Method and system for evaluating service life of gearbox

Abstract

The invention relates to the technical field of data processing, in particular to a gearbox service life evaluation method and system. The method comprises the following steps of collecting shaft current of a gearbox under an electromechanical coupling working condition, carrying out current characteristic association on each bearing, and generating a current characteristic sequence of each bearing; according to the current characteristic sequence of each bearing, judging the main circulation path and branch of the current between a gear meshing pair in the gear box, and carrying out electric corrosion damage evaluation to generate a bearing-tooth surface electric corrosion damage ratio; calculating a fatigue life reduction coefficient of the part according to the bearing-tooth surface electric corrosion damage ratio, and performing dynamic linear damage accumulation treatment to obtain a fatigue damage contribution value of each part in a period; evaluating the service life of the gearbox according to the fatigue damage contribution value of each part in the cycle, and generating the residual life percentage of the gearbox. According to the method, the residual life of the gearbox under the electromechanical coupling working condition is accurately predicted through collaborative evaluation of the electric corrosion damage and the vibration amplification effect.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method and system for evaluating the service life of a gearbox. Background Art

[0002] As a core component in a mechanical transmission system, at present, since many mechanical systems adopt the motor drive mode, the gearbox works in an electro-mechanical coupling environment for a long time. Under such working conditions, the influence of the electromagnetic field on the material properties and fatigue life of the gearbox is becoming increasingly significant. The failure mode of the gearbox under the electro-mechanical coupling working condition presents a complex characteristic. On the one hand, the harmonic torque generated by the motor drive causes a variable amplitude cyclic load on the tooth surface, accelerating the initiation of fatigue cracks. On the other hand, the induced current caused by the electromagnetic field will form a micro-arc discharge phenomenon on the gear contact surface, generating microscopic electro-erosion pits, which become stress concentration sources and significantly reduce the fatigue life of the gear. Especially under the working conditions of frequent start-stop and variable load, this electro-mechanical coupling effect is more prominent. For a gearbox working in a strong electromagnetic field environment, especially a high-power density gear transmission system with a lightweight design, its actual service life is often significantly lower than the predicted value of the traditional method, and the phenomenon of premature failure is widespread. However, the traditional gearbox life evaluation method is mainly based on pure mechanical stress analysis and material fatigue theory, and most of them simplify the working environment to pure mechanical load conditions, ignoring the influence of the electromagnetic field on the microscopic structure and surface characteristics of the material, resulting in a significant deviation between the evaluation result and the actual service life. Summary of the Invention

[0003] Based on this, the present invention provides a method and system for evaluating the service life of a gearbox to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for evaluating the service life of a gearbox includes the following steps: Step S1: Collect the shaft current of the gearbox under the electro-mechanical coupling working condition, and perform the correlation of the current characteristics of each bearing to generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing to generate the internal electromagnetic disturbance snapshot data; Step S2: Determine the main circulation path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, and estimate the current distribution ratio to generate the estimated current share data of the meshing pair-bearing; obtain the design parameters of the gearbox; perform the electro-erosion damage evaluation through the estimated current share data of the meshing pair-bearing based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox to generate the electro-erosion damage ratio of the bearing-tooth surface; Step S3: Calculate the fatigue life reduction coefficient of the component according to the electro-erosion damage ratio of the bearing-tooth surface, and perform the dynamic linear damage accumulation process to obtain the fatigue damage contribution value of each component in the cycle; Step S4: Analyze the fatigue damage degree of the dominant components based on the fatigue damage contribution values of each component in the cycle, evaluate the service life of the gearbox, and generate the percentage of the remaining service life of the gearbox.

[0005] Preferably, the present invention further provides a gearbox service life evaluation system that executes the gearbox service life evaluation method as described above. The gearbox service life evaluation system includes: An electromagnetic feature acquisition module, configured to collect the shaft current of the gearbox under the electromechanical coupling condition, correlate the current characteristics of each bearing, and generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, and generate the internal electromagnetic disturbance snapshot data; An electric erosion path evaluation module, configured to determine the main flow path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, estimate the current distribution ratio, and generate the estimated current share data of the meshing pair-bearing; obtain the design parameters of the gearbox; perform electric erosion damage evaluation through the estimated current share data of the meshing pair-bearing based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox, and generate the proportion of bearing-to-tooth surface electric erosion damage; A fatigue damage accumulation module, configured to calculate the fatigue life reduction coefficient of the components according to the proportion of bearing-to-tooth surface electric erosion damage, and perform dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in the cycle; A life prediction and analysis module, configured to analyze the fatigue damage degree of the dominant components based on the fatigue damage contribution values of each component in the cycle, evaluate the service life of the gearbox, and generate the percentage of the remaining service life of the gearbox.

[0006] By comprehensively considering the influence of electromagnetic fields on the gearbox life under the electro-mechanical coupling condition, the present invention significantly improves the accuracy and reliability of life assessment. It innovatively directly correlates the current characteristics with the electrical erosion damage, breaking through the limitation of traditional assessment methods that only consider mechanical stress and ignore electromagnetic factors. By establishing a current flow path model and analyzing the proportion of electrical erosion damage, it accurately quantifies the differential influence of electromagnetic fields on different gear components, effectively solving the problem of life prediction deviation caused by insufficient electromagnetic shielding in lightweight gearboxes. It is particularly suitable for environments with frequent start-stop and variable load conditions, and can accurately capture the fatigue acceleration effect caused by harmonic torque and micro-arc discharge, significantly improving the coincidence degree between the prediction result and the actual service life. Through the dynamic linear damage accumulation processing mechanism, it can track the fatigue state evolution process of each component in real time and timely identify potential early failure hazards. In addition, this method can also adaptively adjust the assessment parameters according to the electromagnetic disturbance characteristics under different working conditions, so that the assessment results maintain high precision under various complex working conditions. Compared with traditional methods, this assessment method incorporates the influence of electromagnetic fields as a core factor into the calculation model, resulting in an improvement in assessment accuracy of more than 30%, especially performing well in high-power density drive systems. Through the analysis of the fatigue damage degree of the main components, it can accurately locate the weakest links in the gearbox that are most prone to failure. This method innovatively establishes an electro-mechanical-material multi-field coupling damage mechanism, filling the gap in the field of gearbox life assessment in the electromagnetic environment, providing strong technical support for improving the reliability of mechatronic equipment and extending its service life, and having broad engineering application prospects. Therefore, a gearbox life assessment method of the present invention synchronously collects shaft current and electromagnetic field data through a high-frequency response Rogowski coil and a micro magnetic field probe array, combines gear meshing topology to analyze the current flow path, and establishes a current share distribution model for the meshing pair-bearing; introduces ultrasonic oil film thickness monitoring and electro-thermal-force disturbance analysis to construct a lubrication state assessment system based on the oil film thickness ratio; innovatively multiplies the vibration amplification factor by the proportion of electrical erosion damage to form an electro-mechanical coupling high-risk component identification mechanism; realizes the accurate quantification of the fatigue damage accumulation process through the combination of coupled vibration enhanced stress history calculation and electrical erosion damage reduction coefficient; and finally dynamically predicts the remaining life of the gearbox based on the damage rate of the main components, solving the assessment deviation problem caused by traditional methods ignoring the electro-mechanical coupling effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 It is a schematic flow chart of the steps of the gearbox life assessment method of the present invention; The realization, functional characteristics and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0008] To achieve the above object, please refer to Figure 1, the present invention provides a method for evaluating the service life of a gearbox, comprising the following steps: Step S1: Collect the shaft current of the gearbox under the electromechanical coupling condition, correlate the current characteristics of each bearing, and generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, and generate the internal electromagnetic disturbance snapshot data; Step S2: Determine the main flow path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, estimate the current distribution ratio, and generate the estimated current share data of the meshing pair - bearing; obtain the design parameters of the gearbox; based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox, conduct an electro - erosion damage assessment through the estimated current share data of the meshing pair - bearing, and generate the proportion of bearing - tooth surface electro - erosion damage; Step S3: Calculate the fatigue life reduction coefficient of the components according to the proportion of bearing - tooth surface electro - erosion damage, and conduct dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in each cycle; Step S4: Analyze the fatigue damage degree of the dominant components according to the fatigue damage contribution value of each component in each cycle, and conduct a service life assessment of the gearbox to generate the percentage of the remaining service life of the gearbox.

[0009] In an embodiment of the present invention, the method for evaluating the service life of the gearbox comprises the following steps: Step S1: Collect the shaft current of the gearbox under the electromechanical coupling condition, correlate the current characteristics of each bearing, and generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, and generate the internal electromagnetic disturbance snapshot data; In the embodiments of the present invention, high-frequency response Rogowski coils with the model number HRC-50 are installed on the sun gear input bearing seat, the planet carrier output bearing seat of the gearbox, and the outer rings of the four planet gear bearings. The inner diameter of the coil is 40 mm, the outer diameter is 60 mm, the thickness is 10 mm, and the frequency response range is 10 Hz to 100 kHz. A micro magnetic field probe array with the model number MS-100 is arranged on the outer wall of the planet gear bearing area of the box body and the outer wall near the fixed end of the ring gear, with a total of 16 probes. A high-speed data acquisition device with the model number DAQ-9000 is used for wide-band sampling of the shaft current. The sampling frequency is set to 500 kHz, and the sampling duration is 60 seconds. The gearbox operates at the rated speed of 1500 rpm, and the load is 75% of the rated load. A 4096-point FFT transform is performed on the collected original shaft current time-domain sequence. The window function is selected as the Hanning window, and the overlapping rate of adjacent windows is 50%. The main harmonic components are screened through a 5% amplitude threshold, generating the main harmonic amplitude sequence and frequency sequence of the shaft current, and correlating them to form the current characteristic sequence of each bearing. At the same time, a three-axis magnetic field probe is used to collect the magnetic field data on the surface of the box body, with a sampling frequency of 10 kHz. The internal space of the gearbox is divided into 100,000 grid units by the finite element method to reconstruct the internal magnetic field distribution. The internal space is divided into key functional areas, and the statistical characteristics of the magnetic field intensity in each area are calculated. Combining with the current characteristic sequence, the electromagnetic disturbance level is evaluated, generating internal electromagnetic disturbance snapshot data, including component names, position coordinates, magnetic field intensity, main excitation frequencies, and disturbance levels.

[0010] Step S2: Determine the main circulation path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, and estimate the current distribution ratio, generating the estimated current share data of the meshing pair - bearing; obtain the design parameters of the gearbox; based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox, conduct an electro-erosion damage assessment through the estimated current share data of the meshing pair - bearing, generating the proportion of bearing - tooth surface electro-erosion damage; In the embodiment of the present invention, according to the bearing current characteristic sequences obtained in step S1, the effective current value of the sun gear input bearing is extracted as 150 mA, the effective current value of the planet carrier output bearing is 105 mA, and the effective current values of the four planet gear bearings are 38 mA, 35 mA, 39 mA, and 37 mA respectively. Based on the connection topology of the sun gear - planet gear - ring gear (the number of teeth of the sun gear is 25, the number of teeth of the planet gear is 35, the number of teeth of the internal ring gear is 95, and the number of planet gears is 4), a current flow network model is established. The analysis shows that the proportions of the 150 mA current flowing into the four planet gears from the sun gear input bearing are 25%, 23%, 27%, and 25%. Set the number of equivalent conductive contact points of the bearings in the gearbox: 5 for the sun gear input bearing, 7 for the planet carrier output bearing, and 4 for the planet gear bearings; the contact resistance range: 15 - 25 ohms for the sun gear input bearing, 10 - 18 ohms for the planet carrier output bearing, and 20 - 35 ohms for the planet gear bearings. Calculate the current distribution ratios of the sun gear - planet gear meshing pair and the planet gear - internal ring gear meshing pair, and generate the estimated current share data of the meshing pair - bearing. Obtain the material properties from the gearbox design parameters: 20CrMnTi gear material, the critical electric erosion current density threshold is 0.8 A / mm²; GCr15 bearing material, the critical electric erosion current density threshold is 0.6 A / mm². Calculate the instantaneous effective conductive contact area of each meshing point and the bearing contact point area, and obtain the distribution range of the average current density of the tooth surface and the bearing current density. Calculate the severity index of the working condition in the meshing area using the electrothermal - mechanical disturbance data of the tooth surface, evaluate the electric erosion damage rate, and generate the proportion of the bearing - tooth surface electric erosion damage.

[0011] Step S3: Calculate the reduction coefficient of the fatigue life of the component according to the proportion of the bearing - tooth surface electric erosion damage, and perform dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in the cycle; In the embodiment of the present invention, high-bandwidth torque sensors with models TM-5000 and TM-8000 are installed at the input shaft flange and the output shaft spline of the gearbox, with rated ranges of 5000 N·m and 8000 N·m respectively, and a sampling frequency of 20 kHz. Six triaxial high-frequency acceleration sensors with model PCB-356A33 are installed at the planet carrier bearing housing and the sun gear bearing housing, with a sampling frequency of 25.6 kHz. Apply FFT to the double-ended torque time domain sequence to extract the amplitude and phase of the harmonic torque component, and generate the harmonic torque component spectrum. Conduct spectral analysis on the multi-channel vibration data, compare it with the potential electromagnetic excitation frequency data in the internal electromagnetic disturbance snapshot data, and screen out the effective electromagnetic vibration response frequency points. Identify potential electromechanical coupling frequency pairs through frequency alignment and proximity matching, calculate the vibration amplification factor, and generate high-risk coupled vibration data for each component in combination with the proportion of bearing-to-tooth surface electrical erosion damage. Use the Hertz contact theory to calculate the contact stress history during the gear meshing process, and enhance it using the high-risk coupled vibration data to generate the enhanced stress history of the coupled vibration. Calculate the fatigue life reduction coefficient of the components according to the proportion of bearing-to-tooth surface electrical erosion damage. The reduction coefficient of the sun gear - planet gear 1 meshing pair is 1.65, and the reduction coefficient of the sun gear input bearing is 1.29. Use the linear damage accumulation theory to calculate the fatigue damage. The fatigue damage contribution value of the sun gear - planet gear 1 meshing pair in the current monitoring period is 0.2475, and the fatigue damage contribution values of each component in the period are obtained.

[0012] Step S4: Analyze the fatigue damage degree of the leading components based on the fatigue damage contribution values of each component in the period, and conduct a life assessment of the gearbox to generate the remaining life percentage of the gearbox.

[0013] In the embodiment of the present invention, a gearbox life assessment model is established according to the fatigue damage contribution values of each component in the period. First, accumulate the fatigue damage contribution values of each component, and record the total operating time and cumulative fatigue damage of the gearbox. For the sun gear - planet gear 1 meshing pair, the current cumulative fatigue damage is 3.75, accounting for 37.5% of the design life; the cumulative fatigue damage of the sun gear input bearing is 2.15, accounting for 21.5% of the design life; the fatigue damage of other components is less than 20%. By analyzing the proportion of fatigue damage of each component, it is determined that the sun gear - planet gear 1 meshing pair is the leading component, and its damage rate increases by 7.5% of damage per 1000 hours of operation. Based on the damage accumulation rate of the leading component, predict the remaining life of the gearbox. The calculation formula takes into account the electrical erosion damage acceleration effect, the vibration coupling enhancement effect, and the material degradation effect. The comprehensive evaluation shows that the remaining life of the gearbox is 8333 hours, which is equivalent to 62.5% of the design life. The system generates a report on the remaining life percentage of the gearbox, including the damage status, damage rate, predicted remaining life value, and maintenance suggestions of each key component, providing a scientific basis for maintenance decision-making for equipment management personnel.

[0014] Preferably, in step S1, the shaft current of the gearbox is collected under the electromechanical coupling condition, and the correlation of the current characteristics of each bearing includes: Install high-frequency response Rogowski coils on the outer rings of the input bearing seat of the sun gear, the output bearing seat of the planetary carrier, and at least one planetary gear bearing of the gearbox; arrange a micro magnetic field probe array on the outer wall of the planetary gear bearing area and near the outer wall of the fixed end of the ring gear of the middle box of the gearbox; Use the high-frequency response Rogowski coil to perform wide-band sampling of the shaft current to obtain the original shaft current time-domain sequence; Perform a fast Fourier transform on the original shaft current time-domain sequence, and then extract the amplitude and phase of each frequency component to generate the original shaft current spectrum data; Perform main harmonic component analysis on the original shaft current spectrum data through a preset amplitude threshold to generate the main harmonic amplitude sequence of the shaft current; Extract the harmonic frequencies corresponding to the main harmonic amplitude sequence of the shaft current from the original shaft current spectrum data to obtain the main harmonic frequency sequence of the shaft current; Correlate the main harmonic amplitude sequence of the shaft current and the main harmonic frequency sequence of the shaft current to generate the current characteristic sequence of each bearing.

[0015] In an embodiment of the present invention, a high-frequency response Rogowski coil with model number HRC-50 is installed on the sun gear input bearing seat of the gearbox. The inner diameter of the coil is 40 mm, the outer diameter is 60 mm, and the thickness is 10 mm. The coil winding uses 120 turns of 0.5 mm enameled wire, and the frequency response range is from 10 Hz to 100 kHz. A Rogowski coil with the same specifications is installed on the planet carrier output bearing seat. For the planet gear bearings, a small high-frequency response Rogowski coil with model number HRC-30 is installed on the outer ring of each planet gear bearing, with an inner diameter of 25 mm, an outer diameter of 40 mm, and a thickness of 8 mm. Eight miniature magnetic field probes with model number MS-100 are arranged on the outer wall of the planet gear bearing area of the gearbox housing, with a probe spacing of 45 degrees, forming an annular array; eight miniature magnetic field probes of the same model are also arranged on the outer wall near the fixed end of the ring gear, forming a probe array. All coils and probes are connected to the data acquisition system through shielded cables. A high-speed data acquisition device with model number DAQ-9000 is used for wide-band sampling of the shaft current, the sampling frequency is set to 500 kHz, the sampling duration is 60 seconds, and each sampling collects the Rogowski coil signals of the sun gear input bearing seat, the planet carrier output bearing seat, and the outer rings of all planet gear bearings respectively. The input impedance of the data acquisition device is set to 10 MΩ, the analog-to-digital conversion accuracy is 16 bits, and the acquisition gain is set to 10 times. During the acquisition process, the gearbox operates at the rated speed of 1500 rpm, and the load is 75% of the rated load. The acquired original shaft current time-domain sequences are stored separately according to the bearing positions, and the data format is a binary floating-point array, recording the current amplitude of each sampling point, with the unit of milliamperes (mA). When performing a fast Fourier transform on the acquired original shaft current time-domain sequences, a 4096-point FFT transform window is used, the window function is selected as the Hanning window, and the overlapping rate of adjacent windows is 50%. During the FFT calculation process, first, the time-domain sequence is segmented according to the window length, each segment of data is multiplied by the Hanning window function, and then the FFT of each segment of data is calculated to obtain the complex-frequency domain representation. Then, the modulus value of the complex result is extracted as the amplitude, and the phase angle of the complex result is extracted as the phase, forming a frequency-amplitude-phase triple. The calculated spectral resolution is 122 Hz (sampling frequency divided by the number of FFT points). The time-domain sequences of each bearing position are processed separately to generate the corresponding original shaft current spectrum data, and the spectrum data contains all frequency components in the range of 0 Hz to 250 kHz. The amplitude threshold is set to 5% of the maximum amplitude in the spectrum. This threshold is determined by analyzing the shaft current spectrum characteristics of healthy gearboxes in historical data. By calculating the spectrum data of 100 healthy gearboxes under different working conditions and statistically analyzing the amplitude ratio of secondary harmonics to primary harmonics, it is concluded that a threshold of 5% can effectively distinguish primary harmonics and secondary harmonics. During the screening process, all frequency points in the spectrum are traversed. When the amplitude of a certain frequency point is greater than or equal to the threshold, the amplitude corresponding to that frequency point is extracted and arranged in ascending order of frequency to form the shaft current main harmonic amplitude sequence.This sequence usually contains 10 to 20 main harmonic components, which record the amplitudes of the frequency points where the energy in the shaft current of the gearbox is concentrated. For each main harmonic amplitude identified in step 4, find the corresponding frequency value in the original spectral data. The extraction process uses an exact indexing method, that is, directly obtain the corresponding frequency value according to the position of the amplitude in the spectral data. To improve the frequency recognition accuracy, perform quadratic interpolation near the original frequency points, and determine the exact frequency corresponding to the amplitude peak through three-point quadratic polynomial fitting. The extracted frequency values are arranged in the same order as the main harmonic amplitude sequence to form the main harmonic frequency sequence of the shaft current. The frequency values in this sequence are accurate to 0.1 Hz, which record the exact frequency positions of the main energy distribution in the shaft current. Integrate and analyze the main harmonic amplitude sequence and frequency sequence of the shaft current obtained from each measurement point to establish a bearing current characteristic correlation model. First, identify the characteristic frequencies of the sun gear input bearing, the planet carrier output bearing, and the planet gear bearings respectively. These frequencies are pre-calculated according to the bearing geometric parameters (inner ring diameter, outer ring diameter, rolling element diameter, number of rolling elements) and the rotational speed. Then, match the measured main harmonic frequencies with the characteristic frequencies of each bearing, and extract the harmonic components and their amplitudes that are close to the characteristic frequencies of each bearing (error less than 1%) to generate the current characteristic sequences of each bearing. These characteristic sequences contain the current harmonic information unique to each bearing, reflecting the electrical state of the bearing.

[0016] Preferably, in step S1, synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance levels borne by each component of the gearbox according to the current characteristic sequences of each bearing, including: Use a micro magnetic field probe array to synchronously collect the magnetic field intensities at each measurement point to obtain discrete magnetic field data on the box surface; Perform three-axis component analysis on the discrete magnetic field data on the box surface to evaluate the electromagnetic field leakage intensity and direction at the measurement points, and obtain spatial electromagnetic field distribution data; Perform three-dimensional space coordinate mapping of the gearbox according to the spatial electromagnetic field distribution data, and perform spatial magnetic field calculation to reconstruct the equivalent leakage magnetic field intensity distribution near the inner ring of the planet carrier bearing and the meshing line between the sun gear and the planet gear in the gearbox, and generate internal equivalent magnetic field intensity cloud data; Perform spatial region division on the internal equivalent magnetic field intensity cloud data, and calculate the average and peak magnetic field intensities of the raceways of the planet gear bearings, the tooth surfaces of the sun gear and the planet gear in the gearbox to generate surface magnetic induction characteristic data of key components; Evaluate the electromagnetic excitation of the rotating components of the planetary gear train based on the current characteristic sequences of each bearing to generate potential electromagnetic excitation frequency data; Evaluate the electromagnetic disturbance levels borne by each component of the gearbox according to the potential electromagnetic excitation frequency data and the surface magnetic induction characteristic data of key components, and extract electromagnetic disturbance characteristics to generate internal electromagnetic disturbance snapshot data.

[0017] In the embodiments of the present invention, an MF-300 three-axis magnetic field probe array is used to collect the magnetic field intensity on the surface of the gearbox. The probe sensitivity is 0.5 μT, the measurement range is ±2000 μT, and the sampling frequency is set to 10 kHz. Eight probes are installed on the outer wall of the planetary gear bearing area of the gearbox housing, arranged in a circular array with a probe spacing of 45 degrees; eight probes are installed on the outer wall near the fixed end of the gear ring, also arranged in a circular array. All probes synchronously collect signals through a 16-channel synchronous data acquisition device, and the acquisition duration is 60 seconds. During the acquisition process, the gearbox runs at a rated speed of 1500 rpm, and the load is 75% of the rated load. Each probe collects magnetic field intensity data in the X, Y, and Z directions, and 600,000 sampling points are generated in each direction, forming a three-dimensional matrix data structure. After the acquisition is completed, all probe data are calibrated according to the spatial position to generate discrete magnetic field data on the surface of the housing containing position information, and the data format is [measurement point number, X coordinate, Y coordinate, Z coordinate, time point, magnetic field intensity in the X direction, magnetic field intensity in the Y direction, magnetic field intensity in the Z direction]. When performing three-axis component analysis on the discrete magnetic field data on the surface of the housing collected, first perform time-domain analysis on the magnetic field data in the X, Y, and Z directions of each measurement point, and calculate the mean value, standard deviation, maximum value, and minimum value. Then, convert the time-domain signal into a frequency-domain signal through fast Fourier transform, and analyze the amplitude and phase of each frequency component. For the frequency-domain signal, extract the first 10 main frequency components, and these components usually correspond to the characteristic frequencies of the mechanical components in the gearbox. The magnetic field data in the three directions are synthesized into the total magnetic field intensity, and the calculation formula is , where \(M_t\) represents the total magnetic field intensity, and \(M_x\), \(M_y\), and \(M_z\) represent the magnetic field intensities in the X, Y, and Z directions respectively. By analyzing the direction and magnitude of the total magnetic field intensity, the electromagnetic field leakage intensity of each measurement point is determined, with a numerical range between 5 μT and 60 μT, and the main direction of the magnetic field is determined. The analysis results of all measurement points are integrated to generate spatial electromagnetic field distribution data containing spatial coordinates and three-axis components of the magnetic field. A spatial coordinate system is established based on the three-dimensional CAD model of the gearbox, with the origin set at the center of the gearbox, the X-axis pointing forward of the gearbox, the Y-axis pointing to the right, and the Z-axis pointing upward. The 16 measured points are accurately positioned in this coordinate system, and the position accuracy of the measurement points is controlled within ±1 mm. The magnetic field inside the gearbox is deduced using the magnetic field inverse problem solving method. Specifically, in implementation, the finite element method is used to divide the internal space of the gearbox into 100,000 grid cells, and the side length of each cell does not exceed 2 mm. Based on the magnetic field intensity and direction measured on the surface, the internal magnetic field distribution is solved through Maxwell's equations. The magnetic permeability of the gearbox material (the relative magnetic permeability of steel material is taken as 100), as well as the geometric shapes and material properties of components such as gears and bearings, are considered during the solving process. Through iterative calculation (the number of iterations is 500 times, and the convergence threshold is set to 0.1%), the three-dimensional magnetic field distribution inside the gearbox is reconstructed, especially the magnetic field intensity distribution near the inner ring of the planet carrier bearing and the meshing line between the sun gear and the planet gears. The calculation results form internal equivalent magnetic field intensity cloud data, with a data accuracy reaching 1 μT. Based on the structural characteristics of the gearbox, the internal space is divided into key functional regions: the sun gear region, the planet gear region, the internal gear ring region, the planet carrier region, and each bearing region. Each region is further divided into multiple sub-regions. For example, the planet gear bearing region is divided into four sub-regions: the inner ring, the outer ring, the rolling elements, and the cage. Statistical analysis is performed on the magnetic field intensity data within each sub-region to calculate the average magnetic field intensity, standard deviation, maximum value, and minimum value. For the planet gear bearing raceway, the calculated average magnetic field intensity is 25 μT, and the peak magnetic field intensity is 45 μT; for the sun gear tooth surface, the average magnetic field intensity is 30 μT, and the peak magnetic field intensity is 55 μT; for the planet gear tooth surface, the average magnetic field intensity is 28 μT, and the peak magnetic field intensity is 50 μT. At the same time, the gradient distribution of the magnetic field intensity in space is analyzed to identify regions where the magnetic field intensity changes violently, and these regions are usually positions with strong electromagnetic disturbances. By comprehensively analyzing the magnetic field intensity distribution characteristics on the surfaces of key components, key component surface magnetic induction characteristic data are generated, and the data includes component name, position coordinates, average magnetic field intensity, peak magnetic field intensity, and the main direction of the magnetic field. The obtained bearing current characteristic sequences are combined with the kinematic parameters of the gearbox to analyze the relationship between the current frequency and the motion frequency of mechanical components. The kinematic parameters of the gearbox include: the rotational speed of the sun gear is 1500 rpm (corresponding frequency 25 Hz), the rotational speed of the planet gears is 428.6 rpm (corresponding frequency 7.14 Hz), and the rotational speed of the planet carrier is 150 rpm (corresponding frequency 2.5 Hz).Through harmonic analysis, the components related to these mechanical frequencies and their multiples in the bearing current are extracted. For the sun gear input bearing, the main electromagnetic excitation frequencies are 25 Hz, 50 Hz, and 75 Hz; for the carrier output bearing, the main electromagnetic excitation frequencies are 2.5 Hz, 5 Hz, 7.5 Hz, and 25 Hz; for the planet gear bearing, the main electromagnetic excitation frequencies are 7.14 Hz, 14.28 Hz, and 21.42 Hz. Calculate the energy distribution of each frequency component to evaluate the electromagnetic excitation intensity of different frequencies on each component. For the sun gear - planet gear meshing frequency (the calculation formula is the number of teeth of the sun gear multiplied by the rotational speed frequency of the sun gear, i.e., 25×25 Hz = 625 Hz), analyze the performance of this frequency and its multiples and sub - multiples in the current characteristic sequence to judge the electromagnetic excitation situation during the meshing process. Integrate the energy and distribution characteristics of each frequency component to generate potential electromagnetic excitation frequency data, including information such as frequency values, energy magnitudes, associated components, and excitation intensities. Establish an evaluation standard for the electromagnetic disturbance level, and divide the disturbance level into five levels: weak (0 - 10 μT), slight (10 - 30 μT), medium (30 - 50 μT), strong (50 - 80 μT), and intense (>80 μT). Combine the potential electromagnetic excitation frequency data with the surface magnetic induction characteristic data of key components to evaluate the electromagnetic disturbance level of each component in the gearbox. The evaluation process considers three key factors: magnetic field strength, frequency characteristics, and action time. For the tooth surface of the sun gear, the average magnetic field strength is 30 μT, mainly excited by the 25 Hz frequency, and is evaluated as a medium disturbance level; for the tooth surface of the planet gear, the average magnetic field strength is 28 μT, mainly excited by the 7.14 Hz and 25 Hz frequencies, and is evaluated as a medium disturbance level; for the raceway of the planet gear bearing, the average magnetic field strength is 25 μT, mainly excited by the 7.14 Hz frequency, and is evaluated as a slight disturbance level; for the carrier bearing, the average magnetic field strength is 35 μT, mainly excited by the 2.5 Hz frequency, and is evaluated as a medium disturbance level; for the sun gear input bearing, the average magnetic field strength is 45 μT, mainly excited by the 25 Hz frequency, and is evaluated as a medium disturbance level. Summarize the evaluation results to form internal electromagnetic disturbance snapshot data, including information such as component names, position coordinates, magnetic field strength, main excitation frequencies, disturbance levels, and potential impacts.

[0018] Preferably, in step S2, determining the main circulation path and branches of the current between the gear meshing pairs in the gearbox according to each bearing current characteristic sequence and estimating the current distribution ratio includes: Obtain the connection topology of the sun gear - planet gear - ring gear in the gearbox and the geometric constraint data of the planetary gear train; Extract the current values of each bearing according to each bearing current characteristic sequence; Based on the connection topology of the sun gear - planet gear - ring gear, conduct a conductive connection topology analysis on the current values of each bearing, and based on the geometric constraint data of the planetary gear train, identify the main current flow paths and branches between the gear meshing pairs to obtain the main current path data between the gears; among them, the gear meshing pairs include the sun gear - planet gear meshing pair and the planet gear - internal gear ring meshing pair; Set the number of equivalent conductive contact points and the contact resistance range of the bearings in the gearbox according to the main current path data between the gears to generate bearing shunt characteristic data; Based on the bearing shunt characteristic data, estimate the current distribution ratio of the sun gear - planet gear meshing pair and the planet gear - internal gear ring meshing pair through the main current path data between the gears to generate the estimated current share data of the meshing pair - bearing.

[0019] In the embodiments of the present invention, the connection topology of the sun gear - planet gear - ring gear is obtained from the gearbox design drawings, including that the number of teeth of the sun gear is 25, the number of teeth of the planet gear is 35, and the number of teeth of the internal gear ring is 95. The number of planet gears is 4, evenly distributed around the sun gear, and the angle between adjacent planet gears is 90 degrees. The sun gear forms a pair of meshing pairs with each planet gear, and each planet gear forms a pair of meshing pairs with the internal gear ring, totaling 8 pairs of meshing pairs. Record the geometric constraint data of the planetary gear train, including the center distance: the center distance from the sun gear to the planet gear is 75 mm, and the center distance from the planet gear to the internal gear ring is 125 mm; the diameter of the sun gear input shaft is 40 mm, and the diameter of the planet carrier output shaft is 60 mm; the diameter of the planet gear shaft is 25 mm; the bearing model of the sun gear is 6208, the bearing model of the planet carrier is 6212, and the bearing model of the planet gear is 6205. The gear material is 20CrMnTi, the heat treatment hardness is HRC58 - 62, and the tooth surface accuracy grade is 6. Analyze the frequencies in the characteristic sequence and compare the spectral characteristics at different bearing positions. For the current characteristic sequence of the sun gear input bearing, extract the current amplitudes of the main harmonic frequencies of 25 Hz, 50 Hz, and 75 Hz, which are 120 mA, 85 mA, and 40 mA respectively; for the current characteristic sequence of the planet carrier output bearing, extract the current amplitudes of the main harmonic frequencies of 25 Hz, 50 Hz, and 75 Hz, which are 80 mA, 60 mA, and 30 mA respectively; for the current characteristic sequences of the four planet gear bearings, extract the current amplitudes of the main harmonic frequencies of 25 Hz, 50 Hz, and 75 Hz respectively. The current amplitudes of planet gear 1 are 30 mA, 20 mA, and 10 mA, the current amplitudes of planet gear 2 are 28 mA, 19 mA, and 9 mA, the current amplitudes of planet gear 3 are 31 mA, 21 mA, and 11 mA, and the current amplitudes of planet gear 4 are 29 mA, 20 mA, and 10 mA. Calculate the effective current values of each bearing through time-domain integration. The effective current value of the sun gear input bearing is 150 mA, the effective current value of the planet carrier output bearing is 105 mA, and the effective current values of the four planet gear bearings are 38 mA, 35 mA, 39 mA, and 37 mA respectively. Establish a current flow network model based on the connection topology of the sun gear - planet gear - ring gear, regarding each component in the gearbox as a node and the gear meshing pair as a conductive path. In this model, the current enters from the sun gear input shaft, is shunted to each planet gear through the sun gear - planet gear meshing pair, then flows to the housing through the planet gear - internal gear ring meshing pair, and finally flows out through the planet carrier output shaft. Based on the measured current values of each bearing, calculate the current distribution between each node through network flow analysis.The analysis results show that the proportion of the 150 mA inflow current of the sun gear input bearing distributed to the four planet gears is 25%, 23%, 27%, and 25%, which are 37.5 mA, 34.5 mA, 40.5 mA, and 37.5 mA respectively; among the currents received by the planet gears, 80% flows through the planet gear-ring gear meshing pair to the housing, and 20% directly flows through the planet gear bearing to the planet carrier; the main current path is sun gear input shaft → sun gear → planet gear → ring gear → housing → planet carrier → output shaft, and the circulation proportion of the current on this path is about 75%. Calculate the number of equivalent conductive contact points according to the bearing type and size. For the sun gear input bearing (type 6208), the number of rolling elements is 9, and each rolling element forms one contact point with the inner and outer rings, with a total of 18 contact points. Considering the load distribution, the actual number of equivalent conductive contact points bearing the load is 5; for the planet carrier output bearing (type 6212), the number of rolling elements is 12, and the number of equivalent conductive contact points is 7; for the planet gear bearing (type 6205), the number of rolling elements is 8, and the number of equivalent conductive contact points is 4. The contact resistance range is calculated from the material resistivity, contact area, and lubricating oil film thickness: the contact resistance range of the sun gear input bearing is 15 - 25 ohms, the contact resistance range of the planet carrier output bearing is 10 - 18 ohms, and the contact resistance range of the planet gear bearing is 20 - 35 ohms. The number of contact points of the gear meshing pair depends on the contact line length and tooth width. The number of equivalent contact points of the sun gear-planet gear meshing pair is 8, and the contact resistance range is 8 - 15 ohms; the number of equivalent contact points of the planet gear-ring gear meshing pair is 10, and the contact resistance range is 6 - 12 ohms. Using the calculation principle of the parallel circuit, estimate the current distribution ratio of the sun gear-planet gear meshing pair and the planet gear-ring gear meshing pair based on the bearing shunt characteristic data. First, calculate the equivalent resistance of each component: the equivalent resistance of the sun gear input bearing is 20 ohms, the equivalent resistance of the planet carrier output bearing is 14 ohms, the equivalent resistance of the planet gear bearing is 28 ohms, the equivalent resistance of the sun gear-planet gear meshing pair is 12 ohms, and the equivalent resistance of the planet gear-ring gear meshing pair is 9 ohms. Based on these equivalent resistance values, calculate the distribution ratio of the 150 mA current flowing in from the sun gear input shaft on each path: the current share of the sun gear-planet gear 1 meshing pair is 38 mA (accounting for 25.3% of the total current), the current share of the sun gear-planet gear 2 meshing pair is 36 mA (accounting for 24.0% of the total current), the current share of the sun gear-planet gear 3 meshing pair is 39 mA (accounting for 26.0% of the total current), and the current share of the sun gear-planet gear 4 meshing pair is 37 mA (accounting for 24.7% of the total current). Among the currents received by the planet gears, the current share of the planet gear 1-ring gear meshing pair is 30.4 mA, and the current share of the planet gear 1 bearing is 7.6 mA; the current distribution of the remaining planet gears is estimated according to a similar ratio, and finally, the estimated current share data of the meshing pair-bearing is generated.

[0020] Preferably, the evaluation of electrical erosion damage to the estimated current share data of the meshing pair - bearing based on the internal electromagnetic disturbance snapshot data and the gearbox design parameters in step S2 includes: Set the critical electrical erosion damage threshold for the gear / bearing according to the gearbox design parameters; Extract the instantaneous effective conductive contact area of each meshing point and the conductive area of the bearing roller / raceway contact point according to the gearbox design parameters; Calculate the average current density of the tooth surface based on the estimated current share data of the meshing pair - bearing and the instantaneous effective conductive contact area of each meshing point to obtain the tooth surface meshing current density data; Estimate the bearing current density based on the estimated current share data of the meshing pair - bearing and the conductive area of the bearing roller / raceway contact point to obtain the bearing current density distribution range; Analyze the electro - thermal - mechanical disturbance characteristics of the tooth surface based on the internal electromagnetic disturbance snapshot data and the tooth surface meshing current density data to generate the electro - thermal - mechanical disturbance data of the tooth surface; Conduct an electrical erosion damage evaluation using the electro - thermal - mechanical disturbance data of the tooth surface and the bearing current density distribution range based on the critical electrical erosion damage threshold of the gear / bearing to generate the proportion of bearing - tooth surface electrical erosion damage.

[0021] In the embodiments of the present invention, based on the design parameters of the gearbox, the critical electro-erosion damage threshold is determined by combining the relationship model between current density and electro-erosion damage. For gears made of 20CrMnTi material with a surface hardness of HRC58 - 62, the critical current density threshold is obtained through an electro-erosion acceleration test. During the test, pulsed current is applied to the gear samples at different current densities for a duration of 500 hours, and the damage initiation point is determined through surface roughness change, microstructure analysis, and hardness testing. The test results show that the critical electro-erosion current density threshold for the gear tooth surface is 0.8 A / mm². When the value is lower than this, obvious electro-erosion damage will not occur on the tooth surface material. For bearings, based on the material (GCr15), heat treatment state (HRC60 - 65), and surface finishing process (grinding Ra0.4 μm) of different types of bearings, combined with the lubrication condition (ISOVG320 gear oil), the critical electro-erosion current density threshold for the bearing rolling elements / raceways is determined to be 0.6 A / mm². In addition, based on the analysis of long-term operation data, the time threshold for cumulative electro-erosion damage is determined to be 3000 hours. When the time exceeds this and the current density exceeds the critical value, significant electro-erosion damage will occur. The instantaneous effective conductive contact area of each meshing point is calculated based on the gear meshing theory and Hertz contact theory. For the sun gear - planet gear meshing pair, the gear module is 4 mm, the tooth width is 65 mm, the pressure angle is 20 degrees, and the gear accuracy grade is 6. Through the Hertz contact equation, the major axis of the contact ellipse for single-tooth meshing is 2.8 mm, the minor axis is 0.4 mm, and the instantaneous contact area for single-tooth meshing is 3.52 mm². Considering the contact ratio of 1.6, on average, 1.6 pairs of teeth are meshing simultaneously during the actual meshing process, and the total instantaneous effective contact area is 5.63 mm². For the planet gear - internal gear ring meshing pair, the major axis of the contact ellipse is 3.2 mm, the minor axis is 0.45 mm, the instantaneous contact area for single-tooth meshing is 4.52 mm², the contact ratio is 1.8, and the total instantaneous effective contact area is 8.14 mm². For the bearing contact points, according to the bearing model and load conditions, the area of each contact point is calculated using the Hertz contact theory: the major axis of the contact ellipse between the rolling elements and the inner / outer rings of the sun gear input bearing (type 6208) is 1.2 mm, the minor axis is 0.15 mm, and the area of a single contact point is 0.57 mm²; the contact point area of the planet carrier output bearing (type 6212) is 0.85 mm²; the contact point area of the planet gear bearing (type 6205) is 0.42 mm². Considering the load distribution, the actual number of contact points under load is 5, 7, and 4 respectively. Combining the estimated current share data of the meshing pair - bearing with the instantaneous effective conductive contact area of each meshing point, the average current density of the tooth surface is calculated. The calculation formula is , where \(J\) represents the current density (\(A / mm^2\)), \(I\) represents the current value (\(A\)), and \(A\) represents the contact area (\(mm^2\)). For the sun gear - planet gear 1 meshing pair, the estimated current share is \(38 mA\), the instantaneous effective contact area is \(5.63 mm^2\), and the calculated average current density on the tooth surface is \(0.0675 A / mm^2\); for the sun gear - planet gear 2 meshing pair, the estimated current share is \(36 mA\), the instantaneous effective contact area is \(5.63 mm^2\), and the calculated average current density on the tooth surface is \(0.0639 A / mm^2\); for the sun gear - planet gear 3 meshing pair, the estimated current share is \(39 mA\), the instantaneous effective contact area is \(5.63 mm^2\), and the calculated average current density on the tooth surface is \(0.0693 A / mm^2\); for the sun gear - planet gear 4 meshing pair, the estimated current share is \(37 mA\), the instantaneous effective contact area is \(5.63 mm^2\), and the calculated average current density on the tooth surface is \(0.0657 A / mm^2\). For the planet gear - internal gear ring meshing pair, the calculated current density of the planet gear 1 - internal gear ring meshing pair is \(0.0373 A / mm^2\), the current density of the planet gear 2 - internal gear ring meshing pair is \(0.0353 A / mm^2\), the current density of the planet gear 3 - internal gear ring meshing pair is \(0.0381 A / mm^2\), and the current density of the planet gear 4 - internal gear ring meshing pair is \(0.0362 A / mm^2\). These data are summarized to form the tooth surface meshing current density data. According to the estimated current share data of the meshing pair - bearing and the conductive area of the contact points between the bearing rollers / raceways, the bearing current density is calculated. For the sun gear input bearing, the estimated current share is \(150 mA\), the number of effective contact points is 5, the area of each contact point is \(0.57 mm^2\), the total contact area is \(2.85 mm^2\), and the calculated average current density is \(0.0526 A / mm^2\). Considering the uneven load distribution, the current density actually shows an uneven distribution. The maximum contact point current density is 1.8 times the average value, that is, \(0.0947 A / mm^2\), and the minimum contact point current density is 0.5 times the average value, that is, \(0.0263 A / mm^2\), forming a current density distribution range of \([0.0263 A / mm^2, 0.0947 A / mm^2]\). For the planet carrier output bearing, the estimated current share is \(105 mA\), the number of effective contact points is 7, the area of each contact point is \(0.85 mm^2\), the total contact area is \(5.95 mm^2\), the calculated average current density is \(0.0176 A / mm^2\), and the current density distribution range is \([0.0088 A / mm^2, 0.0317 A / mm^2]\).For the planetary gear bearings, the estimated current shares are 7.6 mA, 7.2 mA, 7.9 mA, and 7.4 mA respectively. The number of effective contact points is 4, the area of each contact point is 0.42 mm², and the total contact area is 1.68 mm². The average current densities of the four planetary gear bearings are calculated to be 0.0045 A / mm², 0.0043 A / mm², 0.0047 A / mm², and 0.0044 A / mm² respectively, and the current density distribution range is [0.0022 A / mm², 0.0085 A / mm²]. The internal electromagnetic disturbance snapshot data is combined with the tooth surface meshing current density data to analyze the tooth surface electro-thermal-force disturbance characteristics. The electro-thermal analysis uses the Joule heat model, and the calculation formula is as follows. , where Q represents the heat per unit volume (J / mm³), ρ represents the material resistivity (Ω·mm), J represents the current density (A / mm²), and t represents the current application time (s). For the 20CrMnTi material gear, the resistivity is 0.22 Ω·mm, the average current density of the sun gear-planetary gear meshing pair is 0.0666 A / mm², and the meshing time is 0.016 s (calculated based on the gear speed and meshing angle). The heat generated by a single meshing is calculated to be . Considering the long-term operation of the gearbox, the cumulative heat will cause local temperature rise. The temperature rise in the meshing area is calculated to be 2.8 °C through the heat conduction model. The mechanical disturbance analysis is based on the magnetic force model, and the calculation formula is , where F represents the force (N), B represents the magnetic induction intensity (T), I represents the current (A), and L represents the conductor length (mm). According to the internal electromagnetic disturbance snapshot data, the average magnetic field intensity on the tooth surface of the sun gear is 30 μT, the current is 38 mA, and the contact line length is 65 mm. The additional electromagnetic force is calculated to be , which is almost negligible compared to the normal meshing load (about 1500 N). Combining the electro-thermal and mechanical disturbance analysis results, electro-thermal-force disturbance data of the tooth surface is generated, including the temperature rise value, electromagnetic force value, and comprehensive disturbance level of each meshing pair. Based on the previously set critical electrical erosion damage thresholds (0.8 A / mm² for gears and 0.6 A / mm² for bearings), combined with the tooth surface electro-thermal-force disturbance data and the bearing current density distribution range, the electrical erosion damage assessment is carried out. The assessment uses the electrical erosion damage rate model, and the calculation formula is , where D represents the damage rate (dimensionless, range 0 - 1), k is the material constant (experimentally determined to be 0.0015), J is the actual current density (A / mm²), $J$ is the critical current density ($A / mm^2$), $a$ is the exponent (experimentally determined to be 2.5), and $t$ is the cumulative time ($h$). For the sun gear - planet gear meshing pair, the average current density is $0.0666 A / mm^2$, the critical current density is $0.8 A / mm^2$. Assuming the cumulative operating time is 5000 hours, the calculated damage rate is $0.0055$, accounting for $0.55\%$ of the critical damage. For the planet gear - internal gear ring meshing pair, the average current density is $0.0367 A / mm^2$, and the calculated damage rate is $0.0012$, accounting for $0.12\%$ of the critical damage. For the sun gear input bearing, the maximum current density is $0.0947 A / mm^2$, the critical current density is $0.6 A / mm^2$, and the calculated damage rate is $0.0385$, accounting for $3.85\%$ of the critical damage. For the planet carrier output bearing, the maximum current density is $0.0317 A / mm^2$, and the calculated damage rate is $0.0024$, accounting for $0.24\%$ of the critical damage. For the planet gear bearing, the maximum current density is $0.0085 A / mm^2$, and the calculated damage rate is $0.00005$, accounting for $0.005\%$ of the critical damage. The comprehensive evaluation results show that at the current current level, the risk of electrical erosion damage to the sun gear input bearing is the highest, but it is still far below the critical damage threshold, and the proportion of electrical erosion damage to each component of the gearbox is within the safe range.

[0022] Especially importantly, based on the snapshot data of internal electromagnetic disturbances and the analysis of the tooth surface meshing current density data, the characteristics of the electrothermal - mechanical disturbances on the tooth surface are as follows: Extract the conductivity of the tooth surface material through the gearbox design parameters, and analyze the instantaneous Joule heat power in the meshing area according to the tooth surface meshing current density data to obtain the Joule heat generation rate in the meshing area; Extract the thermal conductivity, specific heat capacity of the gear material and the heat dissipation boundary conditions of the gear body through the gearbox design parameters, and estimate the instantaneous local temperature rise in the tooth surface contact area according to the Joule heat generation rate in the meshing area to obtain the tooth surface instantaneous temperature rise distribution data; Extract the thermal expansion coefficient and elastic modulus of the gear material through the gearbox design parameters, and calculate the corresponding local thermal stress on the tooth surface according to the tooth surface instantaneous temperature rise distribution data to generate the local thermal stress data on the tooth surface.

[0023] Based on the snapshot data of internal electromagnetic disturbances and the tooth surface meshing current density data, preliminarily estimate the electromagnetic force acting on the gear through the Lorentz force calculation formula, and decompose it into the change amount of the ratio of the axial force / radial force on the gear to obtain the change amount of the electromagnetic induced additional force ratio; Arrange the maximum thermal stress value in the local thermal stress data on the tooth surface, the maximum current density value in the tooth surface meshing current density data, and the change amount of the electromagnetic induced additional force ratio in time - series characteristics to generate the electrothermal - mechanical disturbance data on the tooth surface.

[0024] In the embodiment of the present invention, the gear material is extracted from the gearbox design parameters as 20CrMnTi alloy steel, and the conductivity of this material in the heat treatment state (quenching and tempering + carburizing and quenching, HRC58 - 62) is obtained from the material handbook as (equivalent to resistivity ). The conductivity is converted to the value in the International System of Units as . According to the previously calculated tooth surface meshing current density data, the average current density of the sun gear - planet gear 1 meshing pair is 0.0675 A / mm², and when converted to the International System of Units, it is . The calculation formula for the joule heat power density is , where represents the power density (W / m³), represents the current density (A / m²), represents the conductivity ( ). Substituting the values for calculation, the instantaneous joule heat power density of the sun gear - planet gear 1 meshing pair is . The volume of the meshing area is the contact ellipse area (3.52 mm²) multiplied by the effective conduction depth (estimated as the surface hardening layer depth of the material, 0.8 mm), that is . Therefore, the total instantaneous joule heat power in the meshing area is . Using the same method to calculate the instantaneous joule heat power of other meshing pairs, a complete data table of the joule heat generation rate in the meshing area is formed, including the instantaneous heat generation rates of all meshing pairs at different meshing positions. The thermal conductivity of 20CrMnTi alloy steel is extracted from the gearbox design parameters as 42 W / (m·K), the density is 7850 kg / m³, and the specific heat capacity is 460 J / (kg·K). The heat dissipation boundary condition of the gear body is: the gear is immersed in ISOVG320 gear oil, the oil temperature is 60 °C, and the heat convection coefficient is 800 W / (m²·K). Based on the instantaneous heat conduction model, the calculation formula for the local temperature rise of the tooth surface is , where ΔT represents the temperature rise (K), q represents the heat power (W), t represents the heat generation time (s), ρ represents the material density (kg / m³), c represents the specific heat capacity (J / (kg·K)), and V represents the heated volume (m³). The instantaneous joule heat power of the sun gear - planet gear 1 meshing pair is , the single - meshing contact time is 0.016 s (calculated based on the gear speed of 1500 rpm, the number of teeth of 25, and the meshing angle of 20°), and the heated volume is , substituting into the formula, the instantaneous temperature rise generated by a single meshing is calculated to be 0.0021 K. Considering the heat accumulation effect, the temperature change during continuous meshing is calculated through the numerical solution of the heat conduction equation. Using the finite difference method, the time step is 0.001 s, the spatial grid size is 0.1 mm, and the calculation duration is 10 s. The calculation results show that under steady-state conditions, the maximum temperature rise in the tooth surface contact area is 2.8 K, and the average temperature rise is 1.5 K. The temperature rise distribution presents an ellipse, with the highest temperature at the center and decreasing outward, forming the tooth surface instantaneous temperature rise distribution data. The thermal expansion coefficient of 20CrMnTi alloy steel is extracted from the gearbox design parameters as , the elastic modulus is 210 GPa, and the Poisson's ratio is 0.3. Based on the thermoelastic theory, the three-dimensional stress-strain relationship is used for thermal stress calculation. Due to the non-uniform temperature distribution, the temperature gradient effect needs to be considered in thermal stress calculation. A rectangular coordinate system is established, with the center of the contact ellipse as the origin, the x-axis along the major axis direction of the contact ellipse, the y-axis along the minor axis direction, and the z-axis perpendicular to the contact surface. The temperature distribution function is expressed as , where represents the maximum temperature rise (2.8 K), and a, b, and c are the characteristic lengths of the temperature distribution in the three directions (1.4 mm, 0.2 mm, and 0.4 mm respectively). The calculation formula for the thermal stress tensor is , where G represents the shear modulus (G = E / (2(1 + ν)) = 80.8 GPa), α represents the thermal expansion coefficient, ΔT represents the temperature rise, represents the Kronecker function, ν represents the Poisson's ratio, and represent the displacement gradient. By solving the displacement equation, the local thermal stress distribution on the tooth surface is calculated. The calculation results show that the maximum thermal stress appears at the center of the contact ellipse, with a value of 25.2 MPa, presenting a biaxial tensile state. The stress distribution presents an ellipse and decreases as the distance from the contact center increases. The stress distribution data is organized into a three-dimensional matrix form, including the three principal stress values of each grid point, forming the local thermal stress data on the tooth surface. Based on the magnetic field intensity distribution in the internal electromagnetic disturbance snapshot data and the tooth surface meshing current density data, the electromagnetic force acting on the gear is estimated through the Lorentz force calculation formula. The Lorentz force calculation formula is , where F represents the force (N), J represents the current density vector (A / m²), B represents the magnetic induction intensity vector (T), and dV represents the volume element (m³). For the sun gear - planet gear 1 meshing pair, the average current density on the tooth surface is , the magnetic field intensity is , the current direction is along the tooth surface tangential direction, and the magnetic field direction is approximately perpendicular to the tooth surface. The volume of the contact area is , substituting into the calculation, the magnitude of the electromagnetic force is . This force is decomposed into axial and radial components: the axial component , radial component , where θ represents the pressure angle (20°). The normal gear meshing force is 1500 N, among which the axial component is 513 N and the radial component is 1410 N. Calculate the change in the axial force / radial force ratio caused by the electromagnetic force: the original ratio is 513 / 1410 = 0.3638, and the ratio after adding the electromagnetic force is , and the change amount is , which is almost negligible. Using the same method to calculate the change amount of the electromagnetic-induced additional force ratio of other meshing pairs, the results all show that the influence of the electromagnetic force on the gear meshing force ratio is extremely small. Based on the actual operating conditions of the gearbox, record the data per minute during the 60-minute operation process to form a time-series feature dataset. For the sun gear - planet gear 1 meshing pair, extract the maximum thermal stress value in the local thermal stress data of the tooth surface to form a time series {25.2, 25.3, 25.1, 25.4,..., 25.2} MPa, with a total of 60 data points; extract the maximum current density value in the tooth surface meshing current density data to form a time series {0.0675, 0.0678, 0.0672, 0.0680,..., 0.0675} A / mm², with a total of 60 data points; extract the change amount of the electromagnetic-induced additional force ratio to form a time series , with a total of 60 data points. Extract the statistical features of these three time series, and calculate the mean value, standard deviation, maximum value, minimum value, and coefficient of variation. The results show that the mean value of the maximum thermal stress is 25.25 MPa, the standard deviation is 0.12 MPa, and the coefficient of variation is 0.0048; the mean value of the maximum current density is 0.0676 A / mm², the standard deviation is 0.0003 A / mm², and the coefficient of variation is 0.0044; the mean value of the change amount of the electromagnetic-induced additional force ratio is , the standard deviation is , and the coefficient of variation is 0.0312. Combine these statistical features with the original time series data to form the tooth surface electro-thermal-force disturbance data of the sun gear - planet gear 1 meshing pair. Use the same method to process the data of other meshing pairs, and finally generate a complete tooth surface electro-thermal-force disturbance dataset.

[0025] Preferably, the electro-erosion damage assessment based on the critical electro-erosion damage threshold of the gear / bearing using the tooth surface electro-thermal-force disturbance data and the bearing current density distribution range includes: Install an ultrasonic oil film thickness sensor in the lubricating oil channel near the meshing area of the planet gear in the gearbox to measure the minimum oil film thickness of the lubricating oil channel in real time and obtain the real-time sampling value of the oil film thickness; Calculate the minimum oil film thickness ratio of the critical area according to the real-time sampling value of the oil film thickness; Based on the electro-thermal-force perturbation data of the tooth surface, analyze the lubrication state of the current cycle for the minimum oil film thickness ratio and the dynamic monitoring curve of the oil fluid resistivity in the critical region, and conduct an electro-erosion risk assessment for the meshing region to generate the severity index of the meshing region working conditions; Based on the tooth surface meshing current density data and the severity index of the meshing region working conditions, estimate the increment of the equivalent micro electro-erosion pit density on the tooth surface during the current monitoring cycle by using the preset correlation table of the electro-erosion rate of the gear material; Estimate the increment of the equivalent micro electro-erosion pit density of the bearing raceway generated by the bearing during the current monitoring cycle according to the maximum current density estimated value in the bearing current density distribution interval; Perform periodic electro-erosion pit density accumulation on the increment of the equivalent micro electro-erosion pit density of the tooth surface and the increment of the equivalent micro electro-erosion pit density of the bearing raceway, and divide them by the corresponding critical electro-erosion damage thresholds of the gear / bearing respectively to obtain the electro-erosion damage ratio of the bearing-tooth surface.

[0026] In the embodiment of the present invention, an ultrasonic oil film thickness sensor with the model number UT-8000 is installed in the lubricating oil channel near the meshing area of the planetary gear in the gearbox. The diameter of the sensor is 8 mm, the measurement range is 0.1 - 500 μm, and the accuracy is ±0.05 μm. The installation position of the sensor is on the oil channel wall surface 20 mm below the meshing point of each planetary gear and the internal gear ring. The sensor probe is flush with the inner wall of the oil channel, and the surface of the probe is polished, and the surface roughness is controlled within Ra0.2 μm. The emission frequency of the sensor is 10 MHz, the pulse repetition frequency is 1000 Hz, and the longitudinal wave ultrasonic measurement principle is adopted. The sensor is installed on the gearbox housing through a special sealing joint, and the M12×1.5 thread connection is used, and the torque is controlled at 25 N·m. The sensor signal is connected to an ultrasonic oil film measuring instrument with the model number UM-2000 through a shielded cable. The sampling frequency is set to 100 Hz, the duration of each sampling is 0.1 ms, and continuous sampling is carried out for 60 minutes to form the time series data of the oil film thickness. The data recording format is [timestamp (s), oil film thickness (μm)]. The measured data is processed by digital filtering, and the filtering bandwidth is 10 - 1000 Hz to eliminate the influence of high-frequency noise. Based on the real-time sampling value of the oil film thickness, calculate the minimum oil film thickness ratio in the critical region through the elastohydrodynamic lubrication theory. The calculation formula is , where λ represents the minimum oil film thickness ratio (dimensionless), represents the measured minimum oil film thickness (μm), represents the arithmetic mean roughness of the gear tooth surface (μm), represents the arithmetic mean roughness of the internal gear ring tooth surface (μm). Extract the arithmetic mean roughness of the gear tooth surface = 0.4 μm, and the arithmetic mean roughness of the internal gear ring tooth surface = 0.5 μm, substitute into the formula to calculate and obtain = 0.64 μm. Taking the planet gear 1 as an example, the minimum oil film thickness measured by the ultrasonic sensor is 2.8 μm, and the calculated minimum oil film thickness ratio λ = 2.8 / 0.64 = 4.38. For all planet gears, the corresponding minimum oil film thickness ratios are calculated respectively. The minimum oil film thickness ratio of planet gear 2 is 4.22, the minimum oil film thickness ratio of planet gear 3 is 4.53, and the minimum oil film thickness ratio of planet gear 4 is 4.31. Based on the elastohydrodynamic lubrication theory, λ < 1 indicates boundary lubrication, 1 ≤ λ < 3 indicates mixed lubrication, and λ ≥ 3 indicates full fluid lubrication. Therefore, all the current planet gears are in the full fluid lubrication state when they exit the meshing zone. Based on the previously obtained tooth surface electrothermal-force disturbance data, the lubrication state analysis is carried out in combination with the minimum oil film thickness ratio in the critical region. First, the dynamic monitoring data of the oil resistivity is extracted from the gearbox monitoring system. The resistivity of the current ISOVG320 gear oil is , and it is monitored in real time through an on-line oil monitor. The tooth surface electrothermal-force disturbance data shows that the mean value of the maximum thermal stress of the sun gear-planet gear 1 meshing pair is 25.25 MPa, and the mean value of the maximum current density is 0.0676 A / mm². Combining these data with the minimum oil film thickness ratio λ = 4.38, a lubrication state evaluation model is constructed. The evaluation model adopts the weighted factor method, and the calculation formula is , where RI represents the severity index of the meshing zone working condition (dimensionless), λ represents the actual minimum oil film thickness ratio, represents the reference minimum oil film thickness ratio (the value is 3.0), J represents the actual current density (A / mm²), represents the reference current density (the value is 0.05 A / mm²), σ represents the actual thermal stress (MPa), represents the reference thermal stress (the value is 20 MPa), They are weight coefficients (determined through experiments to be 0.5, 0.3, and 0.2 respectively). Substituting the values into the calculation, the working condition severity index of the sun gear - planet gear 1 meshing pair is 0.63. Using the same method to calculate the working condition severity indices of other meshing pairs, the value for planet gear 2 - internal gear ring is 0.65, for planet gear 3 - internal gear ring is 0.60, and for planet gear 4 - internal gear ring is 0.62. The preset correlation table of gear material electro - erosion rate is obtained through laboratory accelerated electro - erosion tests. During the test, current is applied to 20CrMnTi gear material samples under different current densities (0.01 - 1 A / mm²) and different lubrication conditions (oil film thickness ratio 1 - 10) for a duration of 100 hours. Then, the number and size of micro - electro - erosion pits generated on the surface are observed and counted through a microscope, and a relationship model between electro - erosion pit density, current density, and working condition severity index is established. The data structure of the correlation table is [current density (A / mm²), working condition severity index, electro - erosion pit density increment (number / mm²·h)]. For example, [0.05, 0.5, 0.8] means that under the condition of a current density of 0.05 A / mm² and a working condition severity index of 0.5, 0.8 micro - electro - erosion pits are generated per square millimeter per hour. The electro - erosion pit density increment under the current condition is obtained through interpolation calculation. For the sun gear - planet gear 1 meshing pair, the current density is 0.0676 A / mm² and the working condition severity index is 0.63. Through bilinear interpolation, the electro - erosion pit density increment is calculated to be 1.25 number / mm²·h. The current monitoring period is 60 minutes, so the equivalent micro - electro - erosion pit density increment on the tooth surface of this meshing pair within this period is 1.25 number / mm²·h × 1 h = 1.25 number / mm². Using the same method to calculate the electro - erosion pit density increments of other meshing pairs: for planet gear 2 - internal gear ring is 1.30 number / mm², for planet gear 3 - internal gear ring is 1.20 number / mm², and for planet gear 4 - internal gear ring is 1.23 number / mm². Extract the maximum current density estimated values from the previously calculated bearing current density distribution intervals: for the sun gear input bearing is 0.0947 A / mm², for the planet carrier output bearing is 0.0317 A / mm², and for the planet gear bearing is 0.0085 A / mm². The equivalent micro - electro - erosion pit density increment of the bearing raceway is calculated through the bearing material electro - erosion model, which is established based on the electro - erosion characteristic tests of GCr15 bearing steel. In the model, the formula for calculating the electro - erosion pit density increment is , where N represents the electro - erosion pit density increment (number / mm²), k represents the material constant (determined through experiments to be 25), J represents the current density (A / mm²), α represents the exponent (determined through experiments to be 1.8), t represents the time (h), and f(λ) represents the lubrication coefficient (a function related to the minimum oil film thickness ratio, For the sun gear input bearing, the maximum current density is 0.0947 A / mm², the lubrication coefficient f(λ)=exp(-0.5×4.38)=0.114, the monitoring period is 1 hour. Substituting these values into the formula, the increment of the electric erosion pit density is calculated as 25×(0.0947)^1.8×1×0.114 = 0.235 pits / mm². For the planet carrier output bearing, the maximum current density is 0.0317 A / mm², with the same lubrication coefficient, and the calculated increment of the electric erosion pit density is 0.031 pits / mm². For the planet gear bearing, the maximum current density is 0.0085 A / mm², and the calculated increment of the electric erosion pit density is 0.002 pits / mm². The accumulation of the electric erosion pit density is realized by a loop-updated accumulator. The initial value of the accumulator is set to zero. After each monitoring period ends, the increment of the electric erosion pit density in the current period is added to the accumulator. Specifically, a data structure [component name, cumulative operating time (h), cumulative electric erosion pit density (pits / mm²)] is established to record the cumulative situation of the electric erosion damage of each component. Taking the sun gear - planet gear 1 meshing pair as an example, assuming the current cumulative operating time is 1000 hours, the previously accumulated electric erosion pit density is 1250 pits / mm², and the increment in this period is 1.25 pits / mm². The updated cumulative electric erosion pit density is 1251.25 pits / mm². For the sun gear input bearing, assuming the current cumulative operating time is 1000 hours, the previously accumulated electric erosion pit density is 200 pits / mm², and the increment in this period is 0.235 pits / mm². The updated cumulative electric erosion pit density is 200.235 pits / mm². The critical electric erosion damage thresholds for gears obtained from material tests are 2000 pits / mm², and for bearings are 500 pits / mm². Calculate the damage ratio: The electric erosion damage ratio of the sun gear - planet gear 1 meshing pair is 1251.25 / 2000 = 0.6256 (62.56%), and the electric erosion damage ratio of the sun gear input bearing is 200.235 / 500 = 0.4005 (40.05%). Using the same method to calculate the electric erosion damage ratios of other components: planet gear 2 - internal gear ring is 62.87%, planet gear 3 - internal gear ring is 61.10%, planet gear 4 - internal gear ring is 61.54%, planet carrier output bearing is 6.23%, planet gear bearing is 0.41%. Generate a radar chart of the electric erosion damage ratio to visually display the severity of damage to each component and predict the remaining time for each component to reach the critical damage threshold under the current operating conditions.

[0027] Preferably, based on the tooth surface electro-thermal-force disturbance data, analyze the lubrication state of the current period for the minimum oil film thickness ratio in the critical region and the dynamic monitoring curve of the oil resistivity, and conduct an electro-erosion risk assessment in the meshing zone, including: When the minimum oil film thickness ratio in the critical region continuously exceeds 2.0, or the maximum current density value in the electro-thermal-mechanical disturbance data of the tooth surface is lower than 0.05 A / mm², the boundary lubrication coefficient is set to a high value, and the electro-erosion risk level is set to low, indicating good lubrication, and low-risk lubrication-electro-erosion state data is generated; When the minimum oil film thickness ratio in the critical region is between 1.0 and 2.0, and the maximum current density value in the electro-thermal-mechanical disturbance data of the tooth surface is higher than 0.1 A / mm², the boundary lubrication coefficient is set to a medium value, and the electro-erosion risk level is set to medium, and medium-risk lubrication-electro-erosion state data is generated; When the minimum oil film thickness ratio in the critical region is less than 1.0, the boundary lubrication coefficient is set to a low value, and the electro-erosion risk level is set to high, and high-risk lubrication-electro-erosion state data is generated; Based on the low-risk lubrication-electro-erosion state data, medium-risk lubrication-electro-erosion state data, and high-risk lubrication-electro-erosion state data, the severity weighted index of the current meshing zone is quantified through the maximum thermal stress value and the change amount of the ratio of the electromagnetic-induced additional force in the electro-thermal-mechanical disturbance data of the tooth surface, and the severity index of the meshing zone working condition is generated.

[0028] In the embodiment of the present invention, the data recorded by the real-time monitoring system shows that the minimum oil film thickness ratio in the critical region of the planet gear 1 is 4.38, continuously exceeding the threshold of 2.0 for 120 minutes, and at the same time, the maximum current density value in the electro-thermal-mechanical disturbance data of the tooth surface is 0.0676 A / mm². Based on the preset judgment logic, the system sets the boundary lubrication coefficient to 0.9 (high value, range 0-1), indicating good lubrication state. The electro-erosion risk assessment module sets the risk level to 1 (low risk, range 1-5). The data processing unit generates low-risk lubrication-electro-erosion state data, and the data structure is [bearing / meshing pair ID, timestamp, minimum oil film thickness ratio, maximum current density, boundary lubrication coefficient, risk level]. For the planet gears 2, 3, and 4, since the minimum oil film thickness ratios are all greater than 2.0 (4.22, 4.53, 4.31 respectively), low-risk lubrication-electro-erosion state data is also generated. The system stores these data in the monitoring database and at the same time displays a green indicator light on the monitoring interface to indicate the current good lubrication state. The low-risk lubrication-electro-erosion state data also includes the oil fluid resistivity of Record. During the simulated high-load condition test, the minimum oil film thickness ratio in the critical area of the planetary gear 1 dropped to 1.8, which is within the medium lubrication range of 1.0 to 2.0 and lasted for 30 minutes. Meanwhile, the electro-thermal-mechanical disturbance data of the tooth surface showed that the maximum current density value increased to 0.12 A / mm², exceeding the threshold of 0.1 A / mm². According to the preset judgment criteria, the system set the boundary lubrication coefficient to 0.5 (median, range 0 - 1), indicating that the lubrication state is at a medium level. The electro-erosion risk assessment module set the risk level to 3 (medium risk, range 1 - 5). The data processing unit generated medium-risk lubrication-electro-erosion state data, and the data structure is [bearing / mesh pair ID, timestamp, minimum oil film thickness ratio, maximum current density, boundary lubrication coefficient, risk level, oil resistivity]. At this time, the oil resistivity decreased slightly to , indicating a slight deterioration of the oil properties. The system also generated medium-risk lubrication-electro-erosion state data for other planetary gears (such as planetary gear 2 with a minimum oil film thickness ratio of 1.7 and a maximum current density of 0.115 A / mm²). The monitoring interface showed a yellow warning light, indicating that the lubrication state is at a relatively high risk level. In this medium-risk state, the system increased the data acquisition frequency from the regular once every 60 seconds to once every 15 seconds. During the extreme condition test, the minimum oil film thickness ratio in the critical area of the planetary gear 1 dropped sharply to 0.85, below the critical value of 1.0, and lasted for 10 minutes, indicating that the gear meshing area has entered the boundary lubrication state. The electro-thermal-mechanical disturbance data of the tooth surface showed that the maximum current density value further increased to 0.18 A / mm². The system immediately set the boundary lubrication coefficient to 0.2 (low value, range 0 - 1), indicating that the lubrication state is at a dangerous level. The electro-erosion risk assessment module set the risk level to 5 (high risk, range 1 - 5). The data processing unit generated high-risk lubrication-electro-erosion state data, and the data structure is [bearing / mesh pair ID, timestamp, minimum oil film thickness ratio, maximum current density, boundary lubrication coefficient, risk level, oil resistivity, temperature]. The additional parameters recorded at this time included the oil resistivity dropped to , and the oil temperature increased to 75 °C. The system also generated high-risk lubrication-electro-erosion state data for other planetary gears (the minimum oil film thickness ratio of planetary gear 2 is 0.88, planetary gear 3 is 0.90, and planetary gear 4 is 0.87). The monitoring interface showed a red alarm light and triggered an audible alarm signal. The system entered the high-frequency data acquisition mode, and the sampling frequency increased to once every 5 seconds. At the same time, the magnetic field neutralization device was started to try to reduce the current density in the gear meshing area. Calculate the severity index of the meshing area working condition by combining the key parameters in the electro-thermal-mechanical disturbance data of the tooth surface. The calculation formula is , where WI represents the severity index of the meshing area working condition (dimensionless, range 0 - 10), BL represents the boundary lubrication coefficient (0.9, 0.5, 0.2 for low, medium, and high risk states respectively), σ represents the maximum thermal stress value (MPa), represents the reference thermal stress value (taking 20 MPa), represents the change amount ratio of the electromagnetic induced additional force, represents the reference change amount (taking ), represents the minimum oil film thickness ratio, represents the reference oil film thickness ratio (taking 2.0), α, β, γ, δ represent the weight coefficients (determined to be 0.4, 0.3, 0.1, 0.2 through regression analysis). For the planet gear 1 under normal working conditions (low-risk state), σ = 25.25 MPa, , λ = 4.38, and 0.87 is calculated. For the medium-risk state, WI = 3.25; for the high-risk state, WI = 7.83. The system stores these severity index values in the database and sets different maintenance warning thresholds according to the index size: WI < 3 is the normal operation range, 3 ≤ WI < 6 is the warning range, and WI ≥ 6 is the dangerous range, and maintenance measures need to be taken immediately.

[0029] Preferably, step S3 includes the following steps: Step S31: Install high-bandwidth torque sensors at the input shaft flange and output shaft spline of the gearbox respectively, synchronously collect the dynamic signals of the input and output torques, and obtain the double-end torque time domain sequence; Step S32: Install triaxial high-frequency acceleration sensors at the planet carrier bearing seat and sun gear bearing seat of the gearbox, synchronously collect multi-point and multi-direction vibration signals, and obtain multi-channel vibration data; Step S33: Extract the amplitude and phase of the mechanical load harmonic torque component from the double-end torque time domain sequence, and generate the harmonic torque component spectrum; Step S34: Perform spectral analysis on the multi-channel vibration data, and screen out the electromagnetic excitation components whose corresponding vibration response amplitudes exceed the preset noise threshold through the potential electromagnetic excitation frequency data in the internal electromagnetic disturbance snapshot data, and obtain the effective electromagnetic vibration response frequency points; Step S35: Identify the high-risk vibration coupling components through the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points, and generate the high-risk coupling vibration data of each component; Step S36: Analyze the contact stress history of the gearbox according to the harmonic torque component spectrum, and enhance the coupling vibration by using the high-risk coupling vibration data of each component to generate the enhanced coupling vibration stress history; Step S37: Calculate the component fatigue life reduction coefficient according to the bearing-to-tooth surface electrical erosion damage ratio, and perform linear damage accumulation processing according to the enhanced coupling vibration stress history to obtain the fatigue damage contribution value of each component in the cycle.

[0030] In the embodiment of the present invention, a high-bandwidth torque sensor with model TM-5000 is installed at the input shaft flange of the gearbox. The rated range is 5000 N·m, the accuracy class is 0.1 level, and the frequency response range is 0 - 5 kHz. The sensor is installed by the standard flange connection method, using 8 high-strength bolts of M12×1.5, and the bolt torque is controlled at 85 N·m. A torque sensor with model TM-8000 is installed at the spline of the output shaft. The rated range is 8000 N·m, and it is fixed by the coaxial spline connection method. The connection surface is smeared with molybdenum-based grease to reduce contact friction. The two sensors are respectively connected to the high-speed data acquisition system through the signal conditioning unit. The acquisition card model is NI-9234, the sampling frequency is set to 20 kHz, the acquisition accuracy is 24 bits, and the voltage range is ±5V. The data acquisition duration is 60 seconds. The synchronous trigger signal is provided by the photoelectric encoder. After the two-channel torque signals are processed by the low-pass filter (cutoff frequency 5 kHz), a double-ended torque time-domain sequence is formed. The data storage format is [time (s), input torque (N·m), output torque (N·m)]. Four triaxial high-frequency acceleration sensors with model PCB-356A33 are installed at the planet carrier bearing seat of the gearbox. The sensor sensitivity is 100 mV / g, the measurement range is ±50g, and the frequency response is 0.5 - 10 kHz. The sensors are fixed on the pre-machined plane on the outer surface of the bearing seat by special screws (M5×0.8), and the installation torque is controlled at 5 N·m. The installation surface is smeared with thermal conductive silicone grease to improve the thermal coupling between the sensor and the installation surface. Two sensors of the same model are installed at the sun gear bearing seat, arranged on both sides of the bearing seat, respectively monitoring the axial and radial vibrations. Each sensor provides vibration signals in three directions of X, Y, and Z, totaling 18 vibration signal channels. The signals are connected to the multi-channel data acquisition system with model DAS-8500 through shielded cables. The sampling frequency is set to 25.6 kHz, and each channel has an independent A / D conversion with a resolution of 16 bits. During the data acquisition process, the gearbox operates under stable working conditions, the input speed is 1500 rpm, and the load is 75% of the rated load. The acquired vibration signals are processed by band-pass filtering (20 Hz - 10 kHz) to form a multi-channel vibration data matrix. The data structure is [time point, sensor 1-X, sensor 1-Y, sensor 1-Z,..., sensor 6-Z]. The fast Fourier transform (FFT) is applied to the obtained double-ended torque time-domain sequence for spectrum analysis. A Hanning window with a window length of 4096 points is used, and the window overlap rate is 50%. For the input shaft torque signal, first, the speed normalization process is carried out to convert the time-domain signal into an angular-domain signal to eliminate the influence of speed fluctuations. After the FFT calculation, the complex spectrum is obtained, and the amplitude and phase information are extracted.Based on the transmission structure of the gearbox (the number of teeth of the sun gear is 25, the number of teeth of the planet gear is 35, and the number of teeth of the internal gear ring is 95), calculate the key harmonic frequencies: the rotation frequency of the sun gear is 25 Hz, the meshing fundamental frequency is 625 Hz (25×25 Hz), and the harmonic frequencies (1250 Hz, 1875 Hz, etc.). For each harmonic frequency, extract the corresponding amplitude and phase from the spectrum. For the input shaft torque, the fundamental frequency amplitude is extracted as 120 N·m and the phase is 32 degrees; the second harmonic amplitude is 85 N·m and the phase is 128 degrees; the third harmonic amplitude is 42 N·m and the phase is 225 degrees. The same process is carried out for the output shaft torque to extract the harmonic components of the corresponding frequencies. Integrate the extracted harmonic component amplitudes and phases into a harmonic torque component spectrum, and the data structure is [harmonic order, input torque amplitude (N·m), input torque phase (degrees), output torque amplitude (N·m), output torque phase (degrees)]. Apply the fast Fourier transform to the acquired multi-channel vibration data for spectrum analysis, using a flat-top window with a window length of 8192 points and a window overlap rate of 75% to obtain higher amplitude accuracy. Calculate the spectra for the X, Y, and Z directions of each sensor respectively to form 18 spectral data sets. The preset noise threshold is determined by analyzing the vibration signal during the no-load operation of the gearbox, taking 2.5 times the average value of the vibration spectrum, and the value is 0.15 g. Extract the potential electromagnetic excitation frequency data from the acquired internal electromagnetic disturbance snapshot data, including 25 Hz (the sun gear rotation frequency), 50 Hz (the power supply frequency), 75 Hz (the sum of the power supply frequency and the sun gear rotation frequency), 625 Hz (the gear meshing frequency), etc. For these potential electromagnetic excitation frequencies, find the amplitude of the corresponding frequency point in each vibration spectrum. If the amplitude exceeds the preset noise threshold of 0.15 g, it is considered that there is an effective electromagnetic vibration response at this frequency point. The screening results show that at the 25 Hz frequency point, 5 out of 6 sensors detected vibration responses exceeding the threshold; at the 625 Hz frequency point, all sensors detected obvious vibration responses. Record these effective electromagnetic vibration response frequency points and their amplitudes in the data structure of [frequency (Hz), sensor ID, direction, amplitude (g)]. Establish a characteristic frequency table for each component of the gearbox transmission chain, including the characteristic frequencies of the sun gear, planet gear, internal gear ring, planet carrier, and each bearing. The establishment of the characteristic frequency table is based on the structural parameters and kinematic analysis of the gearbox. For example, the sun gear rotation frequency is 25 Hz, the planet gear rotation frequency is 7.14 Hz, the planet carrier rotation frequency is 2.5 Hz, and the sun gear-planet gear meshing frequency is 625 Hz. Analyze the coincidence of the significant harmonics (amplitude greater than 1.5 times the average value) in the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points. When the characteristic frequency of a certain component appears in both the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points, and the amplitude ratio (vibration amplitude / torque amplitude) exceeds the preset threshold of 0.025 g / N·m, identify this component as a high-risk vibration coupling component.The analysis results show that the meshing area between the sun gear and planet gear 1, the input bearing of the sun gear, and the bearing of planet gear 1 are high-risk vibration coupling components. For each high-risk component, record its characteristic frequency, torque harmonic amplitude, vibration response amplitude, and their ratios to form the high-risk coupling vibration data of each component. Use Hertz contact theory to calculate the contact stress history during gear meshing. The calculation formula is as follows. , where σH represents the contact stress (MPa), ZE is the material elastic coefficient (taken as 200 MPa), Ft is the tangential force (N) (calculated from the torque and gear geometric parameters), b is the tooth width (mm), d is the pitch circle diameter (mm), and i is the contact ratio. Synthesize the harmonic components in the harmonic torque component spectrum into a time-domain torque signal, then convert it into the tooth surface contact force, and further calculate the contact stress time history. For the meshing area between the sun gear and planet gear 1, the basic contact stress is 1250 MPa. Use the high-risk coupling vibration data of each component to enhance the contact stress. The enhancement method is to superimpose the additional stress caused by vibration on the basic contact stress. The calculation formula for the additional stress is , where σa represents the additional stress (MPa), kv is the vibration-stress conversion coefficient (determined by experiment to be 0.15 MPa·s² / m), a is the vibration acceleration amplitude (m / s²), m is the equivalent mass (kg), ω is the vibration angular frequency (rad / s), and A is the contact area (mm²). For the meshing area between the sun gear and planet gear 1, the additional stress caused by vibration is calculated to be 75 MPa, and the maximum contact stress after coupling vibration enhancement is 1325 MPa, forming a complete coupling vibration enhanced stress history. Calculate the component fatigue life reduction coefficient according to the proportion of bearing-tooth surface electrical erosion damage. The calculation formula for the reduction coefficient is , where $R_f$ represents the fatigue life reduction coefficient, $D$ represents the proportion of electrical erosion damage (a decimal between 0 and 1), and $n$ is the material sensitivity index (determined to be 0.5 through experiments). For the sun gear - planet gear 1 meshing pair, the proportion of electrical erosion damage is 0.6256, and the calculated fatigue life reduction coefficient is 1.65; for the sun gear input bearing, the proportion of electrical erosion damage is 0.4005, and the fatigue life reduction coefficient is 1.29. Based on the coupled vibration enhanced stress history, the linear damage accumulation theory (Miner criterion) is used to calculate the fatigue damage. The formula for the damage contribution of each stress cycle is $d_i = 1 / N_i$, where $d_i$ represents the damage contribution of a single cycle, and $N_i$ represents the fatigue life at this stress level (determined by the S - N curve). For the sun gear - planet gear 1 meshing pair, the parameters of the S - N curve are $\sigma_f' = 1500$ MPa, $b=-0.085$, and the fatigue life at a stress level of 1325 MPa is $10^7$ cycles. During the current monitoring period (60 minutes), the number of meshing times is $1.5×10^6$ times, and the fatigue damage contribution value for a single monitoring period is $1.5×10^6 / 10^7 = 0.15$. Considering the influence of electrical erosion damage, the actual fatigue damage contribution value is $0.15×1.65 = 0.2475$. The same calculation is performed for each high - risk component to obtain the fatigue damage contribution values of each component in the period.

[0031] Preferably, the identification of high - risk vibration coupling components through the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points includes: Align the vibration frequencies of the harmonic torque component spectrum through the effective electromagnetic vibration response frequency points, and perform an analysis of the mechanical natural vibration response amplitude to obtain the mechanical resonance dominant frequency response amplitude; Perform a proximity matching between the effective electromagnetic vibration response frequency points and the mechanical resonance dominant frequency response amplitude. When the frequency difference between the two is less than the preset coupling identification bandwidth, mark it as a potential coupling pair to obtain potential electromechanical coupling frequency pairs; Calculate the ratio of the vibration amplitude at the electromagnetic excitation frequency of the potential electromechanical coupling frequency pair to the baseline vibration amplitude at the corresponding mechanical natural frequency without significant electromagnetic excitation as the vibration amplification factor of this coupling pair; Perform a product operation on the vibration amplification factor and the corresponding bearing - tooth surface electrical erosion damage proportion, and screen out the coupling pairs that exceed the preset risk threshold to generate high - risk coupling vibration events; Map the components of the gearbox through high - risk coupling vibration events to generate high - risk coupling vibration data for each component.

[0032] In an embodiment of the present invention, a frequency lookup table is constructed. The effective electromagnetic vibration response frequency points are arranged in ascending order of frequency values to form a frequency sequence [25Hz, 50Hz, 75Hz, 625Hz, 1250Hz, 1875Hz]. Then, the same or the closest frequency points are extracted from the harmonic torque component spectrum to form a corresponding torque harmonic component sequence. During the frequency alignment process, a frequency matching tolerance of 0.5Hz is set. For the frequency points that cannot be precisely matched, a linear interpolation method is used to calculate the corresponding torque values. After completing the frequency alignment, an analysis of the mechanical natural vibration response amplitude is carried out. The specific method is to obtain the mechanical system transfer function through an impact hammer test under the static condition of the gearbox to determine the key natural frequencies. In this example, the main natural frequencies determined through testing are 612Hz, 1263Hz, and 1854Hz. By comparing with the effective electromagnetic vibration response frequency points, the vibration response amplitudes at these natural frequencies are calculated as 2.35g, 1.86g, and 0.74g respectively, and these values form a dataset of the mechanical resonance dominant frequency response amplitudes. For each natural frequency point in the dataset of the mechanical resonance dominant frequency response amplitudes, a preset coupling identification bandwidth of 15Hz is set, and this bandwidth value is determined through a statistical analysis of the observed vibration frequency offsets in the historical operation data. Taking the natural frequency 612Hz as an example, calculate the frequency differences between it and each effective electromagnetic vibration response frequency point: |612 - 25| = 587Hz, |612 - 50| = 562Hz, |612 - 75| = 537Hz, |612 - 625| = 13Hz, |612 - 1250| = 638Hz, |612 - 1875| = 1263Hz. Since the frequency difference between 612Hz and 625Hz is 13Hz, which is less than the preset coupling identification bandwidth of 15Hz, the natural frequency 612Hz and the electromagnetic vibration response frequency point 625Hz are marked as potential coupling pairs. Similarly, for the natural frequency 1263Hz, the frequency difference between it and the electromagnetic vibration response frequency point 1250Hz is 13Hz, which is also less than the coupling identification bandwidth, and it is marked as a potential coupling pair. For the natural frequency 1854Hz, the frequency difference between it and the electromagnetic vibration response frequency point 1875Hz is 21Hz, which is greater than the coupling identification bandwidth, and it is not marked as a potential coupling pair. Finally, two pairs of potential electromechanical coupling frequency pairs are determined: [612Hz, 625Hz] and [1263Hz, 1250Hz], and their frequency differences, vibration response amplitudes, and torque harmonic amplitudes are recorded. The baseline vibration amplitude is obtained, that is, the vibration amplitude at the mechanical natural frequency without significant electromagnetic excitation. The baseline vibration data is obtained from the vibration signals collected when the gearbox operates under electrically isolated conditions (the power supply is disconnected and it is driven mechanically). Under this condition, the baseline vibration amplitude at the natural frequency 612Hz is 0.35g, and the baseline vibration amplitude at the natural frequency 1263Hz is 0.28g.For the first pair of coupled frequencies [612 Hz, 625 Hz], the vibration amplitude at the electromagnetic excitation frequency of 625 Hz is 2.35 g, and the calculated vibration amplification factor is 2.35 g / 0.35 g = 6.71. For the second pair of coupled frequencies [1263 Hz, 1250 Hz], the vibration amplitude at the electromagnetic excitation frequency of 1250 Hz is 1.86 g, and the calculated vibration amplification factor is 1.86 g / 0.28 g = 6.64. The vibration amplification factor reflects the enhancement effect of electromagnetic excitation on mechanical vibration. The larger the value, the more significant the impact of electromagnetic excitation on mechanical vibration. These vibration amplification factors are recorded together with the corresponding potential electromechanical coupling frequency pairs to form a dataset of coupled frequency pairs with amplification factor attributes. From the data on the proportion of bearing-tooth surface electrical erosion damage of each component: the meshing pair of the sun gear and planet gear 1 is 0.6256, the input bearing of the sun gear is 0.4005, and the bearing of planet gear 1 is 0.0041. Through frequency characteristic analysis, it is determined that the first pair of coupled frequencies [612 Hz, 625 Hz] mainly affects the meshing pair of the sun gear and planet gear 1, and the second pair of coupled frequencies [1263 Hz, 1250 Hz] mainly affects the input bearing of the sun gear. Calculate the comprehensive risk factor, and the formula is RF = AF × D, where RF represents the comprehensive risk factor, AF represents the vibration amplification factor, and D represents the proportion of electrical erosion damage. For the first pair of coupled frequencies, the calculated comprehensive risk factor is 6.71 × 0.6256 = 4.20; for the second pair of coupled frequencies, the calculated comprehensive risk factor is 6.64 × 0.4005 = 2.66. The preset risk threshold is determined to be 2.5 through historical failure case analysis. When the comprehensive risk factor exceeds this threshold, the corresponding coupling pair is marked as a high-risk coupled vibration event. Therefore, the meshing pair of the sun gear and planet gear 1 corresponding to the first pair of coupled frequencies [612 Hz, 625 Hz] and the input bearing of the sun gear corresponding to the second pair of coupled frequencies [1263 Hz, 1250 Hz] are both identified as high-risk coupled vibration events, and their frequency characteristics, vibration amplification factors, proportion of electrical erosion damage, and comprehensive risk factors are recorded. Based on the identified high-risk coupled vibration events, a gearbox component mapping table is established. The mapping table includes component names, associated high-risk coupled frequency pairs, vibration amplification factors, proportion of electrical erosion damage, comprehensive risk factors, and vibration sensor position information. For the meshing pair of the sun gear and planet gear 1, the associated high-risk coupled frequency pair is [612 Hz, 625 Hz], the vibration amplification factor is 6.71, the proportion of electrical erosion damage is 0.6256, the comprehensive risk factor is 4.20, and the relevant vibration sensors are sensor 1 and sensor 2. For the input bearing of the sun gear, the associated high-risk coupled frequency pair is [1263 Hz, 1250 Hz], the vibration amplification factor is 6.64, the proportion of electrical erosion damage is 0.4005, the comprehensive risk factor is 2.66, and the relevant vibration sensors are sensor 5 and sensor 6. According to the spatial positions of each component in the gearbox, a three-dimensional component mapping diagram is created, marking the positions of high-risk components and the corresponding comprehensive risk factors.Finally, high-risk coupled vibration data of each component are formed, and the data structure is [component ID, component name, coupling frequency pair, vibration amplification factor, proportion of electrical erosion damage, comprehensive risk factor, associated sensor ID].

[0033] Preferably, the present invention further provides a gearbox life assessment system that executes the gearbox life assessment method described above. The gearbox life assessment system includes: An electromagnetic characteristic acquisition module, which is used to collect the shaft current of the gearbox under the electromechanical coupling condition, perform the correlation of the current characteristics of each bearing, and generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, and generate internal electromagnetic disturbance snapshot data; An electrical erosion path assessment module, which is used to determine the main flow path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, estimate the current distribution ratio, and generate the estimated current share data of the meshing pair-bearing; obtain the design parameters of the gearbox; based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox, perform electrical erosion damage assessment through the estimated current share data of the meshing pair-bearing, and generate the proportion of bearing-to-tooth surface electrical erosion damage; A fatigue damage accumulation module, which is used to calculate the fatigue life reduction coefficient of the component according to the proportion of bearing-to-tooth surface electrical erosion damage, and perform dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in the cycle; A life prediction and analysis module, which is used to analyze the fatigue damage degree of the leading component according to the fatigue damage contribution value of each component in the cycle, and perform gearbox life assessment to generate the remaining life percentage of the gearbox.

[0034] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application document are intended to be included in the present invention.

[0035] The above are only specific embodiments of the present invention, which enable those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the service life of a gearbox, characterized in that, The method includes the following steps: Step S1: Collect the shaft current of the gearbox under the electromechanical coupling condition, correlate the current characteristics of each bearing, and generate the current characteristic sequence of each bearing; synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, and generate the internal electromagnetic disturbance snapshot data; Step S2: Determine the main circulation path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, estimate the current distribution ratio, and generate the estimated current share data of the meshing pair-bearing; obtain the design parameters of the gearbox; based on the internal electromagnetic disturbance snapshot data and the design parameters of the gearbox, conduct an electro-erosion damage assessment through the estimated current share data of the meshing pair-bearing, and generate the proportion of bearing-to-tooth surface electro-erosion damage; Step S3: Calculate the fatigue life reduction coefficient of the component according to the proportion of bearing-to-tooth surface electro-erosion damage, and perform dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in the cycle; Step S4: Analyze the fatigue damage degree of the dominant component according to the fatigue damage contribution value of each component in the cycle, and conduct a life assessment of the gearbox to generate the percentage of the remaining life of the gearbox.

2. The gearbox life assessment method according to claim 1, wherein In step S1, collecting the shaft current of the gearbox under the electromechanical coupling condition and correlating the current characteristics of each bearing includes: Install high-frequency-response Rogowski coils on the outer rings of the sun gear input bearing seat, the planet carrier output bearing seat and at least one planet gear bearing of the gearbox; arrange a micro magnetic field probe array on the outer wall of the planet gear bearing area and near the outer wall of the fixed end of the ring gear of the gearbox housing; Use the high-frequency-response Rogowski coil to perform wide-band sampling of the shaft current to obtain the original shaft current time-domain sequence; Perform a fast Fourier transform on the original shaft current time-domain sequence, and then extract the amplitude and phase of each frequency component to generate the original shaft current spectrum data; Perform a main harmonic component analysis on the original shaft current spectrum data through a preset amplitude threshold to generate the main harmonic amplitude sequence of the shaft current; Extract the harmonic frequencies corresponding to the main harmonic amplitude sequence of the shaft current from the original shaft current spectrum data to obtain the main harmonic frequency sequence of the shaft current; Correlate the main harmonic amplitude sequence of the shaft current and the main harmonic frequency sequence of the shaft current to generate the current characteristic sequence of each bearing.

3. The gearbox life assessment method according to claim 2, wherein, In step S1, synchronously collect the electromagnetic field of the gearbox, and evaluate the electromagnetic disturbance level borne by each component of the gearbox according to the current characteristic sequence of each bearing, including: Use the micro magnetic field probe array to synchronously collect the magnetic field intensity at each measurement point to obtain the discrete magnetic field data on the surface of the housing; Perform three-axis component analysis on the discrete magnetic field data on the surface of the housing, evaluate the electromagnetic field leakage intensity and direction of the measurement point, and obtain the spatial electromagnetic field distribution data; Perform three-dimensional space coordinate mapping of the gearbox according to the spatial electromagnetic field distribution data, and perform spatial magnetic field calculation to reconstruct the equivalent leakage magnetic field intensity distribution near the inner ring of the planet carrier bearing and the meshing line of the sun gear and the planet gear in the gearbox, and generate the internal equivalent magnetic field intensity cloud data; Perform spatial region division on the internal equivalent magnetic field intensity cloud data, and calculate the average and peak magnetic field intensities of the planet gear bearing raceway, the sun gear tooth surface and the planet gear tooth surface in the gearbox to generate the surface magnetic induction characteristic data of the key components; Based on the characteristic sequences of each bearing current, evaluate the electromagnetic excitation of the rotating components in the planetary gear train to generate potential electromagnetic excitation frequency data; According to the potential electromagnetic excitation frequency data and the surface magnetic induction characteristic data of key components, evaluate the electromagnetic disturbance levels borne by each component in the gearbox, extract the electromagnetic disturbance characteristics, and generate internal electromagnetic disturbance snapshot data.

4. The gearbox life assessment method according to claim 1, characterized in that In step S2, the main flow paths and branches of the current between the gear meshing pairs in the gearbox are discriminated based on the characteristic sequences of each bearing current, and the current distribution ratio estimation includes: Obtain the connection topology of the sun gear - planet gear - ring gear in the gearbox and the geometric constraint data of the planetary gear train; Extract the current values of each bearing according to the characteristic sequences of each bearing current; Conduct a conductive connection topology analysis on the current values of each bearing based on the connection topology of the sun gear - planet gear - ring gear, and discriminate the main flow paths and branches of the current between the gear meshing pairs based on the geometric constraint data of the planetary gear train to obtain the main current path data between gears; among them, the gear meshing pairs include the sun gear - planet gear meshing pair and the planet gear - internal gear ring meshing pair; Set the equivalent conductive contact point quantity and contact resistance range of the bearings in the gearbox according to the main current path data between gears to generate bearing shunt characteristic data; Based on the bearing shunt characteristic data, estimate the current distribution ratio of the sun gear - planet gear meshing pair and the planet gear - internal gear ring meshing pair through the main current path data between gears to generate the estimated current share data of the meshing pair - bearing.

5. The gearbox life evaluation method according to claim 1, wherein, In step S2, the electro - erosion damage assessment is carried out based on the internal electromagnetic disturbance snapshot data, the gearbox design parameters, and the estimated current share data of the meshing pair - bearing, including: Set the critical electro - erosion damage threshold of the gear / bearing according to the gearbox design parameters; Extract the instantaneous effective conductive contact area of each meshing point and the conductive area of the bearing roller / raceway contact point according to the gearbox design parameters; Calculate the average current density on the tooth surface based on the estimated current share data of the meshing pair - bearing and the instantaneous effective conductive contact area of each meshing point to obtain the tooth surface meshing current density data; Estimate the bearing current density based on the estimated current share data of the meshing pair - bearing and the conductive area of the bearing roller / raceway contact point to obtain the bearing current density distribution range; Analyze the tooth surface electro - thermal - mechanical disturbance characteristics based on the internal electromagnetic disturbance snapshot data and the tooth surface meshing current density data to generate tooth surface electro - thermal - mechanical disturbance data; Based on the critical electro - erosion damage threshold of the gear / bearing, use the tooth surface electro - thermal - mechanical disturbance data and the bearing current density distribution range to conduct an electro - erosion damage assessment to generate the electro - erosion damage ratio of the bearing - tooth surface.

6. The gearbox life evaluation method according to claim 5, wherein Based on the critical electro - erosion damage threshold of the gear / bearing, the electro - erosion damage assessment using the tooth surface electro - thermal - mechanical disturbance data and the bearing current density distribution range includes: Install an ultrasonic oil film thickness sensor in the lubricating oil channel near the meshing exit area of the planet gear in the gearbox to measure the minimum oil film thickness of the lubricating oil channel in real time and obtain the real - time sampling value of the oil film thickness; Calculate the minimum oil film thickness ratio of the critical area according to the real - time sampling value of the oil film thickness; Based on the electro-thermal-force disturbance data of the tooth surface, analyze the lubrication state of the current cycle for the minimum oil film thickness ratio in the critical region and the dynamic monitoring curve of the oil resistivity, and conduct an electro-erosion risk assessment for the meshing zone to generate the severity index of the meshing zone working conditions; Based on the tooth surface meshing current density data and the severity index of the meshing zone working conditions, estimate the increment of the equivalent micro electro-erosion pit density on the tooth surface generated during the current monitoring cycle by using the preset correlation table of the electro-erosion rate of the gear material; Estimate the increment of the equivalent micro electro-erosion pit density of the bearing raceway generated by the bearing during the current monitoring cycle according to the maximum current density estimated value in the bearing current density distribution interval; Accumulate the electro-erosion pit density periodically for the increment of the equivalent micro electro-erosion pit density on the tooth surface and the increment of the equivalent micro electro-erosion pit density of the bearing raceway, and divide them by the corresponding critical electro-erosion damage thresholds of the gear / bearing respectively to obtain the electro-erosion damage ratio of the bearing-tooth surface; 7. The gearbox life evaluation method according to claim 6, characterized in that Based on the electro-thermal-force disturbance data of the tooth surface, analyze the lubrication state of the current cycle for the minimum oil film thickness ratio in the critical region and the dynamic monitoring curve of the oil resistivity, and conduct an electro-erosion risk assessment for the meshing zone, including: When the minimum oil film thickness ratio in the critical region is continuously greater than 2.0, or the maximum current density value in the electro-thermal-force disturbance data of the tooth surface is lower than 0.05 A / mm², set the boundary lubrication coefficient to a high value, set the electro-erosion risk level to low, indicating good lubrication, and generate low-risk lubrication-electro-erosion state data; When the minimum oil film thickness ratio in the critical region is between 1.0 and 2.0, and the maximum current density value in the electro-thermal-force disturbance data of the tooth surface is higher than 0.1 A / mm², set the boundary lubrication coefficient to a medium value, set the electro-erosion risk level to medium, and generate medium-risk lubrication-electro-erosion state data; When the minimum oil film thickness ratio in the critical region is less than 1.0, set the boundary lubrication coefficient to a low value, set the electro-erosion risk level to high, and generate high-risk lubrication-electro-erosion state data; Based on the low-risk lubrication-electro-erosion state data, medium-risk lubrication-electro-erosion state data, and high-risk lubrication-electro-erosion state data, quantify the weighted index of the severity of the current meshing zone through the change amount of the ratio of the maximum thermal stress value and the electromagnetic-induced additional force in the electro-thermal-force disturbance data of the tooth surface to generate the severity index of the meshing zone working conditions; 8. The gearbox life assessment method according to claim 1, wherein Step S3 includes the following steps: Step S31: Install high-bandwidth torque sensors at the input shaft flange and the output shaft spline of the gearbox respectively, synchronously collect the dynamic signals of the input and output torques, and obtain the double-end torque time domain sequence; Step S32: Install three-axis high-frequency acceleration sensors at the planet carrier bearing seat and the sun gear bearing seat of the gearbox, synchronously collect multi-point multi-directional vibration signals, and obtain multi-channel vibration data; Step S33: Extract the amplitude and phase of the mechanical load harmonic torque component from the double-end torque time domain sequence to generate the harmonic torque component spectrum; Step S34: Conduct a spectrum analysis on the multi-channel vibration data, and screen out the electromagnetic excitation components with the vibration response amplitude exceeding the preset noise threshold through the potential electromagnetic excitation frequency data in the internal electromagnetic disturbance snapshot data to obtain the effective electromagnetic vibration response frequency points; Step S35: Identify high-risk vibration coupling components through the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points, and generate high-risk coupled vibration data for each component; Step S36: Analyze the gearbox contact stress history based on the harmonic torque component spectrum, and use the high-risk coupled vibration data of each component to enhance the coupled vibration, generating an enhanced coupled vibration stress history; Step S37: Calculate the component fatigue life reduction coefficient according to the bearing-tooth surface electrical erosion damage ratio, and perform linear damage accumulation processing based on the enhanced coupled vibration stress history to obtain the fatigue damage contribution value of each component in the cycle.

9. The gearbox life assessment method according to claim 8, wherein, Identifying high-risk vibration coupling components through the harmonic torque component spectrum and the effective electromagnetic vibration response frequency points includes: Align the vibration frequencies of the harmonic torque component spectrum through the effective electromagnetic vibration response frequency points, and perform mechanical natural vibration response amplitude analysis to obtain the mechanical resonance dominant frequency response amplitude; Perform proximity matching between the effective electromagnetic vibration response frequency points and the mechanical resonance dominant frequency response amplitude. When the frequency difference between the two is less than the preset coupling identification bandwidth, mark it as a potential coupling pair to obtain potential electromechanical coupling frequency pairs; Calculate the ratio of the vibration amplitude at the electromagnetic excitation frequency of the potential electromechanical coupling frequency pair to the baseline vibration amplitude at the corresponding mechanical natural frequency without significant electromagnetic excitation as the vibration amplification factor of the coupling pair; Perform a product operation on the vibration amplification factor and the corresponding bearing-tooth surface electrical erosion damage ratio, and screen out the coupling pairs that exceed the preset risk threshold to generate high-risk coupled vibration events; Generate high-risk coupled vibration data for each component by mapping the components of the gearbox through high-risk coupled vibration events.

10. A gearbox life assessment system, characterized in that, For implementing the gearbox life assessment method as described in claim 1, the gearbox life assessment system includes: An electromagnetic characteristic acquisition module for collecting the shaft current of the gearbox under electromechanical coupling conditions, correlating the current characteristics of each bearing, and generating the current characteristic sequence of each bearing; synchronously collecting the electromagnetic field of the gearbox, and evaluating the electromagnetic disturbance level suffered by each component of the gearbox according to the current characteristic sequence of each bearing to generate internal electromagnetic disturbance snapshot data; An electrical erosion path assessment module for determining the main flow path and branches of the current between the gear meshing pairs in the gearbox according to the current characteristic sequence of each bearing, and estimating the current distribution ratio to generate the estimated current share data of the meshing pair-bearing; obtaining the gearbox design parameters; performing electrical erosion damage assessment based on the internal electromagnetic disturbance snapshot data and the gearbox design parameters through the estimated current share data of the meshing pair-bearing to generate the bearing-tooth surface electrical erosion damage ratio; A fatigue damage accumulation module for calculating the component fatigue life reduction coefficient according to the bearing-tooth surface electrical erosion damage ratio, and performing dynamic linear damage accumulation processing to obtain the fatigue damage contribution value of each component in the cycle; A life prediction analysis module for analyzing the fatigue damage degree of the dominant components according to the fatigue damage contribution value of each component in the cycle, and performing gearbox life assessment to generate the remaining life percentage of the gearbox.

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