A planetary reducer gear shaft machining method for reducing machining error

Abstract

The application relates to the grinding process technical field and discloses a planetary reducer gear shaft machining method capable of reducing machining errors, which comprises the following steps: setting an initial value of a PI coefficient, adjusting grinding parameters of grinding treatment by using a PID control algorithm, collecting surface roughness before and after grinding treatment and vibration values of the grinding treatment; determining a processing effect stability degree of the grinding treatment and a predicted value of surface roughness of the next grinding treatment; determining a PI coefficient reference value of the grinding treatment, vibration-grinding precision correlation and a PI coefficient parameter; determining a PI coefficient optimization value according to the PI coefficient reference value of the grinding treatment, the value of the PI coefficient, the vibration-grinding precision correlation and the PI coefficient parameter; and realizing the planetary reducer gear shaft machining according to the PI coefficient optimization value. The application can reduce cutting machining errors and improve the accuracy of the planetary reducer gear shaft.

Description

Technical Field

[0001] This application relates to the field of grinding technology, specifically to a method for machining planetary reducer gear shafts to reduce machining errors. Background Technology

[0002] Reducing machining errors in planetary reducer gear shafts can improve meshing performance, increase transmission efficiency, meet the demands of high-end machinery, and reduce maintenance costs. The grinding quality of the gear shaft surface, a core component of the planetary reducer, directly affects the overall performance of the machine. To ensure the grinding quality of the gear shaft surface, a PID control algorithm is typically used to adjust the grinding parameters with a fixed PI coefficient.

[0003] However, the surface roughness of different planetary reducer gear shafts treated by different pre-processing techniques is not the same. Using only a fixed PI coefficient to adjust the grinding parameters cannot adapt to the dynamic changes in the surface roughness of different planetary reducer gear shafts, which can easily lead to insufficient or excessive grinding, affecting the machining accuracy of the planetary reducer gear shaft after the grinding parameters are adjusted. Summary of the Invention

[0004] This application provides a method for machining planetary reducer gear shafts to reduce machining errors, thereby solving the problem that grinding parameter adjustment cannot adapt to the different surface roughness of different planetary reducer gear shafts, which easily leads to insufficient or excessive grinding and thus insufficient machining accuracy. The specific technical solution adopted is as follows:

[0005] One embodiment of this application provides a method for machining planetary reducer gear shafts to reduce machining errors. The method includes the following steps:

[0006] Set the initial value of the PI coefficient of the PID control algorithm, use the PID control algorithm to adjust the grinding parameters of the grinding process, and continuously collect the surface roughness of the first preset number of planetary reducer gear shafts before and after the grinding process, as well as the vibration value of the grinding process.

[0007] Based on the difference in surface roughness before and after the same grinding process, the grinding effect of the same grinding process is determined. Based on the difference in the grinding effect of the first preset number of consecutive grinding processes and the difference in surface roughness, the stability of the processing effect of the last grinding process in all grinding processes and the predicted value of the surface roughness after the next grinding process of the last grinding process in all grinding processes are determined.

[0008] Based on the surface roughness before and after the first preset number of grinding processes, the grinding effect, the stability of the grinding effect, the vibration value, the value of the PI coefficient during the grinding process, and the predicted value of the surface roughness after the next grinding process, the reference value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes is determined, as well as the vibration-grinding accuracy correlation and PI coefficient parameters for the last grinding process in all grinding processes.

[0009] Based on the reference value of the PI coefficient for grinding, the value of the PI coefficient, the correlation between vibration and grinding accuracy, and the PI coefficient parameters, the optimized value of the PI coefficient for the next grinding process is determined, and the planetary reducer gear shaft is machined according to the optimized PI coefficient value.

[0010] Furthermore, the vibration value of the grinding process is specifically as follows:

[0011] The average value of all vibration data from the same grinding process is recorded as the vibration value of the grinding process.

[0012] Furthermore, the specific method for determining the grinding effect of the grinding process is as follows:

[0013] The absolute value of the difference in surface roughness before and after the same grinding process is denoted as the roughness difference of the same grinding process, and the ratio of the roughness difference of the same grinding process to the surface roughness after the process is denoted as the grinding effect of the same grinding process.

[0014] Furthermore, the specific method for determining the stability of the processing effect of the grinding process is as follows:

[0015] The variance of the grinding effect of the first preset number of planetary reducer gear shafts in the grinding process is denoted as the first variance of the last grinding process in all grinding processes.

[0016] The variance of the surface roughness of a first preset number of planetary reducer gear shafts after grinding is denoted as the second variance of the last grinding process in all grinding processes.

[0017] The positive correlation between the first and second variances of the grinding process is recorded as the stability of the processing effect of the last grinding process among all grinding processes.

[0018] Furthermore, the specific method for determining the predicted surface roughness value after the next grinding process following the last grinding process in all the grinding processes is as follows:

[0019] Based on the surface roughness of the first preset number of planetary reducer gear shafts after grinding, a predicted value for the surface roughness after the next grinding process is obtained.

[0020] Furthermore, the method for obtaining the PI coefficient reference value is as follows:

[0021] Based on the surface roughness before and after grinding, the grinding effect and the stability of the grinding effect, and the predicted value of the surface roughness after the next grinding, the first preset number of grinding processes are clustered to obtain the first grinding cluster.

[0022] The average value of the PI coefficient during all grinding processes within the first grinding cluster where the last grinding process is located is recorded as the reference value of the PI coefficient for the next grinding process after the last grinding process.

[0023] Furthermore, the specific calculation method for the vibration-grinding accuracy correlation is as follows:

[0024] Based on the surface roughness before and after grinding, the vibration value of grinding, and the value of the PI coefficient during grinding, the first preset number of grinding processes are clustered to obtain the second grinding cluster.

[0025] A vibration value sequence is constructed based on the vibration values ​​of all grinding processes within the second cluster of grinding processes where the last grinding process is located.

[0026] Based on the surface roughness of all grinding processes within the second grinding cluster where the last grinding process is located, a post-processing surface roughness sequence is constructed.

[0027] The absolute value of the correlation coefficient between the vibration value sequence and the post-processing surface roughness sequence is denoted as the vibration-grinding accuracy correlation of the last grinding process in all grinding processes.

[0028] Furthermore, the specific method for determining the PI coefficient parameter is as follows:

[0029] Based on the surface roughness before different grinding processes, the vibration values ​​of the first preset number of grinding processes are clustered to obtain the third grinding cluster;

[0030] The average vibration value of all grinding processes contained in the third grinding cluster is denoted as the average vibration value of the third grinding cluster.

[0031] Based on the vibration mean of all grinding third clusters, a vibration threshold is determined. The average value of the PI coefficient of the grinding processes included in all grinding third clusters with a vibration mean less than the vibration threshold is recorded as the PI coefficient parameter of the last grinding process among all grinding processes.

[0032] Furthermore, the formula for calculating the optimized value of the PI coefficient is:

[0033]

[0034] in, This represents the optimized PI coefficient value for the next grinding process following the last grinding process in all grinding processes. This indicates the vibration-grinding accuracy correlation of the last grinding process in all grinding processes; This represents the value of the PI coefficient for the last grinding process out of all grinding processes. This represents the PI coefficient reference value for the next grinding process following the last grinding process in all grinding processes; This represents the PI coefficient parameter of the last grinding process in all grinding processes.

[0035] Furthermore, the specific method for machining the planetary reducer gear shaft based on the PI coefficient optimization value includes:

[0036] The optimized PI coefficient value of the next grinding process after the last grinding process in all grinding processes is used as the PI coefficient value of the PID control algorithm for this grinding process. The grinding parameters of the planetary reducer gear shaft machining are adjusted using the PID control algorithm.

[0037] The beneficial effects of this application are:

[0038] This application first evaluates the processing effect of grinding on the planetary reducer gear shaft based on the difference in surface roughness before and after the same grinding process, obtaining the grinding effect and the stability of the grinding effect. The greater the stability of the grinding effect, the better the processing effect for the first preset number of consecutive planetary reducer gear shafts. In this case, the PI coefficient value of the selected PID control algorithm is more reasonable, and there is less need to adjust the PI coefficient value. The application also determines the predicted value of the surface roughness after the next grinding process. To better obtain a more suitable PI coefficient value for the PID control algorithm, improve processing accuracy, and reduce processing errors, the grinding process... The relationship between the vibration value and the precision of the grinding process is evaluated to obtain the vibration-grinding precision correlation. Based on the evaluation value of each grinding process, the reference value and parameter of the PI coefficient are determined. Finally, based on the reference value of the PI coefficient, the value of the PI coefficient, the vibration-grinding precision correlation, and the PI coefficient parameter, the optimized value of the PI coefficient for the next grinding process is determined. The planetary reducer gear shaft is processed based on the optimized PI coefficient value. This solves the problem that the grinding parameter adjustment cannot adapt to the different surface roughness of different planetary reducer gear shafts, which easily leads to under-grinding or over-grinding and insufficient machining precision. This reduces cutting errors and improves the precision of the planetary reducer gear shaft. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a schematic flowchart of a planetary reducer gear shaft machining method for reducing machining errors, provided as an embodiment of this application.

[0041] Figure 2 This is a flowchart illustrating the process of obtaining grinding effects according to one embodiment of this application. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0043] Please see Figure 1 The diagram illustrates a process flow chart of a planetary reducer gear shaft machining method for reducing machining errors according to an embodiment of this application. The method includes the following steps:

[0044] Step S001: Set the initial value of the PI coefficient of the PID control algorithm, use the PID control algorithm to adjust the grinding parameters of the grinding process, and continuously collect the surface roughness of the first preset number of planetary reducer gear shafts before and after the grinding process, as well as the vibration value of the grinding process.

[0045] The initial value of the PI coefficient of the PID control algorithm is set, and the grinding parameters are adjusted by the PID control algorithm to continuously grind the first preset number of planetary reducer gear shafts.

[0046] A laser roughness sensor was used to collect the surface roughness of the planetary reducer gear shaft before and after grinding. A vibration sensor was used to collect the vibration data of the grinding wheel spindle during the grinding process of the planetary reducer gear shaft. The average value of all vibration data of the planetary reducer gear shaft in the same grinding process was recorded as the vibration value of the grinding process.

[0047] Preferably, in one embodiment of this application, the data sampling frequency is 1 kHz when collecting vibration data. In practical applications, as other implementations, the implementer can decide the value of the sampling frequency according to the actual situation, and this application does not impose any special restrictions.

[0048] The process involves continuously collecting surface roughness data and vibration values ​​from a first preset number of planetary reducer gear shafts before and after grinding. Based on this data, the PI coefficient value of the PID control algorithm is determined for the next planetary reducer gear shaft grinding process. This ensures that the next grinding operation better meets the surface roughness requirements of the planetary reducer gear shaft, avoiding under-grinding or over-grinding. In this embodiment, the first preset number is set to 50.

[0049] Thus, the surface roughness of the planetary reducer gear shaft before and after grinding, as well as the vibration value of the grinding process, are obtained.

[0050] Step S002: Based on the difference in surface roughness before and after the same grinding process, determine the grinding effect of the same grinding process. Based on the difference in grinding effect of the first preset number of consecutive grinding processes and the difference in surface roughness, determine the stability of the processing effect of the last grinding process in all grinding processes and the predicted value of the surface roughness after the next grinding process of the last grinding process in all grinding processes.

[0051] In order to adjust the grinding parameters in a timely manner, it is necessary to adjust the value of the PI coefficient of the PID control algorithm according to the grinding effect of the planetary reducer gear shaft. This will make the next grinding process more in line with the surface roughness requirements of the planetary reducer gear shaft and avoid the problems of insufficient or excessive grinding.

[0052] The grinding effect of the same grinding process is determined by the difference in surface roughness before and after the same grinding process.

[0053] The absolute value of the difference in surface roughness before and after the same grinding process is denoted as the roughness difference of the same grinding process, and the ratio of the roughness difference of the same grinding process to the surface roughness after the process is denoted as the grinding effect of the same grinding process.

[0054] The greater the grinding effect on the planetary reducer gear shaft, the better the machining effect of the grinding process on the planetary reducer gear shaft. The flowchart for obtaining the grinding effect is as follows: Figure 2 As shown.

[0055] The variance of the grinding effect of a first preset number of planetary reducer gear shafts in the grinding process is denoted as the first variance of the last grinding process in all grinding processes; the variance of the surface roughness of a first preset number of planetary reducer gear shafts after grinding is denoted as the second variance of the last grinding process in all grinding processes; the positive correlation result between the first variance and the second variance of the grinding process is denoted as the stability of the processing effect of the last grinding process in all grinding processes.

[0056] It is understood that a positive correlation is applied to the first and second variances of the grinding process, ensuring that the first and second variances of the grinding process are positively correlated with the stability of the grinding effect. It is also understood that the positive correlation in this application refers to the relationship between the independent and dependent variables, where the independent variables are the first and second variances of the grinding process, and the dependent variable is the stability of the grinding effect. A positive correlation means that the dependent variable increases (decreases) as the independent variable increases (decreases), and can be an additive or multiplicative relationship.

[0057] Preferably, as an embodiment of this application, the normalized value of the reciprocal of the mean of the first variance and the second variance of the grinding process is recorded as the stability of the processing effect of the last grinding process among all grinding processes.

[0058] In this embodiment, the sigmoid function is used to calculate the normalized value. The sigmoid function is a well-known technique and will not be described in detail here. As for other implementations, the implementer can use other methods from the prior art, such as the tanh function. During the reciprocal calculation, to avoid the denominator being zero, a preset value needs to be added to the denominator. In this embodiment, the preset value is 0.01.

[0059] The greater the stability of the grinding effect, the better the grinding effect of the first preset number of planetary reducer gear shafts. At this time, the PI coefficient of the selected PID control algorithm is more reasonable, and there is less need to adjust the PI coefficient.

[0060] It is important to understand that when the number of grinding cycles prior to the grinding process is less than the first preset number, the surface roughness before and after the grinding process, as well as the vibration value of the grinding process, are collected from historical grinding processes to calculate the stability of the grinding effect.

[0061] The surface roughness of the first preset number of planetary reducer gear shafts after grinding is arranged sequentially to obtain a surface roughness sequence. The surface roughness sequence is then processed using a time series prediction algorithm to obtain the predicted value of the surface roughness after the next grinding process following the last grinding process.

[0062] In this embodiment, the ARIMA autoregressive integral moving average model in time series forecasting algorithms is used to predict surface roughness. In practical applications, as other implementation methods, in addition to achieving the purpose of data prediction, implementers can use other existing technologies such as autoregressive model (AR), moving average model (MA), autoregressive moving average model, seasonal autoregressive integral moving average model (SARIMA), exponential smoothing method, etc., to achieve data prediction.

[0063] Thus, the stability of the grinding effect and the predicted values ​​of the surface roughness after the next grinding process are obtained.

[0064] Step S003: Based on the surface roughness before and after the first preset number of grinding processes, the grinding effect, the stability of the grinding effect, the vibration value, the value of the PI coefficient during the grinding process, and the predicted value of the surface roughness after the next grinding process, determine the reference value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes, as well as the vibration-grinding accuracy correlation and PI coefficient parameters for the last grinding process in all grinding processes.

[0065] The surface roughness before and after grinding, the grinding effect and the stability of the grinding effect, and the predicted surface roughness after the next grinding are arranged in sequence to obtain the first feature sequence of grinding. The Euclidean distance between the first feature sequences of different grinding is used as the distance between different grinding. The first preset number of grinding processes are clustered to obtain the first grinding cluster.

[0066] The average value of the PI coefficient during all grinding processes within the first grinding cluster where the last grinding process is located is recorded as the reference value of the PI coefficient for the next grinding process after the last grinding process.

[0067] The rotational speed and feed rate of the grinding tool affect the vibration data of the grinding process. The greater the vibration during grinding, the lower the grinding accuracy. In order to obtain a more suitable PI coefficient value for the PID control algorithm, improve the machining accuracy, and reduce the machining error, the relationship between the vibration value and the accuracy of the grinding process is evaluated.

[0068] The surface roughness before and after grinding, the vibration value of grinding, and the value of PI coefficient during grinding are arranged in sequence to obtain the second feature sequence of grinding. The Euclidean distance between the second feature sequences of different grinding processes is used as the distance between different grinding processes. The first preset number of grinding processes are clustered to obtain the second grinding cluster.

[0069] The vibration values ​​of all grinding processes within the second grinding cluster containing the last grinding process are arranged in chronological order to obtain a vibration value sequence. The surface roughness of all grinding processes within the second grinding cluster containing the last grinding process is arranged in chronological order to obtain a post-processing surface roughness sequence. The absolute value of the correlation coefficient between the vibration value sequence and the post-processing surface roughness sequence is denoted as the vibration-grinding accuracy correlation of the last grinding process among all grinding processes.

[0070] In this embodiment, the Pearson correlation coefficient is used to calculate the correlation coefficient between the vibration value sequence and the post-processed surface roughness sequence, i.e., the Pearson correlation coefficient is used to evaluate the correlation between the two sequences. As another implementation, based on achieving the purpose of measuring the correlation between the two sequences, the implementer may use other methods in the prior art, such as cosine similarity, Spearman correlation coefficient, etc., to obtain the correlation between the two sequences, and this application does not impose any special limitations.

[0071] The greater the correlation between vibration and grinding accuracy, the more significant the relationship between the vibration value of the grinding process and the accuracy of the grinding process. When determining the value of the PI coefficient of the PID control algorithm for the next grinding process, the influence of the vibration value of the grinding process should be taken into consideration.

[0072] The Euclidean distance between the surface roughness levels before different grinding processes is used as the distance between different grinding processes. The vibration values ​​of the first preset number of grinding processes are clustered to obtain a third grinding cluster. The mean of the vibration values ​​of all grinding processes included in the third grinding cluster is recorded as the vibration mean of the third grinding cluster. The Otsu's method is used to process the vibration mean of all grinding third clusters to obtain a vibration threshold. The mean of the PI coefficients of the grinding processes included in all grinding third clusters with a vibration mean less than the vibration threshold is recorded as the PI coefficient parameter of the last grinding process.

[0073] In this embodiment, the DBSCAN clustering algorithm is used for clustering. In practical applications, while achieving the goal of clustering, implementers may use other existing methods such as Mean Shift clustering, OPTICS clustering, Gaussian Mixture Models clustering, and Spectral Clustering for clustering. This application does not impose any special restrictions.

[0074] At this point, the reference value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes is obtained, as well as the vibration-grinding accuracy correlation and PI coefficient parameters of the last grinding process in all grinding processes.

[0075] Step S004: Based on the reference value of the PI coefficient for grinding, the value of the PI coefficient, the correlation between vibration and grinding accuracy, and the PI coefficient parameters, determine the optimized value of the PI coefficient for the next grinding process, and realize the machining of the planetary reducer gear shaft based on the optimized value of the PI coefficient.

[0076] Based on the reference value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes, as well as the value of the PI coefficient for the last grinding process in all grinding processes, the vibration-grinding accuracy correlation, and the PI coefficient parameters, the optimized value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes is determined. The formula for calculating the optimized PI coefficient is:

[0077]

[0078] in, This represents the optimized PI coefficient value for the next grinding process following the last grinding process in all grinding processes. This indicates the vibration-grinding accuracy correlation of the last grinding process in all grinding processes; This represents the value of the PI coefficient for the last grinding process out of all grinding processes. This represents the PI coefficient reference value for the next grinding process following the last grinding process in all grinding processes; This represents the PI coefficient parameter of the last grinding process in all grinding processes.

[0079] The optimized PI coefficient value of the next grinding process after the last grinding process in all grinding processes is used as the PI coefficient value of the PID control algorithm for this grinding process. The grinding parameters of the planetary reducer gear shaft machining are adjusted using the PID control algorithm.

[0080] The grinding parameters are the spindle speed or feed rate.

[0081] This completes the machining of the planetary reducer gear shaft, and minimizes machining errors during the process.

[0082] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for machining planetary reducer gear shafts to reduce machining errors, characterized in that, The method includes the following steps: Set the initial value of the PI coefficient of the PID control algorithm, use the PID control algorithm to adjust the grinding parameters of the grinding process, and continuously collect the surface roughness of the first preset number of planetary reducer gear shafts before and after the grinding process, as well as the vibration value of the grinding process. Based on the difference in surface roughness before and after the same grinding process, the grinding effect of the same grinding process is determined. Based on the difference in the grinding effect of the first preset number of consecutive grinding processes and the difference in surface roughness, the stability of the processing effect of the last grinding process in all grinding processes and the predicted value of the surface roughness after the next grinding process of the last grinding process in all grinding processes are determined. Based on the surface roughness before and after the first preset number of grinding processes, the grinding effect, the stability of the grinding effect, the vibration value, the value of the PI coefficient during the grinding process, and the predicted value of the surface roughness after the next grinding process, the reference value of the PI coefficient for the next grinding process after the last grinding process in all grinding processes is determined, as well as the vibration-grinding accuracy correlation and PI coefficient parameters for the last grinding process in all grinding processes. Based on the reference value of the PI coefficient for grinding, the value of the PI coefficient, the correlation between vibration and grinding accuracy, and the PI coefficient parameters, the optimized value of the PI coefficient for the next grinding process is determined, and the planetary reducer gear shaft is machined according to the optimized PI coefficient value.

2. The method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The vibration value of the grinding process is specifically: The average value of all vibration data from the same grinding process is recorded as the vibration value of the grinding process.

3. The method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific method for determining the grinding effect of the aforementioned grinding process is as follows: The absolute value of the difference in surface roughness before and after the same grinding process is denoted as the roughness difference of the same grinding process, and the ratio of the roughness difference of the same grinding process to the surface roughness after the process is denoted as the grinding effect of the same grinding process.

4. The method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific method for determining the stability of the processing effect of the grinding process is as follows: The variance of the grinding effect of the first preset number of planetary reducer gear shafts in the grinding process is denoted as the first variance of the last grinding process in all grinding processes. The variance of the surface roughness of a first preset number of planetary reducer gear shafts after grinding is denoted as the second variance of the last grinding process in all grinding processes. The positive correlation between the first and second variances of the grinding process is recorded as the stability of the processing effect of the last grinding process among all grinding processes.

5. A method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific method for determining the predicted surface roughness value after the next grinding process following the last grinding process in all grinding processes is as follows: Based on the surface roughness of the first preset number of planetary reducer gear shafts after grinding, a predicted value for the surface roughness after the next grinding process is obtained.

6. A method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The method for obtaining the PI coefficient reference value is as follows: Based on the surface roughness before and after grinding, the grinding effect and the stability of the grinding effect, and the predicted value of the surface roughness after the next grinding, the first preset number of grinding processes are clustered to obtain the first grinding cluster. The average value of the PI coefficient during all grinding processes within the first grinding cluster where the last grinding process is located is recorded as the reference value of the PI coefficient for the next grinding process after the last grinding process.

7. The method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific calculation method for the vibration-grinding accuracy correlation is as follows: Based on the surface roughness before and after grinding, the vibration value of grinding, and the value of the PI coefficient during grinding, the first preset number of grinding processes are clustered to obtain the second grinding cluster. A vibration value sequence is constructed based on the vibration values ​​of all grinding processes within the second cluster of grinding processes where the last grinding process is located. Based on the surface roughness of all grinding processes within the second grinding cluster where the last grinding process is located, a post-processing surface roughness sequence is constructed. The absolute value of the correlation coefficient between the vibration value sequence and the post-processing surface roughness sequence is denoted as the vibration-grinding accuracy correlation of the last grinding process in all grinding processes.

8. A method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific method for determining the PI coefficient parameter is as follows: Based on the surface roughness before different grinding processes, the vibration values ​​of the first preset number of grinding processes are clustered to obtain the third grinding cluster; The average vibration value of all grinding processes contained in the third grinding cluster is denoted as the average vibration value of the third grinding cluster. Based on the vibration mean of all grinding third clusters, a vibration threshold is determined. The average value of the PI coefficient of the grinding processes included in all grinding third clusters with a vibration mean less than the vibration threshold is recorded as the PI coefficient parameter of the last grinding process among all grinding processes.

9. A method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The formula for calculating the optimized value of the PI coefficient is: in, This represents the optimized PI coefficient value for the next grinding process following the last grinding process in all grinding processes. This indicates the vibration-grinding accuracy correlation of the last grinding process in all grinding processes; This represents the value of the PI coefficient for the last grinding process out of all grinding processes. This represents the PI coefficient reference value for the next grinding process following the last grinding process in all grinding processes; This represents the PI coefficient parameter of the last grinding process in all grinding processes.

10. A method for machining planetary reducer gear shafts to reduce machining errors according to claim 1, characterized in that, The specific method for machining the planetary reducer gear shaft based on the PI coefficient optimization value includes: The optimized PI coefficient value of the next grinding process after the last grinding process in all grinding processes is used as the PI coefficient value of the PID control algorithm for this grinding process. The grinding parameters of the planetary reducer gear shaft machining are adjusted using the PID control algorithm.

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