An evaluation method for aluminum exothermic welding joint quality based on welding process data

Abstract

This invention proposes a quality evaluation method for aluminothermic welded joints based on welding process data, belonging to the field of welding technology. The method includes: collecting on-site parameters during the aluminothermic welding process; calculating the source quality score of the aluminothermic welded joint based on the on-site parameters; and formulating a handling strategy for the aluminothermic welded joint based on the source quality score. This method significantly improves the efficiency and consistency of quality evaluation, overcomes the subjectivity and lag of manual review, accurately identifies the risk levels of different types of defects, and provides data support for differentiated flaw detection and maintenance strategies, thereby comprehensively improving the quality control capabilities of railway welded joints and the level of traffic safety assurance.

Description

Technical Field

[0002] This invention relates to the field of welding technology, and in particular to a method for evaluating the quality of aluminothermic welded joints based on welding process data. Background Technology

[0004] Aluminothermic welding is one of the main methods for welding railway rails, and it is commonly used in scenarios such as turnout welding, emergency repairs, and maintenance of damaged rail components. Since aluminothermic welding operations are usually conducted in the field, modern equipment cannot be effectively used to control the welding process. Therefore, the quality of the joints relies primarily on the welder's mastery of the welding process and their personal experience.

[0005] The quality of aluminothermic welded joints is primarily determined by the quality of the welding materials and the welding process. Process parameters such as gas flow rate, preheating time, rail gap, weld spalling time, and demolding time all significantly impact weld quality. Rail steel is a high-carbon alloy steel, requiring thorough preheating of the base material before welding to prevent rapid weld cooling and defects. The preheating effect, determined by the rail gap, gas flow rate, and preheating time, is a crucial factor affecting aluminothermic weld quality. Simultaneously, the rail gap affects the filling effect of the molten steel into the cavity. An excessively large rail gap increases the filling requirement of the molten steel; insufficient molten steel generated by the flux will result in an unacceptable weld appearance. During aluminothermic welding, premature demolding and weld spalling, while the weld remains in a high-temperature, low-strength state, can lead to hot cracking defects.

[0006] Weather conditions significantly impact welding quality during aluminothermic welding. TB / T 1632 stipulates that welding sites should have rain protection measures. When rails are damp, they should be dried within a 400mm radius of the rail end face to be welded; when the rail temperature is below 10℃, preheating should be performed within a 400mm radius of the rail end face. Both aluminothermic welding material manufacturers and the railway industry have imposed additional requirements for welding under special weather conditions. For example, some aluminothermic welding material manufacturers specify that during welding in rainy or snowy weather, the heating and drying of the rail within a 500mm radius on both sides of the rail joint should be strengthened. Railway management departments require that aluminothermic welding operations avoid strong winds and adverse weather conditions. If operation is necessary, windbreak measures should be taken, and the preheating, demolding, and sprue-pushing times should be adjusted appropriately based on the preheating effect. After sprue-pushing, insulation measures should be implemented according to the actual situation to prevent the joint surface from rapidly cooling and quenching due to wind.

[0007] Approximately 200,000 aluminothermic welded joints are generated annually in the railway system. To ensure the standardization of aluminothermic welding operations and to conduct effective risk assessments of these joints, railway management requires operators to complete detailed paper welding record forms and establish corresponding welding ledgers based on actual welding conditions. Dedicated auditors then manually compare these records with work instructions, on-site records, and process videos to analyze deviations in operational standardization and potential quality risks.

[0008] In the aforementioned quality management system for aluminothermic welding of railway rails, the quality evaluation of welded joints relies heavily on manual review of work records and process videos to identify non-standard practices and potential quality risks. This method has significant drawbacks:

[0009] 1. Faced with a huge number of welding projects (approximately 200,000 joints per year), manual review is inefficient and feedback is delayed, making it difficult to control risks in a timely manner;

[0010] 2. The evaluation criteria are constrained by the auditor's subjective experience. Different auditors have different standards for judging welding quality, which may lead to misjudgment or omission.

[0011] 3. The scope of the audit is mostly limited to obvious violations. When there is insufficient understanding of the relationship between violations and welding defects, the accuracy of the evaluation results is low and the guidance for joint maintenance is limited.

[0012] 4. The current evaluation results fail to assess the severity of different defects, have low specificity for joint defect types, and cannot provide accurate basis for setting joint flaw detection cycles and differentiated maintenance strategies, thus hindering the improvement of railway line safety assurance effectiveness.

[0013] In view of this, based on years of experience in production and design in this and related fields, the inventor has designed a quality evaluation method for aluminothermic welded joints based on welding process data through repeated experiments, in order to solve the problems existing in the prior art. Summary of the Invention

[0015] The purpose of this invention is to provide a method for evaluating the quality of aluminothermic welded joints based on welding process data, which can effectively improve the accuracy of the quality evaluation structure for aluminothermic welded joints.

[0016] To achieve the above objectives, this invention proposes a method for evaluating the quality of aluminothermic welded joints based on welding process data. The method includes: collecting on-site parameters during the aluminothermic welding process of the aluminothermic welded joint; calculating a source quality score for the aluminothermic welded joint based on the on-site parameters; and formulating a handling strategy for the aluminothermic welded joint based on the source quality score.

[0017] Compared with the prior art, the present invention has the following features and advantages:

[0018] This invention proposes a quality evaluation method for aluminothermic welded joints based on welding process data. By collecting environmental data and process parameters during the aluminothermic welding process, a multi-level evaluation model is established based on the formation mechanism of welding defects. The overall quality score and defect risk score of the joint are calculated using directional deviation scoring and dynamic weight matrix, realizing automated and standardized evaluation of the quality of aluminothermic welded joints. This quality evaluation method significantly improves the efficiency and consistency of quality evaluation, overcomes the subjectivity and lag of manual review, can accurately identify the risk level of different types of defects, and provides data support for differentiated flaw detection and maintenance strategies, thereby comprehensively improving the quality control capability of railway welded joints and the level of traffic safety assurance. Attached Figure Description

[0020] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way. Furthermore, the shapes and proportions of the components in the drawings are merely illustrative to aid in understanding the invention and do not specifically limit the shapes and proportions of the components. Those skilled in the art, guided by the teachings of this invention, can select various possible shapes and proportions to implement the invention according to specific circumstances.

[0021] Figure 1 This is a schematic diagram of the data processing process of the present invention;

[0022] Figure 2 This is a schematic diagram of the evaluation method of the present invention. Detailed Implementation

[0024] The details of the present invention can be more clearly understood by referring to the accompanying drawings and the description of specific embodiments. However, the specific embodiments of the present invention described herein are for illustrative purposes only and should not be construed as limiting the invention in any way. Under the teachings of this invention, those skilled in the art can conceive of any possible modifications based on the invention, and these should all be considered to fall within the scope of the invention.

[0025] like Figure 2 As shown, this invention proposes a method for evaluating the quality of aluminothermic welded joints based on welding process data. The method includes: collecting on-site parameters during the aluminothermic welding process of the aluminothermic welded joint; calculating the source quality score of the aluminothermic welded joint based on the on-site parameters; and formulating a handling strategy for the aluminothermic welded joint based on the source quality score.

[0026] The aluminothermic welded joint quality evaluation method proposed in this invention collects environmental and process data during the aluminothermic welding process and automatically calculates the joint quality score based on a unified algorithm model. This achieves an objective and efficient evaluation of the quality of aluminothermic welded joints, overcoming the problems of low efficiency, strong subjectivity, and inconsistent standards in manual review. It provides an accurate and consistent decision-making basis for the differentiated maintenance of joints.

[0027] In one optional embodiment of the present invention, the field parameters include field environmental data and field process data.

[0028] In this embodiment, the method for evaluating the source quality of aluminothermic welded joints uses environmental and process data from the welding operation as inputs. Environmental data includes climate information such as precipitation, wind speed, temperature, and air pressure, while process data includes actual process parameters such as preheating time, preheating gas flow rate, settling time, and pouring time. The environmental and process data collected during welding are compared with the technical requirements in current standards and other relevant regulations. An aluminothermic weld source quality score is calculated, and the source quality of the joint is evaluated based on this score, providing a basis for maintenance and repair decisions.

[0029] The quality evaluation method for aluminothermic welded joints proposed in this invention includes environmental data, process data, data processing, and the degree of joint defect risk. The environmental and process data cover most factors affecting joint quality. The calculation formula is based on the analytic hierarchy process (AHP) and the experience of leading experts in rail welding. The degree of joint defect risk is based on over 100 failure analysis reports of aluminothermic welded joints in rail welding. The weights and joint risk levels in the calculation formula can be adjusted based on the trial results of the evaluation method proposed in this invention.

[0030] In this embodiment, the requirements for environmental and process data are as follows:

[0031] (1) Environmental data, including air temperature, humidity, air pressure, rain and snow conditions, and wind speed, should be collected using professional meteorological sensors. The sensor collection range and data accuracy requirements are shown in Table 1.

[0032] Table 1:

[0033] Data Name Collection range Accuracy requirements Rail temperature -40~50℃ 0.1℃ air temperature -40~50℃ 0.1℃ humidity 5~95% 1% air pressure 400~1050hPa 0.1hPa Rain and snow conditions "Yes" or "No" / wind speed 0.5-15m / s 0.1m / s

[0034] (2) Process data include rail gap, gas flow rate, preheating time, time from preheating end to ignition, calming time, bulge pushing time, rail displacement, etc. Data can be collected manually or using specialized equipment. The data acquisition accuracy requirements are shown in Table 2, where the gas flow rate should be the standard flow rate.

[0035] Table 2:

[0036] Data Name Collection range Accuracy requirements Rail gap 20~50 mm 1 mm Gas flow rate 0~200 SLPM 0.1SLPM preheating time / 1s Preheating time to ignition / 1s Calm Time / 1s Tumor pushing time / 1s rail displacement -78.4~78.4 m / s² (-8~8g) 10Hz, 0.098 m / s² (0.01g)

[0037] In this embodiment, by dividing the field parameters into field environmental data and field process data, and collecting corresponding data according to the specified collection range and accuracy, most factors affecting the quality of aluminothermic welded joints can be covered. This provides comprehensive and accurate basic data for subsequent calculation of the source quality score of aluminothermic welded joints based on field parameters, avoiding evaluation deviations caused by omission of key influencing factors or insufficient data accuracy. At the same time, it ensures that the collected data fits the actual working conditions of aluminothermic welding, laying a data foundation for improving the accuracy and pertinence of subsequent quality evaluation results.

[0038] In an optional embodiment of the present invention, calculating the source quality score of the aluminothermic weld joint based on on-site parameters includes:

[0039] By comparing the field parameters with the corresponding standard values, a field parameter score vector is obtained.

[0040] Calculate the defect score based on the on-site parameter scoring vector;

[0041] The source quality score of the aluminothermic weld joint is calculated based on the defect score.

[0042] In one alternative embodiment of this implementation, each field parameter is compared with its corresponding standard value, and the deviation value between each field parameter and its corresponding standard value is calculated.

[0043] Identify the directionality of each deviation value and score the directionality of each deviation value to obtain the directionality score of each field parameter;

[0044] Construct a field parameter score vector based on the directional scores of all field parameters.

[0045] In calculating the source quality score of the aluminothermic welded joint based on on-site parameters, the collected on-site parameters are first compared with their corresponding standard values. For each process and environmental data point, the difference between the actual value and the standard value is calculated, the directional characteristics of the parameter deviation are identified, positive and negative deviations are defined, and positive and negative deviation scores are calculated respectively. A process and environmental data score vector is constructed based on the directional scores of all parameters. Next, a defect score is calculated based on this score vector. By multiplying the score vector with a weight matrix established based on the analytic hierarchy process (AHP) and expert experience, the original scores for different defect types are obtained, and the original scores are processed to obtain the defect scores. Finally, the source quality score of the aluminothermic welded joint is calculated based on the defect scores. By multiplying the defect score vector with another weight vector established based on the AHP and expert experience, the overall quality score of the joint is obtained, achieving a quantitative and objective evaluation of the quality of the aluminothermic welded joint.

[0046] In constructing the field parameter scoring vector, the positive deviation score is calculated by determining whether the deviation value is greater than zero and applying a piecewise linear function, while the negative deviation score is calculated by determining whether the deviation value is less than zero and applying a corresponding piecewise linear function. When the deviation value is zero, both the positive and negative deviation scores are set to fixed values; when the absolute value of the deviation value exceeds the maximum allowable deviation value, the score for the corresponding direction is fixed to another specific value. Finally, based on the positive and negative deviation scores of all field parameters, a field parameter scoring vector is constructed. By comparing each field parameter with the standard value and calculating the directional score, the degree and direction of deviation of process and environmental parameters from the standard state can be accurately quantified, thereby establishing a data foundation corresponding to the formation mechanism of welding defects and providing standardized and quantitative input for subsequent defect risk assessment.

[0047] In one optional example, the formula for calculating the deviation value is:

[0048] (1)

[0049] In the formula, δ y Let D be the deviation value of the y-th field parameter. y It is the y-th field parameter. It is the standard value corresponding to the y-th field parameter.

[0050] In this embodiment, the field parameters are process data, and the environmental data are measured values ​​D collected from the field. y y represents the y-th process or environmental data item, where D1: rail temperature, D2: air temperature, D3: humidity, D4: air pressure, D5: rain / snow conditions, D6: wind speed, D7: rail gap, D8: gas flow rate, D9: preheating time, D 10 : Duration from the end of preheating to ignition, D 11 :Quiet Time, D 12 Tumor pushing time, D 13 Rail displacement.

[0051] For each field parameter D y The difference δ between the actual value and the standard value is calculated using formula (1). y , It is the standard value of the y-th parameter.

[0052] After obtaining the field parameter D y Then, immediately read the corresponding standard value. According to the formula δ y =D y - Complete the subtraction operation and output the deviation value δ. y Then, the direction of the deviation value is determined; if δ y For positive deviation, it is defined as positive deviation. If δ y If it is negative, it is defined as a negative deviation. And substitute them into the directional scoring formula (2) or (4) respectively to calculate p y or n y This transforms the measured deviation of each field parameter into a comparable directional score, which is then used to construct the field parameter score vector C. In this implementation, the deviation value is obtained in one step by subtracting the standard value from the measured value. This compresses field parameters of different dimensions and ranges in the field environment into a unified deviation, providing a unique and concise input for directional identification and scoring. It eliminates errors caused by manual estimation of deviations, enabling accurate and repeatable deviation values ​​to be obtained immediately after welding, ensuring an objective starting point for subsequent scoring chains.

[0053] In an optional example, the formula for calculating the directionality score for each field parameter includes:

[0054] (2)

[0055] (3)

[0056] (4)

[0057] (5)

[0058] In the formula, For positive deviation, p y For positive deviation scoring, For negative deviation, n y A negative bias score;

[0059] Deviations between on-site process data and on-site environmental data during welding exhibit significant directional characteristics. Parameter deviations in a specific direction increase the probability of specific welding defects, while deviations in the opposite direction may decrease the probability of defects. For example, insufficient preheating time (negative deviation) increases the risk of incomplete weld defects, while extended preheating time (positive deviation) compensates by reducing the risk of incomplete weld defects. Therefore, when assessing joint quality, it is essential to first identify the direction of parameter deviations and then conduct targeted risk assessments and quantifications for deviations in that direction.

[0060] Identify the deviation δ of each process data and environmental data. y Directionality, definition Positive deviation The deviation is negative. The deviation is then scored, p. y For positive deviation scoring, n y A negative bias score is given.

[0061] The positive deviation score p is calculated using formulas (2) and (3). y This refers to data exceeding the standard process value. M y Let y be the maximum allowable deviation value for the y-th process and environmental data. The negative deviation score n is calculated using formulas (4) and (5). y This refers to data values ​​that are lower than the standard process (standard value).

[0062] like Figure 1 As shown, in the data processing of the aluminothermic welded joint quality evaluation method, for each collected field parameter (such as rail temperature, air pressure, or rain / snow conditions), the deviation value from the preset standard value is first calculated, and the direction of the deviation is determined to be positive. ) or negative deviation ( Subsequently, positive and negative deviations are processed according to formulas (2)-(5): when a positive deviation is detected, the positive deviation scoring formula is called, based on... Amplitude calculation p y The score adjusts as the deviation increases; when a negative deviation is detected, the score is adjusted based on the negative deviation scoring formula. Amplitude calculation n y Ultimately, the directional score for each field parameter is determined by p. y or n y This method of evaluating the quality of aluminothermic welded joints involves independently determining and generating a quantitative score that includes directional information, providing a foundation for subsequent score vector construction. By independently calculating positive and negative deviation scores, this method can accurately quantify the directional differences in field parameters deviating from standard values ​​(such as field parameters being too high or too low), avoiding the neglect of directional information in traditional single-scoring models. This two-way scoring mechanism not only improves the sensitivity of detecting abnormal field parameters but also provides more specific guidance for adjusting welding processes, such as increasing or decreasing certain process parameters.

[0063] Preferably, the formula for calculating the on-site parameter scoring vector is:

[0064] (6)

[0065] In the formula, C represents the directional score.

[0066] When δ y When =0, =0 and =0, p y n y Both are 10. When or More than M y When, n y p y Set to 0. Construct a process and environment score vector C, containing directional scores for all parameters.

[0067] In the data processing of the aluminothermic welded joint quality evaluation method, the scoring results of various field parameters (such as welding rail temperature, air pressure, rain and snow conditions, etc.) are obtained. y or n y According to formula (6), the directional scores C of each parameter are combined according to preset weights or order to generate a score vector containing multi-dimensional directional information. In specific implementation, the scores of each on-site parameter are converted into a unified dimension and then superimposed to form a parameter score vector that reflects the overall welding process quality characteristics, providing structured data input for subsequent defect score calculation. By constructing the on-site parameter score vector, the integration and quantification of multi-parameter directional scores are realized, overcoming the limitations of single-parameter evaluation. This vector can comprehensively reflect the overall state of each parameter deviating from the standard value during the welding process (such as multiple parameters being simultaneously high or low), providing richer feature information for the quality evaluation model.

[0068] In one alternative example of this implementation, the score for each defect is defined as Bx, where x is the x-th defect, and B1: shrinkage cavity, B2: porosity, B3: incomplete weld, B4: pore, B5: slag inclusion, B6: hot crack. A vector B for the defect scores is constructed.

[0069]

[0070] In one alternative embodiment of this implementation, the defect score is calculated based on the on-site parameter scoring vector, including:

[0071] A relational matrix W between the field parameter scoring vector and the defect scoring vector B is established based on the analytic hierarchy process (AHP). C ,

[0072] (7)

[0073] The original score B for the defect is calculated based on the relation matrix. raw ,

[0074] (8)

[0075] Based on the original score B raw Calculate defect score B x ,

[0076] (9)

[0077] In the formula, B x For defect scoring, B raw For the original rating, w x，j This represents the strength and nature of the influence of a specific deviation direction on Bx. When j is odd (j=2y-1), it corresponds to the positive deviation score p of parameter y. yWhen j is even (j=2y), the corresponding negative deviation score n for parameter y is... y w x,j When the deviation is greater than 0, the direction of this deviation affects the risk of defect x; w x,j When the deviation is 0, the direction of the deviation does not affect the risk of defect x. The original score B for different defects is calculated using formula (8). raw .

[0078] The defect score derived from the weight matrix established using the Analytic Hierarchy Process (AHP) is limited to within 10 points. However, in actual welding production, operators often need to adjust process parameters according to on-site conditions to compensate for potential quality reduction risks. To more realistically reflect this compensation effect, matrix W... C Some weighting coefficients in the calculation can increase the defect score. When over-compensation of the process occurs, the relevant defect score may exceed the limit threshold, resulting in a B rating. x The case is >10. Therefore, formula (9) is used to score the original defect B. raw Process it.

[0079] In the quality evaluation method for aluminothermic welded joints, a defect score is first generated based on welding process data. This score is derived by integrating the degree of anomaly from multiple dimensions using a preset algorithm. Finally, the evaluation results generate a quality report, serving as a key basis for the quality evaluation of the aluminothermic welded joint. By directly outputting various aluminothermic welding defect scores, rapid and objective evaluation of welding defects is achieved, avoiding subjective errors inherent in manual review. Furthermore, it can promptly capture minute anomalies during the welding process, effectively improving defect early warning capabilities.

[0080] In one alternative embodiment of this implementation, the source quality score of the aluminothermic weld joint is calculated based on the defect score, including:

[0081] A relationship vector between defect scores and source quality scores of aluminothermic welded joints was established using the analytic hierarchy process (AHP).

[0082] (10)

[0083] and,

[0084] (11)

[0085] (12)

[0086] In the formula, B x For defect scoring, A represents the source quality score of the aluminothermic weld joint. Defect score B x The influence weight of the source quality score A of the aluminothermic welded joint.

[0087] Specifically, the recommended actions after calculating the score are as follows:

[0088] The initiation cycle, severity, identifiability, and distribution location of different welding defects in aluminothermic welded joints of rails vary. Using process and environmental data collected on-site, and after evaluating the source quality of the aluminothermic welded joint, two types of indicators can be obtained: overall joint score A and various defect scores B. x .

[0089] When one or more defects are rated B x A lower score will lead to a decrease in the overall score A, and therefore a lower defect score B. x The score reflects the risk level of a particular defect, while the overall score A reflects the overall quality of the joint. Therefore, tiered treatment recommendations should be given for these two types of indicators.

[0090] (1) Recommendations for handling a thermite weld joint with a source quality rating of A

[0091] The quality rating of the aluminothermic weld joint source is divided into 4 levels:

[0092] (a) A≥a1, joint quality score is excellent. All process and environmental data are basically consistent with the standards, and the risk of various defects in the joint is extremely low. It can be managed as a normal joint through flaw detection.

[0093] (b) a1>A≥a2, the joint quality score is good. There are minor deviations in some process and environmental data, and the risk of various defects in the joint is low. Full-section flaw detection should be carried out within 24 hours, and targeted flaw detection should be carried out according to the defect score results to check whether corresponding defects are found. If no corresponding defects are found, flaw detection management can be carried out as for ordinary joints.

[0094] (c) a2>A≥a3, joint quality score is qualified. Multiple process and environmental data deviations exist, or key process and environmental data deviations exist. The risk of multiple minor defects in the joint is relatively high. Full-section flaw detection should be performed on the joint as soon as possible after welding, and targeted flaw detection should be carried out based on the defect score results. Maintenance and repair of the joint should be carried out based on the flaw detection results; if no excessive echoes are found, the flaw detection cycle should be increased.

[0095] (d) a3 > A, the joint quality score is unqualified. Significant deviations in key process and environmental data indicate a high risk of one or more highly hazardous defects. Full-section flaw detection should be performed on the joint as soon as possible after welding, and inspection should be strengthened based on the defect score results. Maintenance and repair of the joint should be carried out based on the flaw detection results. If no excessive echoes are found in the joint, magnetic particle and penetrant testing techniques should be used to strengthen the inspection, and the flaw detection cycle should be further increased.

[0096] Where a1, a2, and a3 are thresholds determined based on the statistical quantiles of the target dataset.

[0097] (2) Recommendations for handling defect score Bx

[0098] Defects in aluminothermic welded joints include shrinkage cavities, porosity, incomplete fusion, pores, slag inclusions, and hot cracks. Different defects vary in their initiation cycle, severity, identifiability through flaw detection, and spatial distribution. Therefore, after obtaining the defect score Bx, recommendations should be made regarding the frequency of flaw detection, detection locations, and detection procedures.

[0099] (a) Defect rating Bx classification

[0100] ① Bx≥b1, defect score is excellent. All process and environmental data are basically consistent with the standards, and the risk of this type of defect occurring is extremely low.

[0101] ② b1>Bx≥b2, defect score is good. Some low-weighted process and environmental data have biases, and the risk of this type of defect is low.

[0102] ③ If b2 > Bx ≥ b3, the defect quality score is acceptable. Multiple deviations in process or environmental data, or deviations in key process or environmental data, indicate a higher risk of this type of defect.

[0103] ④ b3 > Bx, defect quality score is unqualified. Significant deviations exist in various process and environmental data, indicating a high risk of this type of defect.

[0104] Where b1, b2, and b3 are thresholds determined based on the statistical quantiles of the target dataset.

[0105] (b) Targeted flaw detection recommendations for different defects

[0106] Defect scoring should be based on the defect occurrence cycle and the difficulty of flaw detection, and specific recommendations are shown in Table 3.

[0107] Table 3:

[0108] Defect types Shape features Typical spatial distribution Key areas of focus for flaw detection Targeted scanning methods and precautions High incidence of fractures Stable monitoring period shrinkage cavity Volumetric defects weld centerline, below riser From the center of the rail head to the upper part of the rail web Single probe scanning ≤200Mt ≥400Mt loose Diffuse volume defects Rail head center, rail bottom triangular area Rail head center, rail bottom triangular area Single probe scanning ≤100Mt ≥200Mt Unwelded planar defects Track bottom angle Track bottom angle 1. Dual-probe scanning method. 2. Combined with magnetic particle or penetrant testing. ≤200Mt ≥400Mt pores Volumetric defects Rail head surface, rail base angle Rail head near surface, rail base angle 1. Use a single-probe scanning method. 2. Be aware of near-surface defects that may go undetected. ≤300Mt ≥600Mt Slag Volumetric defects Near the fusion line, at the bottom corner of the rail Near the fusion line, at the bottom corner of the rail 1. Use a single-probe scanning method. 2. Be aware of near-surface defects that may go undetected. ≤300Mt ≥600Mt Hot crack planar defects Stress concentration locations, joint stress locations Rail head jaw, rail base angle, rail base 1. Dual-probe scanning method. 2. Combined with magnetic particle or penetrant testing. ≤100Mt ≥300Mt

[0109] The detailed explanations of the above embodiments are intended only to explain the present invention so as to facilitate a better understanding of the present invention. However, these descriptions should not be construed as limiting the present invention for any reason. In particular, the various features described in different embodiments can be arbitrarily combined with each other to form other embodiments. Unless there is an explicit description to the contrary, these features should be understood to be applicable to any embodiment, and not limited to the described embodiments.

Claims

1. A method for evaluating the quality of aluminothermic welded joints based on welding process data, characterized in that, The method for evaluating the quality of aluminothermic welded joints includes: Collect on-site parameters during the aluminothermic welding process of the aluminothermic welded joint; Calculate the source quality score of the aluminothermic welding joint based on the aforementioned on-site parameters; A treatment strategy for the aluminothermic weld joint is formulated based on the source quality score of the aluminothermic weld joint.

2. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 1, characterized in that, The field parameters include field environmental data and field process data.

3. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 1, characterized in that, The quality score of the aluminothermic weld joint source is calculated based on the aforementioned on-site parameters, including: The on-site parameters are compared with the corresponding standard values ​​to obtain the on-site parameter score vector; Calculate the defect score based on the on-site parameter scoring vector; The source quality score of the aluminothermic welded joint is calculated based on the defect score.

4. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 3, characterized in that, Compare each of the field parameters with the corresponding standard values, and calculate the deviation value between each of the field parameters and the corresponding standard values; Identify the directionality of each deviation value and score the directionality of each deviation value to obtain a directionality score for each field parameter; The field parameter score vector is constructed based on the directional scores of all the field parameters.

5. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 4, characterized in that, The formula for calculating the deviation value is: （1） In the formula, δ y Let D be the deviation value of the y-th field parameter. y D is the y-th field parameter. y 0 It is the standard value corresponding to the y-th field parameter.

6. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 4, characterized in that, Formula for calculating the directional score of each field parameter include: （2） （3） （4） （5） In the formula, δ y + For positive deviation, p y For positive deviation scoring, δ y - For negative deviation, n y A negative bias score.

7. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 6, characterized in that, The formula for calculating the on-site parameter scoring vector is: （6） In the formula, C represents the directional score.

8. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 3, characterized in that, The defect score is calculated based on the on-site parameter scoring vector, including: The relationship matrix W between the on-site parameter scoring vector and the defect scoring vector B is established based on the analytic hierarchy process (AHP). C , （7） The original score B of the defect is calculated based on the aforementioned relationship matrix. raw , （8） Based on the original score B raw Calculate defect score B. （9） In the formula, B x For defect scoring, B raw For the original rating, w x,j Indicates the specific deviation direction for B x The intensity and nature of the influence.

9. The method for evaluating the quality of aluminothermic welded joints based on welding process data as described in claim 3, characterized in that, The source quality score of the aluminothermic welded joint is calculated based on the defect score, including: A relationship vector between defect scores and source quality scores of aluminothermic welded joints was established using the analytic hierarchy process (AHP). （10） and, （11） （12） In the formula, B x For defect scoring, A represents the source quality score of the aluminothermic weld joint. Defect score B x The influence weight of the source quality score A of the aluminothermic welded joint.

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