A fine machining method and machining device for a vacuum pump rotor

Abstract

The present invention relates to the technical field of fine machining of vacuum pump rotors, and provides a fine machining method and a machining device for vacuum pump rotors, including: collecting vibration data and milling cutter rotation speed during the machining process of a Roots vacuum pump rotor, and obtaining a vibration sequence of the main shaft according to the vibration data of the same main shaft; marking the target main shaft and the target vibration data, and determining the main shaft vibration abnormality coefficient of the target main shaft; determining the synergy of different main shafts and the main shaft difference coefficient of the target main shaft; combining the milling cutter rotation speed of the main shaft at all acquisition moments, adjusting the actual cutting speed of the milling cutter of the main shaft, and realizing the fine machining of the vacuum pump rotor. The present invention can improve the machining quality of the vacuum pump rotor.

Description

Technical Field

[0001] The present invention relates to the technical field of fine machining of vacuum pump rotors, and particularly relates to a fine machining method and a machining device for a vacuum pump rotor. Background Art

[0002] The rotor is one of the key components in a Roots vacuum pump. The rotor of a Roots vacuum pump usually consists of two rotor blades that rotate synchronously in opposite directions, and realizes the compression and discharge of gas through rotation to create a vacuum environment. In order to ensure that the rotor of the Roots vacuum pump can still operate normally under the influence of factors such as thermal effects, stress, and vibration, a certain gap needs to be maintained between the two rotors. Since both too large and too small gaps will affect the pumping efficiency of the Roots vacuum pump, and the machining error of the rotor is directly related to the size of the gap, therefore, when machining the rotor of the Roots vacuum pump, it is necessary to adjust the machining parameters in a timely manner through a feedback control system in real time to ensure the pumping efficiency of the Roots vacuum pump.

[0003] During the process of realizing mass production of the rotor of the Roots vacuum pump on a numerically controlled machine tool, the milling cutter may be worn during long-term operation, resulting in a reduction in the coordination between the main shafts of the numerically controlled machine tool. However, the traditional feedback control system is difficult to accurately capture and compensate for the machining error caused by the wear of the milling cutter, often resulting in a decrease in the machining quality of the rotor of the Roots vacuum pump as the number of machined parts increases. Summary of the Invention

[0004] The present invention provides a fine machining method and a machining device for a vacuum pump rotor to solve the problem that the wear of the milling cutter gradually generated during the machining process of the vacuum pump rotor affects the machining quality of the vacuum pump rotor. The specific technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a fine machining method for a vacuum pump rotor, and the method includes the following steps:

[0006] During the machining process of the rotor of the Roots vacuum pump, collect the vibration data of each main shaft of the numerically controlled machine tool and the milling cutter speed of each milling cutter, and obtain the vibration sequence of the same main shaft according to the vibration data of the same main shaft;

[0007] Denote any one of the main shafts as the target main shaft, and denote any one of the vibration data in the vibration sequence of the target main shaft as the target vibration data. According to the change trend of the vibration data in the vibration sequence of the target main shaft, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude. According to all the abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target main shaft, and the autocorrelation of the vibration sequence of the target main shaft, determine the main shaft vibration abnormal coefficient of the target main shaft;

[0008] Determine the synergy of different main shafts based on the correlation of vibration data of vibration sequences of different main shafts. Determine the main shaft difference coefficient of the target main shaft based on the main shaft vibration anomaly coefficient of the target main shaft, the synergy of all different main shafts, as well as all abnormal amplitudes of all main shafts and the recovery steady time of all abnormal amplitudes.

[0009] Adjust the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool according to the milling cutter speed of the target main shaft at all acquisition moments and the main shaft difference coefficient of the target main shaft, and adjust the actual cutting speed of the milling cutters of all main shafts of the numerical control machine tool to achieve fine machining for the vacuum pump rotor.

[0010] Further, the method for determining the abnormal amplitude is as follows:

[0011] Record the local maximum value of the vibration sequence of the target main shaft as the abnormal amplitude.

[0012] Further, the method for determining the recovery steady time of the abnormal amplitude is as follows:

[0013] Construct a sliding window with a length of centered on the target vibration data, perform linear fitting on all vibration data included in the sliding window of the target vibration data to obtain the slope of the fitting line. When the absolute value of the slope of the fitting line is less than , it is determined that the target vibration data is in a steady state; where is the first preset threshold, is the second preset threshold;

[0014] For each abnormal amplitude in the vibration sequence of the target main shaft, record the time interval between the acquisition moment of the first vibration data in a steady state within the acquisition moments after the abnormal amplitude and the acquisition moment of the abnormal amplitude as the recovery steady time of the abnormal amplitude.

[0015] Further, the specific method for determining the main shaft vibration anomaly coefficient of the target main shaft based on all abnormal amplitudes and the recovery steady time of the abnormal amplitudes in the vibration sequence of the target main shaft, as well as the autocorrelation of the vibration sequence of the target main shaft, includes:

[0016] Record the product of the value of the abnormal amplitude in the vibration sequence of the target main shaft and the recovery steady time of the abnormal amplitude as the abnormal fluctuation degree of the abnormal amplitude, and record the mean value of the abnormal fluctuation degrees of all abnormal amplitudes in the vibration sequence of the target main shaft as the abnormal amplitude fluctuation mean value of the target main shaft;

[0017] Set the number of time lag periods to 1, and calculate the time autocorrelation coefficient of the vibration sequence of each main shaft respectively;

[0018] Determine the spindle vibration anomaly coefficient of the target spindle based on the average value of the abnormal amplitude fluctuations of the target spindle and the autocorrelation coefficient of the vibration sequence of the target spindle over time.

[0019] Further, the specific method for determining the spindle vibration anomaly coefficient of the target spindle based on the average value of the abnormal amplitude fluctuations of the target spindle and the autocorrelation coefficient of the vibration sequence of the target spindle over time is as follows:

[0020] Denote the ratio of the average value of the abnormal amplitude fluctuations of the target spindle to the autocorrelation coefficient of the vibration sequence of the target spindle over time as the spindle vibration anomaly coefficient of the target spindle.

[0021] Further, the method for determining the synergy of different spindles is as follows:

[0022] Denote the Pearson correlation coefficient of the vibration sequences of two different spindles as the synergy of the two different spindles.

[0023] Further, the method for obtaining the spindle difference coefficient of the target spindle is as follows:

[0024]

[0025] In the formula, represents the target spindle of the CNC machine tool of the spindle difference coefficient; represents the target spindle of the CNC machine tool of the spindle vibration anomaly coefficient; represents the target spindle of the CNC machine tool , and the th spindle different from the target spindle the average value of all abnormal amplitudes included in the vibration sequence; represents the target spindle of the CNC machine tool , and the th spindle different from the target spindle the standard deviation of the recovery stabilization time of all abnormal amplitudes included in the vibration sequence; represents the number of spindles of the CNC machine tool different from the target spindle ; represents the th spindle different from the target spindle and the target spindle of the synergy; ; represents the adjustment parameter.

[0026] Further, the specific method for adjusting the actual cutting speed of the milling cutter of the target spindle of the CNC machine tool according to the milling cutter speed of the target spindle at all acquisition moments and the spindle difference coefficient of the target spindle is as follows:

[0027] The difference between the mean value of the milling cutter speeds of the target main shaft at all acquisition moments and the mean value of the preset values of the milling cutter speeds at all acquisition moments is denoted as the first difference of the target main shaft, and the product of the normalized value of the main shaft difference coefficient of the target main shaft and the first difference of the target main shaft is denoted as the feedback coefficient of the target main shaft;

[0028] According to the feedback coefficient of the target main shaft, adjust the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool.

[0029] Furthermore, the method of adjusting the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool according to the feedback coefficient of the target main shaft specifically includes:

[0030] Take the feedback coefficient of the target main shaft as the deviation of the PID controller, use the PID controller to output the control signal of the numerical control machine tool, and adjust the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool based on the control signal.

[0031] In a second aspect, an embodiment of the present application provides a fine machining device for a vacuum pump rotor. The fine machining device includes: a data acquisition module, a main shaft abnormality analysis module, a main shaft collaborative analysis module, and a fine machining adjustment module.

[0032] The data acquisition module is used to collect the vibration data of each main shaft of the numerical control machine tool and the milling cutter speed of each milling cutter during the processing of the roots vacuum pump rotor, and obtain the vibration sequence of the same main shaft according to the vibration data of the same main shaft;

[0033] The main shaft abnormality analysis module is used to denote any main shaft as the target main shaft, denote any vibration data in the vibration sequence of the target main shaft as the target vibration data, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude according to the change trend of the vibration data in the vibration sequence of the target main shaft, and determine the main shaft vibration abnormality coefficient of the target main shaft according to all the abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target main shaft, and the autocorrelation of the vibration sequence of the target main shaft;

[0034] The main shaft collaborative analysis module is used to determine the collaboration of different main shafts according to the correlation of the vibration data of the vibration sequences of different main shafts, and determine the main shaft difference coefficient of the target main shaft according to the main shaft vibration abnormality coefficient of the target main shaft, the collaboration of all different main shafts, and all the abnormal amplitudes and the recovery stable time of all the abnormal amplitudes of all the main shafts;

[0035] The fine machining adjustment module is used to adjust the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool according to the milling cutter speed of the target main shaft at all acquisition moments and the main shaft difference coefficient of the target main shaft, and adjust the actual cutting speed of the milling cutters of all the main shafts of the numerical control machine tool to achieve fine machining for the vacuum pump rotor.

[0036] The beneficial effects of the present invention are as follows:

[0037] Based on the limitation that when the rotor of the Roots vacuum pump adopts the rotary cutting method, the vibration data of the spindle corresponding to the worn milling cutter shows the characteristics of periodic abnormal vibration, this application analyzes to obtain the vibration data of the corresponding abnormal vibration and the time when the vibration data of the abnormal vibration returns to normal, and evaluates the degree of abnormality of the vibration sequence of the spindle to determine the spindle vibration abnormality coefficient of the target spindle; further, analyze the coordination among the spindles of the CNC machine tool. Since the working state of the worn milling cutter will change and the cutting force cannot be guaranteed to be unified, it will affect the synchronization and coordination between different spindles. Analyze the coordination of the distribution and change trend of the vibration data of different milling cutters to determine the coordination of different spindles, and further obtain the spindle difference coefficient of the target spindle. The spindle difference coefficient is used to evaluate the influence degree of the milling cutter wear corresponding to the target spindle on the target spindle; finally, according to the milling cutter speed of the target spindle at all acquisition moments and the spindle difference coefficient of the target spindle, adjust the actual cutting speed of the milling cutter of the target spindle of the CNC machine tool, and further adjust the actual cutting speed of the milling cutters of all spindles of the CNC machine tool to achieve fine machining for the vacuum pump rotor, solve the problem that the wear of the milling cutter gradually generated during the processing of the vacuum pump rotor affects the processing quality of the vacuum pump rotor, and ensure the high-quality processing of the vacuum pump rotor. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0039] Figure 1 It is a schematic flowchart of a fine machining method for a vacuum pump rotor provided by an embodiment of the present invention;

[0040] Figure 2 It is a schematic structural diagram of a fine machining device for a vacuum pump rotor provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0042] Please refer to Figure 1 , which shows a flowchart of a fine machining method for a vacuum pump rotor provided by an embodiment of the present invention. The method includes the following steps:

[0043] Step S001, during the machining process of the Roots vacuum pump rotor, collect the vibration data of each spindle of the numerical control machine tool and the milling cutter speed of each milling cutter. According to the vibration data of the same spindle, obtain the vibration sequence of the same spindle.

[0044] In this embodiment, the Roots vacuum pump rotor is selected, and a fine feedback adjustment is performed on the machining process of the Roots vacuum pump rotor to optimize the machining process of the Roots vacuum pump rotor.

[0045] During the machining process of the Roots vacuum pump rotor, use a vibration sensor to collect the vibration data of each spindle of the numerical control machine tool, arrange the vibration data of the same spindle in the order of acquisition time, and obtain the vibration sequence of the same spindle. Use the numerical control machine tool to extract the milling cutter speed of all milling cutters at each acquisition time.

[0046] Preferably, in an embodiment of the present application, the acquisition frequencies of the vibration data and the milling cutter speed are both Hz, and the acquisition durations of the vibration data and the milling cutter speed are both minutes.

[0047] Process the vibration sequence with a Gaussian filter to remove interference noise. Among them, using a Gaussian filter for denoising is a well-known technology, and its implementation process will not be elaborated.

[0048] So far, obtain the vibration sequence of each spindle during the machining process of the Roots vacuum pump rotor.

[0049] Step S002, mark any one spindle as the target spindle, mark any one vibration data in the vibration sequence of the target spindle as the target vibration data. According to the change trend of the vibration data in the vibration sequence of the target spindle, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude. According to all the abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target spindle, and the autocorrelation of the vibration sequence of the target spindle, determine the spindle vibration abnormality coefficient of the target spindle.

[0050] When the numerical control machine tool is machining a large number of Roots vacuum rotors, the milling cutter of the numerical control machine tool will run continuously for a long time. Such continuous long-term operation will cause the milling cutter to wear, resulting in uneven cutting effect and reducing the machining quality of the Roots vacuum pump rotor. The wear of the milling cutter occurs gradually. Therefore, during the working process of the numerical control machine tool, it is necessary to perform feedback control on the speed of the milling cutter according to the actual machining conditions to ensure the quality of the machined Roots vacuum rotor.

[0051] The rotor of a Roots vacuum pump is a three-dimensional figure that is axisymmetric and centrosymmetric. Therefore, multiple main shafts are usually used to synchronously machine the rotor of a Roots vacuum pump, and the operating parameters such as the feed speed, cutting depth, and machining path of different main shafts are kept highly consistent to ensure the synchronization and coordination between the main shafts. When the milling cutter wears, due to the rotary cutting used in the numerical control machine tool for machining the rotor of a Roots vacuum pump, the working state of the milling cutter will change due to wear, resulting in the vibration data of the main shaft corresponding to the milling cutter showing periodic abnormal vibration, and this abnormality will affect the synchronization and coordination between different main shafts. Therefore, the abnormal degree of the vibration sequence of the main shaft and the coordination between the main shafts of the numerical control machine tool can be analyzed, and the working state of the milling cutter can be judged according to the coordination between the main shafts.

[0052] First, analyze the abnormal degree of the vibration sequence of the main shaft.

[0053] When the milling cutter is running normally, the difference between the vibration data of the main shaft corresponding to the milling cutter is small, and the vibration data shows stable and non-periodic characteristics. Therefore, the vibration sequences of the main shafts corresponding to the normally running milling cutters have a high degree of similarity at different lag times. When the milling cutter wears, due to the limitation of the rotary cutting processing method, the worn position of the milling cutter makes periodic contact with the rotor of the Roots vacuum pump being machined. When the worn position of the milling cutter contacts the rotor of the Roots vacuum pump being machined, the amplitude of the main shaft corresponding to the milling cutter will increase significantly, while when the non-worn position of the milling cutter contacts the rotor of the Roots vacuum pump being machined, the amplitude of the main shaft corresponding to the milling cutter will return to the original smaller value. Therefore, when the milling cutter wears, the difference between the vibration data in the vibration sequence of the main shaft corresponding to the milling cutter is large, and the vibration data shows periodic fluctuation characteristics, and the vibration sequences of the main shafts have a low degree of similarity at different lag times.

[0054] Set the number of time lag periods to 1, and calculate the time autocorrelation coefficient of the vibration sequence of each main shaft respectively.

[0055] Among them, calculating the time autocorrelation coefficient of the vibration sequence is a well-known technology, and the implementation process will not be elaborated.

[0056] When the time autocorrelation coefficient of the vibration sequence of the main shaft is larger, the similarity of the vibration sequence of the main shaft at different lag times is larger, and the possibility that the milling cutter of the main shaft is working normally is greater.

[0057] When the milling cutter wears, the vibration data in the vibration sequence of the main shaft corresponding to the milling cutter shows periodic fluctuation characteristics. At the same time, it can be understood that the more severely the milling cutter wears, the more abnormal data appears in the vibration data, the larger the value, and the longer it takes for the vibration data to return to normal.

[0058] Denote any one of the main shafts as the target main shaft, and denote any one of the vibration data in the vibration sequence of the target main shaft as the target vibration data. Construct a sliding window with a length of centered on the target vibration data. Use the least squares linear fitting technique to perform a linear fit on all the vibration data included in the sliding window of the target vibration data, and obtain the slope of the fitted straight line. When the absolute value of the slope of the fitted straight line is less than , it is determined that the target vibration data is in a stable state.

[0059] Among them, is the first preset threshold, is the second preset threshold. Both the first preset threshold and the second preset threshold are preset constants. In this embodiment, the values of the first preset threshold and the second preset threshold are 7 and 0.01 respectively.

[0060] Adopt an automatic multi-scale peak search algorithm to obtain the local maxima of the vibration sequence of the target main shaft and the acquisition times corresponding to the local maxima, and denote all the local maxima as abnormal amplitudes.

[0061] Among them, the process of performing a linear fit using the least squares linear fitting technique and the process of obtaining the local maxima of the vibration sequence using the automatic multi-scale peak search algorithm are both well-known techniques, and the implementation process will not be elaborated here.

[0062] For each abnormal amplitude in the vibration sequence of the target main shaft, denote the time interval between the acquisition time of the first vibration data in a stable state within the acquisition time after the abnormal amplitude and the acquisition time of the abnormal amplitude as the recovery stable time of the abnormal amplitude.

[0063] The recovery stable times of all abnormal amplitudes in the vibration sequences of all main shafts can be obtained in the same way.

[0064] It can be understood that the recovery stable time of the abnormal amplitude is the time required for the abnormal amplitude in the vibration data of the main shaft of the numerical control machine tool corresponding to the abnormal amplitude to return to a stable state.

[0065] According to all the abnormal amplitudes and the recovery stable times of the abnormal amplitudes in the vibration sequence of the target main shaft, as well as the time autocorrelation coefficient of the vibration sequence of the target main shaft, determine the main shaft vibration abnormality coefficient of the target main shaft.

[0066] Preferably, as an embodiment of the present application, the product of the value of the abnormal amplitude in the vibration sequence of the target main shaft and the time for the abnormal amplitude to return to stability is denoted as the abnormal fluctuation degree of the abnormal amplitude, and the average value of the abnormal fluctuation degrees of all the abnormal amplitudes in the vibration sequence of the target main shaft is denoted as the average abnormal amplitude fluctuation of the target main shaft; the ratio of the average abnormal amplitude fluctuation of the target main shaft to the time autocorrelation coefficient of the vibration sequence of the target main shaft is denoted as the main shaft vibration abnormality coefficient of the target main shaft.

[0067] When the milling cutter is worn and the wear is more severe, the abnormal vibration data included in the vibration sequence of the main shaft is larger, the time for the abnormal vibration data to return to stability is longer, and the time autocorrelation coefficient of the vibration sequence of the main shaft is smaller. At this time, the main shaft vibration abnormality coefficient of the main shaft is larger, and the influence degree of the milling cutter wear on the processing quality of the Roots vacuum pump rotor is greater.

[0068] The main shaft vibration abnormality coefficients of all the main shafts of the CNC machine tool can be obtained in the same way. That is to say, for each main shaft of the CNC machine tool, there is a corresponding main shaft vibration abnormality coefficient.

[0069] Thus far, the main shaft vibration abnormality coefficients of all the main shafts of the CNC machine tool have been obtained.

[0070] Step S003: Determine the synergy of different main shafts according to the correlation of the vibration data of the vibration sequences of different main shafts, and determine the main shaft difference coefficient of the target main shaft according to the main shaft vibration abnormality coefficient of the target main shaft, the synergy of all different main shafts, and all the abnormal amplitudes and the time for all the abnormal amplitudes to return to stability of all the main shafts.

[0071] Furthermore, analyze the synergy between the main shafts of the CNC machine tool.

[0072] When the milling cutter is worn, the working state of the milling cutter will change, the cutting force cannot be guaranteed to be unified, and multiple abnormal amplitudes of different sizes different from the normal vibration data are generated, affecting the synchronization and coordination between different main shafts.

[0073] When all the milling cutters of the CNC machine tool are working properly, the distribution and change trend of the vibration data of different main shafts are basically the same, and the synergy is relatively significant; while the distribution and change trend of the vibration data corresponding to the worn milling cutter will be affected by the abnormal vibration data. Therefore, there is a large difference between the distribution and change trend of the vibration data of the worn milling cutter and that of the normally working milling cutter, and the synergy is not obvious.

[0074] Calculate the Pearson correlation coefficient of the vibration sequences of every two different main shafts, and denote the Pearson correlation coefficient of the vibration sequences of the two different main shafts as the synergy of the two different main shafts.

[0075] Among them, calculating the Pearson correlation coefficient of the vibration sequences of two different main shafts is a well-known technology, and the implementation process will not be elaborated here.

[0076] Determine the main shaft difference coefficient of the target main shaft according to the main shaft vibration anomaly coefficient of the target main shaft, the synergy of all different main shafts, and all abnormal amplitudes of all main shafts and the recovery stable time of all abnormal amplitudes.

[0077]

[0078] In the formula, represents the main shaft difference coefficient of the target main shaft of the CNC machine tool ; represents the main shaft vibration anomaly coefficient of the target main shaft of the CNC machine tool ; represents the average value of all abnormal amplitudes included in the vibration sequences of the target main shaft of the CNC machine tool, and the th main shaft different from the target main shaft ; represents the standard deviation of the recovery stable time of all abnormal amplitudes included in the vibration sequences of the target main shaft of the CNC machine tool, and the th main shaft different from the target main shaft ; represents the number of main shafts different from the target main shaft included in the CNC machine tool ; represents the th synergy between the main shaft different from the target main shaft and the target main shaft ; ; represents the adjustment parameter, which is a preset constant and is used to prevent the denominator from being zero. In this embodiment, the value of the adjustment parameter is 0.01.

[0079] When the milling cutter of the target main shaft is worn, there will be more abnormal vibration data in the vibration sequence of the target main shaft, and the synergy of different main shafts of the CNC machine tool is damaged. Therefore, all abnormal amplitudes included in the vibration sequence of the target main shaft are larger, the difference between the recovery stable time of all abnormal amplitudes included in the vibration sequence of the target main shaft and the recovery stable time of all abnormal amplitudes included in the vibration sequences of other main shafts is larger, the synergy between the target main shaft and other main shafts is smaller, and the main shaft vibration anomaly coefficient of the target main shaft is larger. At this time, the main shaft difference coefficient of the target main shaft is larger, and the influence degree of the milling cutter wear on the target main shaft is larger, which further affects the processing quality of the rotor of the Roots vacuum pump.

[0080] The spindle difference coefficient takes into account the significance of the abnormal characteristics of the vibration data of each spindle during the machining process of a numerically controlled machine tool, as well as the asynchronous operating state between the spindles. Therefore, according to the spindle difference coefficient, the abnormal changes of the spindle during the machining process of the numerically controlled machine tool can be accurately reflected. During the machining process of a Roots vacuum rotor on a numerically controlled machine tool, the more severely the spindle is affected by the wear of the milling cutter, the greater the obtained spindle difference coefficient, and the more likely it is to affect the machining accuracy of the Roots vacuum pump rotor.

[0081] Thus, the spindle difference coefficient of the target spindle is obtained.

[0082] Step S004: According to the milling cutter speed of the target spindle at all acquisition moments and the spindle difference coefficient of the target spindle, adjust the actual cutting speed of the milling cutter of the target spindle of the numerically controlled machine tool, and adjust the actual cutting speed of the milling cutters of all the spindles of the numerically controlled machine tool to achieve fine machining for the vacuum pump rotor.

[0083] The difference between the average value of the milling cutter speeds of the target spindle at all acquisition moments and the average value of the preset values of the milling cutter speeds at all acquisition moments is denoted as the first difference of the target spindle. The product of the normalized value of the spindle difference coefficient of the target spindle and the first difference of the target spindle is denoted as the feedback coefficient of the target spindle. Use the feedback coefficient of the target spindle as the deviation of the PID controller, and use the PID controller to output the control signal of the numerically controlled machine tool. Based on the control signal, adjust the actual cutting speed of the milling cutter of the target spindle of the numerically controlled machine tool to ensure high-quality machining of the Roots vacuum pump rotor.

[0084] It should be noted that in this embodiment, the Z-Score standard normalization method is used to calculate the normalized value. In the actual application process, implementers can use other methods of existing technologies, such as the maximum-minimum normalization method, sigmoid function, etc., to calculate the normalized value, which is not limited here.

[0085] Among them, before machining the Roots vacuum pump rotor, it is necessary to preset the machining parameters of the numerically controlled machine tool at each moment. The milling cutter speed is one of the machining parameters of the numerically controlled machine tool. Therefore, the preset values of the milling cutter speeds at all acquisition moments can be directly extracted from the numerically controlled machine tool.

[0086] In the same way, the feedback coefficients of each spindle of the numerically controlled machine tool can be obtained, and the feedback coefficient of the target spindle is used as the deviation of the PID controller. Use the PID controller to output the control signal of the numerically controlled machine tool, and based on the control signal, adjust the actual cutting speed of the milling cutter of the target spindle of the numerically controlled machine tool to ensure high-quality machining of the Roots vacuum pump rotor.

[0087] Thus, fine machining for the vacuum pump rotor is achieved.

[0088] Based on the same inventive concept as the above method, an embodiment of the present invention further provides a fine machining device for a vacuum pump rotor, and the fine machining device is used to implement the steps of any one of the above methods for a fine machining method for a vacuum pump rotor.

[0089] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a fine machining device for a vacuum pump rotor provided by an embodiment of the present application. In this embodiment, each unit included in the device is used to execute each step in the corresponding embodiment of a fine machining method for a vacuum pump rotor. Refer to Figure 2 , the fine machining device includes: a data acquisition module, a main shaft abnormality analysis module, a main shaft collaborative analysis module, and a fine machining adjustment module.

[0090] The data acquisition module is used to collect the vibration data of each main shaft of the numerical control machine tool and the milling cutter speed of each milling cutter during the machining process of the roots vacuum pump rotor, and obtain the vibration sequence of the same main shaft according to the vibration data of the same main shaft;

[0091] The main shaft abnormality analysis module is used to record any one main shaft as the target main shaft, record any one vibration data in the vibration sequence of the target main shaft as the target vibration data, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude according to the change trend of the vibration data in the vibration sequence of the target main shaft, and determine the main shaft vibration abnormality coefficient of the target main shaft according to all the abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target main shaft, and the autocorrelation of the vibration sequence of the target main shaft;

[0092] The main shaft collaborative analysis module is used to determine the collaboration of different main shafts according to the correlation of the vibration data of the vibration sequences of different main shafts, and determine the main shaft difference coefficient of the target main shaft according to the main shaft vibration abnormality coefficient of the target main shaft, the collaboration of all different main shafts, and all the abnormal amplitudes and the recovery stable time of all the abnormal amplitudes of all the main shafts;

[0093] The fine machining adjustment module is used to adjust the actual cutting speed of the milling cutter of the target main shaft of the numerical control machine tool and the actual cutting speeds of the milling cutters of all the main shafts of the numerical control machine tool according to the milling cutter speed of the target main shaft at all the acquisition moments and the main shaft difference coefficient of the target main shaft, so as to realize the fine machining of the vacuum pump rotor.

[0094] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A fine machining method for a vacuum pump rotor, characterized in that, The method comprises the following steps: During the machining process of the Roots vacuum pump rotor, vibration data of each spindle of the CNC machine tool and the milling cutter speed of each milling cutter are collected, and a vibration sequence of the same spindle is obtained based on the vibration data of the same spindle; Record any spindle as a target spindle, record any vibration data in the vibration sequence of the target spindle as target vibration data, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude based on the change trend of the vibration data in the vibration sequence of the target spindle, and determine the spindle vibration abnormality coefficient of the target spindle based on all abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target spindle and the autocorrelation of the vibration sequence of the target spindle; Determine the synergy of different spindles based on the correlation of vibration data of vibration sequences of different spindles, and determine the spindle difference coefficient of the target spindle based on the spindle vibration anomaly coefficient of the target spindle, the synergy of all different spindles, all abnormal amplitudes of all spindles, and the recovery and stabilization time of all abnormal amplitudes; According to the milling cutter speed of the target spindle at all acquisition moments and the spindle variability coefficient of the target spindle, the actual cutting speed of the milling cutter of the target spindle of the CNC machine tool is adjusted, and the actual cutting speed of the milling cutter of all spindles of the CNC machine tool is adjusted to achieve fine processing of the vacuum pump rotor.

2. The fine machining method for a vacuum pump rotor according to claim 1, wherein The method for determining the abnormal amplitude is: The local maximum value of the vibration sequence of the target spindle is recorded as the abnormal amplitude.

3. A fine machining method for a vacuum pump rotor according to claim 1, characterized in that, The method for determining the recovery stable time of the abnormal amplitude is: Construct a sliding window with a length centered on the target vibration data and perform a linear fit on all the vibration data contained within the sliding window of the target vibration data to obtain the slope of the fitted line. When the absolute value of the slope of the fitted line is less than , it is determined that the target vibration data is in a steady state; where is the first preset threshold and is the second preset threshold. For each abnormal amplitude in the vibration sequence of the target spindle, the time interval between the acquisition time of the first stable vibration data after the abnormal amplitude and the acquisition time of the abnormal amplitude is recorded as the abnormal amplitude recovery stable time.

4. A fine machining method for a vacuum pump rotor according to claim 1, characterized in that The method of determining the spindle vibration anomaly coefficient of the target spindle based on all abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target spindle, and the autocorrelation of the vibration sequence of the target spindle, includes the following specific methods: The product of the abnormal amplitude value in the vibration sequence of the target main shaft and the recovery stable time of the abnormal amplitude is recorded as the abnormal fluctuation degree of the abnormal amplitude, and the average of the abnormal fluctuation degrees of all abnormal amplitudes in the vibration sequence of the target main shaft is recorded as the abnormal amplitude fluctuation mean value of the target main shaft; The time lag period is set to 1, and the time autocorrelation coefficient of the vibration series of each main axis is calculated respectively; The spindle vibration anomaly coefficient of the target spindle is determined according to the abnormal amplitude fluctuation mean value of the target spindle and the time autocorrelation coefficient of the vibration sequence of the target spindle.

5. A fine machining method for a vacuum pump rotor according to claim 4, characterized in that, The method of determining the spindle vibration anomaly coefficient of the target spindle based on the abnormal amplitude fluctuation mean value of the target spindle and the time autocorrelation coefficient of the vibration sequence of the target spindle includes the following specific methods: The ratio of the mean value of the abnormal amplitude fluctuation of the target spindle to the time autocorrelation coefficient of the vibration sequence of the target spindle is recorded as the spindle vibration abnormality coefficient of the target spindle.

6. A fine machining method for a vacuum pump rotor according to claim 1, characterized in that, The method for determining the synergy of the different main axes is: The Pearson correlation coefficient of the vibration sequences of two different main axes is recorded as the synergy of the two different main axes.

7. A fine machining method for a vacuum pump rotor according to claim 1, characterized in that, The method for obtaining the spindle difference coefficient of the target spindle is: In the formula, represents the target spindle of the numerically controlled machine tool 's spindle difference coefficient; represents the target spindle of the numerically controlled machine tool 's abnormal spindle vibration coefficient; represents the target spindle of the numerically controlled machine tool , and the th spindle different from the target spindle The average value of all abnormal amplitudes included in the vibration sequence; represents the target spindle of the numerically controlled machine tool , and the th spindle different from the target spindle The standard deviation of the recovery steady time of all abnormal amplitudes included in the vibration sequence; represents the number of spindles in the numerically controlled machine tool that are different from the target spindle ; represents the th spindle different from the target spindle and the synergy of the target spindle ; represents the adjustment parameter.

8. A fine machining method for a vacuum pump rotor according to claim 1, characterized in that Adjusting the actual cutting speed of the milling cutter of the target spindle of the numerical control machine tool according to the milling cutter speed at all acquisition moments of the target spindle and the spindle difference coefficient of the target spindle, the specific method included is as follows: Denote the difference between the average value of the milling cutter speeds at all acquisition moments of the target spindle and the average value of the preset values of the milling cutter speeds at all acquisition moments as the first difference of the target spindle, and denote the product of the normalized value of the spindle difference coefficient of the target spindle and the first difference of the target spindle as the feedback coefficient of the target spindle; Adjust the actual cutting speed of the milling cutter of the target spindle of the numerical control machine tool according to the feedback coefficient of the target spindle.

9. A fine machining method for a vacuum pump rotor according to claim 8, characterized in that The adjusting the actual cutting speed of the milling cutter of the target spindle of the numerical control machine tool according to the feedback coefficient of the target spindle, the specific method included is as follows: Use the feedback coefficient of the target spindle as the deviation of the PID controller, use the PID controller to output the control signal of the numerical control machine tool, and adjust the actual cutting speed of the milling cutter of the target spindle of the numerical control machine tool based on the control signal.

10. A fine machining device for a vacuum pump rotor, which implements the method described in any one of claims 1-9, characterized in that, The fine machining device includes: A data acquisition module, which is used to acquire the vibration data of each spindle of the numerical control machine tool and the milling cutter speed of each milling cutter during the machining process of the roots vacuum pump rotor, and obtain the vibration sequence of the same spindle according to the vibration data of the same spindle; A spindle abnormality analysis module, which is used to denote any one spindle as the target spindle, denote any one vibration data in the vibration sequence of the target spindle as the target vibration data, determine the abnormal amplitude and the recovery stable time of the abnormal amplitude according to the change trend of the vibration data in the vibration sequence of the target spindle, and determine the spindle vibration abnormality coefficient of the target spindle according to all the abnormal amplitudes and the recovery stable time of the abnormal amplitudes in the vibration sequence of the target spindle, and the autocorrelation of the vibration sequence of the target spindle; A spindle cooperation analysis module, which is used to determine the cooperation of different spindles according to the correlation of the vibration data of the vibration sequences of different spindles, and determine the spindle difference coefficient of the target spindle according to the spindle vibration abnormality coefficient of the target spindle, the cooperation of all different spindles, and all the abnormal amplitudes and the recovery stable time of all the abnormal amplitudes of all the spindles; A fine machining adjustment module, which is used to adjust the actual cutting speed of the milling cutter of the target spindle of the numerical control machine tool according to the milling cutter speed at all acquisition moments of the target spindle and the spindle difference coefficient of the target spindle, and adjust the actual cutting speed of the milling cutters of all the spindles of the numerical control machine tool to achieve fine machining for the vacuum pump rotor.

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