Deep hole gun drill processing method for high voltage switch shaft parts through hole

Abstract

This application discloses a deep-hole gun drilling method for through holes in high-voltage switch shaft parts, relating to the field of turning technology. The method includes acquiring cutting data for deep-hole gun drilling; obtaining a blockage index based on the cutting data; obtaining a cross-sectional area reduction rate based on the blockage index; obtaining a target feed rate based on the cross-sectional area reduction rate; and adjusting the feed rate of the deep-hole gun drill to the target feed rate. This application constructs a blockage index to quantitatively characterize the blockage development state of the chip removal channel by collecting core cutting data such as the cutting fluid return pressure curve. Then, the cross-sectional area reduction rate of the chip removal channel is derived from the blockage index. Finally, the target feed rate of the deep-hole gun drill is dynamically matched and adjusted based on this reduction rate, achieving real-time, precise, and adaptive control of the feed rate during machining.

Description

Technical Field

[0001] This application relates to the field of turning technology, specifically a deep hole gun drilling method for through holes in high-voltage switch shaft parts. Background Technology

[0002] High-voltage switchgear shafts, as critical pressure-bearing and transmission components in power transmission and distribution systems, often require the machining of high-precision deep through holes to reduce weight or serve as medium channels. Existing processes utilize specialized machine tools or deep-hole drilling systems to machine holes with large length-to-diameter ratios in a single setup. However, when dealing with the specific high-strength alloy materials, complex multi-step shaft structures, and extremely stringent requirements for coaxiality and internal wall surface quality in high-voltage switchgear shafts, significant challenges arise in process adaptability, machining stability, and the reliability of the final parts. For example, the closed nature of the machining process and the complexity of its state evolution make the cutting zone unobservable. Furthermore, uneven material hardness, differences in stiffness across multi-step structures, system stiffness degradation caused by increased drill rod overhang, and the dynamic imbalance between chip generation and fluid transport lead to a continuous accumulation of chip removal channel blockage risk with drilling depth. Traditional fixed-parameter methods cannot perceive the coupled evolution of stiffness degradation and blockage in real time, lacking effective dynamic control mechanisms. This results in poor stability of the machining process under disturbances such as material fluctuations and tool wear, making it difficult to guarantee the coaxiality and internal wall quality of deep holes. Summary of the Invention

[0003] The purpose of this application is to provide a deep hole gun drilling method for through holes in high-voltage switch shaft parts, in order to solve the technical problem that it is difficult to dynamically adjust the feed rate during deep hole machining in order to ensure the quality of deep hole machining.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] Deep hole gun drilling methods for through holes in high-voltage switch shaft parts include:

[0006] Obtain cutting data for deep hole gun drilling; the cutting data includes the backflow pressure curve of the cutting fluid; the horizontal axis of the backflow pressure curve is time, and the vertical axis is the backflow pressure of the cutting fluid;

[0007] Based on the cutting data, a blockage index is obtained; the blockage index is used to characterize at least the magnitude of the increase of each peak in the return pressure curve;

[0008] Based on the blockage index, the cross-sectional area reduction rate is obtained; the cross-sectional area reduction rate is used to characterize the degree of reduction in the cross-sectional area of ​​the chip removal channel during deep hole gun drilling.

[0009] The target feed rate is obtained based on the cross-sectional area reduction rate;

[0010] Adjust the feed rate of the deep hole gun drill to the target feed rate.

[0011] As a specific solution in this application, obtaining the blockage index based on the cutting data includes:

[0012] Based on the backflow pressure curve, multiple time series curve segments are obtained; the time length of each time series curve segment is equal.

[0013] Based on the Fourier transform algorithm, the time-series frequency domain signal corresponding to each time-series curve segment is obtained;

[0014] Based on each time-series frequency domain signal, obtain the time-series main peak power spectral density corresponding to each time-series frequency domain signal;

[0015] The congestion index is obtained based on the power spectral density of the main peak at each time series.

[0016] As a specific solution in this application, the cutting data further includes the time-series drilling depth of the deep hole gun drill spindle; obtaining the blockage index based on the power spectral density of each time-series main peak includes:

[0017] Based on the main peak power spectral density and the drilling depth at each time series, a first fitting curve is obtained; the horizontal axis of the first fitting curve is the drilling depth, and the vertical axis is the main peak power spectral density.

[0018] Based on each time-series frequency domain signal, the time-series blocking oscillation frequency corresponding to each time-series frequency domain signal is obtained; the blocking oscillation frequency is the frequency corresponding to the maximum power spectral density value other than the main peak power spectral density in the corresponding time-series frequency domain signal.

[0019] Based on each time-series congestion oscillation frequency, the time-series sub-peak power spectral density corresponding to each time-series congestion oscillation frequency is obtained;

[0020] A second fitting curve is obtained based on the secondary peak power spectral density and the drilling depth at each time series; the horizontal axis of the second fitting curve is the drilling depth, and the vertical axis is the secondary peak power spectral density.

[0021] The congestion index is obtained based on the first fitted curve and the second fitted curve.

[0022] As a specific solution in this application, obtaining the congestion index based on the first fitting curve and the second fitting curve includes:

[0023] Based on the first and second fitted curves, a third and fourth fitted curves are obtained; the third fitted curve is the curve obtained after normalizing the first fitted curve; the fourth fitted curve is the curve obtained after normalizing the second fitted curve.

[0024] Based on the third and fourth fitted curves, a first curve value and a second curve value are obtained; the first curve value is the curve value corresponding to the current drilling depth in the third fitted curve; the second curve value is the curve value corresponding to the current drilling depth in the fourth fitted curve.

[0025] The congestion index is obtained based on the first curve value and the second curve value; the congestion index is negatively correlated with the first curve value and positively correlated with the second curve value.

[0026] As a specific solution in this application, obtaining the cross-sectional area reduction rate based on the congestion index includes:

[0027] The congestion index is input into the prediction model to obtain the cross-sectional area reduction rate; the prediction model is pre-established.

[0028] As a specific solution in this application, the prediction model includes:

[0029] ;

[0030] in, Indicates the congestion index; Indicates the rate of reduction in cross-sectional area. Greater than or equal to 0, less than 1; Indicates the first coefficient; Indicates the second coefficient; The third coefficient is indicated; the first coefficient, the second coefficient, and the third coefficient are all determined through calibration experiments.

[0031] As a specific solution in this application, obtaining the target feed rate based on the cross-sectional area reduction rate includes:

[0032] Based on the cutting data, the chip generation rate is obtained; the chip generation rate is used to characterize at least the speed of the chips generated by the deep hole gun drill at the current time;

[0033] Based on the cross-sectional area reduction rate and the cutting data, the chip delivery speed is obtained; the chip delivery speed is used at least to characterize the speed of chips discharged by the deep hole gun drill at the current time;

[0034] The target feed rate is obtained based on the chip generation rate and the chip delivery rate.

[0035] As a specific solution in this application, the cutting data includes the current feed rate, current spindle speed, and cutting width of the deep hole gun drill; the step of obtaining the chip generation rate based on the cutting data includes:

[0036] Based on the current feed rate and the current spindle speed, the feed per revolution is obtained; the feed per revolution is equal to the ratio of the current feed rate to the current spindle speed.

[0037] Based on the feed per revolution and the cutting width, the effective cutting area is obtained; the effective cutting area is equal to the product of the feed per revolution and the cutting width.

[0038] The chip generation rate is obtained based on the effective cutting area and the current feed rate.

[0039] As a specific solution in this application, the cutting data further includes the cutting fluid flow rate and the original cross-sectional area of ​​the chip removal channel in the deep hole gun drill; the step of obtaining the chip delivery speed based on the cross-sectional area reduction rate and the cutting data includes:

[0040] Based on the original cross-sectional area of ​​the chip removal channel and the cross-sectional area reduction rate, the current cross-sectional area of ​​the chip removal channel is obtained;

[0041] The chip delivery speed is obtained based on the current cross-sectional area of ​​the chip removal channel and the cutting fluid flow rate.

[0042] As a specific solution in this application, obtaining the target feed rate based on the chip generation rate and the chip delivery rate includes:

[0043] A first feed rate is obtained based on the chip generation rate and the chip delivery rate; the first feed rate is the feed rate corresponding to the equality of the chip generation rate and the chip delivery rate.

[0044] Based on the third fitted curve, the current slope is obtained; the current slope is the slope corresponding to the current drilling depth in the third fitted curve.

[0045] The first feed rate is corrected based on the current slope to obtain the target feed rate.

[0046] Compared with the prior art, the beneficial effects of this application are:

[0047] This application constructs a blockage index to quantitatively characterize the blockage development state of the chip removal channel by collecting core cutting data such as the cutting fluid return pressure curve. Then, it derives the cross-sectional area reduction rate of the chip removal channel from the blockage index. Finally, based on this reduction rate, it dynamically matches and adjusts the target feed rate of the deep hole gun drill, realizing real-time, precise, and adaptive control of the feed rate during the machining process. This method overcomes the technical limitations of traditional fixed machining parameters in handling the closed-loop and dynamically evolving states of deep hole machining. It can perceive the coupled effects of changes in chip removal channel patency and drill rod stiffness degradation in real time, and achieve a dynamic balance between chip generation and removal by dynamically adjusting the feed rate. This effectively reduces the risk of chip removal channel blockage and avoids problems such as drill rod wobble, tool wear, and decreased workpiece surface quality caused by blockage. It ensures the coaxiality and inner wall surface quality of key precision requirements for deep hole machining of high-voltage switch shaft parts, and improves the stability and reliability of the machining process. At the same time, compared with the conservative machining method of blindly reducing the feed rate, this method takes into account machining efficiency while avoiding machining risks. It is suitable for the harsh machining conditions of high-strength alloy materials and multi-step shaft structures of high-voltage switch shaft parts, and can improve the process adaptability and finished product qualification rate of deep hole machining of high-voltage switch shaft parts. Attached Figure Description

[0048] Figure 1 This is a schematic flowchart of a deep hole gun drilling method for through holes in high-voltage switch shaft parts proposed in an embodiment of this application. Detailed Implementation

[0049] 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.

[0050] The terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. For example, the first fitting curve and the second fitting curve mentioned below are different fitting curves. It should be understood that such names can be used interchangeably where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules in the embodiments of this application is merely a logical division. In actual applications, there may be other division methods. For example, multiple modules may be combined into or integrated into another system, or some features may be ignored or not performed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms. None of these are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0051] To address the technical problem mentioned in the background art—the difficulty in dynamically adjusting the feed rate during deep hole machining to ensure machining quality—this application proposes an embodiment of a deep hole gun drilling method for through holes in high-voltage switch shaft parts. Specifically, as shown... Figure 1 As shown, the deep hole gun drilling method for through holes in high-voltage switch shaft parts includes steps 100 to 500.

[0052] Step 100: Obtain cutting data for deep hole gun drilling.

[0053] In this embodiment, the cutting data includes the backflow pressure curve of the cutting fluid. The horizontal axis of the backflow pressure curve represents time, and the vertical axis represents the backflow pressure of the cutting fluid.

[0054] The data acquisition time period covers the entire cycle of a single cutting operation, from the start of tool contact with the workpiece to the end of tool retraction, with a typical duration of 10 to 300 seconds; the sampling frequency of the cutting data is no less than 100 Hz to ensure that transient characteristics of pressure fluctuations (such as sudden changes caused by tool chipping or chip blockage) can be captured.

[0055] In deep hole gun drilling, the role of cutting fluid is to efficiently cool the cutting head of the gun drill, promptly removing the large amount of heat generated during cutting in the enclosed area of ​​deep hole machining, preventing wear and burning of the cutting head due to high temperature, and extending tool life. At the same time, it lubricates the workpiece and tool in the cutting area, reducing frictional resistance during the cutting process, reducing machining scratches on the workpiece surface, and improving the surface finish of the inner wall of the deep hole of high-voltage switch shaft parts. In addition, the cutting fluid can also use its own fluid flow dynamics to smoothly flush and transport the chips generated during machining from the chip removal channel of the deep hole to the outside, achieving a chip removal effect. The change in the return pressure of the cutting fluid can also directly reflect the unobstructed state of the chip removal channel, providing key physical monitoring data for subsequent judgment of chip removal channel blockage.

[0056] In this embodiment, a pressure sensor can be installed in the cutting fluid return line. The installation position of the pressure sensor can be selected as close as possible to the return channel of the workpiece outlet. The sensor can adopt a piezoelectric structure, which works by utilizing the characteristic of a piezoelectric crystal to generate charge when subjected to pressure, converting the pressure signal into an electrical signal. Piezoelectric sensors have high-frequency response characteristics and can capture rapid pressure changes during the cutting process. The charge signal output by the pressure sensor is converted into a voltage signal by a charge amplifier and then filtered by a low-pass filter to remove high-frequency noise. The cutoff frequency of the low-pass filter can be set to ten times the rotational frequency corresponding to the highest spindle speed.

[0057] Step 200: Based on the cutting data, obtain the blockage index.

[0058] In this embodiment, the blockage index is used at least to characterize the magnitude of the increase in each peak in the backflow pressure curve.

[0059] It is important to note that the asymmetric structure of a gun drill's single-edge cutting edge determines that its cutting force exhibits a significant periodicity: with each rotation of the spindle, the cutting edge completes the entire process from entering the uncut material, reaching the maximum cutting thickness, to exiting the cutting zone. The cutting force also exhibits a periodic variation, increasing from zero to a peak value and then falling back to zero, with this variation frequency strictly matching the spindle rotation frequency. Simultaneously, the radial cutting force of the gun drill causes bending deformation of the drill bit, leading to a periodic change in the annular gap between the drill rod's outer wall and the hole wall. That is, when the drill rod bends to one side, the gap on that side decreases, and the gap on the opposite side increases, with the frequency of this gap change also matching the spindle rotation frequency. Ultimately, this causes the cutting fluid return pressure to pulsate at the same frequency. This pulsation, reflected in the power spectrum, forms a sharp peak at the spindle rotation frequency, i.e., the main peak. In short, as long as the gun drill is in normal cutting mode, the main peak at the spindle rotation frequency will inevitably exist; this is determined by the inherent physical characteristics of the gun drill's single-edge structure. Therefore, in this embodiment, step 200, which obtains the blockage index based on the cutting data, includes steps 210 to 240.

[0060] Step 210: Based on the backflow pressure curve, obtain multiple time-series curve segments.

[0061] In this embodiment, the time lengths of each time series curve segment are equal.

[0062] It is important to note that dividing a time-related curve (i.e., the reflux pressure curve) into multiple curve segments of equal length (i.e., various time-series curve segments) is a mature technique. For example, a preset time window length (e.g., 50ms or 100ms) can be determined first. Starting from the processing start time, the reflux pressure curve can be slid or segmented according to this fixed time window length. If it is a sliding segmentation, the overlap rate of adjacent time windows can be set (e.g., 50% to improve data continuity). If it is a direct segmentation, it can be segmented sequentially according to the time window. Finally, the entire continuous reflux pressure time curve is divided into several time-series curve segments of completely consistent length in the time dimension, covering the entire processing process. Each curve segment contains all reflux pressure data points within the corresponding time range, and the time coordinates and pressure coordinates of each segment are consistent.

[0063] Step 220: Based on the Fourier transform algorithm, obtain the time-series frequency domain signal that corresponds one-to-one with each time-series curve segment.

[0064] It is important to understand that using Fourier transform algorithms to convert time-series curve segments into time-series frequency domain signals is a mature technology, which will not be elaborated upon here. For example, a fast Fourier transform can be performed on the discrete pressure data points of each time-series curve segment of equal duration. First, the time-domain pressure-time discrete sequence is zero-padded to improve the frequency domain resolution. Then, the Fourier transform algorithm is used to map the time-domain signal to the frequency domain, obtaining the corresponding complex form frequency domain sequence. After solving for the modulus of this complex sequence and performing normalization, a time-series frequency domain signal with frequency as the horizontal axis and power spectrum as the vertical axis can be obtained, completely extracting the frequency composition of the return pressure signal and the energy characteristics corresponding to each frequency within that time period.

[0065] Step 230: Based on each time-series frequency domain signal, obtain the time-series main peak power spectral density corresponding to each time-series frequency domain signal.

[0066] In this embodiment, the main peak power spectral density comprehensively reflects the state of cutting force and drill rod stiffness. If the cutting force is greater, the drill rod will bend more severely, the annular gap between the outer wall of the drill rod and the hole wall will change more significantly, the pressure pulsation will be stronger, and the main peak will be higher. If the drilling depth of the drill rod is greater, the bending of the drill rod caused by the same cutting force will be greater, the annular gap between the outer wall of the drill rod and the hole wall will change more significantly, the pressure pulsation will be stronger, and the main peak will be higher.

[0067] Step 240: Obtain the blockage index based on the power spectral density of each time series main peak.

[0068] In this embodiment, the clogging index can be the slope of the power spectral density curves of each time series peak. The larger the slope, the greater the degree of drill pipe bending. The greater the degree of drill pipe bending, the smaller the annular gap between the drill pipe outer wall and the hole wall, which directly worsens the chip removal conditions. At the same chip generation rate, a narrower channel is more prone to clogging, and the feed rate should be reduced accordingly.

[0069] As mentioned above, since the slope of the power spectral density curves of each time series peak can only reflect the degree of bending of the drill pipe, it is difficult to accurately characterize the blockage index by slope alone. In order to obtain a more accurate blockage index, in one embodiment of this application, step 240, based on the power spectral density of each time series peak, obtains the blockage index, including steps 241 to 245.

[0070] In this embodiment, the cutting data also includes the timing drilling depth of the deep hole gun drill spindle.

[0071] In this embodiment, the time-series drilling depth can be calculated based on the feed rate of the deep hole gun drill. Specifically, a feed rate curve can be obtained based on the time-series feed rate of the deep hole gun drill, with the horizontal axis representing time and the vertical axis representing the feed rate of the deep hole gun drill. Further, the time-series drilling depth of the deep hole gun drill spindle is equal to the integral of the feed rate over time from the start of machining to the current time. If there is a stage in the machining process where the feed rate is constant, the drilling depth of that stage can be directly obtained by multiplying the constant feed rate by the duration of that stage. The overall time-series drilling depth is the cumulative value of the drilling depths of each stage, thus achieving accurate calculation of the drilling depth at any given time under different feed rate variations. Calculating the integral value of a curve in a computer is a mature technology and will not be elaborated upon here.

[0072] In other embodiments of this application, the time-series drilling depth can also be obtained directly based on sensor measurement. For example, a magnetic grating ruler displacement sensor or an optical grating ruler displacement sensor can be used. The measuring end of the sensor is rigidly connected to the feed slide of the deep hole gun drill spindle. Displacement data is collected synchronously with the feed movement of the slide. The sensor converts the real-time displacement signal into an electrical signal and transmits it to the CNC system. The system analyzes and records the collected displacement signal in real time to directly obtain the time-series drilling depth of the deep hole gun drill spindle at different time points. Alternatively, a wire-type displacement sensor can be used, with the fixed end of the sensor mounted on the machine tool bed. The cable end is connected to the gun drill spindle, and the extension and retraction of the cable are used to accurately detect the spindle's feed displacement, enabling continuous measurement of the drilling depth over time. This type of sensor has a fast response speed and high measurement accuracy, and can adapt to the dynamic detection requirements of feed motion during deep hole gun drilling. Alternatively, a laser displacement sensor can be used, which uses a non-contact laser ranging method to detect changes in the gun drill spindle's feed position in real time. This avoids the mechanical friction between contact sensors and moving parts of the machine tool, reducing wear and improving measurement stability. The detection data from the laser displacement sensor is converted by the data processing module to output accurate time-series drilling depth information. Measuring the movement displacement of an object using the above sensors are all mature technologies and will not be elaborated upon here.

[0073] Step 241: Based on the power spectral density of the main peak at each time series and the drilling depth at each time series, obtain the first fitting curve.

[0074] In this embodiment, the horizontal axis of the first fitting curve represents the drilling depth, and the vertical axis represents the main peak power spectral density. Fitting the horizontal axis values ​​(i.e., drilling depth) and the vertical axis values ​​(i.e., main peak power spectral density) to obtain the corresponding fitting curve (i.e., the first fitting curve) is a mature technology. Specifically, the least squares method can be used to complete the curve fitting operation. First, based on the discrete data set of the actual collected drilling depth and the corresponding main peak power spectral density, a suitable fitting function type (e.g., polynomial function or exponential function) is selected. Then, the coefficients of each term of the fitting function are solved by the least squares method to minimize the sum of squared errors between the fitting function and the discrete data points, thereby obtaining the first fitting curve that can accurately characterize the correlation between drilling depth and main peak power spectral density. The calculation process and implementation method of the relevant fitting are well known to those skilled in the art and will not be described in detail here.

[0075] Step 242: Based on each time-series frequency domain signal, obtain the time-series jamming oscillation frequency that corresponds one-to-one with each time-series frequency domain signal.

[0076] In this embodiment, the blocking oscillation frequency is the frequency corresponding to the maximum power spectral density in the corresponding time-series frequency domain signal, excluding the main peak power spectral density.

[0077] It is important to note that when the chip generation rate of a deep hole gun drill exceeds the cutting fluid's ability to continuously carry away chips (i.e., the chip delivery rate mentioned below), chips accumulate in the chip removal channel. This leads to a decrease in the cross-sectional area of ​​the chip removal channel, an increase in the flow resistance of the cutting fluid, and an increase in the return pressure of the cutting fluid. If the return pressure of the cutting fluid increases, it will accelerate the cutting fluid and increase its thrust. When the thrust is sufficient to disperse the chips accumulated in the chip removal channel, the cross-sectional area of ​​the chip removal channel recovers, the return pressure of the cutting fluid drops, and then the chips accumulate in the chip removal channel again. The frequency of this "accumulation-dispersion" self-excited oscillation (i.e., the blocking oscillation frequency) is much lower than the spindle rotation frequency, and in the power spectrum, this low-frequency oscillation is characterized by a peak in the low-frequency range.

[0078] Step 243: Based on each time-series congestion oscillation frequency, obtain the time-series second-peak power spectral density corresponding to each time-series congestion oscillation frequency.

[0079] As mentioned above, the blocking oscillation frequency is the frequency corresponding to the maximum power spectral density in the corresponding time-series frequency domain signal, excluding the main peak power spectral density. In other words, the second-peak power spectral density is the power spectral density value corresponding to the blocking oscillation frequency of that time series. It is the second largest power spectral density value in the frequency domain signal, second only to the main peak power spectral density, and its magnitude directly reflects the energy strength of the self-excited oscillation of chip accumulation and dispersion within the chip removal channel.

[0080] In this embodiment, the higher the power spectral density of the time sequence second peak, the more intense the oscillation of the cutting fluid backflow pressure and the more severe the blockage of the chip removal channel.

[0081] Step 244: Obtain the second fitting curve based on the power spectral density of each time series sub-peak and the drilling depth of each time series.

[0082] In this embodiment, the horizontal axis of the second fitting curve represents the drilling depth, and the vertical axis represents the secondary peak power spectral density. Fitting the horizontal axis values ​​(i.e., drilling depth) and the vertical axis values ​​(i.e., secondary peak power spectral density) to obtain the corresponding fitting curve (i.e., the second fitting curve) is a mature technology and will not be elaborated here.

[0083] Step 245: Obtain the congestion index based on the first fitted curve and the second fitted curve.

[0084] As mentioned above, the first fitting curve mainly reflects the correlation between the drill pipe drilling depth and the main peak power spectral density. Its core characteristic is the change trend of the basic clearance of the chip removal channel caused by the drill pipe bending degree and cutting force changes as the drilling depth increases. Its numerical changes can intuitively reflect the fundamental impact of drill pipe stiffness degradation and bending deformation on the unobstructedness of the chip removal channel. The second fitting curve mainly reflects the correlation between the drill pipe drilling depth and the secondary peak power spectral density. It focuses on the intensity of the self-excited oscillation of chip accumulation and dispersion within the chip removal channel as the drilling depth increases, directly characterizing the actual blockage development state of the chip removal channel. Therefore, in this embodiment, it is necessary to combine the changing characteristics of both curves to comprehensively determine the degree of blockage in the chip removal channel. Based on this, in this embodiment, step 245, obtaining the blockage index based on the first and second fitting curves, may include steps 245a to 245c.

[0085] Step 245a: Based on the first fitting curve and the second fitting curve, obtain the third fitting curve and the fourth fitting curve.

[0086] In this embodiment, the third fitting curve is the curve obtained by normalizing the first fitting curve. The fourth fitting curve is the curve obtained by normalizing the second fitting curve.

[0087] It is important to understand that normalizing a curve (e.g., the first or second fitted curve) to obtain its corresponding normalized curve (e.g., the third and fourth fitted curves) is a mature technique. For example, the minimum-maximum normalization method or the mean normalization method can be used to map all the values ​​in the curve to the range of [0,1].

[0088] Furthermore, the values ​​of the fitted curves are mapped to the [0,1] interval, where the normalized denominator can be a preset system limit power spectral density or a calibration peak value in the early stage of processing (such as the first 10 seconds) to avoid index jumps caused by changes in the data range as processing progresses.

[0089] Step 245b: Based on the third and fourth fitted curves, obtain the first curve value and the second curve value.

[0090] In this embodiment, the first curve value is the curve value corresponding to the current drilling depth in the third fitted curve. The second curve value is the curve value corresponding to the current drilling depth in the fourth fitted curve.

[0091] In this embodiment, the current drilling depth refers to any drilling depth where it is necessary to confirm whether the feed rate is appropriate. Specifically, during deep hole gun drilling, the actual axial depth of the drill bit penetrating into the workpiece from the workpiece machining start face at a certain moment is the real-time drilling depth value corresponding to the currently collected cutting data and used to calculate the blockage index and target feed rate.

[0092] Step 245c: Obtain the congestion index based on the first curve value and the second curve value.

[0093] In this embodiment, the congestion index is negatively correlated with the first curve value and positively correlated with the second curve value.

[0094] In one embodiment of this application, step 245c, based on the first curve value and the second curve value, obtains the calculation formula for the congestion index as follows:

[0095] ;

[0096] in, This indicates the blockage index corresponding to the current drilling depth; This represents the first curve value corresponding to the current drilling depth; This represents the second curve value corresponding to the current drilling depth; This represents the zero-prevention coefficient, used to avoid the denominator being 0 in extreme cases; it is also known as the zero-prevention coefficient. It can be any positive number close to 0, for example, the zero-prevention coefficient. It can be 0.01 or 0.001, etc.

[0097] In another embodiment of this application, step 245c, based on the first curve value and the second curve value, obtains the calculation formula for the congestion index as follows:

[0098] ;

[0099] in, This indicates the blockage index corresponding to the current drilling depth; This represents the first curve value corresponding to the current drilling depth; This represents the second curve value corresponding to the current drilling depth; This represents an exponential function with the natural constant e as its base.

[0100] In this embodiment, if the chip removal channel removes chips smoothly, the first curve value is larger and the second curve value is smaller, that is, the blockage index is smaller; if chips accumulate in the chip removal channel, the second curve value increases sharply, that is, the blockage index increases.

[0101] Step 300: Based on the congestion index, obtain the cross-sectional area reduction rate.

[0102] In this embodiment, the cross-sectional area reduction rate is used to characterize the degree of reduction in the cross-sectional area of ​​the chip removal channel during deep hole gun drilling.

[0103] As mentioned above, in this embodiment, the congestion index can be directly used as the cross-sectional area reduction rate; the smaller the congestion index, the smaller the cross-sectional area reduction rate; the larger the congestion index, the larger the cross-sectional area reduction rate. To obtain an accurate cross-sectional area reduction rate, in one embodiment of this application, step 300, obtaining the cross-sectional area reduction rate based on the congestion index, includes: inputting the congestion index into a prediction model to obtain the cross-sectional area reduction rate.

[0104] In this embodiment, the prediction model is pre-established. Specifically, the prediction model includes:

[0105] ;

[0106] in, Indicates the congestion index; Indicates the rate of reduction in cross-sectional area. Greater than or equal to 0, less than 1; Indicates the first coefficient; Indicates the second coefficient; The third coefficient is indicated; the first coefficient, the second coefficient, and the third coefficient are all determined through calibration experiments.

[0107] It should be noted that, based on the pre-calibrated prediction model, the corresponding cross-sectional area reduction rate can be calculated in reverse from the currently calculated congestion index through numerical calculation or inverse function solution.

[0108] In this embodiment, the first coefficient To reflect the amplification factor of pressure fluctuations caused by blockage, it is dimensionless; the second coefficient An index related to flow state, typically Greater than or equal to 1, less than or equal to 2; third coefficient Represents inherent noise, when (That is, when the chip removal channel is not blocked) =b; with the rate of reduction of cross-sectional area Increase, congestion index Non-linear growth.

[0109] To calibrate the first to third coefficients mentioned above, experiments can be designed for precise control and measurement in a laboratory environment. For example, this application proposes an offline-indirect calibration method, as shown in steps a to c.

[0110] Step a, construct an equivalent hydraulic testing platform: In a laboratory environment, construct a test loop that is hydraulically equivalent to the chip removal channel of a real gun drill. This loop uses the same cutting fluid pump and piping specifications (including inner diameter, length, and surface roughness) as the production machine tool, and includes a simulated blockage module (e.g., a pipe section with a precision taper valve or insertable mandrels of different diameters) to physically simulate different... The channel status below.

[0111] Step b, Simulate cutting peak pressure pulsation: In the test circuit, a periodic flow disturbance with the same frequency and controllable amplitude as the spindle rotation frequency is injected into the system through a pulsating flow generator controlled by the spindle speed signal, in order to simulate the periodic pressure pulsation generated by single-edge cutting in real machining.

[0112] Step c, Relationship Calibration: Run the machining system under chip-free conditions, collect pressure signals, and calculate the baseline clogging index. This value corresponds to... The situation is as follows: .

[0113] Then, the simulated blockage module was adjusted, and a series of different cross-sectional area reduction rates were precisely set. ;in, This represents the i-th cross-sectional area reduction rate, where i is greater than or equal to 1 and less than or equal to N, and N is a positive integer greater than or equal to 3.

[0114] In each Under the given settings, run the test loop and collect the pressure signal at the loop outlet.

[0115] The pressure signal was subjected to the same spectral analysis as that used in online monitoring to calculate the simulated blockage index. ; This represents the congestion index corresponding to the i-th cross-sectional area reduction rate.

[0116] This yields N sets of calibration data pairs. .

[0117] According to calibration data The coefficients, first coefficient k and second coefficient m, are determined by fitting using the nonlinear least squares method.

[0118] Then, a prediction model is obtained based on the known first to third coefficients.

[0119] In another embodiment, to calibrate the first to third coefficients mentioned above, based on historically processed big data, sample data containing different degrees of congestion characteristics are selected, and the coefficients in the prediction model are calibrated through regression analysis. The calibration of the first to third coefficients can be implemented by the implementer according to specific circumstances, and no specific limitations are imposed here.

[0120] It should be noted that although this calibration process is insufficient to simulate the irregular shape and flow process of chips, as well as the changes in the characteristics of the chip fluid during blockage, considering that this application is aimed at the interventionable condition of "brief blockage followed by clearance", rather than the non-stop, non-interventionable condition of complete blockage or blockage that cannot be cleared, the characteristics of the chip fluid will not change continuously. Therefore, it is not necessary to overfit nonlinear factors during the calibration process to avoid distortion.

[0121] Step 400: Obtain the target feed rate based on the cross-sectional area reduction rate.

[0122] In this embodiment, the target feed rate can be obtained based on the cross-sectional area reduction rate using any reasonable method. As mentioned above, a larger cross-sectional area reduction rate indicates more severe blockage of the chip removal channel, meaning the feed rate should be reduced; conversely, a smaller cross-sectional area reduction rate indicates normal chip removal, meaning the feed rate can be maintained or appropriately increased. Therefore, in one embodiment of this application, the target feed rate can be linearly negatively correlated with the cross-sectional area reduction rate; that is, a larger cross-sectional area reduction rate results in a smaller target feed rate, and vice versa.

[0123] It is important to note that if the target feed rate is too high, the chip generation rate will continuously exceed the chip conveying speed of the chip removal channel. Chips will accumulate rapidly in the enclosed deep hole machining area, further reducing the cross-sectional area of ​​the chip removal channel and exacerbating blockage. Furthermore, chip compression will increase drill rod wobble, severely affecting the coaxiality of deep holes in high-voltage switch shaft parts. Simultaneously, heat from the cutting zone cannot be dissipated with the chips in time, leading to accelerated tool wear, scratches or ablation on the workpiece surface, and reduced machining quality of the deep hole's inner wall. In extreme cases, drill rod jamming and drill breakage may occur. Conversely, if the target feed rate is too low, it will reduce the overall deep hole machining efficiency, increasing machining time and production costs for high-voltage switch shaft parts. At the same time, excessively low feed rates will cause slight slippage between the cutting edge and the workpiece material instead of effective cutting, easily leading to tool deflection, excessive surface roughness, and abnormal chip morphology due to insufficient cutting force. These fine chips are more likely to adhere to the inner wall of the chip removal channel, increasing the probability of micro-blockage and affecting the stability of the machining process. In order to accurately and dynamically determine the target feed rate that is suitable for the current processing state, achieve a dynamic balance between chip generation and discharge, and avoid the problem of increased clogging caused by excessive feed rate and the problem of decreased processing efficiency and quality caused by excessively low feed rate, in one embodiment of this application, step 400, obtaining the target feed rate based on the cross-sectional area reduction rate, includes steps 410 to 430.

[0124] Step 410: Based on the cutting data, obtain the chip generation rate.

[0125] In this embodiment, the chip generation rate is used to characterize at least the speed of chips generated by the deep hole gun drill at the current time. Specifically, the cutting data includes the current feed rate, current spindle speed, and cutting width of the deep hole gun drill.

[0126] In this embodiment, the cutting width refers to the effective cutting edge length of the deep hole gun drill in contact with the workpiece to be machined, which is the cutting edge of the deep hole gun drill on a plane perpendicular to the feed direction of the gun drill. It is also the radial cutting dimension when the gun drill cuts with a single edge. Its value is determined by the tool structure parameters of the gun drill and is a key process parameter characterizing the radial coverage of a single cut by the gun drill (determining the cutting width and other structural parameters of the deep hole gun drill is a mature technology and will not be elaborated here).

[0127] In this embodiment, step 410, obtaining the chip generation rate based on the cutting data, includes steps 411 to 413.

[0128] Step 411: Based on the current feed rate and the current spindle speed, obtain the feed per revolution.

[0129] In this embodiment, the feed per revolution is equal to the ratio of the current feed rate to the current spindle speed.

[0130] Step 412: Based on the feed per revolution and the cutting width, obtain the effective cutting area.

[0131] In this embodiment, the effective cutting area is equal to the product of the feed per revolution and the cutting width.

[0132] Step 413: Based on the effective cutting area and the current feed rate, obtain the chip generation rate.

[0133] Specifically, the formula for calculating the chip generation rate can be as follows:

[0134] ;

[0135] in, Indicates the chip generation rate; Indicates the cutting width; Indicates the current feed rate; Indicates the current spindle speed. This indicates the effective cutting area.

[0136] The drilling process involves full-circumferential cutting, no tool deflection, and uniform chip filling of the hole cavity, making it suitable for the steady-state stage of deep-hole gun drilling. In another embodiment of this application, this is used as a benchmark model for chip generation rate, and the feed rate is subsequently dynamically adjusted based on chip removal capability. Therefore, the formula for calculating the chip generation rate can be as follows:

[0137] ;

[0138] in, Let be the cross-sectional area of ​​the borehole, which is a constant. D represents the drill bit diameter.

[0139] Step 420: Obtain the chip delivery speed based on the cross-sectional area reduction rate and the cutting data.

[0140] In this embodiment, the chip delivery speed is used at least to characterize the speed of chips discharged from the deep hole gun drill at the current time. Specifically, the cutting data also includes the cutting fluid flow rate and the original cross-sectional area of ​​the chip removal channel in the deep hole gun drill.

[0141] In this embodiment, step 420, obtaining the chip conveying speed based on the cross-sectional area reduction rate and the cutting data, includes steps 421 and 422.

[0142] Step 421: Based on the original cross-sectional area of ​​the chip removal channel and the cross-sectional area reduction rate, obtain the current cross-sectional area of ​​the chip removal channel.

[0143] Specifically, the formula for calculating the current cross-sectional area of ​​the chip removal channel is as follows:

[0144] ;

[0145] in, Indicates the current cross-sectional area of ​​the chip removal channel; Indicates the rate of reduction in cross-sectional area; This represents the original cross-sectional area of ​​the chip removal channel.

[0146] Step 422: Obtain the chip conveying speed based on the current cross-sectional area of ​​the chip removal channel and the cutting fluid flow rate.

[0147] In this embodiment, the formula for calculating the chip conveying speed can be as follows:

[0148] ;

[0149] in, Indicates the chip conveying speed; Indicates the current cross-sectional area of ​​the chip removal channel; Indicates the cutting fluid flow rate; The conveying efficiency (generally greater than or equal to 0.2 and less than or equal to 0.6, used to reflect the actual ability of the cutting fluid to carry chips; for example, for fine-grained chips, the conveying efficiency β can be greater than or equal to 0.4 and less than or equal to 0.6; for ribbon-like chips, the conveying efficiency β can be greater than or equal to 0.2 and less than or equal to 0.3). In one embodiment of this application, the conveying efficiency β can be taken as an empirical value of 0.4.

[0150] Although the cutting fluid pump is a constant flow source, when local blockage occurs in the deep hole chip removal channel, the effective flow cross-sectional area decreases, and the flow resistance increases sharply. This may cause the pump outlet pressure to reach the limit and trigger the safety valve, or the flow rate to decrease, resulting in a reduction in the actual effective volumetric flow rate available for carrying chips. Therefore, the chip delivery speed can be used as an indirect indicator of chip removal capacity degradation.

[0151] Step 430: Obtain the target feed rate based on the chip generation rate and the chip delivery rate.

[0152] It should be noted that the chip generation rate and chip conveying rate mentioned in this embodiment refer to the volumetric flow rate of chips passing through a certain cross section per unit time, and their units are mm³ / s (or equivalent volumetric flow rate units), rather than linear velocity.

[0153] In embodiments of this application, the target feed rate can be obtained based on the chip generation rate and the chip delivery rate in any reasonable manner. For example, in the early stages of drilling, the chip generation rate can be slightly greater than the chip delivery rate (e.g., ;or, ;in, Indicates the chip generation rate; This indicates the chip delivery speed, in order to improve work efficiency; in the later stages of drilling, the chip generation rate can be slightly lower than the chip delivery speed (e.g., ...). ;or, ;in, Indicates the chip generation rate; This indicates the chip conveying speed, to ensure chip discharge efficiency and avoid chip channel blockage.

[0154] In one specific embodiment of this application, the chip generation rate can be equal to the chip conveying rate. If the chip generation rate is equal to the chip conveying rate, the following calculation formula (hereinafter referred to as the first calculation formula) can be obtained:

[0155] ;

[0156] in, Indicates the cutting width; This indicates the target feed rate (i.e., the feed rate when the chip generation rate equals the chip delivery rate). Indicates the current spindle speed; Indicates the current cross-sectional area of ​​the chip removal channel; Indicates the cutting fluid flow rate; This indicates the conveying efficiency.

[0157] Based on the first calculation formula, the formula for calculating the target feed rate can be derived as follows:

[0158] ;

[0159] in, Indicates the target feed rate; Indicates the current cross-sectional area of ​​the chip removal channel; Indicates the cutting fluid flow rate; Indicates conveying efficiency; Indicates the cutting width; This indicates the current spindle speed.

[0160] It should be noted that the target feed rate obtained by simply matching the chip generation rate and the chip delivery rate does not take into account the dynamic changes in the machining state caused by stiffness degradation and bending deformation during drill pipe drilling. This makes it difficult to adapt to the complex working conditions of deep hole machining of high-voltage switch shaft parts. In order to make the control of the feed rate more in line with the real-time state of actual machining and further improve the machining stability, based on the obtained chip generation rate and chip delivery rate, this application further refines the feed rate (i.e., the first feed rate below) through the following steps 431 to 433 to obtain the final target feed rate.

[0161] Step 430: Based on the chip generation speed and the chip delivery speed, obtain the target feed speed, including steps 431 to 433.

[0162] Step 431: Obtain the first feed speed based on the chip generation speed and the chip delivery speed.

[0163] In this embodiment, the first feed rate is the feed rate corresponding to the condition where the chip generation rate and the chip delivery rate are equal. In this embodiment, the calculation formula for the first feed rate is as follows:

[0164] ;

[0165] in, Indicates the first feed rate; Indicates the current cross-sectional area of ​​the chip removal channel; Indicates the cutting fluid flow rate; Indicates conveying efficiency; Indicates the cutting width; This indicates the current spindle speed.

[0166] Step 432: Obtain the current slope based on the third fitted curve.

[0167] In this embodiment, the current slope is the slope corresponding to the current drilling depth in the third fitted curve. The third fitted curve is the normalized first fitted curve, with the horizontal axis representing the drilling depth and the vertical axis representing the main peak power spectral density. That is, the first fitted curve is the fitted curve obtained in step 241.

[0168] Step 433: Correct the first feed rate based on the current slope to obtain the target feed rate.

[0169] As mentioned above, a higher slope indicates a faster increase in the main peak power spectral density with increasing drilling depth, a more significant trend in drill pipe bending deformation with increasing drilling depth, a faster reduction in the annular gap between the drill pipe outer wall and the borehole wall, a more pronounced deterioration in the basic unobstructedness of the chip removal channel, and a worse foundation for chip removal, making blockage more likely; therefore, the target feed rate should be reduced. Based on this, in this embodiment, the formula for calculating the target feed rate is as follows:

[0170] ;

[0171] in, Indicates the target feed rate; Indicates the first feed rate; This indicates the current slope.

[0172] Step 500: Adjust the feed rate of the deep hole gun drill to the target feed rate.

[0173] It is important to understand that adjusting the feed rate of a deep hole gun drill to the target feed rate is a routine operation in the field of CNC machining. It can be achieved through standard G-code instructions or the adaptive control module of the CNC system. The specific execution method is well known to those skilled in the art and will not be elaborated here.

[0174] The deep hole gun drilling method for through holes of high-voltage switch shaft parts proposed in this application collects core cutting data such as the cutting fluid return pressure curve, constructs a blockage index to quantitatively characterize the blockage development state of the chip removal channel, and then derives the chip removal channel cross-sectional area reduction rate from the blockage index. Finally, based on the reduction rate, the target feed rate of the deep hole gun drill is dynamically matched and adjusted, realizing real-time, precise and adaptive control of the feed rate during the machining process. This method overcomes the technical limitations of traditional fixed machining parameters in handling the closed-loop and dynamically evolving states of deep hole machining. It can perceive the coupled effects of changes in chip removal channel patency and drill rod stiffness degradation in real time, and achieve a dynamic balance between chip generation and removal by dynamically adjusting the feed rate. This effectively reduces the risk of chip removal channel blockage and avoids problems such as drill rod wobble, tool wear, and decreased workpiece surface quality caused by blockage. It ensures the coaxiality and inner wall surface quality of key precision requirements for deep hole machining of high-voltage switch shaft parts, and improves the stability and reliability of the machining process. At the same time, compared with the conservative machining method of blindly reducing the feed rate, this method takes into account machining efficiency while avoiding machining risks. It is suitable for the harsh machining conditions of high-strength alloy materials and multi-step shaft structures of high-voltage switch shaft parts, and can improve the process adaptability and finished product qualification rate of deep hole machining of high-voltage switch shaft parts.

[0175] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0176] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the methods, apparatuses, and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or modules may be electrical, mechanical, or other forms.

[0178] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0179] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0180] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0181] The computer program product includes one or more computer instructions. When the computer program is loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video optical disc), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0182] Although embodiments of this application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles of this application.

Claims

1. A deep hole gun drilling method for high voltage switch shaft parts through hole, characterized in that, include: Obtain cutting data for deep hole gun drilling; the cutting data includes the backflow pressure curve of the cutting fluid; The horizontal axis of the backflow pressure curve represents time, and the vertical axis represents the backflow pressure of the cutting fluid. Based on the cutting data, a blockage index is obtained; the blockage index is used to characterize at least the magnitude of the increase of each peak in the return pressure curve; Based on the blockage index, the cross-sectional area reduction rate is obtained; the cross-sectional area reduction rate is used to characterize the degree of reduction in the cross-sectional area of ​​the chip removal channel during deep hole gun drilling. The target feed rate is obtained based on the cross-sectional area reduction rate; Adjust the feed rate of the deep hole gun drill to the target feed rate; The process of obtaining the blockage index based on the cutting data includes: Based on the backflow pressure curve, multiple time series curve segments are obtained; the time length of each time series curve segment is equal. Based on the Fourier transform algorithm, the time-series frequency domain signal corresponding to each time-series curve segment is obtained; Based on each time-series frequency domain signal, obtain the time-series main peak power spectral density corresponding to each time-series frequency domain signal; The blockage index is obtained based on the power spectral density of each time series main peak; The cutting data also includes the time-series drilling depth of the deep hole gun drill spindle; obtaining the blockage index based on the power spectral density of each time-series main peak includes: Based on the main peak power spectral density and the drilling depth at each time series, a first fitting curve is obtained; the horizontal axis of the first fitting curve is the drilling depth, and the vertical axis is the main peak power spectral density. Based on each time-series frequency domain signal, the time-series blocking oscillation frequency corresponding to each time-series frequency domain signal is obtained; the blocking oscillation frequency is the frequency corresponding to the maximum power spectral density value other than the main peak power spectral density in the corresponding time-series frequency domain signal. Based on each time-series congestion oscillation frequency, the time-series sub-peak power spectral density corresponding to each time-series congestion oscillation frequency is obtained; A second fitting curve is obtained based on the secondary peak power spectral density and the drilling depth at each time series; the horizontal axis of the second fitting curve is the drilling depth, and the vertical axis is the secondary peak power spectral density. The congestion index is obtained based on the first fitted curve and the second fitted curve; The step of obtaining the congestion index based on the first fitted curve and the second fitted curve includes: Based on the first and second fitted curves, a third and fourth fitted curves are obtained; the third fitted curve is the curve obtained after normalizing the first fitted curve; the fourth fitted curve is the curve obtained after normalizing the second fitted curve. Based on the third and fourth fitted curves, a first curve value and a second curve value are obtained; the first curve value is the curve value corresponding to the current drilling depth in the third fitted curve; the second curve value is the curve value corresponding to the current drilling depth in the fourth fitted curve. The congestion index is obtained based on the first curve value and the second curve value; the congestion index is negatively correlated with the first curve value and positively correlated with the second curve value.

2. The method for machining the deep hole gun drill for the through hole of the high voltage switch shaft type part according to claim 1, characterized in that, The step of obtaining the cross-sectional area reduction rate based on the congestion index includes: The congestion index is input into the prediction model to obtain the cross-sectional area reduction rate; the prediction model is pre-established.

3. The method for machining the deep hole gun drill for the through hole of the high pressure switch shaft part according to claim 2, characterized in that, The prediction model includes: ； in, Indicates the congestion index; Indicates the rate of reduction in cross-sectional area. Greater than or equal to 0, less than 1; Indicates the first coefficient; Indicates the second coefficient; The third coefficient is indicated; the first coefficient, the second coefficient, and the third coefficient are all determined through calibration experiments.

4. The deep hole gun drilling method for through holes in high-voltage switch shaft parts according to claim 1, characterized in that, The step of obtaining the target feed rate based on the cross-sectional area reduction rate includes: Based on the cutting data, the chip generation rate is obtained; the chip generation rate is used to characterize at least the speed of the chips generated by the deep hole gun drill at the current time; Based on the cross-sectional area reduction rate and the cutting data, the chip delivery speed is obtained; the chip delivery speed is used at least to characterize the speed of chips discharged by the deep hole gun drill at the current time; The target feed rate is obtained based on the chip generation rate and the chip delivery rate.

5. The deep hole gun drilling method for through holes in high-voltage switch shaft parts according to claim 4, characterized in that, The cutting data includes the current feed rate, current spindle speed, and cutting width of the deep hole gun drill; The step of obtaining the chip generation rate based on the cutting data includes: Based on the current feed rate and the current spindle speed, the feed per revolution is obtained; the feed per revolution is equal to the ratio of the current feed rate to the current spindle speed. Based on the feed per revolution and the cutting width, the effective cutting area is obtained; the effective cutting area is equal to the product of the feed per revolution and the cutting width. The chip generation rate is obtained based on the effective cutting area and the current feed rate.

6. The deep hole gun drilling method for through holes in high-voltage switch shaft parts according to claim 4, characterized in that, The cutting data also includes the cutting fluid flow rate and the original cross-sectional area of ​​the chip removal channel in the deep hole gun drill; obtaining the chip delivery speed based on the cross-sectional area reduction rate and the cutting data includes: Based on the original cross-sectional area of ​​the chip removal channel and the cross-sectional area reduction rate, the current cross-sectional area of ​​the chip removal channel is obtained; The chip delivery speed is obtained based on the current cross-sectional area of ​​the chip removal channel and the cutting fluid flow rate.

7. The deep hole gun drilling method for through holes in high-voltage switch shaft parts according to claim 4, characterized in that, The step of obtaining the target feed rate based on the chip generation rate and the chip delivery rate includes: A first feed rate is obtained based on the chip generation rate and the chip delivery rate; the first feed rate is the feed rate corresponding to the equality of the chip generation rate and the chip delivery rate. Based on the third fitted curve, the current slope is obtained; the current slope is the slope corresponding to the current drilling depth in the third fitted curve. The first feed rate is corrected based on the current slope to obtain the target feed rate.

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