Failure detection method for planetary gear shaft of differential mechanism of new energy automobile

Abstract

The invention relates to the technical field of mechanical failure analysis, in particular to a failure detection method for a planetary gear shaft of a differential mechanism of a new energy automobile, which comprises the following steps of: processing and analyzing vibration, load and temperature signals by simulating working conditions, and extracting and analyzing typical characteristics of the signals; the aging state and the specific failure type of the planetary gear shaft can be quickly judged, the failure detection period can be effectively shortened, and the detection cost can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical failure analysis, and in particular to a failure detection method for a planetary gear shaft of a differential of a new energy vehicle. Background Art

[0002] As a core component in a vehicle's differential, the planetary gear shaft primarily secures the axial position of the two planetary gears and continuously rotates with the axle during vehicle operation. During vehicle operation, if there is a speed difference between the left and right wheels, relative motion between the planetary gears can occur, causing friction at the interface between the planetary gears and the planetary gear shaft.

[0003] Compared to traditional fuel-powered vehicles, electric motor-driven new energy vehicles experience significantly more rapid changes in driving force due to the variable torque characteristics of the motor. This also creates more complex forces within the planetary gear train within the differential. Especially when operating in harsh operating environments, the contact areas between the planetary gear shafts and the planetary gears can frequently wear out, leading to wear-out failures. This undoubtedly increases vehicle safety risks and poses a serious threat to driving safety. If a planetary gear shaft fails in the differential, the axial position of the two planetary gears deviates from their designed position, resulting in a loss of differential function. This not only makes cornering difficult but also forces the left and right wheels to rotate at the same speed, exacerbating tire wear. Furthermore, planetary gear shaft failure can cause transmission anomalies in the drivetrain, leading to various malfunctions and negatively impacting vehicle handling.

[0004] Those skilled in the art have been committed to the judgment of planetary gear shaft failure and the identification of failure types, and have proposed various prediction methods. For example, the patent with publication number CN115062430B, "A real-time prediction method for the reliability of shaft products based on cumulative damage simulation", discloses a prediction method that attempts to improve the accuracy and timeliness of the reliability prediction of shaft products by simulating the amount of wear using numerical simulation methods. However, this method only predicts the reliability of shaft products based on the amount of wear, and is unable to deeply analyze the friction and wear failure process caused by friction on the shaft surface. Therefore, when the shaft is under complex wear conditions, it is difficult to predict the failure type of the shaft using this method.

[0005] How to accurately determine whether a planetary gear shaft has failed and identify its failure type has always been a problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0006] The purpose of the present invention is to address the corresponding deficiencies of the existing technology and provide a failure detection method for the planetary gear shaft of the differential of new energy vehicles. By simulating the working conditions to process and analyze the vibration, load and temperature signals, extracting and analyzing the typical characteristics of the signals, the aging state and specific failure type of the planetary gear shaft can be quickly determined, which can effectively shorten the failure detection cycle and reduce the detection cost.

[0007] The purpose of the present invention is to adopt the following scheme to achieve:

[0008] A method for detecting a failure of a planetary gear shaft in a differential of a new energy vehicle comprises the following steps:

[0009] 1) Determine a single-cycle operating condition that simulates actual operation, and install the normal shaft sample and the shaft sample to be tested on a simulation test bench to perform a failure cycle detection test, and obtain monitoring data of the normal shaft sample and the shaft sample to be tested respectively;

[0010] 2) Processing the acquired monitoring data of the normal shaft sample and the shaft sample to be tested to obtain the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested respectively;

[0011] 3) Analyze the results obtained in step 2) to determine the evaluation index, and then use the determined evaluation index to judge the specific failure type of the shaft specimen to be tested.

[0012] Preferably, in step 1), the specific process of the failure cycle detection test is as follows:

[0013] 1-1) Determine the single-cycle operating condition for simulating actual operation based on the design speed of the road type and the proportion of road types in the city;

[0014] 1-2) Install the normal shaft sample and the shaft sample to be tested on the simulation test bench respectively, and set up multiple sensors near the installation contact points;

[0015] 1-3) The installed normal shaft sample and the shaft sample to be tested are debugged, and under single-cycle working conditions, multiple sensors installed near the installation contact points are used to collect monitoring data of the normal shaft sample and the shaft sample to be tested.

[0016] Preferably, the single-cycle operating condition includes a standard operating condition, an extreme operating condition, and a speed-changing operating condition, and the monitoring data includes acceleration monitoring data, load monitoring data, and temperature monitoring data.

[0017] Preferably, in step 2), the monitoring data of the normal shaft sample and the to-be-tested shaft sample are processed to obtain the acceleration root mean square, the frequency peak amplitude, the load standard deviation, the load extreme value number, and the temperature standard deviation of the normal shaft sample and the to-be-tested shaft sample, in the following specific manner:

[0018] 2-1) Calculate the acceleration root mean square by using the acceleration monitoring data, and transform the acceleration monitoring data to obtain the frequency peak amplitude;

[0019] 2-2) Calculate the load standard deviation according to the load monitoring data, and record the load extreme value number;

[0020] 2-3) Calculate the temperature standard deviation by using the temperature monitoring data.

[0021] Preferably, in step 3), according to the results obtained in step 2), the evaluation indexes determined include the damage factor, the modal transition value, the frequency peak offset, the load extreme value number, and the temperature standard deviation.

[0022] Preferably, the specific formula of the damage factor is as follows:

[0023] DF=w1Acc rms +w2F std +w3M std

[0024] In the formula, DF is the damage factor; w1 is the weighted coefficient of the acceleration root mean square; Acc rms is the acceleration root mean square of the to-be-tested shaft sample; w2 is the weighted coefficient of the load standard deviation; F std is the load standard deviation of the to-be-tested shaft sample; w3 is the weighted coefficient of the temperature standard deviation; M std is the temperature standard deviation of the to-be-tested shaft sample.

[0025] Preferably, the specific formula of the modal transition value is as follows:

[0026]

[0027] In the formula, D is the modal transition value; ω i is the i-th component of the main modal of the normal shaft sample; ω1 is the 1st component of the main modal of the normal shaft sample; ω2 is the 2nd component of the main modal of the normal shaft sample; ω sti is the i-th component of the main modal of the to-be-tested shaft sample; ω st1 is the 1st component of the main modal of the to-be-tested shaft sample; ω st2 is the 2nd component of the main modal of the to-be-tested shaft sample.

[0028] Preferably, the specific formula of the frequency peak offset is as follows:

[0029]

[0030] Where Δf is the frequency peak offset; f i is the ith frequency peak of the normal shaft specimen; f sti is the i-th frequency peak of the shaft sample to be tested; f1 is the first frequency peak of the normal shaft sample; f2 is the second frequency peak of the normal shaft sample; f st1 is the first frequency peak of the shaft sample to be tested; f st2 It is the second frequency peak of the shaft sample to be tested.

[0031] Preferably, in step 3), the process of determining the specific failure type of the shaft specimen to be tested based on the number of load extreme values, the temperature standard deviation, and the determined damage factor, modal transition value, and frequency peak offset is as follows:

[0032] If the "modal transition value" is abnormal, the failure type of the shaft specimen to be tested can be directly determined based on the "temperature standard deviation":

[0033] (1) If the "temperature standard deviation" is normal, the failure type of the shaft sample to be tested is fatigue wear;

[0034] (2) If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear;

[0035] If the "modal transition value" is normal, further determine whether the "damage factor" is abnormal:

[0036] (1) If the "damage factor" is normal, the failure type of the shaft specimen to be tested can be directly determined based on the "frequency peak offset":

[0037] ① If the "frequency peak offset" is normal, the failure type of the shaft specimen to be tested is slight corrosion wear;

[0038] ② If the "frequency peak offset" is abnormal, the failure type of the shaft specimen to be tested is abrasive wear;

[0039] (2) If the "damage factor" is abnormal, further determine whether the "temperature standard deviation" is abnormal:

[0040] ① If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear;

[0041] ② If the "temperature standard deviation" is normal, further determine whether the "load extreme value number" is abnormal:

[0042] a. If the "Load Extreme Number" is normal, the failure type of the shaft specimen to be tested is abrasive wear;

[0043] b. If the "load extreme value number" is abnormal, the failure type of the shaft specimen to be tested is fatigue wear.

[0044] The beneficial effects of the present invention include the following:

[0045] A method for detecting a failure of a planetary gear shaft in a differential of a new energy vehicle comprises the following steps:

[0046] 1) Determine a single-cycle operating condition that simulates actual operation, and install the normal shaft sample and the shaft sample to be tested on a simulation test bench to perform a failure cycle detection test, and obtain monitoring data of the normal shaft sample and the shaft sample to be tested respectively;

[0047] 2) Processing the acquired monitoring data of the normal shaft sample and the shaft sample to be tested to obtain the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested respectively;

[0048] 3) Analyze the results obtained in step 2) to determine the evaluation index, and then use the determined evaluation index to judge the specific failure type of the shaft specimen to be tested.

[0049] The present invention carries out a failure cycle detection test by installing a normal shaft sample and a shaft sample to be tested on a simulation test bench, so that the two shaft samples can obtain detection data under the same working conditions, effectively ensuring the reliability of the data and the credibility of the detection results.

[0050] The present invention processes multidimensional signals such as vibration, load and temperature to construct a comprehensive characteristic parameter system including frequency, load fluctuation and temperature change, which can more comprehensively reflect the failure characteristics of the planetary gear shaft. Based on standardized test procedures and quantitative criteria, the failure state and failure type of the shaft sample to be tested are accurately and quickly identified by analyzing multiple evaluation indicators. It can effectively avoid the subjectivity of manual experience judgment and the time of repeated debugging and analysis in traditional monitoring, and effectively reduce the test cycle and detection cost.

[0051] Preferably, in step 1), the specific process of the failure cycle detection test is as follows:

[0052] 1-1) Determine the single-cycle operating condition for simulating actual operation based on the design speed of the road type and the proportion of road types in the city;

[0053] 1-2) Install the normal shaft sample and the shaft sample to be tested on the simulation test bench respectively, and set up multiple sensors near the installation contact points;

[0054] 1-3) The installed normal shaft sample and the shaft sample to be tested are debugged, and under single-cycle working conditions, multiple sensors installed near the installation contact points are used to collect monitoring data of the normal shaft sample and the shaft sample to be tested.

[0055] By determining single-cycle operating conditions based on the design speed of the road type and the proportion of urban road types, this method enables the test conditions to more accurately replicate the load and operating state of the planetary gear shaft under actual complex road conditions, ensuring that the test results effectively reflect the actual failure scenario. Furthermore, prior to testing, the present invention ensures the stability of the shaft specimen's installation and consistent loading conditions through debugging. Combined with data collection under single-cycle operating conditions, this method effectively reduces test errors, providing a reliable data foundation for subsequent failure analysis and improving the accuracy of test results.

[0056] Preferably, the single-cycle operating condition includes a standard operating condition, an extreme operating condition, and a speed-changing operating condition, and the monitoring data includes acceleration monitoring data, load monitoring data, and temperature monitoring data.

[0057] By setting standard, extreme, and variable-speed operating conditions within a single cycle, this method allows the test to truly reflect the actual operation of the planetary gear shaft, providing a reliable basis for accurately detecting its failure type. Furthermore, by combining multiple operating conditions with various types of monitoring data, it can provide rich data support for various subsequent evaluation indicators.

[0058] Preferably, the specific formula of the damage factor is as follows:

[0059] DF=w1Acc rms +w2F std +w3M std

[0060] Where DF is the damage factor; w1 is the weighting coefficient of the acceleration root mean square; Acc rms is the root mean square acceleration of the shaft specimen to be tested; w2 is the weighting coefficient of the load standard deviation; F std is the load standard deviation of the shaft sample to be tested; w3 is the weighting coefficient of the temperature standard deviation; M std is the temperature standard deviation of the shaft sample to be tested.

[0061] By calculating the damage factor and using it as one of the evaluation indicators, the present invention can integrate multiple key parameters to form a comprehensive assessment of the operating status of the planetary gear shaft, effectively avoiding the limitations of single signal analysis and significantly improving the accuracy and reliability of planetary gear shaft failure detection under complex working conditions.

[0062] Preferably, the specific formula of the modal transition value is as follows:

[0063]

[0064] Where D is the modal transition value; ω iis the i-th component of the main mode of the normal shaft specimen; ω1 is the first component of the main mode of the normal shaft specimen; ω2 is the second component of the main mode of the normal shaft specimen; ω sti is the i-th component of the main mode of the shaft specimen to be tested; ω st1 is the first component of the main mode of the shaft specimen to be tested; ω st2 It is the second component of the main mode of the shaft specimen to be tested.

[0065] The present invention captures the changes in the dynamic characteristics of the planetary gear shaft caused by slight changes in the internal structure during operation by comparing the various components of the main modes of a normal shaft sample and the shaft sample to be tested, thereby accurately reflecting the changes in the internal structure of the planetary gear shaft. At the same time, it can effectively distinguish easily confused failure types when judging the failure type, thereby improving the accuracy of failure detection.

[0066] Preferably, the specific formula of the frequency peak offset is as follows:

[0067]

[0068] Where Δf is the frequency peak offset; f i is the ith frequency peak of the normal shaft specimen; f sti is the i-th frequency peak of the shaft sample to be tested; f1 is the first frequency peak of the normal shaft sample; f2 is the second frequency peak of the normal shaft sample; f st1 is the first frequency peak of the shaft sample to be tested; f st2 It is the second frequency peak of the shaft sample to be tested.

[0069] The present invention directly compares the corresponding frequency peaks of the normal shaft sample and the shaft sample to be tested, and accurately quantifies the failure characteristic of the frequency peak offset, which can provide a key quantitative basis for the accurate judgment of the failure type and greatly improve the accuracy of failure detection.

[0070] Preferably, in step 3), the process of determining the specific failure type of the shaft specimen to be tested based on the number of load extreme values, the temperature standard deviation, and the determined damage factor, modal transition value, and frequency peak offset is as follows:

[0071] If the "modal transition value" is abnormal, the failure type of the shaft specimen to be tested can be directly determined based on the "temperature standard deviation":

[0072] (1) If the "temperature standard deviation" is normal, the failure type of the shaft sample to be tested is fatigue wear;

[0073] (2) If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear;

[0074] If the "modal transition value" is normal, further determine whether the "damage factor" is abnormal:

[0075] 1. If the damage factor is normal, the failure type of the to-be-tested shaft sample is determined directly according to the frequency peak shift amount:

[0076] 1. If the frequency peak shift amount is normal, the failure type of the to-be-tested shaft sample is slight corrosion wear;

[0077] 2. If the frequency peak shift amount is abnormal, the failure type of the to-be-tested shaft sample is abrasive wear;

[0078] 3. If the damage factor is abnormal, it is further determined whether the temperature standard deviation is abnormal:

[0079] 1. If the temperature standard deviation is abnormal, the failure type of the to-be-tested shaft sample is adhesive wear;

[0080] 2. If the temperature standard deviation is normal, it is further determined whether the number of load extreme values is abnormal:

[0081] a. If the number of load extreme values is normal, the failure type of the to-be-tested shaft sample is abrasive wear;

[0082] b. If the number of load extreme values is abnormal, the failure type of the to-be-tested shaft sample is fatigue wear.

[0083] The present application can accurately distinguish different failure types according to the characteristic differences of different failure types on various parameters by using multiple key parameters and their combined states, thereby accurately identifying different failure modes and capturing failure characteristics comprehensively, and greatly improving the accuracy of failure type judgment.

[0084] Nomenclature:

[0085] Normal shaft sample: In the present application, it refers to a planetary gear shaft sample that meets the quality standard and has not appeared failure. Compared with a brand new shaft, the normal shaft refers to a planetary gear shaft sample that has been used.

[0086] To-be-tested shaft sample: In the present application, it refers to a planetary gear shaft sample that needs to be detected for failure and failure type.

[0087] Brand new shaft: In the present application, it also refers to a planetary gear shaft sample that meets the quality standard. However, compared with the normal shaft, the brand new shaft refers to a planetary gear shaft sample that has not been used.

[0088] Design speed of road type and proportion of road type in city: In the present application, it refers to the standard driving speed of different types of roads in city traffic planning and road design, and the proportion of each type of road in the city road system. BRIEF DESCRIPTION OF DRAWINGS

[0089] Figure 1is a flow chart of the present invention;

[0090] Figure 2 A logical diagram of failure type judgment of the present invention;

[0091] Figure 3 Schematic diagram of the reducer;

[0092] Figure 4 A schematic diagram of the basic features of the simulation test bench required for the present invention;

[0093] Figure 5 This is an example diagram of the acceleration history in an embodiment of the present invention;

[0094] Figure 6 : is an FFT spectrum diagram of acceleration in an embodiment of the present invention;

[0095] Figure 7 This is an example diagram of load change history in an embodiment of the present invention;

[0096] Figure 8 This is an example diagram of the temperature change process in an embodiment of the present invention. DETAILED DESCRIPTION

[0097] like Figures 1 to 8 As shown, a failure detection method for a planetary gear shaft of a differential of a new energy vehicle comprises the following steps:

[0098] 1) Determine a single-cycle operating condition that simulates actual operation, and install the normal shaft specimen and the shaft specimen to be tested on a simulation test bench to perform a failure cycle detection test. The specific process of the above-mentioned failure cycle detection test is as follows:

[0099] 1-1) To simulate the actual operating conditions of the differential planetary gear of new energy vehicles, comprehensive consideration is given based on the design speed of the road type and the proportion of urban road types (such as urban roads, highways, snowy areas, mountainous areas, etc.), while taking into account driving conditions such as acceleration, deceleration, and sharp turns. Among them, the urban road types strictly refer to the relevant provisions of the "Urban Road Engineering Design Code" (CJJ37-2012) to determine the single-cycle operating conditions that can simulate actual operation. In addition, the above-mentioned single-cycle operating conditions include standard operating conditions, extreme operating conditions, and speed-changing operating conditions. The specific single-cycle operating condition settings include:

[0100] ① Set standard operating conditions: Based on the proportion of roads at all levels in general cities, calculate the speed of the shaft samples (including normal shaft samples and shaft samples to be tested) when the simulation test bench is started, as well as the torque of the motor, to determine the standard operating conditions.

[0101] At the same time, if Figure 3As shown, the planetary shaft pattern speed can be calculated according to the speed difference between the left and right wheels when the vehicle is running and the working principle of the differential:

[0102] ω s = 0.5Δω

[0103] where ω s is the planetary shaft pattern speed, and Δω is the speed difference between the left and right wheels. In this embodiment, the speed of the shaft sample under standard working conditions is 25 rpm.

[0104] 2) Set extreme working conditions: In this embodiment, the shaft sample to be tested is taken from a vehicle that is often used in snowy road conditions. Therefore, the corresponding speed and torque are set for extreme working conditions such as typical snowy roads and icy roads, and the characteristics of the extreme working conditions are shown in Table 2 below:

[0105] Table 2 Characteristics of extreme working conditions

[0106] Road type Road characteristics Speed ​​difference (rpm) Torque (Nm) <![CDATA[ω s (rpm)]]> snow road More slippery 300 70 150 Ice Road Slip 600 35 300

[0107] Since the probability of wheel slip is high under this condition, the speed difference between the left and right wheels can reach more than 300 rpm. Therefore, only the differential speed and torque under snowy road conditions are considered in the extreme working conditions, and the speed of the shaft sample (i.e., the speed of the planetary gear shaft during testing) is designed to be 150 rpm.

[0108] 3) Set the variable speed working condition: This refers to the shaft pattern during the test process, with a speed of zero as the standard working condition. When the standard working condition and the extreme working condition are alternately operated, the intermediate state between the two is used for transition adjustment. That is, during the test process, when converting from the standard working condition to the extreme working condition, or when converting from the extreme working condition back to the standard working condition, an adjustment phase is required. The running state of the shaft sample during this adjustment phase is the variable speed working condition. In this embodiment, the running time of the variable speed working condition is set to 10 s.

[0109] Specifically, when designing a single cycle working condition, the running time of the above-mentioned standard working condition and extreme working condition should be maintained for a certain period of time to ensure the completeness of data collection. In this embodiment, the running time of the standard working condition is 30 s, and the running time of the extreme working condition is controlled to be 60 s. In addition, since temperature has a certain influence on the wear of the planetary gear shaft, the shaft sample needs to be preheated to the temperature of the planetary gear shaft under normal working conditions before detection. According to the above-mentioned working condition setting, the designed single cycle working condition is shown in Table 3 below. During the test process, the standard working condition and the extreme working condition need to be alternately operated 10 times, and finally the standard working condition is ended.

[0110] Table 1 Cycle characteristics of the test

[0111]

[0112] 1-2) As Figure 2As shown in the figure, the simulation test bench mainly includes a servo motor, a reducer, a coupling, a hole sample, multiple sensors, a hydraulic cylinder and a test bench. The normal shaft sample and the shaft sample to be tested are respectively installed on the simulation test bench to contact the hole sample, and multiple sensors are set at positions close to the installation contact points and without affecting the movement of each component, so as to directly capture the vibration, load and temperature signals of the shaft sample in the key stress area, avoid signal distortion caused by sensor position deviation, and improve the sensitivity and characterization accuracy of the monitoring data to the shaft failure characteristics.

[0113] Sensors include temperature sensors, load sensors, and acceleration sensors. Specifically, when setting up the simulation test bench, the following requirements must be met: The entire simulation test bench is driven by a servo motor. To ensure that the motor has sufficient power to stably drive the shaft specimen to simulate actual operating conditions, the performance specifications of the servo motor must meet the standards of rated power above 5kW, rated speed above 3000rpm, and torque above 20Nm. In addition, a reducer with a reduction ratio of no less than 1:6 is installed at the rear end of the servo motor to adjust the speed and torque output of the motor, so that the shaft specimen obtains operating parameters that meet the test requirements.

[0114] A hydraulic cylinder is mounted on a simulated test bench, with its hydraulic rod acting on the bore specimen via a force sensor. The force sensor accurately measures the force applied to the bore specimen. An acceleration sensor and temperature sensor, both mounted on the bore specimen, monitor the specimen's acceleration and temperature in real time during the test, providing a basis for subsequent data processing and analysis.

[0115] During installation, one end of the shaft specimen is connected to the reducer via a rigid coupling. This ensures a reliable connection between the two, reduces vibration and displacement at the connection, and ensures stable power transmission. The other end of the shaft specimen passes through the hole specimen and connects to the fixed test bench. Rolling bearings are installed at the contact point between the shaft specimen and the bench. The rolling bearings reduce friction between the shaft specimen and the bench, ensuring smooth rotation of the shaft specimen.

[0116] In addition, when installing the test device on the simulation test bench, it is necessary to strictly follow the standard installation procedures. First, accurately connect the shaft specimen to the reducer through the coupling to ensure that the connection is firm. Then adjust the levelness and rigidity of the test bench to ensure that the center line of the specimen shaft is accurately aligned with the output shaft of the reducer to avoid additional stress and vibration of the shaft specimen during rotation due to axis deviation, which affects the accuracy of the test results. Then install the hole specimen and fix it to the hydraulic rod (i.e. push rod) of the hydraulic cylinder so that the load can be applied to the shaft specimen through the hydraulic cylinder. Before loading, the hydraulic sensor must be zero-point calibrated to eliminate the system error of the sensor and ensure that the measured load data is true and reliable, thereby ensuring the accuracy and stability of loading throughout the test process.

[0117] 1-3) Debug the installed, normal shaft specimen and the shaft specimen to be tested. This involves starting the servo motor and running the shaft specimen at a set speed for a period of time (in this embodiment, the no-load operation time is 3 minutes). The baseline value of the vibration signal is further observed to ensure that the system is stable. Abnormal vibration indicates a possible problem with the device and requires further debugging. Then, according to the test design (i.e., the test torque, speed, and time requirements described above), gradually increase the thrust of the hydraulic cylinder until the load reaches the target value and maintains a constant state. This ensures that the shaft specimen can be subjected to the set load conditions in subsequent tests, preparing for obtaining valid data for subsequent formal tests.

[0118] After debugging is completed, under single-cycle working conditions, multiple sensors installed near the installation contact point are used to collect monitoring data of normal shaft specimens and shaft specimens to be tested. The data types include acceleration monitoring data, load monitoring data, and temperature monitoring data. In this embodiment, in order to ensure the accuracy of the experiment, multiple experiments are usually carried out on each group of shaft specimens (more than 3 times are recommended). During each experiment, full-cycle data of vibration, load, and temperature are collected. At the same time, during data collection, a high-frequency data sampling system (sampling frequency is not less than 5kHz) is used to record real-time signals to avoid signal distortion. In order to reduce the impact of experimental randomness on the results, three groups of specimens are used for repeated tests under each working condition, and the average value of the obtained data is used as the final result.

[0119] 2) The acquired monitoring data of the normal shaft sample and the shaft sample to be tested are processed to obtain the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested respectively. The specific method is as follows:

[0120] 2-1) The specific formula for calculating the acceleration root mean square using acceleration monitoring data is as follows:

[0121]

[0122] Where Acc rms is the root mean square value of acceleration; N is the number of acceleration sampling points; Acc i is the acceleration value of the i-th sampling point.

[0123] At the same time, the acceleration monitoring data is processed by fast Fourier transform to obtain the acceleration spectrum of the shaft sample in the vertical radial direction (such as Figure 6 As shown in the figure), and the frequency peak amplitude is obtained according to the acceleration spectrum. Specifically, using the formula The acceleration variation period T1 is obtained, where τ is the shaft sample rotation speed. In this embodiment, the shaft sample rotation speed τ is 60 r / min, that is, T1 = 1 s. By clarifying the acceleration variation period, the number of acceleration sampling points can be determined.

[0124] 2-2) The specific formula for calculating the load standard deviation based on load monitoring data is as follows:

[0125]

[0126] Where, F std is the load standard deviation, N is the number of load sampling points, F i is the load of the i-th sampling point, F m is the load mean. Among them, the load mean F m It is the external force value designed according to the working conditions, and the external force is achieved by a device with servo control effect such as a hydraulic cylinder.

[0127] Because the shaft specimen is affected by its own surface structure (such as cylindricity tolerance) when rotating, it will produce periodic load fluctuations when contacting the hole specimen. Therefore, in order to quantitatively analyze this load fluctuation, it is necessary to record the load extreme value number B (that is, the extreme value number of the original data), that is:

[0128] B=number(F i >1.2F m )

[0129] When determining the load extreme value number, the load extreme value number taken should be selected from sampling points that are 0.2% higher than the load mean value, so as to effectively reflect the peak value in the load fluctuation.

[0130] 2-3) After the temperature stabilizes, record the average temperature of the shaft sample T m , and the temperature standard deviation, and the specific formula for calculating the temperature standard deviation using temperature monitoring data is as follows:

[0131]

[0132] Where M mTo record the average temperature of the shaft sample after the temperature stabilizes, M i is the single cycle temperature, M std is the temperature standard deviation, and N is the number of temperature sampling points.

[0133] In this embodiment, the obtained statistical values ​​of the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the shaft sample to be tested are shown in Table 4:

[0134] Table 4

[0135]

[0136] 3) Analyze the acceleration root mean square, frequency peak amplitude, load standard deviation, number of load extremes, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested obtained in step 2) to determine various evaluation indicators, wherein the various evaluation indicators include damage factor, modal transition value, frequency peak offset, number of load extremes, and temperature standard deviation.

[0137] ①The specific formula for obtaining the damage factor is as follows:

[0138] DF=w1Acc rms +w2F std +w3M std

[0139]

[0140] Where DF is the damage factor; w1 is the weighting coefficient of the acceleration root mean square; Acc rms is the root mean square acceleration of the shaft specimen to be tested; w2 is the weighting coefficient of the load standard deviation; F std is the load standard deviation of the shaft sample to be tested; w3 is the weighting coefficient of the temperature standard deviation; M std is the temperature standard deviation of the shaft sample to be tested; Acc rms_sd is the acceleration test value of a new shaft; F std_sd It is the standard test value of the load of a new shaft; M std_sd is the temperature standard deviation of a new shaft.

[0141] Specifically, w1, w2, and w3 are obtained using a brand new planetary gear shaft and based on the experiment in Table 3 above.

[0142] ② In this embodiment, in order to obtain the modal transition value of the planetary gear shaft, a rotating mechanical exciter is used to apply continuous disturbance to the shaft sample on the test bench, thereby simulating the external excitation that the shaft sample may be subjected to in actual working conditions, causing the shaft sample to vibrate. During the vibration process of the shaft sample, the vibration behavior data is recorded using an acceleration sensor. Then, in software such as Matlab, the specific mode of the shaft sample is solved using the following formula, and finally the main mode of the planetary gear shaft ω is obtained. i :

[0143]

[0144] Where [M] is the mass matrix; [C] is the damping matrix; [K] is the stiffness matrix; and F(t) is the excitation external force.

[0145] Finally, using the calculated components of the normal shaft specimen and the main mode of the shaft specimen to be tested, the specific formula for the modal transition value is obtained as follows:

[0146]

[0147] Where D is the modal transition value; ω i is the i-th component of the main mode of the normal shaft specimen; ω1 is the first component of the main mode of the normal shaft specimen; ω2 is the second component of the main mode of the normal shaft specimen; ω sti is the i-th component of the main mode of the shaft specimen to be tested; ω st1 is the first component of the main mode of the shaft specimen to be tested; ω st2 It is the second component of the main mode of the shaft specimen to be tested.

[0148] ③ During the frequency analysis process, the recorded vibration acceleration signal is first processed by Fast Fourier Transform (FFT) to analyze the offset of each main frequency peak in the frequency domain. The frequency peak offset is used to measure the difference between the corresponding frequency peaks of the normal shaft sample and the shaft sample to be tested. The calculation formula is:

[0149]

[0150] Where Δf is the frequency peak offset; f i is the ith frequency peak of the normal shaft specimen; f sti is the i-th frequency peak of the shaft sample to be tested; f1 is the first frequency peak of the normal shaft sample; f2 is the second frequency peak of the normal shaft sample; f st1 is the first frequency peak of the shaft sample to be tested; f st2 It is the second frequency peak of the shaft sample to be tested.

[0151] By comparing the i-th frequency peak of a healthy shaft specimen with that of the shaft specimen under test, the frequency peak offset is calculated. The magnitude of this offset reflects changes in the structural characteristics or stress state of the shaft specimen during operation. If the frequency peak offset exceeds the normal range, it indicates that the vibration characteristics of the shaft specimen under test have changed, which may indicate shaft faults such as wear or looseness, providing important evidence for determining the type of planetary gear shaft failure.

[0152] The method for determining the normal range values ​​of various evaluation indicators is as follows: more than 10 planetary gear shafts that meet the factory standards are used as normal shaft samples, and they are fatigue tested under standard working conditions. In this embodiment, the fatigue test time is set to 12 hours. Focus on statistics of various evaluation indicator data of each normal shaft sample in the final stage of fatigue testing. In this embodiment, the duration of this final stage is 5 minutes. The average value of each evaluation indicator is obtained by calculation. Subsequently, the obtained average values ​​of various evaluation indicators are compared and analyzed with the detection values ​​of various evaluation indicators corresponding to the batch of planetary gear shafts when they leave the factory, that is, the actual parameters of the normal sample shafts such as vibration acceleration during the test are compared and analyzed with the parameters corresponding to the batch of planetary gear shafts when they leave the factory, so as to determine the normal range values ​​of various evaluation indicators. The specific values ​​are shown in Table 5 below.

[0153] Table 5

[0154]

[0155] Compare and analyze the various evaluation indicators of the shaft specimen to be tested with the normal range values ​​of each evaluation indicator to determine whether each evaluation indicator is in a normal state or an abnormal state. The specific method is as follows:

[0156] ① If the damage factor of the shaft sample to be tested is higher than the damage factor of the normal shaft sample, it is determined that the damage factor of the shaft sample to be tested is abnormal; otherwise, it is determined that the damage factor of the shaft sample to be tested is normal;

[0157] ② If the temperature standard deviation of the shaft sample to be tested is greater than the temperature standard deviation of the normal shaft sample, it is determined that the temperature standard deviation of the shaft sample to be tested is abnormal; otherwise, it is determined that the temperature standard deviation of the shaft sample to be tested is normal;

[0158] ③ If the load extreme value number of the shaft sample to be tested is greater than the load extreme value number of the normal shaft sample, it is determined that the load extreme value number of the shaft sample to be tested is abnormal; otherwise, it is determined that the load extreme value number of the shaft sample to be tested is normal;

[0159] ④ If the frequency peak offset of the shaft sample to be tested is greater than the frequency peak offset of the normal shaft sample, it is determined that the frequency peak offset of the shaft sample to be tested is abnormal; otherwise, it is determined that the frequency peak offset of the shaft sample to be tested is normal;

[0160] ⑤ If the modal shift value of the shaft sample to be tested is greater than the modal shift value of the normal shaft sample, the modal shift value of the shaft sample to be tested is judged to be abnormal; otherwise, the modal shift value of the shaft sample to be tested is judged to be normal.

[0161] Based on the load extreme value number, standard temperature difference, and the determined damage factor, modal transition value, and frequency peak offset, the specific failure process of the shaft specimen to be tested is determined as follows:

[0162] If the "modal transition value" is abnormal, the failure type of the shaft specimen to be tested can be directly determined based on the "temperature standard deviation":

[0163] (1) If the "temperature standard deviation" is normal, the failure type of the shaft sample to be tested is fatigue wear;

[0164] (2) If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear;

[0165] If the "modal transition value" is normal, further determine whether the "damage factor" is abnormal:

[0166] (1) If the "damage factor" is normal, the failure type of the shaft specimen to be tested can be directly determined based on the "frequency peak offset":

[0167] ① If the "frequency peak offset" is normal, the failure type of the shaft specimen to be tested is slight corrosion wear; it is worth noting that severe corrosion wear can be directly judged by observation.

[0168] ② If the "frequency peak offset" is abnormal, the failure type of the shaft specimen to be tested is abrasive wear;

[0169] (2) If the "damage factor" is abnormal, further determine whether the "temperature standard deviation" is abnormal:

[0170] ① If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear;

[0171] ② If the "temperature standard deviation" is normal, further determine whether the "load extreme value number" is abnormal:

[0172] a. If the "Load Extreme Number" is normal, the failure type of the shaft specimen to be tested is abrasive wear;

[0173] b. If the "load extreme value number" is abnormal, the failure type of the shaft specimen to be tested is fatigue wear.

[0174] In this embodiment, the specific failure type of the shaft specimen to be tested is determined based on the obtained evaluation indicators. The specific process is as follows:

[0175] According to the damage factor calculation formula, the damage factor DF of the shaft specimen to be tested is calculated to be 29.3, while the damage factor DF of the normal shaft specimen is calculated to be 20. The vibration acceleration of the shaft specimen (including the shaft specimen to be tested and the normal shaft specimen) under a given external force is obtained using an exciter, and the frequency peaks under this state are obtained through fast Fourier transform (FFT) analysis. The frequency peak offset is calculated to be 0.2Hz using the formula. At the same time, the test bench system is simplified to a two-degree-of-freedom system consisting of the shaft specimen and other components, and the modal analysis of this system is performed based on this. In this embodiment, the modal transition value of the shaft specimen to be tested is 2.1, and the modal transition value of the normal shaft specimen is 2.03.

[0176] In this embodiment, based on the results of the above-mentioned evaluation indicators and in combination with the corresponding judgment process, the specific process of judging the failure type of the shaft specimen to be tested in this embodiment is as follows:

[0177] First, the modal transition values ​​of the tested shaft sample and the normal shaft sample are compared. The results show that the modal transition value of the tested shaft sample is within the normal range. Subsequently, it is judged whether the damage factor is abnormal. In this embodiment, the damage factor DF of the tested shaft sample is 29.3, which is significantly higher than the damage factor value of the normal shaft sample. It can be determined that its damage factor is abnormal. Since the temperature standard deviation of the outer surface of the tested shaft sample differs from the test value of the normal shaft by 20%, and the normal range is a difference of ±50%, it is determined that the temperature standard deviation of the tested shaft sample is within the normal range. Finally, the load extreme value number is analyzed. Since the load extreme value number of the tested shaft sample is 24, which is significantly greater than the normal range (10±5), it can be determined that the load extreme value number is abnormal. In summary, the damage factor and load extreme value number of the tested shaft are abnormal, while the temperature standard deviation is normal, so it can be determined that the tested shaft sample is fatigue wear failure.

[0178] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications made to the present invention by those skilled in the art without departing from the spirit of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle, characterized in that: The following steps are involved: 1) Determine a single-cycle operating condition that simulates actual operation, and install the normal shaft sample and the shaft sample to be tested on a simulation test bench to perform a failure cycle detection test, and obtain monitoring data of the normal shaft sample and the shaft sample to be tested respectively; 2) Processing the acquired monitoring data of the normal shaft sample and the shaft sample to be tested to obtain the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested respectively; 3) Analyze the results obtained in step 2) to determine the evaluation index, and then use the determined evaluation index to judge the specific failure type of the shaft specimen to be tested.

2. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 1, characterized in that: In step 1), the specific process of the failure cycle detection test is as follows: 1-1) Determine the single-cycle operating condition for simulating actual operation based on the design speed of the road type and the proportion of road types in the city; 1-2) Install the normal shaft sample and the shaft sample to be tested on the simulation test bench respectively, and set up multiple sensors near the installation contact points; 1-3) The installed normal shaft sample and the shaft sample to be tested are debugged, and under single-cycle working conditions, multiple sensors installed near the installation contact points are used to collect monitoring data of the normal shaft sample and the shaft sample to be tested.

3. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 2, characterized in that: The single-cycle operating conditions include standard operating conditions, extreme operating conditions, and speed-changing operating conditions, and the monitoring data include acceleration monitoring data, load monitoring data, and temperature monitoring data.

4. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 3, characterized in that: In step 2), the acquired monitoring data of the normal shaft sample and the shaft sample to be tested are processed to obtain the acceleration root mean square, frequency peak amplitude, load standard deviation, load extreme value number, and temperature standard deviation of the normal shaft sample and the shaft sample to be tested. The specific method is as follows: 2-1) Calculate the acceleration root mean square using the acceleration monitoring data, and transform the acceleration monitoring data to obtain the frequency peak amplitude; 2-2) Calculate the load standard deviation based on the load monitoring data and record the number of load extremes; 2-3) Calculate the temperature standard deviation using temperature monitoring data.

5. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 1, characterized in that: In step 3), based on the results obtained in step 2), various evaluation indicators are determined, including damage factor, modal transition value, frequency peak offset, number of load extremes, and temperature standard deviation.

6. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 5, characterized in that: The specific formula of the damage factor is as follows: DF=w1Accrms+w2F std +w3T std Where DF is the damage factor; w1 is the weighting coefficient of the acceleration root mean square; Acc rms is the root mean square acceleration of the shaft specimen to be tested; w2 is the weighting coefficient of the load standard deviation; F std is the load standard deviation of the shaft sample to be tested; w3 is the weighting coefficient of the temperature standard deviation; T std is the temperature standard deviation of the shaft sample to be tested.

7. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 5, characterized in that: The specific formula of the modal transition value is as follows: Where D is the modal transition value; ω i is the i-th component of the main mode of the normal shaft specimen; ω1 is the first component of the main mode of the normal shaft specimen; ω2 is the second component of the main mode of the normal shaft specimen; ω sti is the i-th component of the main mode of the shaft specimen to be tested; ω st1 is the first component of the main mode of the shaft specimen to be tested; ω st2 It is the second component of the main mode of the shaft specimen to be tested.

8. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 5, characterized in that: The specific formula of the frequency peak offset is as follows: Where Δf is the frequency peak offset; f i is the ith frequency peak of the normal shaft specimen; f sti is the i-th frequency peak of the shaft sample to be tested; f1 is the first frequency peak of the normal shaft sample; f2 is the second frequency peak of the normal shaft sample; f st1 is the first frequency peak of the shaft sample to be tested; f st2 It is the second frequency peak of the shaft sample to be tested.

9. The method for detecting failure of a planetary gear shaft of a differential of a new energy vehicle according to claim 5, characterized in that: In step 3), based on the number of load extremes, temperature standard deviation, and the determined damage factor, modal transition value, and frequency peak offset, the specific failure type of the shaft specimen to be tested is determined, including: If the "modal transition value" is abnormal, the failure type of the shaft specimen to be tested can be directly determined based on the "temperature standard deviation": (1) If the "temperature standard deviation" is normal, the failure type of the shaft specimen to be tested is fatigue wear; (2) If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear; If the "modal transition value" is normal, further determine whether the "damage factor" is abnormal: (1) If the "damage factor" is normal, the failure type of the shaft specimen to be tested can be directly determined based on the "frequency peak offset": ① If the "frequency peak offset" is normal, the failure type of the shaft specimen to be tested is slight corrosion wear; ② If the "frequency peak offset" is abnormal, the failure type of the shaft specimen to be tested is abrasive wear; (2) If the "damage factor" is abnormal, further determine whether the "temperature standard deviation" is abnormal: ① If the "temperature standard deviation" is abnormal, the failure type of the shaft specimen to be tested is adhesive wear; ② If the "Temperature Standard Deviation" is normal, further determine whether the "Load Extreme Value Number" is abnormal: a. If the "Load Extreme Number" is normal, the failure type of the shaft specimen to be tested is abrasive wear; b. If the "Load Extreme Number" is abnormal, the failure type of the shaft specimen to be tested is fatigue wear.

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