A method, system, device and medium for non-destructive testing of a large gear

Abstract

The application provides a large gear nondestructive testing method, system, device and medium, relates to gear detection technical field, and the method comprises the following steps: a plurality of standard test blocks are used to establish a mapping model between nondestructive testing signal characteristics and carburized layer depth and surface hardness; a nondestructive testing probe is used to collect multi-source electromagnetic signals on the tooth surface of the large gear to be detected, and the same signal characteristic parameters as the nondestructive testing signal characteristics are extracted; the nondestructive testing probe is provided with an arc-shaped positioning support, the arc matches the tooth surface curvature of the large gear to be detected, the interval matches the gear modulus, the arc-shaped positioning support is clamped on both sides of the tooth during detection, so that the nondestructive testing probe is aligned with the tooth surface centerline and is vertically attached to the tooth surface; the signal characteristic parameters are input into the mapping model, and the predicted carburized layer depth and the predicted surface hardness of the large gear to be detected are output; and then whether the large gear to be detected is qualified is determined. By implementing the technical scheme, the detection efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of gear testing technology, specifically to a non-destructive testing method, system, equipment, and medium for large gears. Background Technology

[0002] Large, heavy-duty gears are core transmission components in critical equipment such as metallurgy, mining, and wind power generation. They typically undergo carburizing and quenching to form a hardened tooth surface layer. Surface hardness and carburized layer depth are key indicators for evaluating the quality of gear heat treatment. Currently, the industry primarily relies on destructive testing methods such as metallography and microhardness gradient methods. These methods require cutting samples from the gear, resulting in cumbersome procedures, high costs, and long cycles. They cannot comprehensively inspect large gears, allowing only small-scale sampling inspections and posing a risk of missed detections. Furthermore, they are difficult to perform quickly on-site, resulting in insufficient efficiency and practicality. Therefore, a technical solution is urgently needed that enables non-destructive and rapid testing of surface hardness and carburized layer depth in large gears. Summary of the Invention

[0003] To address the aforementioned technical problems, this application provides a non-destructive testing method, system, equipment, and medium for large gears.

[0004] Firstly, this application provides a non-destructive testing method for large gears, comprising: establishing a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness using multiple standard test blocks, wherein the standard test blocks are made of the same material and undergo the same heat treatment process as the large gear to be tested; employing a non-destructive testing probe integrating a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit to collect multi-source electromagnetic signals on the tooth surface of the large gear to be tested, extracting signal characteristic parameters identical to the non-destructive testing signal characteristics from the multi-source electromagnetic signals, wherein the signal characteristic parameters include at least one surface sensitive characteristic parameter and one depth sensitive characteristic parameter, the non-destructive testing probe is equipped with an arc-shaped positioning bracket, the arc of the arc-shaped positioning bracket matching the curvature of the tooth surface of the large gear to be tested, and the spacing matching the gear module, wherein during testing, the arc-shaped positioning bracket is clamped on both sides of the tooth, so that the non-destructive testing probe is aligned with the centerline of the tooth surface and perpendicularly attached to the tooth surface; inputting the signal characteristic parameters into the mapping model, and outputting the predicted carburized layer depth and predicted surface hardness of the large gear to be tested; and determining whether the large gear to be tested is qualified based on the predicted carburized layer depth and predicted surface hardness.

[0005] By adopting the above technical solution, a mapping model is established using a standard test block with the same material and heat treatment process as the large gear under test, ensuring the compatibility between the model and the gear under test. A non-destructive testing probe integrating surface characteristic sensitive detection units and depth characteristic sensitive detection units is used to collect multi-source electromagnetic signals and extract signal feature parameters, comprehensively acquiring surface and depth-related information. An arc-shaped positioning bracket ensures the non-destructive testing probe is accurately aligned with the centerline of the tooth surface and perpendicularly fitted, guaranteeing accurate detection position. Inputting the signal feature parameters into the mapping model outputs predicted carburized layer depth and predicted surface hardness, enabling non-destructive testing of large gears. Finally, based on the prediction results, the gear's qualification is determined, allowing for rapid and effective quality assessment of large gears and improving the testing efficiency of large gears.

[0006] Optionally, a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness can be established using multiple standard test blocks. This includes: for each standard test block, using a non-destructive testing probe to acquire multi-source electromagnetic signals and extract sample signal characteristic parameters; performing destructive testing on each standard test block to determine the actual carburized layer depth and actual surface hardness; and establishing a mapping model using a regression algorithm with the sample signal characteristic parameters as input and the actual carburized layer depth and actual surface hardness as output.

[0007] By adopting the above technical solution and establishing a mapping model using standard test blocks, the carburized layer depth and surface hardness of large gears can be predicted based on the characteristics of non-destructive testing signals. This avoids the cumbersome process, high cost, and long cycle of traditional destructive testing methods, enabling non-destructive and rapid testing of large gears. Destructive testing of standard test blocks to obtain the actual carburized layer depth and surface hardness ensures the accuracy of the mapping model. Using a regression algorithm to establish the mapping model improves the reliability of the prediction results.

[0008] Optionally, destructive testing is performed on each standard test block to determine the actual carburized layer depth and actual surface hardness, including: cutting the standard test block along a direction perpendicular to the carburized surface, and obtaining a cross-section after inlaying, grinding, and polishing; using a micro Vickers hardness tester, measuring the hardness value every 0.1 mm starting from the surface, and taking the depth corresponding to the hardness value dropping to the preset hardness as the actual carburized layer depth; and using a Vickers hardness tester to measure the actual surface hardness on the surface of the standard test block.

[0009] By adopting the above technical solution, the actual carburized layer depth and actual surface hardness of the standard test block can be accurately obtained, providing an accurate data basis for establishing a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness, thereby improving the accuracy of non-destructive testing of large gears.

[0010] Optionally, the surface characteristic sensitive detection unit is a Barkhausen noise detection unit, and the depth characteristic sensitive detection unit is a high-frequency eddy current detection unit; the surface sensitive characteristic parameters are derived from the Barkhausen noise signal collected by the Barkhausen noise detection unit and are used to characterize the physical properties related to surface hardness; the depth sensitive characteristic parameters are derived from the eddy current signal collected by the high-frequency eddy current detection unit and are used to characterize the physical properties related to conductivity and permeability gradients along the depth direction.

[0011] By adopting the above technical solution, using the Barkhausen noise detection unit as a surface characteristic sensitive detection unit, Barkhausen noise signals can be collected and surface-sensitive feature parameters used to characterize the physical properties related to surface hardness can be extracted; using the high-frequency eddy current detection unit as a depth characteristic sensitive detection unit, eddy current signals can be collected and depth-sensitive feature parameters used to characterize the physical properties related to conductivity and permeability gradients along the depth direction can be extracted. This enables non-destructive testing of the surface hardness and carburized layer depth of large gears, avoiding the cumbersome process, high cost, and long cycle of traditional destructive testing methods, improving testing efficiency and practicality, and reducing the risk of missed detections.

[0012] Optionally, the surface-sensitive characteristic parameters include at least one of the root mean square value and peak position of the Barkhausen noise signal; the depth-sensitive characteristic parameters include at least one of the impedance phase angle and impedance amplitude of the eddy current signal.

[0013] By adopting the above technical solutions, using at least one of the root mean square value and peak position of the Barkhausen noise signal as a surface-sensitive characteristic parameter, the physical properties related to surface hardness can be characterized more accurately; using at least one of the impedance phase angle and impedance amplitude of the eddy current signal as a depth-sensitive characteristic parameter, the physical properties related to conductivity and permeability gradient along the depth direction can be better characterized, thereby improving the accuracy of non-destructive testing of the carburized layer depth and surface hardness of large gears.

[0014] Optionally, the arc-shaped positioning bracket is a replaceable structure. For large gears under test with different tooth surface curvature radii, an arc-shaped positioning bracket with the corresponding curvature can be replaced.

[0015] By adopting the above technical solution, the arc-shaped positioning bracket adopts a replaceable structure. By replacing the arc-shaped positioning bracket with the corresponding arc-shaped bracket for the large gear under test with different tooth surface curvature radii, the non-destructive testing probe can be better adapted to large gears with different tooth surface curvatures. This ensures that the testing probe is aligned with the center line of the tooth surface and is perpendicular to the tooth surface, improving the accuracy and applicability of the test. It is suitable for non-destructive testing of more large gears of different specifications.

[0016] Optionally, based on the predicted carburized layer depth and predicted surface hardness, the large gear to be tested is determined to be qualified, including: comparing the predicted carburized layer depth and predicted surface hardness with preset qualified ranges for carburized layer depth and surface hardness, respectively; if both are within the corresponding qualified ranges, the large gear to be tested is determined to be qualified, otherwise the large gear to be tested is determined to be unqualified.

[0017] By adopting the above technical solution, it is possible to accurately determine whether large gears are qualified based on the predicted carburized layer depth and surface hardness, avoiding the problems of traditional destructive testing methods such as cumbersome process, high cost, long cycle, risk of missed detection, and insufficient testing efficiency and practicality, thus achieving non-destructive and rapid qualification determination of large gears.

[0018] Optionally, the above method further includes: before starting the inspection of the large gear to be tested, using a non-destructive testing probe to measure a pre-calibrated reference part, the reference part having the same material and heat treatment process as the large gear to be tested, and the reference carburized layer depth and reference surface hardness of the reference part being known; inputting the signal characteristic parameters measured on the reference part into a mapping model to obtain the first carburized layer depth and the first surface hardness of the reference part; calculating the first deviation coefficient K1 between the first carburized layer depth and the reference carburized layer depth, and the second deviation coefficient K2 between the first surface hardness and the reference surface hardness; when inspecting the large gear to be tested, multiplying the predicted carburized layer depth output by the mapping model by the reciprocal of K1 and multiplying the predicted surface hardness by the reciprocal of K2 to obtain the final predicted value after drift compensation.

[0019] By adopting the above technical solution, using a reference part with the same material and heat treatment process as the large gear to be tested for measurement, calculating the deviation coefficient, and performing drift compensation on the predicted carburized layer depth and predicted surface hardness output by the mapping model, the accuracy of non-destructive testing results of large gears can be improved.

[0020] In a second aspect of this application, a non-destructive testing system for large gears is also provided, for performing the non-destructive testing method for large gears according to any of the preceding claims, comprising: a model building unit, used to establish a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness using multiple standard test blocks, wherein the standard test blocks are made of the same material and heat treatment process as the large gear to be tested; and an acquisition unit, used to acquire multi-source electromagnetic signals on the tooth surface of the large gear to be tested using a non-destructive testing probe integrating a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit, and extracting the same non-destructive testing signal characteristics from the multi-source electromagnetic signals. The signal characteristic parameters include at least one surface-sensitive characteristic parameter and one depth-sensitive characteristic parameter. The non-destructive testing probe is equipped with an arc-shaped positioning bracket. The arc of the positioning bracket matches the curvature of the tooth surface of the large gear under test, and the spacing matches the gear module. During testing, the arc-shaped positioning bracket is locked on both sides of the tooth, so that the non-destructive testing probe is aligned with the center line of the tooth surface and perpendicularly attached to the tooth surface. The mapping unit is used to input the signal characteristic parameters into the mapping model and output the predicted carburized layer depth and predicted surface hardness of the large gear under test. The judgment unit is used to determine whether the large gear under test is qualified based on the predicted carburized layer depth and predicted surface hardness.

[0021] In a third aspect of this application, an electronic device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor executes the program to implement the method steps of any of the above claims.

[0022] In a fourth aspect of this application, a computer-readable storage medium is also provided, which stores instructions that, when executed, perform the method steps of any of the above claims.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. A mapping model is established using a standard test block with the same material and heat treatment process as the large gear under test, ensuring the model's compatibility with the gear. A non-destructive testing probe integrating surface characteristic sensitive detection units and depth characteristic sensitive detection units is used to acquire multi-source electromagnetic signals and extract signal feature parameters, comprehensively obtaining surface and depth-related information. An arc-shaped positioning bracket ensures the non-destructive testing probe is accurately aligned with the tooth surface centerline and perpendicularly fitted, guaranteeing accurate detection positioning. The signal feature parameters are input into the mapping model to output predicted carburized layer depth and predicted surface hardness, enabling non-destructive testing of large gears. Finally, the gear's qualification is determined based on the prediction results, allowing for rapid and effective quality assessment of large gears and improving testing efficiency. 2. The arc-shaped positioning bracket adopts a replaceable structure. By replacing the arc-shaped positioning bracket with one of the corresponding arc curvature for the large gears to be tested with different tooth surface curvature radii, the non-destructive testing probe can be better adapted to large gears with different tooth surface curvatures. This ensures that the testing probe is aligned with the center line of the tooth surface and is perpendicular to the tooth surface, improving the accuracy and applicability of the test. It is suitable for non-destructive testing of more large gears of different specifications. Attached Figure Description

[0024] Figure 1 This is a flowchart of a non-destructive testing method for large gears provided in an embodiment of this application; Figure 2 This is a structural block diagram of a non-destructive testing system for large gears provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0025] Explanation of reference numerals in the attached figures: 300 - Electronic device; 301 - Processor; 302 - Communication bus; 303 - User interface; 304 - Network interface; 305 - Memory. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0027] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0028] In the description of the embodiments of this application, the term "multiple" means two or more. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0029] This application provides a non-destructive testing method for large gears, such as... Figure 1 The above, Figure 1This is a flowchart of a non-destructive testing method for large gears provided in an embodiment of this application, including the following steps: Step S101: Establish a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness using multiple standard test blocks. The standard test blocks are made of the same material and heat treatment process as the large gear to be tested. Step S102: A non-destructive testing probe integrating a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit is used to collect multi-source electromagnetic signals on the tooth surface of the large gear to be tested. Signal feature parameters with the same characteristics as the non-destructive testing signals are extracted from the multi-source electromagnetic signals. The signal feature parameters include at least one surface sensitive feature parameter and one depth sensitive feature parameter. The non-destructive testing probe is equipped with an arc-shaped positioning bracket. The arc of the arc-shaped positioning bracket matches the curvature of the tooth surface of the large gear to be tested, and the spacing matches the gear module. During the test, the arc-shaped positioning bracket is locked on both sides of the tooth, so that the non-destructive testing probe is aligned with the center line of the tooth surface and perpendicularly attached to the tooth surface. Step S103: Input the signal feature parameters into the mapping model and output the predicted carburized layer depth and predicted surface hardness of the large gear under test. Step S104: Based on the predicted carburized layer depth and predicted surface hardness, determine whether the large gear to be tested is qualified.

[0030] Through the above steps, a mapping model is established using a standard test block with the same material and heat treatment process as the large gear under test, ensuring the compatibility between the model and the gear. A non-destructive testing probe integrating surface characteristic sensitive detection units and depth characteristic sensitive detection units is used to collect multi-source electromagnetic signals and extract signal feature parameters, comprehensively acquiring surface and depth-related information. An arc-shaped positioning bracket ensures the non-destructive testing probe is accurately aligned with the centerline of the tooth surface and perpendicularly fitted, guaranteeing accurate detection positioning. Inputting the signal feature parameters into the mapping model outputs predicted carburized layer depth and predicted surface hardness, enabling non-destructive testing of large gears. Finally, based on the prediction results, the gear's qualification is determined, allowing for rapid and effective quality assessment of large gears and improving the testing efficiency.

[0031] This embodiment provides a non-destructive testing method for the carburized layer depth and surface hardness of large gears. The core principle lies in a "pre-modeling" approach, using a standard test block identical in material and manufacturing process to the gear under test, to pre-establish a precise mathematical relationship between the characteristics of non-destructive electromagnetic signals and key material properties (carburized layer depth, surface hardness), i.e., a "mapping model." Then, during on-site testing, a combined probe integrating two electromagnetic detection units with different detection depths and sensitivity characteristics is used, along with a cleverly designed arc-shaped positioning bracket matched to the gear's geometry, to ensure stable and accurate acquisition of composite electromagnetic signals on the complex tooth surface. Finally, the signal characteristics acquired on-site are input into the pre-established mapping model, allowing for instantaneous and reverse analysis to determine the carburized layer depth and surface hardness of the gear, and thus, a judgment of whether it is qualified or not.

[0032] In step S101, before the formal testing, a standard test block with the same material and heat treatment process as the large gear to be tested is first used to establish a mathematical relationship between the non-destructive testing signal and the parameters to be tested (carburized layer depth, surface hardness). The carburized layer depth and surface hardness of the standard test block are known (obtained through destructive calibration). At the same time, electromagnetic signals of these test blocks are collected and features are extracted using a non-destructive testing probe. Through machine learning methods, the mapping relationship between signal features and carburized layer depth and hardness is learned to form a mapping model. Here, "standard test block" refers to a specially prepared test block with the same furnace number, batch, and heat treatment as the gear to be tested. These test blocks are small in size, which facilitates destructive calibration. For example, 60 (or 100, or other numbers) standard test blocks are prepared, with carburized layer depths covering the range of 1.0-6.0 mm (or other values). Non-destructive testing signal features refer to quantifiable parameters extracted from electromagnetic signals, such as the root mean square value of Barkhausen noise, the impedance phase angle of eddy current signals, etc. The mapping model refers to the mathematical relationship between the input signal feature parameters and the output carburized layer depth / hardness. It can be a mathematical formula, a set of coefficients, or a trained neural network model. In step S102, a specially designed non-destructive testing probe is used to collect electromagnetic signals on the tooth surface of the large gear under test, and the same signal feature parameters as those used in modeling are extracted. The surface characteristic sensitive detection unit is a sensor unit sensitive to changes in the surface hardness of the material, typically using a Barkhausen noise sensor; the depth characteristic sensitive detection unit is a sensor unit sensitive to changes in the material's depth characteristics, typically using a multi-frequency eddy current sensor. Multi-source electromagnetic signals refer to various electromagnetic signals from different physical principles, including Barkhausen noise signals and eddy current signals. The arc-shaped positioning bracket is a mechanical structure installed at the front end of the probe. Its curvature matches the radius of curvature of the gear tooth surface, and the spacing of the bracket matches the gear module. During testing, the bracket is positioned between two adjacent teeth, allowing the probe to automatically align with the center line of the tooth surface and maintain a vertically fitted posture. Large gears typically refer to gears with a diameter greater than 1000 mm or a module of not less than 10. In some practical applications, the diameter can reach several meters to over 10 meters. In step S103, the signal feature parameters extracted from the large gear under test are input into a pre-trained mapping model. The model automatically calculates the predicted values ​​of the carburized layer depth and surface hardness of the gear. In step S104, the predicted values ​​output by the mapping model are compared with the preset process acceptance range to determine whether the large gear meets the quality requirements.

[0033] In related technologies, the detection of carburized layer depth in large gears relies on destructive sampling methods (such as the microhardness gradient method). This method requires cutting samples from the finished gear, embedding them, polishing, and then measuring the hardness point by point. This is not only costly and time-consuming (lasting several days), but also cannot perform full inspection of the gear body, allowing only sampling and posing a risk of missed detections. Furthermore, existing methods must be performed in a laboratory environment, which cannot meet the rapid testing needs of production sites. This embodiment achieves non-destructive, rapid, and on-site testing of large gears. The testing process does not require cutting the gear, and the single-point testing time is only a few seconds, enabling full inspection of the gear. The test results can be fed back instantly, providing a basis for adjusting the heat treatment process. Simultaneously, the arc-shaped positioning bracket solves the probe fitting problem caused by the curvature of the large gear tooth surface, ensuring the stability and repeatability of the test signal. This achieves integrated, non-destructive, rapid, and on-site testing of carburized layer depth and surface hardness in large gears, significantly reducing testing costs and improving testing coverage and efficiency.

[0034] In an optional embodiment, a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness is established using multiple standard test blocks. This includes: for each standard test block, acquiring multi-source electromagnetic signals using a non-destructive testing probe and extracting sample signal characteristic parameters; performing destructive testing on each standard test block to determine the actual carburized layer depth and actual surface hardness; and establishing a mapping model using a regression algorithm with the sample signal characteristic parameters as input and the actual carburized layer depth and actual surface hardness as output.

[0035] In this embodiment, a mapping model is established using standard test blocks. Based on the characteristics of non-destructive testing signals, the depth of carburized layer and surface hardness of large gears can be predicted, avoiding the cumbersome process, high cost and long cycle of traditional destructive testing methods, and realizing non-destructive and rapid testing of large gears. Destructive testing of standard test blocks to obtain the actual depth of carburized layer and surface hardness can ensure the accuracy of the mapping model. Using a regression algorithm to establish the mapping model can improve the reliability of the prediction results.

[0036] This embodiment describes the complete process of establishing a mapping model from standard test blocks. The principle is as follows: by simultaneously performing non-destructive signal acquisition and destructive calibration on the same batch of standard test blocks, paired input and output data are obtained. Then, a regression algorithm is used to learn the mathematical relationship between the two, forming a mapping model that can be used for prediction. Specifically, for each standard test block, multi-source electromagnetic signals are acquired using the same probe and parameter settings as in subsequent field testing, and the same signal feature parameters as in the previous embodiment are extracted as input training data for the mapping model. Here, "sample signal feature parameters" refers to the feature data acquired from the standard test blocks used to train the model, and the types of feature parameters are exactly the same as those extracted during subsequent field testing. For the same standard test block, a destructive method (such as the microhardness gradient method) is used to determine its true carburized layer depth and surface hardness, which are used as output training data (i.e., label values) for the mapping model. The input features and output labels of all standard test blocks are used to form a training dataset. Regression algorithms (such as linear regression, multinomial regression, support vector regression, or neural networks) are used to learn the mapping relationship from input to output, resulting in a mapping model capable of predicting new data. Regression algorithms are a supervised machine learning method used to establish a functional relationship between input variables and continuous output variables. Taking the simplest linear regression as an example, its goal is to find a set of coefficients that minimizes the sum of squared errors between the linear combination of input features and the output labels. For nonlinear relationships, methods such as support vector regression or neural networks can be used. This embodiment obtains true values ​​as training labels through destructive calibration, enabling the mapping model to have accurate predictive capabilities. The input-output relationship is automatically learned through regression algorithms, eliminating the need for manually setting empirical formulas. The model can be reused after training, with a one-time investment in modeling costs and extremely low amortized costs for subsequent unlimited testing. A systematic modeling process is provided to ensure that the mapping model has sufficient accuracy and generalization ability, accurately converting lossless signals collected on-site into test parameters.

[0037] In an optional embodiment, destructive testing is performed on each standard test block to determine the actual carburized layer depth and the actual surface hardness, including: cutting the standard test block along a direction perpendicular to the carburized surface, and obtaining a cross-section after inlaying, grinding, and polishing; using a micro Vickers hardness tester, measuring the hardness value every 0.1 mm starting from the surface, and taking the depth corresponding to the hardness value dropping to a preset hardness as the actual carburized layer depth; and using a Vickers hardness tester to measure the actual surface hardness on the surface of the standard test block.

[0038] In this embodiment, the actual carburized layer depth and actual surface hardness of the standard test block can be accurately obtained, providing an accurate data basis for establishing a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness, thereby improving the accuracy of non-destructive testing of large gears.

[0039] The standard test block is cut perpendicular to the carburized surface, and after mounting, grinding, and polishing, a cross-section is obtained: the carburized surface is the surface of the test block that has undergone carburizing treatment; perpendicular cutting ensures that the cross-section is perpendicular to the direction of the carburized layer, accurately presenting the layer depth distribution; mounting, grinding, and polishing are standard metallographic sample preparation procedures, removing the cutting damage layer and obtaining a smooth and clean test cross-section, ensuring the accuracy of hardness measurement. Using a micro Vickers hardness tester, hardness values ​​are measured every 0.1 mm starting from the surface, and the depth corresponding to the hardness value dropping to the preset hardness is taken as the actual carburized layer depth: the micro Vickers hardness tester is a standard metallographic hardness measurement device; measurements every 0.1 mm ensure dense and accurate hardness gradient data; the preset hardness is usually 550 HV (the industry-standard judgment standard), and the depth from the surface to the core where the hardness drops to this value is the effective carburized layer depth, conforming to the industry definition. The actual surface hardness is measured on the surface of the standard test block using a Vickers hardness tester: the Vickers hardness is measured on a flat area of ​​the carburized surface of the test block, converted to HRC, and used as the true surface hardness value, ensuring consistency with the surface hardness definition of gears. This embodiment provides a unified and traceable metrological foundation for the entire nondestructive testing method. By adopting standardized destructive testing methods, the authority and consistency of model calibration data are ensured, thereby guaranteeing the accuracy and comparability of the final nondestructive testing results from the source.

[0040] In an optional embodiment, the surface characteristic sensitive detection unit is a Barkhausen noise detection unit, and the depth characteristic sensitive detection unit is a high-frequency eddy current detection unit; the surface sensitive feature parameters are derived from the Barkhausen noise signal collected by the Barkhausen noise detection unit and are used to characterize the physical properties related to surface hardness; the depth sensitive feature parameters are derived from the eddy current signal collected by the high-frequency eddy current detection unit and are used to characterize the physical properties related to the conductivity and permeability gradient along the depth direction.

[0041] In this embodiment, a Barkhausen noise detection unit is used as a surface characteristic sensitive detection unit to collect Barkhausen noise signals and extract surface-sensitive feature parameters used to characterize physical properties related to surface hardness. A high-frequency eddy current detection unit is used as a depth characteristic sensitive detection unit to collect eddy current signals and extract depth-sensitive feature parameters used to characterize physical properties related to conductivity and permeability gradients along the depth direction. This enables non-destructive testing of the surface hardness and carburized layer depth of large gears, avoiding the cumbersome process, high cost, and long cycle of traditional destructive testing methods, improving testing efficiency and practicality, and reducing the risk of missed detections.

[0042] A Barkhausen noise detection unit is a sensor assembly that utilizes the Barkhausen noise effect. It typically includes a U-shaped magnetic yoke (for applying an alternating magnetic field), an excitation coil (to generate the alternating magnetic field), and a receiving coil (to pick up the pulse signals generated by domain jumping). When an alternating magnetic field is applied, discontinuous jumping occurs in the domain walls within the ferromagnetic material, inducing electrical pulse signals in the receiving coil. The intensity of this signal is closely related to the material's hardness, residual stress, and microstructure. A high-frequency eddy current detection unit is a sensor assembly that utilizes the principle of electromagnetic induction. It typically includes one or more excitation coils (to generate a high-frequency alternating magnetic field) and a receiving coil (to pick up the induced signal). When a high-frequency alternating magnetic field acts on a conductive material, eddy currents are induced on the material surface. The secondary magnetic field generated by these eddy currents reacts on the coil, changing its equivalent impedance. By measuring the change in impedance, information such as the material's conductivity and permeability can be deduced. Eddy currents of different frequencies have different penetration depths; therefore, depth information can be obtained through multi-frequency excitation. The characteristic parameters used to characterize surface hardness are extracted from Barkhausen noise signals. These parameters are physically correlated with the surface hardness of the material. The intensity and distribution of the Barkhausen noise signal are positively correlated with surface hardness, and its characteristic parameters directly reflect the surface hardness level, unaffected by deep structural components. The characteristic parameters used to characterize the depth of the carburized layer are extracted from eddy current signals. These parameters are related to the changes in the electromagnetic properties of the material in the depth direction, and these changes in electromagnetic properties correspond to the depth distribution of the carburized layer. The phase and amplitude of the high-frequency eddy current signal change with the depth and gradient of the carburized layer, and its characteristic parameters reflect the changes in the electromagnetic properties of the material from the surface to the core, accurately corresponding to the depth of the carburized layer. This solves the problems in related technologies where a single sensor cannot simultaneously measure hardness and layer depth, and where improper sensor selection leads to signal insensitivity and functional confusion. By utilizing the complementary characteristics of the two electromagnetic detection technologies—Barkhausen is sensitive to surface structure / hardness, and high-frequency eddy current is sensitive to the subsurface conductivity gradient—it accurately meets the dual-index detection requirements, improving the detection specificity and accuracy.

[0043] In an optional embodiment, the surface-sensitive characteristic parameters include at least one of the root mean square value and peak position of the Barkhausen noise signal; the depth-sensitive characteristic parameters include at least one of the impedance phase angle and impedance amplitude of the eddy current signal.

[0044] In this embodiment, at least one of the root mean square value and peak position of the Barkhausen noise signal is used as a surface-sensitive characteristic parameter, which can more accurately characterize the physical properties related to surface hardness; at least one of the impedance phase angle and impedance amplitude of the eddy current signal is used as a depth-sensitive characteristic parameter, which can better characterize the physical properties related to conductivity and permeability gradient along the depth direction, thereby improving the accuracy of non-destructive testing of the carburized layer depth and surface hardness of large gears.

[0045] The original electromagnetic signals (such as Barkhausen noise signals or eddy current signals) are complex analog waveforms and cannot be directly input into the mapping model. Representative and stable numerical features need to be extracted from them. Different feature parameters reflect different aspects of the material's properties, and selecting appropriate feature parameters is crucial to ensuring the model's prediction accuracy. The "Root Mean Square (RMS) value" refers to the square root of the average of the squares of the Barkhausen noise signal waveform. It reflects the overall energy level of the signal. A larger RMS value indicates more intense magnetic domain jumping, usually corresponding to lower hardness; a smaller RMS value corresponds to higher hardness. The RMS value is the most commonly used Barkhausen noise feature parameter. "Peak position" refers to the location of the peak value of the Barkhausen noise signal envelope (usually with the intensity or time of the excitation magnetic field as the abscissa). The peak position reflects the variation of Barkhausen noise with magnetic field strength and is related to the material's coercivity and hardness. The "impedance phase angle" refers to the arctangent of the ratio of the imaginary part to the real part of the equivalent impedance of the eddy current coil, reflecting the phase delay between the induced magnetic field and the excitation magnetic field. The phase angle is sensitive to changes in the material's permeability and is related to the depth distribution of the carburized layer. "Impedance amplitude" refers to the magnitude of the equivalent impedance of the eddy current coil. The impedance amplitude reflects the overall resistance of the material to the alternating magnetic field, and is influenced by both conductivity and permeability, and is related to the thickness of the carburized layer. By selecting feature parameters with clear physical meaning and high signal-to-noise ratio, the original, high-dimensional signal information is refined (dimension reduced) into low-dimensional, highly condensed numerical values. This not only simplifies the construction of subsequent models, but more importantly, by extracting features that are sensitive to target parameters but relatively insensitive to interference factors, the robustness and repeatability of the entire detection method are improved.

[0046] As an optional implementation, the step of acquiring multi-source electromagnetic signals adopts an adaptive optimization acquisition strategy, including: First, a rapid pre-scan is performed by only the Barkhausen noise detection unit to initially assess the approximate range of tooth surface hardness; Second, based on the initially assessed hardness range, an optimal excitation frequency is adaptively selected from multiple preset eddy current detection excitation frequencies that is most sensitive to changes in the depth of the carburized layer within that hardness range; Third, the optimal excitation frequency is used to drive the high-frequency eddy current detection unit to perform formal depth information acquisition; thereby achieving real-time optimization of measurement parameters and improving the signal-to-noise ratio and analytical accuracy of depth-sensitive feature parameters.

[0047] In one optional embodiment, the arc-shaped positioning bracket is a replaceable structure, and an arc-shaped positioning bracket with the corresponding curvature can be replaced for large gears under test with different tooth surface curvature radii.

[0048] In this embodiment, the arc-shaped positioning bracket adopts a replaceable structure. By replacing the arc-shaped positioning bracket with one of the corresponding arc curvature for the large gear under test with one of the different tooth surface curvature radii, the non-destructive testing probe can be better adapted to large gears with different tooth surface curvatures. This ensures that the testing probe is aligned with the center line of the tooth surface and is perpendicular to the tooth surface, thereby improving the accuracy and applicability of the test. It is suitable for non-destructive testing of more large gears of different specifications.

[0049] Large gears of different models have different modules and tooth surface curvature radii, and a single fixed-radius bracket cannot accommodate all gears. By designing the bracket as a quick-change structure, a bracket with a matching curvature can be selected according to the specific specifications of the gear under test, ensuring a good fit between the probe and the tooth surface. The arc-shaped positioning bracket and the probe body are connected detachably (e.g., by threads, snaps, or magnetic attraction), allowing operators to select a bracket with a matching curvature based on the tooth surface curvature radius of the gear under test. "Replaceable structure" means that the bracket and the probe body use a standard interface connection, allowing for assembly and disassembly without tools or with only simple tools. For example, Customer A's wind turbine gear has a diameter of 3 meters, a module of 18, and a tooth surface curvature radius of approximately 1.5 meters at the pitch circle. The testing personnel take an arc-shaped positioning bracket (marked R1500, matching the 1.5-meter curvature radius) from the toolbox, insert it into the mounting slot at the front of the probe, and a "click" indicates installation is complete. The bracket is then placed on both sides of the gear teeth, and the probe automatically aligns with the center line of the tooth surface and fits vertically, ensuring a smooth testing process. Customer B's mining gear has a diameter of 1.2 meters, a module of 10, and a radius of curvature of approximately 0.6 meters at the pitch circle. The inspector removed the R1500 bracket and replaced it with an R600 bracket (matching the 0.6-meter radius of curvature). The replacement process took less than 30 seconds, required no tools, and the inspection was completed smoothly. Through the replaceable bracket design, one inspection system can serve multiple users and various gear models, significantly improving the return on investment.

[0050] In an optional embodiment, determining whether the large gear under test is qualified based on the predicted carburized layer depth and predicted surface hardness includes: comparing the predicted carburized layer depth and predicted surface hardness with preset qualified ranges for carburized layer depth and surface hardness, respectively; if both are within the corresponding qualified ranges, the large gear under test is determined to be qualified; otherwise, the large gear under test is determined to be unqualified.

[0051] In this embodiment, the quality of large gears can be accurately determined based on the predicted carburized layer depth and surface hardness, avoiding the problems of traditional destructive testing methods such as cumbersome procedures, high costs, long cycles, risk of missed detection, and insufficient testing efficiency and practicality, thus achieving non-destructive and rapid quality determination of large gears.

[0052] The predicted carburized layer depth and predicted surface hardness output by the model are compared with preset acceptable ranges. A gear is considered acceptable only if both parameters fall within their respective acceptable ranges; otherwise, it is considered unacceptable. For example, before judgment, two acceptable ranges are preset: a carburized layer depth acceptable range (e.g., 2.8mm-3.4mm) and a surface hardness acceptable range (e.g., 57HRC-61HRC). Then, the predicted values ​​output by the model are compared with these two ranges. For example, if the predicted carburized layer depth is 3.18mm and the predicted surface hardness is 57.8HRC, both conditions are met, and the gear is considered acceptable. The acceptable range is determined by gear designers based on the gear's operating conditions and failure modes. It typically includes a lower limit (to prevent insufficient load-bearing capacity due to insufficient layer depth) and an upper limit (to prevent excessive layer depth leading to increased brittleness or excessive cost). Carburized layer depth and surface hardness are two independent acceptance indicators; failure to meet either will affect the gear's service life and reliability. Therefore, the judgment method must consider both parameters simultaneously, not just one. This embodiment provides a clear and strict qualification judgment rule to ensure that only gears that meet the requirements of both indicators can be judged as qualified, effectively controlling quality risks.

[0053] Optionally, the above method also includes: issuing an audible and visual alarm signal if the large gear under test is determined to be unqualified. Issuing an audible and visual alarm signal when the large gear under test is determined to be unqualified can promptly remind operators, facilitating quick action to handle the unqualified large gear. The audible and visual signals provide a direct indication of the unqualified status, eliminating the need for continuous manual monitoring, quickly identifying abnormal gears, facilitating timely isolation and rework, and preventing unqualified products from flowing into the next process. For example, the operator places the probe against the gear tooth surface, presses the test button, and after 4 seconds, the display shows "qualified," the buzzer is silent, and the alarm light does not illuminate. The operator moves the gear to the qualified product area. If the predicted surface hardness of a certain gear is detected to be 55.2 HRC, below the lower limit of 57 HRC, it is determined to be unqualified. The system immediately triggers an alarm: the buzzer emits a rapid "beep-beep-beep" alarm sound, and the red alarm light flashes rapidly. The operator immediately notices the alarm, moves the gear to the processing area, and reports to the quality control engineer for further analysis. In noisy workshop environments, simple light signals may be blocked or ignored, and simple sound signals may be masked by machine noise. Combining sound and light alarms improves alarm reliability.

[0054] As an optional implementation method, a mapping model is established using multiple standard test blocks, including: dividing the multiple standard test blocks into three categories according to the tooth surface position: tooth root area test blocks, pitch circle area test blocks, and tooth tip area test blocks. The radius of curvature of the arc surface of each type of test block is matched with the actual radius of curvature of the corresponding tooth position of the large gear under test; establishing an independent mapping model for each type of test block to obtain the tooth root area mapping model, pitch circle area mapping model, and tooth tip area mapping model; when acquiring multi-source electromagnetic signals on the tooth surface of the large gear under test, identifying whether the current detection position belongs to the tooth root area, pitch circle area, or tooth tip area, and calling the corresponding mapping model to output the predicted carburized layer depth and predicted surface hardness.

[0055] In an optional embodiment, the method further includes: before starting the testing of the large gear to be tested, measuring a pre-calibrated reference part using a non-destructive testing probe. The reference part has the same material and heat treatment process as the large gear to be tested, and the reference carburized layer depth and reference surface hardness of the reference part are known; inputting the signal characteristic parameters measured on the reference part into a mapping model to obtain the first carburized layer depth and the first surface hardness of the reference part; calculating the first deviation coefficient K1 between the first carburized layer depth and the reference carburized layer depth, and the second deviation coefficient K2 between the first surface hardness and the reference surface hardness; when testing the large gear to be tested, multiplying the predicted carburized layer depth output by the mapping model by the reciprocal of K1 and multiplying the predicted surface hardness by the reciprocal of K2 to obtain the final predicted value after drift compensation.

[0056] In this embodiment, a reference part with the same material and heat treatment process as the large gear under test is used for measurement. The deviation coefficient is calculated, and the drift compensation is performed on the predicted carburized layer depth and predicted surface hardness output by the mapping model, which can improve the accuracy of the non-destructive testing results of the large gear.

[0057] This embodiment adds a drift compensation step before testing, correcting the on-site testing results by measuring the deviation coefficient of a reference piece. The principle is that testing equipment may drift during use (e.g., due to temperature changes, probe wear, electronic component aging), leading to inconsistent testing results for the same object at different times. By measuring a reference piece with a known calibration value before testing, the deviation coefficient between the current measured value and the calibration value is calculated, and this coefficient is then applied to the subsequent gear testing results to compensate for equipment drift. Specifically, before formally testing the large gear to be tested, a reference piece with known true values ​​is measured. This reference piece is manufactured using the same material and heat treatment process as the gear to be tested, and its carburized layer depth and surface hardness have been precisely calibrated through destructive testing, serving as benchmark values. The "reference piece" is a small-sized standard sample block with the same physical properties as the gear being tested but a smaller size, facilitating storage and periodic measurement. The "benchmark carburized layer depth" and "benchmark surface hardness" refer to the true values ​​of the reference piece obtained through destructive testing; these values ​​are valid long-term. Using the exact same process as for testing gears, non-destructive signals from a reference part are acquired, features are extracted, and input into a mapping model to obtain the model's predicted layer depth and hardness of the reference part (referred to as "first carburized layer depth" and "first surface hardness"). The model's predicted values ​​are compared with the baseline values ​​to calculate the degree of deviation; the deviation coefficient can be a ratio (e.g., predicted value / baseline value). When formally testing the large gear to be tested, the model's predicted output is not directly used as the final result. Instead, it is multiplied by the reciprocal of the deviation coefficient for correction. If the model output is too high (deviation coefficient > 1), it is lowered after correction; if the model output is too low (deviation coefficient < 1), it is increased after correction.

[0058] This application also provides a non-destructive testing system for large gears, used to perform the non-destructive testing method for large gears in any of the foregoing embodiments, such as... Figure 2 As shown, the system includes: The model building unit is used to establish a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness using multiple standard test blocks. The standard test blocks are made of the same material and heat treatment process as the large gear to be tested. The acquisition unit is used to acquire multi-source electromagnetic signals on the tooth surface of the large gear under test using a non-destructive testing probe that integrates a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit. The signal characteristic parameters that are the same as the non-destructive testing signal characteristics are extracted from the multi-source electromagnetic signals. The signal characteristic parameters include at least one surface sensitive characteristic parameter and one depth sensitive characteristic parameter. The non-destructive testing probe is equipped with an arc-shaped positioning bracket. The arc of the arc-shaped positioning bracket matches the curvature of the tooth surface of the large gear under test, and the spacing matches the gear module. During the test, the arc-shaped positioning bracket is locked on both sides of the tooth, so that the non-destructive testing probe is aligned with the center line of the tooth surface and perpendicularly attached to the tooth surface. The mapping unit is used to input signal feature parameters into the mapping model and output the predicted carburized layer depth and predicted surface hardness of the large gear under test. The judgment unit is used to determine whether the large gear under test is qualified based on the predicted carburized layer depth and predicted surface hardness.

[0059] It should be noted that the devices or systems provided in the above embodiments are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept. Other device or system embodiments correspond to the aforementioned method embodiments. Other technical features are described in the previous embodiments and will not be repeated here.

[0060] This application also provides a computer-readable storage medium storing instructions that, when executed, perform the steps of any of the methods described above.

[0061] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0062] This application also discloses an electronic device. For example... Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0063] The communication bus 302 is used to enable communication between these components.

[0064] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0065] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0066] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the electronic device (such as a server) using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0067] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a non-destructive testing method for large gears.

[0068] exist Figure 3In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and acquire user input data; while the processor 301 can be used to call an application program of a non-destructive testing method for a large gear stored in the memory 305. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0069] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0070] In the various embodiments provided in this application, it should be understood that the disclosed apparatus or system can be implemented in other ways. For example, the apparatus or system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0071] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the disclosure herein.

[0072] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art that are not described in this disclosure.

Claims

1. A non-destructive testing method for large gears, characterized in that, include: A mapping model between nondestructive testing signal characteristics and carburized layer depth and surface hardness was established using multiple standard test blocks. The standard test blocks were made of the same material and heat treatment process as the large gear to be tested. A non-destructive testing probe integrating a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit is used to collect multi-source electromagnetic signals on the tooth surface of the large gear under test. Signal feature parameters with the same characteristics as the non-destructive testing signal are extracted from the multi-source electromagnetic signals. The signal feature parameters include at least one surface sensitive feature parameter and one depth sensitive feature parameter. The non-destructive testing probe is equipped with an arc-shaped positioning bracket. The arc of the arc-shaped positioning bracket matches the curvature of the tooth surface of the large gear under test, and the spacing matches the gear module. During testing, the arc-shaped positioning bracket is locked on both sides of the tooth, so that the non-destructive testing probe is aligned with the center line of the tooth surface and perpendicularly attached to the tooth surface. The signal feature parameters are input into the mapping model, and the predicted carburized layer depth and predicted surface hardness of the large gear under test are output. Based on the predicted carburized layer depth and the predicted surface hardness, it is determined whether the large gear under test is qualified.

2. The non-destructive testing method for large gears according to claim 1, characterized in that, A mapping model between nondestructive testing signal characteristics and carburized layer depth and surface hardness was established using multiple standard test blocks, including: For each of the standard test blocks, the non-destructive testing probe is used to acquire multi-source electromagnetic signals and extract sample signal characteristic parameters; Each of the standard test blocks was subjected to destructive testing to determine the actual carburized layer depth and the actual surface hardness. Using the sample signal feature parameters as input and the actual carburized layer depth and actual surface hardness as output, the mapping model is established through a regression algorithm.

3. The non-destructive testing method for large gears according to claim 2, characterized in that, The destructive testing of each of the standard test blocks to determine the actual carburized layer depth and actual surface hardness includes: The standard test block was cut along a direction perpendicular to the carburized surface, and the cross-section was obtained after inlaying, grinding, and polishing. Using a micro Vickers hardness tester, hardness values ​​are measured every 0.1 mm starting from the surface, and the depth corresponding to the hardness value dropping to the preset hardness is taken as the actual carburized layer depth. The actual surface hardness was measured on the surface of a standard test block using a Vickers hardness tester.

4. The non-destructive testing method for large gears according to claim 1, characterized in that, The surface characteristic sensitive detection unit is a Barkhausen noise detection unit, and the depth characteristic sensitive detection unit is a high-frequency eddy current detection unit; The surface-sensitive characteristic parameters are derived from the Barkhausen noise signal collected by the Barkhausen noise detection unit and are used to characterize the physical properties related to the surface hardness. The depth-sensitive feature parameters are derived from the eddy current signals acquired by the high-frequency eddy current detection unit and are used to characterize the physical properties related to the conductivity and permeability gradients along the depth direction.

5. The non-destructive testing method for large gears according to claim 1, characterized in that, The surface-sensitive characteristic parameters include at least one of the root mean square value and peak position of the Barkhausen noise signal; the depth-sensitive characteristic parameters include at least one of the impedance phase angle and impedance amplitude of the eddy current signal.

6. The non-destructive testing method for large gears according to claim 1, characterized in that, The arc-shaped positioning bracket is a replaceable structure. For large gears under test with different tooth surface curvature radii, an arc-shaped positioning bracket with the corresponding curvature can be replaced.

7. The non-destructive testing method for large gears according to claim 1, characterized in that, Based on the predicted carburized layer depth and the predicted surface hardness, the determination of whether the large gear under test is qualified includes: The predicted carburized layer depth and the predicted surface hardness are compared with the preset qualified ranges for carburized layer depth and surface hardness, respectively. If both are within the corresponding acceptable range, the large gear under test is deemed acceptable; otherwise, the large gear under test is deemed unacceptable.

8. A non-destructive testing system for large gears, characterized in that, A non-destructive testing method for performing any one of claims 1 to 7 on large gears includes: The model building unit is used to establish a mapping model between non-destructive testing signal characteristics and carburized layer depth and surface hardness using multiple standard test blocks. The standard test blocks are made of the same material and heat treatment process as the large gear to be tested. The acquisition unit is used to acquire multi-source electromagnetic signals on the tooth surface of the large gear under test using a non-destructive testing probe that integrates a surface characteristic sensitive detection unit and a depth characteristic sensitive detection unit. The acquisition unit extracts signal feature parameters that are the same as the non-destructive testing signal features from the multi-source electromagnetic signals. The signal feature parameters include at least one surface sensitive feature parameter and one depth sensitive feature parameter. The non-destructive testing probe is equipped with an arc-shaped positioning bracket. The arc of the arc-shaped positioning bracket matches the curvature of the tooth surface of the large gear under test, and the spacing matches the gear module. During the test, the arc-shaped positioning bracket is locked on both sides of the tooth, so that the non-destructive testing probe is aligned with the center line of the tooth surface and perpendicularly attached to the tooth surface. The mapping unit is used to input the signal feature parameters into the mapping model and output the predicted carburized layer depth and predicted surface hardness of the large gear under test. The determination unit is used to determine whether the large gear under test is qualified based on the predicted carburized layer depth and the predicted surface hardness.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 7.

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