the damaged area of ​​the rail.

[0110] Furthermore, collecting information on the thermal radiation attenuation of the instantaneous hot wire refers to acquiring, in real-time or near real-time, data on the change in thermal radiation signal emitted by the hot wire during the cooling process after the instantaneous hot wire is formed, using infrared thermal imagers, high-speed thermocouple arrays, or other thermal radiation sensors. This data reflects the rate and pattern of heat loss from the instantaneous hot wire to the surrounding rail substrate.

[0111] Therefore, the thermal radiation attenuation information is averaged regionally to obtain the corresponding actual heat dissipation rate. Specifically, since the instantaneous hot wire is a linear region, its thermal radiation attenuation information may have slight differences at different points. By averaging the thermal radiation attenuation information within the linear region, the influence of local noise or minor inhomogeneities can be eliminated, thus obtaining a more representative and stable actual heat dissipation rate value. The actual heat dissipation rate value can more accurately reflect the overall heat dissipation performance of the rail damage area, and thus be used for defect detection and assessment.

[0112] This application's solution, by expanding the instantaneous heating method from point-based to linear and combining it with regional averaging, can more effectively characterize the heat dissipation characteristics of rail damage areas. When the rail matrix is ​​damaged (e.g., cracks, holes, or material inhomogeneities), its heat conduction and heat dissipation properties change. The instantaneous heat line formed by linear scanning heating can cover a longer damage path or a larger damage area, allowing for a more comprehensive capture of the heat propagation and dissipation process within the damage area. The collected instantaneous heat line's thermal radiation attenuation information contains detailed data on the thermophysical properties of the damage area. Subsequently, by performing regional averaging on this information, the interference of a single measurement point or local anomaly on the overall assessment can be effectively reduced, resulting in a more reliable and accurate actual heat dissipation rate. Comparing this actual heat dissipation rate value with the heat dissipation rate of the undamaged area clearly indicates the presence, location, and extent of rail damage, thereby achieving effective detection of rail damage areas.

[0113] Optionally, the steps for laser additive repair of damaged rail areas using repair process parameters include:

[0114] During the laser additive repair process, the current position information of the laser additive equipment on the rail substrate is obtained;

[0115] Based on the current location information, obtain the local difference information corresponding to the current location;

[0116] Based on the information on local differences, the repair process parameters were adjusted;

[0117] Using the adjusted repair process parameters, laser additive repair was performed on the current location of the rail damage area.

[0118] Specifically, during the laser additive repair process, it is necessary to obtain the real-time position information of the laser additive equipment on the rail substrate. Position information can be obtained in various ways, such as using positioning devices like high-precision encoders, laser rangefinders, visual positioning systems, or GPS for real-time monitoring and feedback. The purpose of obtaining the current position information is to accurately determine which part of the rail the laser additive head is repairing, so that targeted parameter adjustments can be made subsequently.

[0119] Local difference information can be understood as the differences in physical, chemical, or geometric properties between the current repair area and other areas of the rail or in an ideal state. These differences may include, but are not limited to, the depth, width, and shape of the damage, the microstructure of the material, chemical composition, thermophysical properties (such as thermal conductivity and specific heat capacity), and surface roughness. Local difference information can be obtained through pre-scanning (e.g., using a 3D scanner, ultrasonic testing equipment, or eddy current testing equipment to perform a comprehensive scan of the damaged area and establish a 3D model and defect distribution map) or real-time detection during the repair process (e.g., monitoring local temperature distribution with an infrared thermal imager, analyzing material composition with a spectrometer, or measuring geometric morphology with a laser displacement sensor). The purpose is to provide accurate input data for subsequent adjustments to process parameters.

[0120] In practical applications, adjusting repair process parameters based on local differences refers to dynamically modifying key additive repair process parameters such as laser power, scanning speed, powder feed rate, spot size, or protective gas flow rate according to the specific local conditions at the current location. For example, when a large depth of the damaged area is detected, the laser power can be appropriately increased or the scanning speed decreased to ensure that the molten pool depth and cladding layer thickness meet the requirements; when a change in material composition is detected, the powder feed rate or powder composition ratio can be adjusted to ensure the chemical composition and mechanical properties of the cladding layer. This adjustment can be achieved based on a preset parameter adjustment rule base, machine learning model, or real-time feedback control algorithm, with the aim of ensuring optimal repair quality and efficiency under different local conditions.

[0121] Therefore, using adjusted repair process parameters to perform laser additive repair on the current location of the rail damage area means that the repair process is no longer static, but dynamically adaptive. Whenever the laser additive equipment moves to a new location, or detects a change in local differences at the current location, the repair process parameters are recalculated and adjusted to ensure that the process parameters most suitable for the current local conditions are always used throughout the repair process of the entire damaged area.

[0122] This application's solution achieves dynamic adjustment of repair process parameters by introducing the acquisition of the current position information of the laser additive manufacturing equipment and the identification of local differences at that current position. Specifically, when the laser additive manufacturing equipment repairs the damaged area of ​​the rail, its current position is monitored in real time. Combined with local difference information (e.g., the geometric features of the damage, material state, etc.), the system can accurately determine the optimal process conditions required for the current repair point. It is precisely because of this real-time position awareness and local difference analysis that the repair process parameters can be precisely and adaptively adjusted, thereby overcoming the limitations of traditional fixed-parameter repair schemes that cannot cope with complex local changes. In this way, the repair process can be finely controlled according to the actual situation of the damaged area of ​​the rail, ensuring that optimal repair results can be obtained in different local areas.

[0123] In some preferred embodiments, a specific example is given below. Suppose a section of rail has an irregular damaged area, the depth and width of which vary significantly at different locations, and microcracks may exist in some areas. During laser additive repair, firstly, the laser additive equipment uses its built-in vision positioning system and encoder to acquire its current position coordinates on the rail in real time. Simultaneously, a laser scanner integrated into the repair head scans the current repair area in real time, acquiring precise three-dimensional geometric data of the area, including the depth and slope information of the damage. In addition, an infrared thermal imager simultaneously monitors the surface temperature distribution of the current area to assess the thermophysical state of the material.

[0124] When the equipment moves to an area with deeper damage and a steeper slope, the control system determines, based on the acquired location and local difference information, that a larger energy input is needed to ensure sufficient fusion. At this point, the repair process parameters are automatically adjusted; for example, the laser power may be increased by 15%, while the scanning speed may be appropriately reduced by 10%, ensuring that the depth and width of the molten pool completely cover the damaged area and form a good metallurgical bond. When the equipment moves to an area with shallower damage or microcracks, the system adjusts parameters based on local difference information to avoid overheating or stress concentration. For example, the laser power may be fine-tuned, and the powder feeding rate may be precisely controlled to form a finer, more uniform cladding layer and effectively fill microcracks. In this way, the entire repair process of the damaged area can be optimized according to its unique local characteristics, thereby ensuring the consistency and reliability of the repair quality.

[0125] Optionally, adjusting the repair process parameters based on local difference information includes the following steps:

[0126] Based on local difference information, determine the material properties and geometric features of the current repair area;

[0127] Calculate the heat dissipation efficiency of the current repair area based on material properties and geometric characteristics;

[0128] Based on the heat dissipation efficiency, the adjustment amounts for laser power, scanning speed, and powder feeding rate are determined to obtain parameter adjustment information.

[0129] The parameter adjustment information is applied to the repair process parameters to obtain the adjusted repair process parameters.

[0130] Specifically, after obtaining the current position information of the laser additive manufacturing equipment on the rail substrate, local difference information corresponding to the current position can be further obtained. This local difference information may include, but is not limited to, the geometry of the damaged area of ​​the rail (e.g., crack depth, width, curvature), surface roughness, and potential material inhomogeneities (e.g., oxide layer, residual stress areas, or different alloy compositions). Based on this local difference information, the material properties and geometric features of the current repair area can be determined. Material properties may refer to thermophysical parameters such as thermal conductivity, specific heat capacity, and density, while geometric features refer to its volume, surface area, and contact area with the surrounding substrate. These features can be acquired and analyzed through prior non-destructive testing (such as ultrasonic testing, eddy current testing, and spectral analysis) or real-time sensor data (such as infrared thermal imagers and vision systems).

[0131] Furthermore, based on the determined material properties and geometric characteristics, the heat dissipation efficiency of the current repair area can be calculated. Heat dissipation efficiency refers to the proportion of heat lost from the repair area to the surrounding environment or substrate per unit time during laser additive manufacturing, relative to the total input heat. Calculations can be performed by establishing a heat conduction model, finite element analysis, or based on empirical formulas. For example, areas with a large surface area or a large contact area with the substrate may have a higher heat dissipation efficiency; materials with high thermal conductivity may also experience faster heat dissipation.

[0132] Therefore, based on the calculated heat dissipation efficiency, the adjustments to laser power, scanning speed, and powder feed rate can be determined, thus obtaining parameter adjustment information. For example, when the heat dissipation efficiency is high, it may be necessary to increase laser power or decrease scanning speed to maintain the stability of the molten pool and the required melt depth; conversely, when the heat dissipation efficiency is low, it may be necessary to decrease laser power or increase scanning speed to avoid overheating. The powder feed rate can be adjusted in conjunction with the required build-up height and molten pool size. These adjustments can be calculated and determined using a pre-established process database, machine learning models, or real-time feedback control algorithms.

[0133] Finally, the parameter adjustment information is applied to the repair process parameters to obtain the adjusted repair process parameters. This means that the original repair process parameters (e.g., the initially set laser power, scanning speed, and powder feeding rate) will be dynamically corrected according to the actual heat dissipation of the current repair area to ensure the best repair effect throughout the entire repair path.

[0134] This application's solution addresses the problem of inaccurate parameter adjustments in traditional methods when faced with complex local variations by introducing precise calculations of the material properties, geometric features, and heat dissipation efficiency of the current repair area. Specifically, by identifying and quantifying the impact of local variations on heat dissipation, the laser additive manufacturing equipment can dynamically adjust laser power, scanning speed, and powder feed rate according to the actual thermophysical environment. This adjustment mechanism based on heat dissipation efficiency ensures a stable molten pool state and appropriate cooling rate in different local areas, thereby avoiding defects caused by heat input mismatch, such as porosity, cracks, or uneven microstructure. It is precisely this refined thermal management that allows the repair process to better adapt to the complexity and diversity of rail damage areas.

[0135] In some preferred embodiments, a specific example is given below. Suppose that during laser additive repair of a section of rail, a deep V-shaped crack and a shallow surface scratch are detected in the damaged area.

[0136] For deeper V-shaped crack regions, the geometric characteristics are characterized by greater depth and smaller width. This results in a relatively large contact area between the molten pool and the surrounding matrix during formation, and heat is more easily dissipated deeper and to the sides, leading to higher heat dissipation efficiency in the region. According to the scheme of this application, after determining this high heat dissipation efficiency, the system calculates the amount of adjustment needed to increase the laser power and / or decrease the scanning speed, while possibly increasing the powder feeding rate to fill a larger volume. For example, the laser power may be adjusted from a preset 2kW to 2.2kW, the scanning speed from 10mm / s to 8mm / s, and the powder feeding rate from 5g / min to 6g / min.

[0137] For shallower surface scratches, the geometric characteristics are characterized by shallow depth and large width, resulting in relatively low heat dissipation efficiency. In this case, the system will determine the amount of adjustment needed to reduce the laser power and / or increase the scanning speed based on the calculated low heat dissipation efficiency to avoid overheating and excessive material buildup. For example, the laser power may be adjusted from the preset 2kW to 1.8kW, the scanning speed from 10mm / s to 12mm / s, and the powder feed rate from 5g / min to 4.5g / min.

[0138] By adjusting these dynamic parameters based on heat dissipation efficiency, optimal molten pool conditions and material deposition can be achieved in different damaged areas, thus enabling high-quality repair.

[0139] Optionally, after determining the adjustment amounts for laser power, scanning speed, and powder feeding rate based on heat dissipation efficiency to obtain parameter adjustment information, the method further includes:

[0140] Obtain real-time environmental parameters for the current repair area;

[0141] Obtain the actual output parameters of the laser additive manufacturing equipment under the current operating conditions;

[0142] The parameter adjustment information is corrected based on heat loss efficiency, real-time environmental parameters, and actual output parameters.

[0143] Specifically, obtaining real-time environmental parameters of the current repair area refers to monitoring and acquiring environmental factors such as temperature, humidity, and airflow velocity around the repair area in real time during the laser additive repair process by deploying corresponding sensors. Changes in these environmental parameters directly affect the material cooling rate and the stability of the molten pool. For example, an increase in ambient temperature may lead to a decrease in the cooling rate, while an increase in airflow velocity may accelerate cooling. Simultaneously, obtaining the actual output parameters of the laser additive equipment under current operating conditions refers to real-time monitoring of the actual output power of the laser, the spot size, the actual scanning speed of the scanning galvanometer, and the actual powder feeding rate of the powder feeder. Although the equipment has preset parameters, due to equipment aging, internal wear, or external interference, the actual output may deviate from the preset values. Therefore, correcting the parameter adjustment information based on heat dissipation efficiency, real-time environmental parameters, and actual output parameters means performing a secondary calibration by combining the initial adjustment amount calculated based on heat dissipation efficiency with real-time environmental data and actual equipment performance data. This correction can be achieved using pre-established mathematical models, lookup tables, or machine learning algorithms to ensure that the final applied repair process parameters are more accurately adapted to the current actual operating conditions.

[0144] This application's solution addresses the lack of precision caused by relying solely on local differences and heat dissipation efficiency for parameter adjustments by incorporating real-time environmental parameters and the actual output parameters of the laser additive manufacturing equipment. Specifically, acquiring real-time environmental parameters allows the system to sense and compensate for the influence of the external environment on the thermal field distribution and cooling process. For example, when the ambient temperature rises, the system can correspondingly fine-tune the laser power or scanning speed to maintain the expected heat input and cooling rate. Simultaneously, monitoring the actual output parameters of the laser additive manufacturing equipment ensures that the system can correct deviations caused by fluctuations in the equipment's performance. For instance, if the actual laser output power is lower than the set value, the system can promptly increase the adjustment amount to compensate for the insufficient energy, thereby ensuring the stability of the molten pool and the repair quality. It is precisely because these dynamically changing external and internal factors are considered and corrected that the adjustment of the repair process parameters becomes more precise and adaptive, significantly improving the robustness of the repair process and the performance of the final repaired part.

[0145] In some preferred embodiments, a specific example is given below. Suppose that during laser additive repair of rails, the system initially calculates that the laser power needs to be increased by 10W based on local difference information and heat dissipation efficiency. However, during the repair process, temperature and humidity sensors located near the repair area detect a sudden increase in ambient temperature of 5°C and a 10% increase in humidity. Simultaneously, the power meter inside the laser monitors that the actual output power of the laser is 2W lower than the set value. At this point, the system uses a preset correction model (e.g., a neural network model trained on historical data or a lookup table containing empirical coefficients) as input to correct the initial 10W adjustment. The correction result may show that, considering the increase in ambient temperature and the decrease in laser power, the final laser power adjustment should be increased by 12W, instead of the initial 10W. In this way, even under fluctuating environmental conditions or minor deviations in equipment performance, precise control of laser energy input and thermal field distribution can be ensured, thereby guaranteeing the stability and consistency of repair quality.

[0146] Optional, combined Figure 2 As shown, the steps to determine the adjustment amounts for laser power, scanning speed, and powder feeding rate based on heat dissipation efficiency, and to obtain parameter adjustment information, include:

[0147] A1. Based on the heat dissipation efficiency, obtain the real-time temperature and stress state information of the current repair area;

[0148] A2, adjust the corresponding thermophysical parameters based on real-time temperature and stress state information;

[0149] A3. Based on the heat dissipation efficiency and the adjusted thermophysical parameters, calculate the instantaneous mapping relationship between the heat dissipation efficiency and the adjustment amounts of laser power, scanning speed, and powder feeding rate.

[0150] A4. Based on the instantaneous mapping relationship, determine the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate to obtain parameter adjustment information.

[0151] Specifically, obtaining real-time temperature and stress state information of the current repair area refers to monitoring and acquiring temperature and internal stress state data of the rail area being repaired in real time during the laser additive repair process using various sensors or detection methods. This information is crucial for accurately assessing the thermophysical behavior of the material under current operating conditions. Real-time temperature information reflects the instantaneous thermal state of the material, while stress state information reflects its mechanical state; both together influence the thermophysical properties of the material.

[0152] Adjusting the corresponding thermophysical parameters based on real-time temperature and stress state information can be understood as dynamically correcting the thermophysical parameters used for calculation based on the actual temperature and stress conditions of the current repair area. For example, parameters such as thermal conductivity, specific heat capacity, and density of materials typically change with temperature and stress. By acquiring this information in real time and updating the corresponding thermophysical parameters, subsequent calculations can be made more closely reflect reality, improving the accuracy of the model or algorithm.

[0153] In practical applications, calculating the instantaneous mapping relationship between heat dissipation efficiency and the adjustments to laser power, scanning speed, and powder feeding rate, based on the heat dissipation efficiency and the adjusted thermophysical parameters, refers to establishing a dynamic, real-time correlation model or lookup table. This mapping relationship can accurately derive the specific adjustments required for laser power, scanning speed, and powder feeding rate based on the current heat dissipation efficiency and thermophysical parameters that consider the effects of real-time temperature and stress. This instantaneous mapping relationship can be based on a physical model, a data-driven model (such as a machine learning model), or a pre-set empirical curve, and its purpose is to provide a precise and dynamic basis for parameter adjustment.

[0154] The proposed solution incorporates real-time temperature and stress state information of the repair area when determining the adjustment amounts for the repair process parameters. Based on this, the thermophysical parameters of the material are dynamically adjusted, enabling a more accurate calculation of the instantaneous mapping relationship between heat dissipation efficiency and the adjustment amounts of the process parameters. It is precisely because the dynamic thermodynamic behavior of the material during the repair process is considered that the determined adjustments for laser power, scanning speed, and powder feeding rate can more precisely adapt to actual working conditions, avoiding repair deviations caused by changes in material parameters.

[0155] In some preferred embodiments, a specific example is given below. Suppose that during laser additive repair of rails, a sudden temperature increase in the repair area is detected in real-time by an infrared thermal imager, and high residual stress is found in the area by ultrasonic testing. Based on this real-time temperature and stress information, the system consults a pre-set material database or uses a real-time calculation model to find that the thermal conductivity and specific heat capacity of the rail material increase under the given temperature and stress conditions. Based on these adjusted thermophysical parameters and the previously calculated heat dissipation efficiency, the system uses a pre-trained instantaneous mapping model (e.g., a neural network-based prediction model) to calculate that to maintain the stability of the molten pool and the desired cooling rate, the laser power needs to be reduced by 5%, the scanning speed needs to be increased by 3%, and the powder feed rate needs to be fine-tuned by 2%. These parameter adjustments are then applied to the current repair process parameters to ensure the stability and quality of the repair process.

[0156] Optionally, the steps of obtaining real-time temperature and stress state information of the current repair area based on heat dissipation efficiency may include the following:

[0157] The steps for obtaining real-time temperature and stress state information of the current repair area based on heat dissipation efficiency include:

[0158] Collect temperature information for the currently repaired area;

[0159] By selecting thermal radiation signals within several specific wavelength ranges and calculating the real-time temperature information of the current repair area based on the intensity ratio of each specific wavelength thermal radiation signal;

[0160] Collect stress state information for the current repair area;

[0161] Ultrasonic waves are generated inside the rail by emitting laser pulses;

[0162] Receive the echo signal after the ultrasonic wave propagates inside the rail;

[0163] Based on the propagation time, attenuation, and frequency shift of the echo signal, calculate the real-time stress state information of the current repair area.

[0164] Specifically, when collecting temperature information of the current repair area, non-contact temperature measurement methods can be used, such as infrared thermometers or multispectral pyrometers. By selecting thermal radiation signals within several specific wavelength ranges, such as measuring in two or more different infrared bands, and calculating the real-time temperature information of the current repair area based on the intensity ratio of the thermal radiation signals at each specific wavelength, this colorimetric thermometry method can effectively eliminate the influence of emissivity changes on temperature measurement and improve the accuracy of temperature measurement.

[0165] Furthermore, ultrasonic testing technology can be used to collect stress state information of the current repair area. Specifically, ultrasonic waves are excited inside the rail by emitting laser pulses. The laser pulses can be short pulses in the nanosecond or picosecond range, with enough energy to induce instantaneous thermal expansion on or inside the material, thereby exciting ultrasonic waves. Subsequently, the echo signals of the ultrasonic waves propagating inside the rail are received. These echo signals can be captured by piezoelectric sensors or laser ultrasonic receivers. Based on the propagation time, attenuation, and frequency shift of the echo signals, real-time stress state information of the current repair area can be calculated. For example, the propagation speed of ultrasonic waves is affected by the internal stress state of the material; the stress can be inferred by measuring the change in propagation time. The attenuation of ultrasonic waves is related to the microstructure and defects of the material, while the frequency shift (such as the Doppler effect) can reflect the motion or strain state of the material. Thus, the residual stress or loaded stress state inside the rail can be accurately assessed.

[0166] This application's solution employs a multi-wavelength thermal radiation signal ratio method for temperature information acquisition, effectively overcoming the errors caused by the uncertainty of material surface emissivity in traditional single-wavelength temperature measurement methods, thus obtaining more accurate real-time temperature information. Simultaneously, by using laser-excited ultrasonic waves and analyzing their echo signal propagation time, attenuation, and frequency shift, the stress state information inside the rail can be obtained non-destructively and in real-time. This precise real-time temperature and stress state information is crucial input for subsequent adjustments to thermophysical parameters and for calculating the instantaneous mapping relationship between heat dissipation efficiency and repair process parameters. By acquiring this high-precision real-time data, the actual thermophysical and mechanical states of the current repair area can be more accurately reflected, providing a reliable basis for subsequent parameter adjustments and ensuring precise control of the laser additive repair process and improved repair quality.

[0167] This application also discloses a rail laser additive manufacturing defect detection system, used to perform rail laser additive manufacturing defect detection, combined with... Figure 3 As shown, the rail laser additive defect detection system 1 includes:

[0168] The instantaneous hot spot formation module 11 is used to instantaneously heat a local area of ​​the rail substrate before laser additive repair of the damaged area of ​​the rail, so as to form an instantaneous hot spot in the corresponding local area.

[0169] The attenuation information acquisition module 12 is used to collect thermal radiation attenuation information of instantaneous hotspots.

[0170] The heat dissipation rate calculation module 13 is used to calculate the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot based on the thermal radiation attenuation information, so as to realize the detection of the rail damage area.

[0171] The process parameter selection module 14 is used to select the repair process parameters for laser additive repair from the pre-stored process parameter combinations based on the actual heat dissipation rate.

[0172] Damage area repair module 15 is used to perform laser additive repair on the damaged area of ​​the rail using repair process parameters.

[0173] This application presents a rail laser additive defect detection system to address the difficulty in detecting internal defects after rail laser additive repair in existing technologies. By instantaneously heating a localized area of ​​the rail substrate to create a momentary hotspot before repair and collecting its thermal radiation attenuation information, the system can calculate the actual heat dissipation rate of the localized area. The heat dissipation rate, as a crucial indicator of the characteristics of the damaged area, can be used for effective detection of the damaged region. Based on the detection results, the system intelligently selects suitable repair process parameters from a pre-stored combination of process parameters, and the damaged area repair module executes the laser additive repair, thereby ensuring repair quality and avoiding the safety hazard of "surface compliance, internal failure."

[0174] Specifically, the instantaneous hotspot formation module can achieve instantaneous heating of localized areas of the rail substrate using various methods. For example, a high-energy laser beam can be focused on a specific area in a very short time, or a high-frequency induction heating coil can be used to rapidly heat the localized area, or a resistance heating element can be brought into contact with the rail surface for instantaneous energization and heating. All these heating methods aim to rapidly increase the temperature of the localized area to form an instantaneous hotspot.

[0175] The attenuation information acquisition module is responsible for acquiring the thermal radiation attenuation information of instantaneous hotspots. The module can be configured as an infrared thermal imager to continuously monitor the surface temperature distribution changes during the cooling process of the hotspot; or it can use a photodetector array to obtain the attenuation curve by measuring the thermal radiation intensity of a specific wavelength at different time points; or it can be a contact temperature sensor based on a thermocouple array to record the temperature drop process of the hotspot area in real time.

[0176] The heat dissipation rate calculation module calculates the actual heat dissipation rate of a local area based on the collected thermal radiation attenuation information. The calculation can be performed by fitting and analyzing the thermal radiation attenuation curve using a preset physical model, such as numerical simulation based on Fourier's law of thermal conduction and convective heat transfer; or by using machine learning algorithms to train the model with a large amount of historical data and directly predict the heat dissipation rate from the thermal radiation attenuation pattern; or by using a finite element analysis method to accurately solve the heat transfer process in the hot spot area.

[0177] The process parameter selection module selects appropriate repair process parameters from pre-stored combinations based on the calculated actual heat dissipation rate. This module can be a lookup table that directly matches the corresponding combination of laser power, scanning speed, and powder feeding rate according to the heat dissipation rate range; it can also be a rule-based expert system that dynamically adjusts the parameter selection strategy based on the value and trend of the heat dissipation rate; or it can be an optimization algorithm that searches for the optimal combination of process parameters while meeting specific repair quality objectives.

[0178] The damaged area repair module is responsible for performing laser additive repair on the damaged areas of the rail using selected repair process parameters. The module typically includes a laser, a powder feeding device, and a motion control system. The laser can be a fiber laser or a CO2 laser, providing the energy required for cladding; the powder feeding device can be coaxial or off-axis, precisely delivering metal powder into the molten pool; the motion control system controls the movement path and speed of the laser head and powder feeding head relative to the rail to achieve a precise cladding trajectory. These components work together to ensure the repair process follows the selected process parameters.

[0179] Traditional rail laser additive repair technology relies primarily on surface optical inspection for quality control after repair. This makes it difficult to detect deep-seated defects within the repair layer, such as brittle structures and excessive residual stress caused by rapid cooling, thus creating a safety hazard of "surface compliance, internal failure." The rail laser additive defect detection system proposed in this application pre-detects damaged areas by introducing instantaneous heating of a localized area of ​​the rail substrate before repair and collecting thermal radiation attenuation information to calculate the actual heat dissipation rate. Furthermore, the system can intelligently select appropriate repair process parameters based on the detection results, effectively avoiding or mitigating internal defects during the repair process. Compared to existing technologies that only focus on surface quality, this system optimizes the repair process from the source, significantly improving the internal quality and reliability of the repair layer. It effectively solves the problem of difficulty in detecting and controlling internal defects during the repair process in existing technologies, providing a more comprehensive and reliable quality assurance for rail laser additive repair.

[0180] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method of laser additive defect detection of a steel rail, characterized in that, The method comprises the following steps: Before laser additive repair of the damaged area of the steel rail, the local area of the steel rail substrate is instantaneously heated to form an instant hot spot in the corresponding local area; Collecting thermal radiation attenuation information of the instant hot spot; According to the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instant hot spot is calculated to realize the detection of the damaged area of the steel rail; According to the actual heat dissipation rate, the repair process parameters for the laser additive repair are selected from the pre-stored process parameter combinations; The damaged area of the steel rail is repaired by laser additive repair using the repair process parameters; After the step of using the repair process parameters to repair the damaged area of the steel rail by laser additive repair, the method further comprises the following steps: During the laser additive repair, the thermal response of the solidification area behind the molten pool is detected; According to the thermal response, the instantaneous cooling rate of the solidification area behind the molten pool is calculated; The instantaneous cooling rate is compared with the preset target cooling rate range to obtain a cooling rate deviation; According to the cooling rate deviation, the repair process parameters corresponding to the unrepaired front path during the laser additive repair are adjusted to guide the instantaneous cooling rate of the unrepaired front path back to the target cooling rate range; The step of using the repair process parameters to repair the damaged area of the steel rail by laser additive repair comprises the following steps: During the laser additive repair, the current position information of the laser additive equipment on the steel rail substrate is obtained; According to the current position information, the local difference information corresponding to the current position is obtained; According to the local difference information, the repair process parameters are adjusted; The current position of the damaged area of the steel rail is repaired by laser additive repair using the adjusted repair process parameters.

2. A method of laser additive defect detection of a steel rail according to claim 1, characterized in that, The step of detecting the thermal response of the solidification area behind the molten pool during the laser additive repair comprises the following steps: During the laser additive repair, the thermal radiation signal of a preset specific wavelength is received by setting a narrowband filter of a high-speed camera; By adjusting the exposure time, the working state of the high-speed camera is adapted to the wide temperature variation of the solidification area behind the molten pool; According to the received thermal radiation signal of the preset specific wavelength and the exposure data of the high-speed camera after adapting to the wide temperature variation, the thermal response of the solidification area behind the molten pool is detected in real time.

3. A method of laser additive defect detection of a steel rail according to claim 1, characterized in that, The step of calculating the actual heat dissipation rate of the local area corresponding to the instant hot spot according to the thermal radiation attenuation information to realize the detection of the damaged area of the steel rail comprises the following steps: The local area of the steel rail substrate is linearly scanned and heated to form an instant hot line; Collecting thermal radiation attenuation information of the instant hot line; The thermal radiation attenuation information is regionally averaged to obtain the corresponding actual heat dissipation rate.

4. A method of laser additive defect detection of a steel rail according to claim 1, characterized in that, The step of adjusting the repair process parameters according to the local difference information comprises the following steps: According to the local difference information, the material properties and geometric structure characteristics of the current repair area are determined; According to the material properties and geometric structure characteristics, the heat dissipation efficiency of the current repair area is calculated; According to the heat dissipation efficiency, an adjustment amount of laser power, an adjustment amount of scanning speed, and an adjustment amount of powder feeding rate are determined to obtain parameter adjustment amount information; The parameter adjustment amount information is applied to the repair process parameters to obtain adjusted repair process parameters.

5. A method of laser additive defect detection of a steel rail according to claim 4, characterized in that, After the step of determining the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate according to the heat dissipation efficiency to obtain parameter adjustment amount information, the method further comprises: Obtaining real-time environmental parameters of the current repair area; Obtaining actual output parameters of the laser additive equipment under the current working condition; According to the heat dissipation efficiency, the real-time environmental parameters, and the actual output parameters, the parameter adjustment amount information is corrected.

6. A method of laser additive defect detection of a steel rail according to claim 4, characterized in that, The step of determining the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate according to the heat dissipation efficiency to obtain parameter adjustment amount information comprises: According to the heat dissipation efficiency, real-time temperature information and stress state information of the current repair area are obtained; According to the real-time temperature information and the stress state information, the corresponding thermal physical parameters are adjusted; According to the heat dissipation efficiency and the adjusted thermal physical parameters, an instantaneous mapping relationship between the heat dissipation efficiency and the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate is calculated; According to the instantaneous mapping relationship, the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate are determined to obtain parameter adjustment amount information.

7. A method of laser additive defect detection of a steel rail according to claim 6, characterized in that, The step of obtaining real-time temperature information and stress state information of the current repair area according to the heat dissipation efficiency comprises: Temperature information of the current repair area is collected; By selecting a plurality of thermal radiation signals of specific wavelength ranges, and according to the intensity ratio of the thermal radiation signals of each specific wavelength, the real-time temperature information of the current repair area is calculated; The stress state information of the current repair area is collected; An ultrasonic wave is excited inside the steel rail by emitting a laser pulse; The echo signal of the ultrasonic wave propagating inside the steel rail is received; According to the propagation time, attenuation, and frequency shift of the echo signal, the real-time stress state information of the current repair area is calculated.

8. A rail laser additive defect detection system for performing rail laser additive defect detection, the rail laser additive defect detection system comprising: Comprise: An instantaneous hot spot forming module is configured to perform instantaneous heating on a local area of a steel rail base before laser additive repair of a damaged area of the steel rail, so as to form an instantaneous hot spot in the corresponding local area; An attenuation information collection module is configured to collect thermal radiation attenuation information of the instantaneous hot spot; A heat dissipation rate calculation module is configured to calculate an actual heat dissipation rate of the local area corresponding to the instantaneous hot spot according to the thermal radiation attenuation information, so as to realize detection of the damaged area of the steel rail; A process parameter selection module is configured to select repair process parameters for the laser additive repair from a pre-stored process parameter combination according to the actual heat dissipation rate; A damaged area repair module is configured to perform the laser additive repair of the damaged area of the steel rail by using the repair process parameters; After the step of performing the laser additive repair of the damaged area of the steel rail by using the repair process parameters, the method further comprises: During the laser additive repair, the thermal response of a solidification area behind a molten pool is detected; According to the thermal response, an instantaneous cooling rate of a solidification area behind the molten pool is calculated; The instantaneous cooling rate is compared with a preset target cooling rate range to obtain a cooling rate deviation; According to the cooling rate deviation, a repair process parameter corresponding to an unrepaired front path in the laser additive repair process is adjusted to guide the instantaneous cooling rate of the unrepaired front path back to the target cooling rate range; The step of repairing the damaged area of the steel rail by using the repair process parameter includes: During the laser additive repair process, current position information of a laser additive device on the steel rail base body is obtained; According to the current position information, local difference information corresponding to the current position is obtained; According to the local difference information, the repair process parameter is adjusted; The current position of the damaged area of the steel rail is repaired by using the adjusted repair process parameter.

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