Steel rail laser additive defect detection method and system

Abstract

The invention relates to the technical field of steel rail repair, and provides a steel rail laser additive defect detection method and system.The method comprises the steps that before laser additive repair is conducted on a steel rail damage area, a local area of a steel rail base body is instantly heated, so that an instant hot spot is formed in the corresponding local area; collecting thermal radiation attenuation information of the instantaneous hot spot; according to the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated so as to achieve detection of the steel rail damage area; according to the actual heat dissipation rate, repairing process parameters used for laser additive repairing are selected from a pre-stored process parameter combination; and carrying out laser additive repair on the damaged region of the steel rail by adopting the repair process parameters. The method has the effect of improving the quality and reliability of steel rail laser additive repair.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel rail repair, and in particular to a steel rail laser additive defect detection method and system. BACKGROUND

[0002] In the daily maintenance of railway infrastructure, surface damage such as fatigue cracks and wear pits is a common problem due to long-term bearing of train load and impact. In order to efficiently and economically repair these damages, laser additive repair technology, that is, laser cladding, is widely used. This technology restores the integrity of the steel rail by cladding a new layer of metal material on the damaged area. However, laser cladding is a process of rapid heating and cooling, and especially in complex field operation environment, factors such as ambient temperature and wind speed will significantly affect the cooling speed of the repaired area. Too fast cooling can cause the formation of hard and brittle microstructure inside the repaired layer, and generate large residual stress, which is not found by existing surface optical detection methods, thus burying the safety hazard of "surface qualified, internal failure".

[0003] The existing online detection system can only see the surface of the cladding layer with its "eyes". It can well find a pore or a small surface crack, because it can directly "see" these geometric discontinuities. However, for the excessive residual stress formed inside the repaired area and the undesirable brittle phase structure generated due to the too fast cooling speed, this system is completely "blind". From the image of the monitoring system, the repaired surface is smooth and flat, without any visible defects, and the system will give a conclusion of "qualified repair quality". But in fact, this seemingly perfect repaired area may be full of invisible internal stress, and its microstructure has become brittle. When the first train passes through this repair point with a huge impact force, these invisible internal defects may expand instantaneously, causing the repaired layer to peel off in large pieces, and even causing more serious safety accidents.

[0004] In view of the above problems, the existing technology needs to be improved. SUMMARY

[0005] The present application discloses a steel rail laser additive defect detection method and system, which aims to solve the problem that it is difficult to effectively detect internal defects of the repaired area in the existing steel rail laser additive repair process, and the repair process parameters are difficult to dynamically adjust according to the actual situation, thereby causing the safety hazard of "surface qualified, internal failure".

[0006] The technical solution of the present application is as follows: In a first aspect, the present application discloses a steel rail laser additive defect detection method, comprising: before laser additive repair is performed on the damaged area of the steel rail, a local area of the steel rail substrate is instantaneously heated to form an instantaneous hot spot in the corresponding local area; thermal radiation decay information of the instantaneous hot spot is collected; According to the thermal radiation decay 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, repair process parameters for laser additive repair are selected from pre-stored process parameter combinations; The repair process parameters are used to perform laser additive repair on the damaged area of the steel rail.

[0007] Through the technical solution, before laser additive repair, the local area of the steel rail substrate is instantaneously heated and the thermal radiation decay information is collected, and then the actual heat dissipation rate is calculated, which realizes the effective detection of the damaged area of the steel rail. Based on the detection result, appropriate repair process parameters can be selected, thereby avoiding the problem of "surface qualified, internal failure" caused by the inability to find internal defects in the traditional method, and significantly improving the repair quality and safety.

[0008] Further, after the step of using the repair process parameters to perform laser additive repair on the damaged area of the steel rail, the method further comprises: During the laser additive repair process, the thermal response of the solidified area behind the molten pool is detected; According to the thermal response, the instantaneous cooling rate of the solidified area behind the molten pool is calculated; The instantaneous cooling rate is compared with a pre-set 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.

[0009] Through the technical solution, the real-time cooling rate monitoring and feedback adjustment mechanism is introduced during the laser additive repair process, which can dynamically control the cooling rate within the target range, effectively avoiding the problems of brittle structure formation and excessive residual stress caused by excessive cooling, and further improving the internal quality and reliability of the repair layer.

[0010] More specifically, in some embodiments, during the laser additive repair process, the step of detecting the thermal response of the solidified area behind the molten pool comprises: During the laser additive repair process, the thermal radiation signal of a pre-set 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 solidified area behind the molten pool; According to the received preset specific wavelength thermal radiation signal and the exposure data of the high-speed camera after the wide temperature change is adapted, the thermal response of the solidification area behind the molten pool is detected in real time.

[0011] Through the technical scheme, the application realizes accurate and real-time detection of the thermal response of the solidification area behind the molten pool by combining the high-speed camera with the narrowband filter and the exposure time adjustment, ensures the accuracy of data acquisition under wide temperature change, and provides a reliable data basis for accurate calculation of the cooling rate and fine adjustment of the process parameters.

[0012] On the basis of the above, the application further proposes that the step of detecting the damage area of the steel rail according to the thermal radiation decay information includes: Linearly scanning and heating the local area of the steel rail base to form a transient hot line; Collecting thermal radiation decay information of the transient hot line; Regionally averaging the thermal radiation decay information to obtain the corresponding actual heat dissipation rate.

[0013] Through the technical scheme, the application can more comprehensively and accurately obtain the heat dissipation characteristics of the local area by linearly scanning and heating to form a transient hot line and regionally averaging, thereby improving the accuracy and reliability of the detection of the damage area of the steel rail, and being especially suitable for the evaluation of larger or irregular damage areas.

[0014] Preferably, the application also discloses a steel rail laser additive defect detection method, wherein the step of laser additive repair of the damage area of the steel rail by using the repair process parameters includes: During the laser additive repair, the current position information of the laser additive equipment on the steel rail base 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 damage area of the steel rail is repaired by laser additive repair by using the adjusted repair process parameters.

[0015] Through the technical scheme, the application introduces a process parameter dynamic adjustment mechanism based on local difference information during the laser additive repair process, which can optimize the repair parameters in real time according to the specific conditions of different positions of the damage area of the steel rail, thereby significantly improving the adaptability and uniformity of the repair, and ensuring the repair quality of complex damage areas.

[0016] On the basis of the above, the application further proposes that the step of adjusting the repair process parameters according to the local difference information includes: 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, 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; The parameter adjustment amount information is applied to the repair process parameters to obtain adjusted repair process parameters.

[0017] Through the technical scheme, the material properties, geometric structure characteristics and heat dissipation efficiency are determined in detail, and the adjustment amounts of laser power, scanning speed and powder feeding rate are calculated accordingly, so that the precise and quantitative adjustment of the repair process parameters is realized, and the control accuracy of the repair process and the stability of the repair quality are greatly improved.

[0018] In some preferred embodiments, 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.

[0019] Through the technical scheme, the influence of real-time environmental parameters and actual output parameters of the equipment is further considered on the basis of parameter adjustment, the parameter adjustment amount information is corrected, the adjustment of the repair process parameters is more close to the actual working condition, the complexity and uncertainty of the field operation environment are effectively coped with, and the robustness and success rate of the repair are further improved.

[0020] On the basis of the above, the method further comprises 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, which 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 stress state information, the corresponding thermal physical parameters are adjusted; According to the heat dissipation efficiency and the adjusted thermal physical parameters, the 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.

[0021] By the technical solution, the real-time temperature and stress state information are acquired, and the thermal physical parameters are adjusted accordingly, and then the instantaneous mapping relationship between the heat dissipation efficiency and the process parameter adjustment amount is calculated, so that the intelligent and adaptive adjustment of the repair process parameters is realized, and the precision and adaptability of the repair process to complex working conditions are greatly improved.

[0022] More specifically, in some embodiments, according to the heat dissipation efficiency, the step of acquiring real-time temperature information and stress state information of the current repair area includes: collecting temperature information of the current repair area; calculating real-time temperature information of the current repair area by selecting thermal radiation signals of several specific wavelength ranges and according to the intensity ratio of the thermal radiation signals of each specific wavelength; collecting stress state information of the current repair area; exciting ultrasonic waves inside the steel rail by emitting laser pulses; receiving echo signals after the ultrasonic waves propagate inside the steel rail; calculating real-time stress state information of the current repair area according to the propagation time, attenuation and frequency shift of the echo signals.

[0023] By the technical solution, the real-time temperature is accurately measured by the multi-wavelength thermal radiation signal ratio method, and the real-time stress state is non-destructively detected by the laser ultrasonic technology, which provides high-precision and real-time internal state data for the adjustment of the thermal physical parameters of the repair area, and significantly improves the intelligence and refinement level of the repair process.

[0024] In a second aspect, the application also discloses a steel rail laser additive defect detection system for performing steel rail laser additive defect detection, comprising: An instantaneous hot spot forming module is configured to heat a local area of a steel rail base body instantaneously 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 acquisition module is configured to acquire 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 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 laser additive repair on the damaged area of the steel rail by using the repair process parameters.

[0025] Through the technical scheme, the steel rail laser additive defect detection system is provided, through the modular design, the pre-repair detection of the steel rail damage area, the intelligent selection of the process parameters and the automation and integration of the repair execution are realized, the limitations of the artificial experience judgment are effectively solved, and the repair efficiency and the stability of the quality are improved.

[0026] Beneficial effects: the steel rail laser additive defect detection method is provided, the local area of the steel rail base body is instantaneously heated to form an instantaneous hot spot before laser additive repair, and the thermal radiation attenuation information is collected. According to the attenuation information, the actual heat dissipation rate of the local area is calculated, so that the detection of the damage area of the steel rail is realized. The method can effectively identify the heat dissipation characteristic difference of the internal steel rail, and then judge whether there is fatigue crack, wear pit and other damage, and overcome the defect that the existing surface optical detection method cannot find internal defects. On this basis, the most suitable repair process parameters are selected from the pre-stored process parameter combinations according to the actual heat dissipation rate, and the parameters are used for laser additive repair. The scheme can dynamically adjust the repair process according to the actual condition of the damage area of the steel rail, and avoid the problems that the internal microstructure of the repair layer is hard and brittle and large residual stress is generated due to the too fast cooling speed, so that the safety hidden danger of'surface qualified and internal failure' is effectively solved. Through the method, the quality and reliability of the steel rail laser additive repair are significantly improved, the service life of the steel rail is prolonged, and the safety of railway transportation is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 The method flow chart of the steel rail laser additive defect detection method in one of the embodiments of the application; Figure 2 The sub-step flow chart of the steel rail laser additive defect detection method in another embodiment of the application; Figure 3 The system block diagram of the steel rail laser additive defect detection system in another embodiment of the application; Explanation of reference signs: 1, steel rail laser additive defect detection system; 11, instantaneous hot spot forming module; 12, attenuation information collection module; 13, heat dissipation rate calculation module; 14, process parameter selection module; 15, damage area repair module. DETAILED DESCRIPTION

[0028] The technical solutions in the present application will be described clearly and completely in the present application in combination with the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present application.

[0029] It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0030] The specific embodiments of the present application disclose a steel rail laser additive defect detection method, which combines Figure 1 as shown, comprising: S1, before laser additive repair of the damaged area of the steel rail, locally heating the local area of the steel rail base to form a transient hot spot in the corresponding local area; S2, collecting thermal radiation attenuation information of the transient hot spot; S3, calculating the actual heat dissipation rate of the local area corresponding to the transient hot spot according to the thermal radiation attenuation information, to realize detection of the damaged area of the steel rail; S4, selecting repair process parameters for laser additive repair from the pre-stored process parameter combinations according to the actual heat dissipation rate; S5, using the repair process parameters to perform laser additive repair on the damaged area of the steel rail.

[0031] Specifically, before laser additive repair of the damaged area of the steel rail, the local area of the steel rail base needs to be locally heated to form a transient hot spot in the corresponding local area. The transient heating can be realized in various ways. For example, a high-energy pulsed laser beam can be used to irradiate the local area for a short time to rapidly raise the surface temperature to form a hot spot; or a high-intensity light source such as a flash lamp or a xenon lamp can be used to radiate and heat the target area in a very short time; or a local induction heating coil can be used to generate eddy current effect in the local area by high-frequency current to achieve rapid heating. These heating methods can all make the local area reach a high temperature in a very short time to form a transient hot spot for subsequent detection.

[0032] Subsequently, the thermal radiation decay information of the transient hot spot needs to be collected. The collection of thermal radiation decay information can be completed by non-contact temperature measurement equipment. For example, an infrared thermometer or a thermal imager can be used to continuously monitor the transient hot spot and record the temperature change curve over time. These devices can capture the change in thermal radiation intensity during the entire process of the hot spot gradually cooling down after heating stops, thereby obtaining the thermal radiation decay information.

[0033] According to the thermal radiation decay information, the actual heat dissipation rate of the local area corresponding to the transient hot spot is calculated to realize the detection of the damaged area of the steel rail. The calculation of the actual heat dissipation rate can be based on a theoretical model of heat conduction. For example, by fitting the collected thermal radiation decay curve with a preset theoretical cooling model, the thermal diffusivity or heat dissipation coefficient of the local area can be inversely deduced, and then the actual heat dissipation rate is obtained. The heat dissipation rate can also be indirectly evaluated by analyzing the time required for the hot spot to drop from the peak temperature to a certain specific temperature, or the temperature drop amplitude within a certain period of time. Abnormal heat dissipation, such as too fast or too slow heat dissipation, usually indicates that there is a defect inside the steel rail, such as a crack, a cavity, or a non-uniform structure, because these defects will change the conduction path and efficiency of heat.

[0034] Further, according to the actual heat dissipation rate, the repair process parameters for laser additive repair are selected from the pre-stored process parameter combinations. The selection process can be based on a pre-established database or mapping relationship. For example, according to different heat dissipation rate ranges, multiple sets of laser power, scanning speed, powder feeding rate, and other repair process parameter combinations can be preset. When a certain actual heat dissipation rate is detected, the system automatically matches or searches for the process parameter combination closest or most suitable to it in the database. This selection can be a simple table lookup matching or a judgment based on empirical rules.

[0035] Finally, the damaged area of the steel rail is repaired by laser additive manufacturing using the repair process parameters. After obtaining the selected repair process parameters, the laser additive manufacturing equipment will operate according to these parameters. For example, the laser will output laser at a set power, the scanning head will move at a set speed, and the powder feeder will deliver metal powder at a set rate. The entire repair process will strictly follow these parameters to achieve the best repair effect under the current detected state of the steel rail substrate. In some embodiments, the repair process parameters can remain fixed throughout the repair process, or only be adjusted according to macro regional division, without real-time, micro dynamic adjustment.

[0036] The scheme of the present application aims at the problem that internal defects after laser additive repair of steel rails are difficult to be effectively detected in the prior art, and proposes a forward-looking solution. Traditional methods often rely on post-repair surface detection and cannot reveal internal brittle structures and residual stresses caused by rapid cooling. The present application can calculate the actual heat dissipation rate reflecting the internal structure and defects by locally and instantaneously heating the steel rail substrate before repair and analyzing its thermal radiation attenuation information. This detection method based on thermal physical properties can effectively identify internal defects that cannot be found by traditional optical detection methods, such as micro-cracks, cavities or uneven structures. By combining the detected heat dissipation rate with the selection of repair process parameters, adaptive adjustment of repair parameters is realized, thereby predicting and avoiding the risk of reduced repair quality caused by substrate defects before repair. Compared with the passive detection and rework mode in the prior art, the scheme of the present application realizes defect prediction before repair and optimization of process parameters, significantly improves the success rate and reliability of repair, and fundamentally solves the safety hazard of "surface qualified, internal failure", which has significant progress.

[0037] Optionally, after the step of laser additive repair of the damaged area of the steel rail using the repair process parameters, the method further comprises: In the process of 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 in the process of laser additive repair are adjusted to guide the instantaneous cooling rate of the unrepaired front path back to the target cooling rate range.

[0038] Specifically, in the process of laser additive repair, the thermal response of the solidification area behind the molten pool needs to be monitored in real time. The thermal response can be understood as the temperature change, thermal radiation intensity or cooling curve of the area, which can directly reflect the thermal behavior of the material during solidification. The solidification area behind the molten pool refers to the area behind the molten pool in the moving process of the laser molten pool, in which the metal material changes from liquid to solid. The cooling rate of the area has a decisive influence on the microstructure and mechanical properties of the final repair layer. The purpose of detecting the thermal response of the area is to obtain its instantaneous thermal state in the actual repair process.

[0039] According to the detected thermal response, the transient cooling rate of the solidification region behind the molten pool can be calculated. The transient cooling rate refers to the magnitude of temperature drop per unit time, which is a key parameter for evaluating the solidification process of the material. For example, the transient cooling rate can be calculated by analyzing the slope of the thermal response curve. The calculated transient cooling rate is compared with a preset target cooling rate range to obtain a cooling rate deviation. The preset target cooling rate range is a desired cooling rate interval determined in advance according to the required microstructure and mechanical properties of the repaired layer. The cooling rate deviation quantifies the deviation between the actual cooling rate and the target range.

[0040] Based on the cooling rate deviation, the repair process parameters corresponding to the front path that has not yet been repaired during the laser additive repair process can be adjusted. This means that the system predicts and adjusts the process parameters, such as laser power, scanning speed, or powder feeding rate, of the subsequent repair region according to the actual cooling condition of the current repaired region. The purpose of the adjustment is to guide the transient cooling rate of the unrepaired front path back to the preset target cooling rate range, thereby achieving real-time adaptive control of the entire repair process.

[0041] In some preferred embodiments, the following is described by a specific example. Suppose that during the laser additive repair of a damaged area of a steel rail, the initially selected repair process parameters, when repairing the front region, result in a transient cooling rate of the solidification region behind the molten pool that is slightly higher than the preset target cooling rate range due to local stress concentration or slight fluctuations in material composition within the steel rail. At this time, the system will detect the thermal response of the solidification region in real time through the infrared thermal imager or high-speed narrowband radiometer arranged behind the repair head, such as obtaining its temperature distribution and variation curve over time. According to these thermal response data, the actual transient cooling rate is calculated. If the calculation result shows that the cooling rate is 150 K / s, while the preset target cooling rate range is 100-120 K / s, the system will identify a cooling rate deviation of 30-50 K / s. Based on this deviation, the control system will immediately adjust the repair process parameters of the subsequent path that has not yet been repaired. For example, in order to reduce the cooling rate, the system may automatically reduce the laser power output, or appropriately increase the scanning speed, or adjust the powder feeding rate to reduce the energy input per unit area, so that the transient cooling rate of the subsequent repair region can be guided back to the target range of 100-120 K / s. Through this real-time feedback and forward-looking 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.

[0042] Optionally, the step of detecting the thermal response of the solidification region behind the molten pool during the laser additive repair process comprises: In the process of laser additive repair, a narrow-band filter of a high-speed camera is set to receive thermal radiation signals of a preset specific wavelength; The working state of the high-speed camera is adjusted to adapt to the wide temperature variation of the solidification area behind the molten pool by adjusting the exposure time; According to the received thermal radiation signals 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.

[0043] Specifically, in the process of laser additive repair, the temperature of the solidification area behind the molten pool will undergo a rapid cooling process from high-temperature liquid to solid state, and the temperature variation range may be very wide. In order to accurately capture the thermal response in this dynamic process, a high-speed camera can be used for data acquisition. The high-speed camera is configured 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 the specific wavelength can be based on the thermal radiation characteristics of the steel rail material to be repaired, for example, selecting a wavelength range with strong radiation intensity at high temperature and less environmental interference.

[0044] Further, in order to ensure that the high-speed camera can still work effectively and obtain accurate thermal response data under wide temperature variation, the exposure time of the high-speed camera needs to be dynamically adjusted. For example, when the solidification area behind the molten pool is at an extremely high temperature, the exposure time can be shortened to avoid overexposure of the image; when the temperature is relatively low, the exposure time can be appropriately extended to ensure sufficient signal intensity. This adaptive adjustment of exposure time enables the high-speed camera to always be in the best working state, thereby accurately capturing the thermal radiation information of the solidification area behind the molten pool during the entire cooling process.

[0045] Thus, according to the received thermal radiation signals 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 can be calculated or derived in real time. The thermal response can be represented by parameters such as temperature and radiation intensity, which can directly reflect the instantaneous thermal state and cooling behavior of the area.

[0046] The scheme of the present application solves the problem of difficult real-time detection of the thermal response of the solidification area behind the molten pool in the process of laser additive repair by introducing a high-speed camera, a narrow-band filter and a mechanism for adaptive adjustment of exposure time. Specifically, the use of a narrow-band filter ensures the purity of the collected thermal radiation signals, eliminating the interference of other wavelengths of stray light on the measurement, making the reception of specific wavelength thermal radiation signals more accurate. At the same time, by dynamically adjusting the exposure time of the high-speed camera, the camera can adapt to the wide temperature change from high temperature to low temperature of the solidification area behind the molten pool, avoiding the overexposure or underexposure problem that may occur at extreme temperatures with traditional fixed exposure time, thereby ensuring the integrity and accuracy of the thermal response data throughout the cooling process. It is precisely due to these synergies that the real-time thermal response of the solidification area behind the molten pool can be accurately detected, providing a reliable data foundation for subsequent instantaneous cooling rate calculation and accurate adjustment of repair process parameters.

[0047] Optionally, the step of calculating the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot according to the thermal radiation decay information to realize the detection of the damaged area of the steel rail can include the following ways: Linearly scanning and heating the local area of the steel rail base to form an instantaneous hot line; Collecting the thermal radiation decay information of the instantaneous hot line; Regionally averaging the thermal radiation decay information to obtain the corresponding actual heat dissipation rate.

[0048] Wherein, linearly scanning and heating the local area of the steel rail base means that through a laser or other instantaneous heating source, a rapid linear moving heating is performed along a specific local area of the steel rail base, thereby forming an instantaneous high-temperature linear area, i.e. an instantaneous hot line, in the area. This linear scanning and heating method aims to cover a larger detection range than the instantaneous hot spot, so as to more comprehensively evaluate the heat dissipation characteristics of the damaged area of the steel rail.

[0049] Further, collecting the thermal radiation decay information of the instantaneous hot line means that after the formation of the instantaneous hot line, an infrared thermal imager, a high-speed thermocouple array or other thermal radiation sensors are used to obtain the data of the change of the thermal radiation signals emitted by the hot line over time in real time or quasi-real time during the cooling process. These data reflect the speed and mode of heat dissipation from the instantaneous hot line to the surrounding steel rail base.

[0050] Thus, the thermal radiation decay information is regionally averaged to obtain the corresponding actual heat dissipation rate. Specifically, since the instantaneous heat line is a linear region, the thermal radiation decay information thereof may have slight differences at different points. By averaging the thermal radiation decay information in the linear region, the influence of local noise or slight non-uniformity can be eliminated, thereby 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 is further used for defect detection and evaluation.

[0051] The scheme of the present application can more effectively represent the heat dissipation characteristics of the rail damage area by extending the instantaneous heating mode from a point to a line and combining regional averaging. When the rail substrate has damage (such as cracks, holes, or material non-uniformity), its heat conduction and heat dissipation performance will change. The instantaneous heat line formed by linear scanning heating can cover a longer damage path or a larger damage area, so that the heat propagation and dissipation process in the damage area can be more comprehensively captured. The thermal radiation decay information of the collected instantaneous heat line contains detailed data of the thermal physical properties of the damage area. Subsequently, by regionally averaging this information, the interference of a single measurement point or local anomalies on the overall evaluation can be effectively reduced, thereby obtaining a more reliable and accurate actual heat dissipation rate. The difference between this actual heat dissipation rate value and the heat dissipation rate of a non-damaged area can clearly indicate the presence, location, and extent of rail damage, thereby achieving effective detection of the rail damage area.

[0052] Optionally, the step of laser additive repair of the rail damage area using the repair process parameters comprises: During the laser additive repair process, the current position information of the laser additive equipment on the rail substrate 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 parameters are adjusted; The current position of the rail damage area is laser additive repaired using the adjusted repair process parameters.

[0053] Specifically, during the laser additive repair process, the current position information of the laser additive equipment on the rail substrate needs to be obtained in real time. The position information can be obtained in various ways, for example, high-precision encoders, laser ranging sensors, visual positioning systems, or global positioning systems can be used for real-time monitoring and feedback. The purpose of obtaining the current position information is to accurately know which part of the rail is being repaired by the laser additive head, so as to subsequently perform targeted parameter adjustment.

[0054] The local difference information can be understood as the differences in physical, chemical or geometric characteristics between the current repair area and other areas of the rail or the ideal state. These differences can include but are not limited to the depth, width, shape, microstructure, chemical composition, thermal physical properties (such as thermal conductivity, specific heat capacity) and surface roughness of the damage. Obtaining local difference information can be achieved by pre-scanning (for example, using a three-dimensional scanner, ultrasonic detection equipment or eddy current detection equipment to comprehensively scan the damage area, establishing a three-dimensional model and defect distribution map of the damage area) or real-time detection during the repair process (for example, monitoring the local temperature distribution by an infrared thermal imager, analyzing the material composition by a spectrometer or measuring the geometric morphology by a laser displacement sensor). The purpose is to provide accurate input data for subsequent process parameter adjustment.

[0055] In practical applications, adjusting the repair process parameters according to the local difference information means dynamically modifying the key process parameters of additive repair such as laser power, scanning speed, powder feeding rate, spot size or protective gas flow according to the specific situation of the current position. For example, when the depth of the damage area is detected to be large, the laser power can be appropriately increased or the scanning speed can be reduced to ensure that the molten pool depth and cladding layer thickness meet the requirements; when the material composition is detected to change, the powder feeding 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 pre-set parameter adjustment rule library, a machine learning model or a real-time feedback control algorithm, and the purpose is to ensure that the best repair quality and efficiency can be obtained under different local conditions.

[0056] Therefore, using the adjusted repair process parameters to perform laser additive repair on the current position of the rail damage area means that the repair process is no longer static, but dynamic and adaptive. Whenever the laser additive equipment moves to a new position or detects a change in the local difference of the current position, the repair process parameters will be recalculated and adjusted to ensure that the most suitable process parameters for the current local conditions are always used during the repair process of the entire damage area.

[0057] The scheme of the present application realizes the dynamic adjustment of the repair process parameters by introducing the acquisition of the current position information of the laser additive equipment and the identification of the local difference information corresponding to the current position. Specifically, when the laser additive equipment is repairing the damaged area of the rail, its current position is monitored in real time, and combined with the local difference information of the position (such as the geometric characteristics of the damage, the material state, etc.), the system can accurately determine the optimal process conditions required for the current repair point. It is precisely due to this real-time position sensing and local difference analysis that the repair process parameters can be accurately and adaptively adjusted, thereby overcoming the limitations of the traditional fixed parameter repair scheme 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 the optimal repair effect is obtained in different local areas.

[0058] In some preferred embodiments, the following is described by a specific example. Suppose a section of rail has an irregular damaged area, the depth and width of which vary significantly at different positions, and there may be micro-cracks in some areas. When laser additive repair is performed, first, the laser additive equipment acquires its current position coordinates on the rail in real time through its built-in visual positioning system and encoder. At the same time, a laser scanner integrated in the repair head scans the current repair area in real time to obtain accurate three-dimensional geometric data of the area, including the depth and slope information of the damage. In addition, an infrared thermal imager synchronously monitors the surface temperature distribution of the current area to evaluate the thermal physical state of the material.

[0059] When the equipment moves to an area with deep damage and large slope, according to the acquired position information and local difference information, the control system determines that a larger energy input is needed to ensure sufficient fusion. At this time, the repair process parameters are automatically adjusted, for example, the laser power may be increased by 15%, and at the same time the scanning speed may be appropriately reduced by 10% to ensure that the depth and width of the molten pool can completely cover the damaged area and form a good metallurgical bond. When the equipment moves to an area with shallow damage or micro-cracks, the system adjusts the parameters according to the 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 more delicate and uniform cladding layer and effectively fill the micro-cracks. In this way, the repair process of the entire damaged area can be optimized according to its unique local characteristics, thereby ensuring the consistency and reliability of the repair quality.

[0060] Optionally, the step of adjusting the repair process parameters according to the local difference information comprises: determining the material properties and geometric structure characteristics of the current repair area according to the local difference information; calculating the heat dissipation efficiency of the current repair area according to the material properties and geometric structure characteristics; determine an adjustment amount of laser power, an adjustment amount of scanning speed, and an adjustment amount of powder feeding rate according to the heat dissipation efficiency, to obtain parameter adjustment amount information; apply the parameter adjustment amount information to the repair process parameters to obtain adjusted repair process parameters.

[0061] Specifically, after obtaining the current position information of the laser additive equipment on the rail base, the local difference information corresponding to the current position can be further obtained. The local difference information can include but is not limited to the geometric shape of the rail damage area (such as the depth, width, and curvature of the crack), the surface roughness, and the possible material inhomogeneity (such as the oxide layer, residual stress area, or different alloy components). Based on these local difference information, the material properties and geometric structure features of the current repair area can be determined. Among them, the material properties can refer to the thermal physical parameters such as the thermal conductivity, specific heat capacity, and density of the area, while the geometric structure features refer to the volume, surface area, and contact area with the surrounding base. These features can be obtained and analyzed through pre-existing 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).

[0062] Further, according to the determined material properties and geometric structure features, the heat dissipation efficiency of the current repair area can be calculated. The heat dissipation efficiency refers to the proportion of the heat dissipated from the repair area to the surrounding environment or the base per unit time to the total input heat during the laser additive process. The calculation can be performed through the establishment of a heat conduction model, finite element analysis, or based on empirical formulas. For example, for an area with a larger surface area or a larger contact area with the base, its heat dissipation efficiency may be higher; for a material with a higher thermal conductivity, the heat dissipation may also be faster.

[0063] Therefore, according to the calculated heat dissipation efficiency, the adjustment amount of laser power, the adjustment amount of scanning speed, and the adjustment amount of powder feeding rate can be determined, thereby obtaining the parameter adjustment amount information. For example, when the heat dissipation efficiency is high, in order to maintain the stability of the molten pool and the required melting depth, it may be necessary to increase the laser power or reduce the scanning speed; when the heat dissipation efficiency is low, it may be necessary to reduce the laser power or increase the scanning speed to avoid overheating. The adjustment of the powder feeding rate can be coordinated according to the required accumulation height and the size of the molten pool. These adjustment amounts can be calculated and determined through a pre-established process database, a machine learning model, or a real-time feedback control algorithm.

[0064] Finally, the parameter adjustment amount information is applied to the repair process parameters to obtain adjusted repair process parameters. This means that the original repair process parameters (e.g., the initial set laser power, scanning speed, 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 repair path.

[0065] The scheme of the present application solves the problem of inaccurate parameter adjustment in the face of complex local differences in traditional methods by introducing accurate calculation of the material properties, geometric structure characteristics and heat dissipation efficiency of the current repair area. Specifically, by identifying and quantifying the impact of local differences on heat dissipation, the laser additive equipment can dynamically adjust the laser power, scanning speed and powder feeding rate according to the actual thermal physical environment. This adjustment mechanism based on heat dissipation efficiency ensures that a stable molten pool state and appropriate cooling rate can be maintained in different local areas, thereby avoiding defects such as pores, cracks or uneven organization caused by mismatched heat input. It is precisely this fine thermal management that enables the repair process to better adapt to the complexity and diversity of the damaged area of the steel rail.

[0066] In some preferred embodiments, the following is described by a specific example. Suppose that during laser additive repair of a section of steel rail, a deep V-shaped crack and a shallow surface scratch are detected in the damaged area.

[0067] For the deep V-shaped crack area, its geometric structure characteristics exhibit a large depth and a small width, which will result in a relatively large contact area between the molten pool and the surrounding matrix during formation, and heat is more easily dissipated to the depth and both sides, thus making the heat dissipation efficiency of the area relatively high. According to the scheme of the present application, after determining this high heat dissipation efficiency, the system will calculate the adjustment amount of the laser power to be increased and / or the adjustment amount of the scanning speed to be reduced, and at the same time, the powder feeding rate may need to be increased to fill a larger volume. For example, the laser power may be adjusted from the 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.

[0068] For the shallow surface scratch area, its geometric structure characteristics exhibit a small depth and a large width, and the heat dissipation efficiency is relatively low. At this time, the system will determine the adjustment amount of the laser power to be reduced and / or the adjustment amount of the scanning speed to be increased according to the calculated lower heat dissipation efficiency, in order to avoid overheating and excessive material accumulation. 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 feeding rate from 5g / min to 4.5g / min.

[0069] Through this dynamic parameter adjustment based on heat dissipation efficiency, it can be ensured that the best molten pool state and material deposition can be obtained in different damage areas, so as to realize high-quality repair.

[0070] Optionally, 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 the parameter adjustment amount information, it further includes: obtaining real-time environmental parameters of the current repair area; obtaining actual output parameters of the laser additive equipment under the current working condition; correcting the parameter adjustment amount information according to the heat dissipation efficiency, the real-time environmental parameters and the actual output parameters.

[0071] Specifically, obtaining real-time environmental parameters of the current repair area means that during the laser additive repair process, corresponding sensors are deployed to monitor and obtain environmental factors such as temperature, humidity and air flow speed around the repair area in real time. Changes in these environmental parameters will directly affect the cooling rate of the material and the stability of the molten pool. For example, an increase in environmental temperature may lead to a decrease in cooling rate, while an increase in air flow speed may accelerate cooling. At the same time, obtaining actual output parameters of the laser additive equipment under the current working condition means monitoring the actual output power of the laser, the actual spot size, the actual scanning speed of the scanning galvanometer and the actual powder feeding rate of the powder feeder, etc. in real time. Although the equipment has preset parameters, due to equipment aging, internal loss or external interference, the actual output may deviate from the preset value. Among them, correcting the parameter adjustment amount information according to the heat dissipation efficiency, the real-time environmental parameters and the actual output parameters means that the preliminary adjustment amount calculated based on the heat dissipation efficiency is combined with real-time environmental data and actual performance data of the equipment for secondary calibration. This correction can be achieved using a pre-established mathematical model, lookup table or machine learning algorithm to ensure that the final repair process parameters applied can more accurately adapt to the current actual working condition.

[0072] The scheme of the present application corrects the preliminary determined parameter adjustment information by introducing real-time environmental parameters and actual output parameters of the laser additive equipment, thereby solving the problem of insufficient precision caused by parameter adjustment only according to local differences and heat dissipation efficiency. Specifically, the acquisition of real-time environmental parameters enables the system to perceive and compensate for the influence of the external environment on the thermal field distribution and the cooling process. For example, when the environmental temperature rises, the system can accordingly fine-tune the laser power or the scanning speed to maintain the expected heat input and cooling rate. At the same time, the monitoring of the actual output parameters of the laser additive equipment ensures that the system can correct the deviations caused by fluctuations in the performance of the equipment itself. For example, if the actual output power of the laser is lower than the set value, the system can timely increase the adjustment amount to make up for the energy deficiency, thereby ensuring the stability of the molten pool and the repair quality. It is precisely because these dynamic external and internal factors are taken into account and corrected that the adjustment of the repair process parameters is more accurate and adaptive, significantly improving the robustness of the repair process and the performance of the final repaired part.

[0073] In some preferred embodiments, the following is described by a specific example. Suppose that during the laser additive repair of a steel rail, the system preliminarily calculates that the laser power needs to be increased by 10W according to the local difference information and the heat dissipation efficiency. However, during the repair, through the temperature sensor and the humidity sensor arranged near the repair area, it is detected in real time that the environmental temperature suddenly rises by 5℃ and the humidity increases by 10%. At the same time, through the power meter inside the laser, it is monitored in real time that the actual output power of the laser is 2W lower than the set value. At this time, the system will correct the preliminary 10W adjustment amount according to the pre-set correction model (for example, a neural network model trained based on historical data or a lookup table containing empirical coefficients) by taking these real-time environmental parameters and actual output parameters as inputs. The correction result may show that considering the increase in environmental temperature and the decrease in laser power, the final laser power adjustment amount should be corrected to an increase of 12W instead of the original 10W. In this way, even in the case of fluctuations in environmental conditions or slight deviations in equipment performance, the accurate control of laser energy input and thermal field distribution can be ensured, thereby ensuring the stability and consistency of repair quality.

[0074] Optionally, in combination with Figure 2 As shown, the step of determining the adjustment amount of the laser power, the adjustment amount of the scanning speed, and the adjustment amount of the powder feeding rate according to the heat dissipation efficiency to obtain the parameter adjustment information comprises: A1, acquiring real-time temperature information and stress state information of the current repair area according to the heat dissipation efficiency; A2, adjusting the corresponding thermal physical parameters according to the real-time temperature information and the stress state information; A3, according to the heat dissipation efficiency and the adjusted thermal physical parameters, calculating the instantaneous mapping relationship between the heat dissipation efficiency and the adjustment amount of the laser power, the adjustment amount of the scanning speed and the adjustment amount of the powder feeding rate; A4, according to the instantaneous mapping relationship, determining the adjustment amount of the laser power, the adjustment amount of the scanning speed and the adjustment amount of the powder feeding rate, and obtaining the parameter adjustment amount information.

[0075] Specifically, obtaining the real-time temperature information and stress state information of the current repair area means that during the laser additive repair process, through various sensors or detection means, the temperature data and internal stress state data of the steel rail area being repaired are monitored and obtained in real time. These information is crucial for accurately assessing the thermal physical behavior of the material under the current working condition. Among them, the real-time temperature information can reflect the instantaneous thermal state of the material, and the stress state information can reflect the mechanical state of the material, both of which affect the thermal physical properties of the material.

[0076] Among them, adjusting the corresponding thermal physical parameters according to the real-time temperature information and stress state information can be understood as dynamically correcting the thermal physical parameters used for calculation according to the actual temperature and stress conditions of the current repair area. For example, the thermal conductivity, specific heat capacity, density and other parameters of the material will change with the change of temperature and stress. By obtaining these information in real time and updating the corresponding thermal physical parameters, it can ensure that the subsequent calculation is more close to the actual situation, and improve the accuracy of the model or algorithm.

[0077] In practical application, according to the heat dissipation efficiency and the adjusted thermal physical parameters, calculating the instantaneous mapping relationship between the heat dissipation efficiency and the adjustment amount of the laser power, the adjustment amount of the scanning speed and the adjustment amount of the powder feeding rate, means establishing a dynamic and real-time correlation model or lookup table. The mapping relationship can accurately derive the specific adjustment amount of the laser power, scanning speed and powder feeding rate according to the current heat dissipation efficiency and the thermal physical parameters considering the real-time temperature and stress influence. 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 an accurate and dynamic parameter adjustment basis.

[0078] The scheme of the present application introduces the acquisition of real-time temperature information and stress state information of the current repair area when determining the repair process parameter adjustment amount, and dynamically adjusts the thermal physical parameters of the material accordingly, so as to more accurately calculate the instantaneous mapping relationship between the heat dissipation efficiency and the process parameter adjustment amount. It is because of considering the dynamic thermodynamic behavior of the material in the repair process that the determined laser power adjustment amount, scanning speed adjustment amount and powder feeding rate adjustment amount can more accurately adapt to the actual working condition, avoiding the repair deviation caused by the change of material parameters.

[0079] In some preferred embodiments, the following is illustrated by a specific example. Suppose that during the laser additive repair of a steel rail, the temperature of the current repair area is suddenly increased by real-time monitoring by an infrared thermal imager, and at the same time, a higher residual stress is found in the area by ultrasonic detection. According to these real-time temperature information and stress state information, the system will consult the pre-set material database or calculate in real time through the model, and find that under the conditions of temperature and stress, the thermal conductivity and specific heat capacity of the steel rail material are increased. Based on these adjusted thermal physical parameters, as well as the previously calculated heat dissipation efficiency, the system will use a pre-trained instantaneous mapping model (for example, a neural network-based prediction model) to calculate that in order 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 feeding rate needs to be fine-tuned by 2%. These parameter adjustment information is then applied to the current repair process parameters to ensure the stability of the repair process and the quality of the repair.

[0080] Optionally, the step of obtaining real-time temperature information and stress state information of the current repair area according to the heat dissipation efficiency can include the following contents: The step of obtaining real-time temperature information and stress state information of the current repair area according to the heat dissipation efficiency includes: Collecting temperature information of the current repair area; By selecting several specific wavelength range thermal radiation signals, and according to the intensity ratio of each specific wavelength thermal radiation signal, the real-time temperature information of the current repair area is calculated; Collecting stress state information of the current repair area; Exciting ultrasonic waves inside the steel rail by emitting laser pulses; Receiving echo signals after the ultrasonic waves propagate inside the steel rail; According to the propagation time, attenuation and frequency shift of the echo signals, the real-time stress state information of the current repair area is calculated.

[0081] Specifically, when collecting temperature information of the current repair area, a non-contact temperature measurement method can be used, such as using an infrared thermometer or a multispectral pyrometer. By selecting several specific wavelength range thermal radiation signals, such as measuring at two or more different infrared wavebands, and according to the intensity ratio of each specific wavelength thermal radiation signal, the real-time temperature information of the current repair area can be calculated. This colorimetric temperature measurement method can effectively eliminate the influence of emissivity changes on temperature measurement and improve the accuracy of temperature measurement.

[0082] In addition, when collecting the stress state information of the current repair area, an ultrasonic detection technology can be used. Specifically, an ultrasonic wave is excited inside the rail by emitting a laser pulse, which can be a short pulse laser of nanosecond or picosecond level, and the energy of the laser pulse is sufficient to cause transient thermal expansion on the surface or inside the material, thereby exciting the ultrasonic wave. Then, the echo signal of the ultrasonic wave after propagating inside the rail is received, and the echo signal can be captured by a piezoelectric sensor or a laser ultrasonic receiver. According to the propagation time, attenuation and frequency shift of the echo signal, the real-time stress state information of the current repair area can be calculated. For example, the propagation speed of the ultrasonic wave is affected by the stress state inside the material, and the stress can be inverted by measuring the change of the propagation time; the attenuation of the ultrasonic wave is related to the microstructure and defects of the material, and the frequency shift (such as the Doppler effect) can reflect the motion or strain state of the material. Thus, the residual stress or loading stress state inside the rail can be accurately evaluated.

[0083] The scheme of the present application can effectively overcome the error caused by the uncertainty of the material surface emissivity in the traditional single-wavelength temperature measurement method by using the multi-wavelength thermal radiation signal ratio method to collect temperature information, thereby obtaining more accurate real-time temperature information. At the same time, by exciting ultrasonic waves with laser and analyzing the propagation time, attenuation and frequency shift of the echo signal, the stress state information inside the rail can be obtained in a non-destructive and real-time manner. These accurate real-time temperature information and stress state information are the key inputs for subsequent adjustment of thermophysical parameters and calculation of the instantaneous mapping relationship between heat dissipation efficiency and repair process parameters. By obtaining these high-precision real-time data, the actual thermophysical state and mechanical state of the current repair area can be more accurately reflected, providing a reliable basis for subsequent parameter adjustment and ensuring accurate control of the laser additive repair process and improvement of the repair quality.

[0084] The specific embodiments of the present application also disclose a rail laser additive defect detection system for performing rail laser additive defect detection, which comprises Figure 3 As shown in the figure, the rail laser additive defect detection system 1 comprises: An instantaneous hot spot forming module 11 is configured to perform instantaneous heating on a local area of the rail base before laser additive repair of the rail damage area, so as to form an instantaneous hot spot in the corresponding local area; An attenuation information collection module 12 is configured to collect thermal radiation attenuation information of the instantaneous hot spot; A heat dissipation rate calculation module 13 is configured to calculate the 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 rail damage area; A process parameter selection module 14 is configured to select repair process parameters for laser additive repair from a pre-stored process parameter combination according to the actual heat dissipation rate; The damage area repair module 15 is configured to perform laser additive repair on the damaged area of the steel rail using repair process parameters.

[0085] The steel rail laser additive defect detection system of the present application aims to solve the problem that internal defects are difficult to detect after laser additive repair of the steel rail in the prior art. By locally heating the steel rail substrate to form a transient hot spot before repair and collecting its thermal radiation decay information, the system can calculate the actual heat dissipation rate of the local area. The heat dissipation rate, as an important indicator of the characteristics of the damaged area of the steel rail, can be used to effectively detect the damaged area. Based on the detection results, the system further intelligently selects appropriate repair process parameters from the pre-stored process parameter combinations, and executes laser additive repair by the damage area repair module, thereby ensuring the repair quality and avoiding the safety hazard of "qualified surface, internal failure".

[0086] Specifically, the transient hot spot forming module can achieve local transient heating of the steel rail substrate in multiple ways. For example, a high-energy laser beam can be focused on a specific area for a very short time, or a high-frequency induction heating coil can be used to quickly heat the local area, or a resistance heating element can be used to contact the surface of the steel rail and perform transient power heating. These heating methods are designed to quickly raise the temperature of the local area to form a transient hot spot.

[0087] The decay information acquisition module is responsible for obtaining the thermal radiation decay information of the transient hot spot. The module can be configured as an infrared thermal imager for continuously monitoring the surface temperature distribution change during the cooling process of the hot spot; or it can use a photodetector array to obtain the decay 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, which records the temperature drop process of the hot spot area in real time.

[0088] The heat dissipation rate calculation module calculates the actual heat dissipation rate of the local area based on the collected thermal radiation decay information. The calculation can be performed by a pre-set physical model, such as numerical simulation based on Fourier's law of heat conduction and convective heat transfer, to analyze and fit the thermal radiation decay curve; or it can use a machine learning algorithm to train the model with a large amount of historical data to directly predict the heat dissipation rate from the thermal radiation decay pattern; or it can use a finite element analysis-based method to accurately solve the heat transfer process in the hot spot area.

[0089] The process parameter selection module selects appropriate repair process parameters from the pre-stored process parameter combinations according to the calculated actual heat dissipation rate. The module can be a lookup table that directly matches the corresponding laser power, scanning speed, and powder feeding rate combination according to the heat dissipation rate range; it can also be a rule-based expert system that dynamically adjusts the parameter selection strategy according to the value and trend of the heat dissipation rate; or it can be an optimization algorithm that searches for the optimal process parameter combination under the premise of meeting a specific repair quality target.

[0090] The damage area repair module is responsible for laser additive repair of the damaged area of the steel rail using the selected repair process parameters. The module usually includes a laser, a powder feeding device, and a motion control system. The laser can be a fiber laser or a CO2 laser, which provides the energy required for cladding; the powder feeding device can be coaxial powder feeding or off-axis powder feeding, which accurately feeds 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 steel rail to achieve precise cladding tracks. These components work together to ensure that the repair process is carried out according to the selected process parameters.

[0091] Traditional existing steel rail laser additive repair technology mainly relies on surface optical detection for quality detection after repair, which is difficult to find deep-seated defects such as brittle structure and excessive residual stress caused by rapid cooling inside the repair layer, thereby burying the safety hazard of "surface qualified, internal failure". The steel rail laser additive defect detection system proposed in the present application realizes pre-detection of the damaged area of the steel rail by introducing transient heating of the local area of the steel rail substrate before repair and collecting thermal radiation attenuation information, and then calculating the actual heat dissipation rate. Further, the system can intelligently select appropriate repair process parameters according to the detection results, thereby effectively avoiding or mitigating the generation of internal defects during the repair process. Compared with the existing technology that only focuses on surface quality detection, the system of the present application can optimize the repair process from the source, significantly improve the internal quality and reliability of the repair layer, and effectively solve the problem that internal defects are difficult to detect and cannot be effectively controlled during the repair process, providing more comprehensive and reliable quality assurance for steel rail laser additive repair.

[0092] The above is only an embodiment of the present application and does not limit the protection scope of the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present 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 is performed on 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.

2. A method of laser additive defect detection of a steel rail according to claim 1, characterized in that, After the step of using the repair process parameters to perform laser additive repair on the damaged area of the steel rail, 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 a pre-set 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.

3. A method of laser additive defect detection of a steel rail according to claim 2, 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 pre-set specific wavelength is received by setting a narrowband filter of a high-speed camera; The working state of the high-speed camera is adjusted to adapt to the wide temperature variation of the solidification area behind the molten pool by adjusting the exposure time; According to the received thermal radiation signal of the pre-set 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.

4. 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.

5. A method of laser additive defect detection of a steel rail as claimed in claim 1, wherein, The step of using the repair process parameters to perform laser additive repair on the damaged area of the steel rail 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.

6. A method of laser additive defect detection of a steel rail according to claim 5, 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.

7. A method of laser additive defect detection of a steel rail according to claim 6, 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.

8. A method of laser additive defect detection of a steel rail according to claim 6, 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, 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.

9. A method of laser additive defect detection of a steel rail according to claim 8, 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; Real-time temperature information of the current repair area is calculated 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; Stress state information of the current repair area is collected; An ultrasonic wave is excited inside the steel rail by emitting a laser pulse; An 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, real-time stress state information of the current repair area is calculated.

10. 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 on the damaged area of the steel rail by using the repair process parameters.

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