Precision manufacturing deburring method based on vibration grinding

Abstract

The present invention relates to the field of vibration grinding technology, and in particular to a precision manufacturing deburring method based on vibration grinding, comprising: obtaining a rough-ground workpiece after rough grinding, visually detecting secondary burrs generated therefrom and constructing a three-dimensional secondary burr model; identifying isolated primary burrs, continuous secondary burrs, tear-type burrs, and micro-burrs present in the model based on a size threshold, obtaining burr characteristic parameters, and determining process parameters of a fine grinding process accordingly; fine grinding the rough-ground workpiece, collecting grinding acoustic emission signals in real time during the process, and adjusting the vibration fine grinding time based on energy entropy; adjusting the vibration fine grinding frequency based on a frequency offset; adjusting the vibration fine grinding amplitude based on the energy rise angle of a pulse signal to obtain a fine-ground workpiece; detecting residual burrs on the fine-ground workpiece, and adjusting the size threshold according to the removal percentage of isolated primary burrs and continuous secondary burrs. The present invention improves the process effect of removing secondary burrs by vibration grinding.

Description

Technical Field

[0001] The present invention relates to the technical field of vibration grinding, and in particular to a precision manufacturing deburring method based on vibration grinding. Background Art

[0002] In the field of precision manufacturing, the vibration grinding deburring process is widely used in the surface treatment of high-value-added parts in aerospace, medical equipment, jade processing, etc. The core of vibration grinding is to drive the interaction between the abrasive and the workpiece through multi-dimensional vibration to achieve burr removal and surface finishing. The specific principle is that the vibration grinder uses a three-dimensional composite motion of up and down vibration, spiral tumbling, and horizontal flipping to make the abrasive and workpiece fully contact. Under the action of vibration, the abrasive particles produce collision, rolling, and micro-cutting, which breaks the burrs and gradually grinds away the burrs and rounds the sharp edges. However, the traditional vibration grinding deburring process has the following defects: the detection and removal process of secondary burrs generated after rough grinding relies entirely on manual experience, making it difficult to capture the microscopic morphological changes of secondary burrs during fine grinding. At the same time, the random distribution characteristics of secondary burrs exacerbate the difficulty of fine grinding control, resulting in poor processing consistency. Complex structure workpieces are prone to local over-grinding or burr residue.

[0003] Chinese patent application publication number CN109571231B discloses a vibration grinding method and apparatus. A powered or freely rotating turret is positioned above a cylinder of a vibration grinder, which rotates under power and is filled with abrasive. Several connecting rods with connecting members are positioned below the turret. A workpiece (such as a metal handle) is secured to the connecting rods via the connecting members, allowing the workpiece to be inserted into the abrasive in the cylinder. As the vibration grinder operates, the workpiece's surface is polished. The vibration of the cylinder drives the abrasive to flow, which in turn moves the workpiece, causing the turret to rotate with it, thereby polishing the workpiece. Compared to existing technologies, this invention effectively prevents workpieces from contacting each other, ensuring high-quality polishing.

[0004] It can be seen from this that the above-mentioned vibration grinding method and device have the problem that vibration grinding of the secondary burrs generated after rough grinding is prone to local over-grinding or burr residue. Summary of the Invention

[0005] To this end, the present invention provides a precision manufacturing deburring method based on vibration grinding, which is used to overcome the problem in the prior art that vibration grinding of secondary burrs generated after rough grinding is prone to local over-grinding or burr residue.

[0006] To achieve the above object, the present invention provides a precision manufacturing deburring method based on vibration grinding, comprising:

[0007] Step S1, obtaining a rough-ground workpiece after rough grinding by a vibration grinder, and basic parameters of the rough-ground workpiece, wherein the basic parameters include the number of workpieces, the hardness of the workpiece, and the weight of the workpiece;

[0008] Step S2, visually inspecting secondary burrs generated on the rough-ground workpiece after rough grinding, and constructing a three-dimensional secondary burr model of the rough-ground workpiece;

[0009] Step S3, based on the size threshold of the secondary burr, identifying isolated main burrs, continuous secondary burrs, tearing burrs and micro burrs in the three-dimensional secondary burr model, and obtaining burr characteristic parameters of the rough-ground workpiece;

[0010] Step S4, determining the fine grinding process parameters according to the burr characteristic parameters, including vibration fine grinding frequency, vibration fine grinding amplitude and vibration fine grinding time;

[0011] Step S5, based on the fine grinding process parameters, fine grinding the rough ground workpiece to remove the secondary burrs, including:

[0012] During the fine grinding process, a grinding acoustic emission signal of the fine grinding is collected in real time, and the vibration fine grinding time is adjusted based on the energy entropy in the grinding acoustic emission signal;

[0013] adjusting the vibration fine grinding frequency based on a frequency offset in the grinding acoustic emission signal;

[0014] adjusting the vibration fine grinding amplitude based on the energy rise angle of the pulse signal in the grinding acoustic emission signal to obtain a finely ground workpiece;

[0015] Step S6: visually inspecting the residual burrs on the finely ground workpiece, and adjusting the size threshold according to the removal percentages of the isolated main burrs and the continuous secondary burrs.

[0016] Furthermore, step S3 includes:

[0017] Step S31, judging the type of each burr according to the size threshold to determine the number of isolated main burrs and the number of micro burrs;

[0018] Step S32, calculating an average height of the isolated main burrs according to the number of the isolated main burrs and the height of each isolated main burr;

[0019] Step S33, determining the length of the continuous secondary burrs and the length of the tearing burrs according to the size threshold;

[0020] Step S34: Calculate the average height of continuous secondary burrs and the average height of tearing-type burrs based on the length of the continuous secondary burrs and the length of the tearing-type burrs to obtain the burr characteristic parameters, wherein the burr characteristic parameters include: the number of isolated main burrs, the average height of isolated main burrs, the length of the continuous secondary burrs, the average height of the continuous secondary burrs, the length of the tearing-type burrs, the average height of the tearing-type burrs, and the number of micro-burrs.

[0021] Furthermore, the step S4 includes:

[0022] Step S41, determining the vibration fine grinding frequency according to the number of isolated main burrs, the length of continuous secondary burrs and the length of tearing burrs;

[0023] Step S42, determining the vibration fine grinding amplitude according to the average height of the isolated main burrs, the average height of the continuous secondary burrs, and the average height of the tearing burrs;

[0024] Step S43, according to the number of isolated main burrs, the length of continuous secondary burrs, the length of tearing burrs, the average height of isolated main burrs, the average height of continuous secondary burrs and the average height of tearing burrs,

[0025] Determine the burr volume equivalent;

[0026] Step S44, determining the vibration fine grinding time according to the total burr volume, the vibration fine grinding frequency, and the vibration fine grinding amplitude;

[0027] Step S45 , judging whether to perform a super-finishing process and determining the time of the super-finishing process according to the number of the micro-burrs.

[0028] Furthermore, the step S5 includes:

[0029] Step S51, using a piezoelectric acoustic emission sensor to collect the original grinding acoustic emission signal during the fine grinding process;

[0030] Step S52, filtering out low-frequency mechanical noise in the original grinding acoustic emission signal through a bandpass filter to obtain an acoustic emission signal;

[0031] Step S53, performing wavelet packet transform on the acoustic emission signal to calculate the energy entropy of the acoustic emission signal to detect and determine the degree of discreteness of energy distribution during the vibration grinding process;

[0032] Step S54, tracking the resonance peak in the acoustic emission signal, and calculating a frequency offset based on the sampling frequency of the piezoelectric acoustic emission sensor to detect and determine the frequency migration caused by stress release or structural resonance inside the workpiece;

[0033] Step S55, calculating the energy rise angle of the pulse signal in the acoustic emission signal to detect and determine the impact strength of the abrasive during the vibration grinding process;

[0034] Step S56 , adjusting the fine grinding process parameters in real time according to the energy entropy, the frequency offset, and the energy rise angle in the acoustic emission signal to obtain a finely ground workpiece.

[0035] Furthermore, before step S51 , there is further provided: determining a time window for collecting grinding acoustic emission signals during the fine grinding process according to the number of the isolated main burrs and the length of the tearing burrs.

[0036] Furthermore, the step S53 includes:

[0037] Step S531, performing wavelet packet transform on the acoustic emission signal to decompose the acoustic emission signal into several sub-bands;

[0038] Step S532, calculating the energy of each of the sub-frequency bands;

[0039] Step S533: Calculate the energy entropy of the acoustic emission signal according to the energy of each sub-frequency band.

[0040] Furthermore, the step S54 includes:

[0041] Step S541, constructing an autoregressive model of the acoustic emission signal;

[0042] Step S542, solving the characteristic equation of the autoregressive model to calculate and obtain a number of frequency components;

[0043] Step S543, identifying a main resonance peak among the frequency components;

[0044] Step S544 : Calculate the frequency offset based on the main resonance peak and the reference frequency of the vibration grinder when it is unloaded.

[0045] Furthermore, the step S55 includes:

[0046] Step S551, calculating a pulse detection threshold according to the ambient noise during non-vibration grinding;

[0047] Step S552, determining whether the signal amplitude in the acoustic emission signal is greater than the pulse detection threshold, and obtaining a pulse signal;

[0048] Step S553, calculating the energy rise angle of the pulse signal according to the rise time of the pulse signal and the voltage peak of the pulse signal;

[0049] Step S554, determining the pulse signal exceeding threshold value according to the material of the workpiece;

[0050] Step S555 , calculating the proportion of pulse signals exceeding the standard and the concentration of high energy rise angles within the time window according to the pulse signal exceeding the standard threshold and the energy rise angle.

[0051] Furthermore, the step S552 also includes: calculating a ring count based on the number of times the signal amplitude exceeds a threshold within a unit time.

[0052] Furthermore, in step S2, morphological feature data of the secondary burr is acquired through multi-angle image acquisition, and based on the morphological feature data, the three-dimensional secondary burr model is generated through a three-dimensional point cloud reconstruction algorithm.

[0053] Compared with the existing technology, the beneficial effect of the present invention is that the present invention greatly improves the process effect of vibration grinding deburring by collecting the sound wave signals in the grinding process in real time, analyzing the processing status, capturing the burr removal status (such as material fracture, abrasive passivation, etc.) in real time, and dynamically optimizing parameters.

[0054] Furthermore, the present invention constructs a multi-objective optimization model based on the ring count, energy entropy and other characteristics of the acoustic emission signal, dynamically adjusts the vibration frequency, amplitude and abrasive ratio, adaptively matches the grinding requirements of different materials (such as aluminum alloy and titanium alloy), improves process compatibility, and at the same time optimizes energy consumption distribution, reduces invalid vibration, and extends equipment life.

[0055] Furthermore, the present invention monitors the energy rise angle of the pulse signal in the acoustic emission signal. When the energy rise angle exceeds a safety threshold, it automatically reduces the amplitude or switches to a high-frequency micro-amplitude mode to inhibit the generation of micro-cracks, ensure the surface integrity of the workpiece, avoid local over-grinding caused by parameter solidification, and improve processing consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a flow chart of a precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention;

[0057] Figure 2 This is a flow chart of step S3 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention;

[0058] Figure 3 This is a flow chart of step S4 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention;

[0059] Figure 4 This is a flow chart of step S5 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0061] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0062] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0063] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0064] Specific embodiments are given below in conjunction with the accompanying drawings. The specific embodiments are only used to describe the technical solutions of the present invention in detail and are not intended to limit the scope of protection of the present application.

[0065] See also Figure 1 As shown, it is a flow chart of a precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention, comprising:

[0066] Step S1, obtaining a rough-ground workpiece after rough grinding by a vibration grinder, and basic parameters of the rough-ground workpiece, wherein the basic parameters include the number of workpieces, the hardness of the workpiece, and the weight of the workpiece;

[0067] Specifically, after obtaining the rough-ground workpiece after rough grinding by the vibration grinder and the basic parameters of the rough-ground workpiece, the abrasive type, abrasive size, abrasive shape and abrasive addition amount in the fine grinding process are determined according to the basic parameters.

[0068] During implementation, the hardness (HRC value) of the rough grinding workpiece is measured by a material hardness tester, and the abrasive type is selected according to the hardness of the rough grinding workpiece. Preferably, when HRC≤50, resin-based abrasive is selected, when 50<HRC≤65, ceramic abrasive is selected, and when HRC>65, brown corundum abrasive is selected.

[0069] It is understandable that the material hardness of the workpiece determines the compressive strength matching of the abrasive, preventing premature passivation of the abrasive and avoiding damage to the workpiece due to the abrasive being too hard relative to the workpiece;

[0070] During implementation, those skilled in the art should also adaptively select abrasives according to the characteristics of the workpiece to be ground. For example, for zinc alloy die-castings, brown corundum grinding stones should be avoided to prevent the workpiece from blackening. The selection of abrasive materials is existing technology and will not be elaborated here.

[0071] During implementation, those skilled in the art should also adaptively select the size and shape of the abrasive according to the size and type of the holes and keyways in the workpiece to be ground, so as to prevent the abrasive from getting stuck, clogging or being unable to vibrate and grind to a specific position. The selection of the size and shape of the abrasive is a prior art and will not be elaborated here.

[0072] In implementation, the total weight of the workpieces is calculated based on the number and weight of the workpieces, and the amount of abrasive added is determined based on the total weight of the workpieces. Preferably, the weight ratio of abrasive to workpieces is 3:1 to 10:1.

[0073] It is understandable that the appropriate weight ratio ensures the effective coverage of the abrasive on the workpiece, while separating the workpieces and reducing collisions between the workpieces. The selection of the amount of abrasive is a prior art and will not be elaborated here.

[0074] Step S2, visually inspecting secondary burrs generated on the rough-ground workpiece after rough grinding, and constructing a three-dimensional secondary burr model of the rough-ground workpiece;

[0075] Specifically, in step S2, the morphological feature data of the secondary burr is acquired by multi-angle image acquisition, and based on the morphological feature data, the three-dimensional secondary burr model is generated by a three-dimensional point cloud reconstruction algorithm.

[0076] During implementation, the rough-ground workpiece is placed on the worktable of a coordinate measuring machine (CMM), and the workpiece is fixed by a vacuum adsorption fixture to ensure that there is no displacement during the inspection process. The workpiece coordinate system is calibrated using a laser locator and aligned with the CAD design model coordinate system. An industrial-grade linear array CCD camera is used. Preferably, the camera resolution is 2048×1080 pixels and the scanning accuracy is ±5μm. A ring-shaped LED array light source (wavelength 625nm) is set to illuminate the workpiece surface at a 45° angle to eliminate reflection interference.

[0077] Specifically, the image acquisition process is as follows: control the CMM to drive the workpiece to rotate at a constant speed of 10mm / s, and the camera continuously captures the workpiece surface image at a rate of 200 frames per second and transmits the image to the industrial computer in real time.

[0078] Use OpenCV library to perform image processing and set area threshold (>0.1mm 2 ) filter noise and retain the effective burr contour; calculate the burr spatial coordinates through the multi-eye vision triangulation principle, use the Point Cloud Library (PCL) to build a point cloud model, and apply the Poisson surface reconstruction algorithm to generate the three-dimensional secondary burr model.

[0079] It is understandable that digital reconstruction modeling of the processed workpiece is an existing technology and will not be described in detail here.

[0080] Step S3, based on the size threshold of the secondary burr, identifying isolated main burrs, continuous secondary burrs, tearing burrs and micro burrs in the three-dimensional secondary burr model, and obtaining burr characteristic parameters of the rough-ground workpiece;

[0081] Please continue reading Figure 2 As shown, it is a flow chart of step S3 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention. Specifically, step S3 includes:

[0082] Step S31, judging the type of each burr according to the size threshold to determine the number of isolated main burrs and the number of micro burrs;

[0083] In implementation, the size threshold includes a height threshold and a length threshold. Preferably, the height threshold is 0.3 mm, and the length threshold is 1.5 mm.

[0084] In implementation, burrs in the three-dimensional secondary burr model that satisfy the burr height greater than or equal to the height threshold and the burr length less than the length threshold are marked as isolated main burrs, and the average number of isolated main burrs of several rough-ground workpieces is counted and recorded as N1.

[0085] In implementation, burrs in the three-dimensional secondary burr model that satisfy both a burr height less than the height threshold and a burr length less than the length threshold are marked as micro-burrs, and the number of micro-burrs is counted and recorded as N2.

[0086] It can be understood that isolated main burrs are the reflection of stress concentration points that are not completely removed during the rough grinding process. They are characterized by high height but short length, and are distributed in a point-like manner along the edge of the workpiece; micro burrs are the residues of abrasive micro-cutting during the rough grinding process or the original surface shape features of the workpiece that cannot be removed during the rough grinding process. They are characterized by low height and short length, and are randomly distributed in a point-like manner.

[0087] The height threshold is used to filter out tiny textures, and the length threshold is used to exclude strip-shaped continuous burrs. By identifying the number of high-stress residual points, the total energy required for burr fracture is estimated.

[0088] Step S32, calculating an average height of the isolated main burrs according to the number of the isolated main burrs and the height of each isolated main burr;

[0089] In implementation, the peak height of each isolated main burr is extracted, and the arithmetic mean of all the peak heights is calculated to obtain the average height of the isolated main burrs, which is recorded as H1.

[0090] Step S33, determining the length of the continuous secondary burrs and the length of the tearing burrs according to the size threshold;

[0091] Step S34: Calculate the average height of continuous secondary burrs and the average height of tearing-type burrs based on the length of the continuous secondary burrs and the length of the tearing-type burrs to obtain the burr characteristic parameters, wherein the burr characteristic parameters include: the number of isolated main burrs, the average height of isolated main burrs, the length of the continuous secondary burrs, the average height of the continuous secondary burrs, the length of the tearing-type burrs, the average height of the tearing-type burrs, and the number of micro-burrs.

[0092] In implementation, burrs in the three-dimensional secondary burr model that satisfy the conditions that the burr height is less than the height threshold and the burr length is greater than or equal to the length threshold are marked as continuous secondary burrs, and the sum of the lengths of all continuous secondary burrs is calculated, recorded as L1; the height peak value in each continuous secondary burr is taken, and the average value of all height peak values ​​is calculated, recorded as H2.

[0093] In implementation, the burrs in the three-dimensional secondary burr model that satisfy the burr height greater than or equal to the height threshold and the burr length greater than or equal to the length threshold are marked as tearing-type burrs, and the sum of the lengths of all tearing-type burrs is calculated, recorded as L2; ​​the height peak value in each tearing-type burr is taken, and the average value of all height peak values ​​is calculated, recorded as H3.

[0094] It can be understood that continuous secondary burrs are bulges caused by the plastic flow of the material during the processing process. They are characterized by low height but long length, similar to surface wrinkles; tear-type burrs are tearing caused by tool chips sticking during processing that cannot be completely removed in the rough grinding process. They are characterized by high height and long length, and are continuously distributed along the edge of the workpiece, similar to a knife edge.

[0095] The present invention converts the physical morphology differences of secondary burrs into the basis of process parameters for fine grinding, no longer relying on operator experience. The burr removal status of the workpiece after rough grinding is observed with the naked eye, providing a quantitative data set for precision deburring.

[0096] Step S4, determining the fine grinding process parameters according to the burr characteristic parameters, including vibration fine grinding frequency, vibration fine grinding amplitude and vibration fine grinding time;

[0097] Please continue reading Figure 3As shown, it is a flow chart of step S4 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention. Specifically, step S4 includes:

[0098] Step S41, determining the vibration fine grinding frequency according to the number of isolated main burrs, the length of continuous secondary burrs and the length of tearing burrs;

[0099] In practice, the calculation formula of the vibration fine grinding frequency is specifically:

[0100] ,

[0101] Among them, F is the vibration fine grinding frequency, the unit is Hz, and 40Hz≤F≤100Hz; a is the frequency coefficient of isolated main burrs, the unit is Hz / piece, preferably, 0.8Hz / piece to 1.2Hz / piece; b is the frequency coefficient of continuous secondary burrs, the unit is Hz / mm, preferably, 0.05Hz / mm to 0.1Hz / mm; c is the frequency coefficient of tearing burrs, the unit is Hz / mm, preferably, 0.15Hz / mm to 0.25Hz / mm.

[0102] It can be understood that a unit isolated main burr requires an independent impact event to remove, the longer the length of the continuous secondary burr, the higher the frequency coverage is required, and the tearing-type burr requires ultra-high frequency to prevent the tertiary burr caused by adhesion; the above-mentioned isolated main burr frequency, continuous secondary burr frequency coefficient and tearing-type burr frequency coefficient are calibrated through experiments, and those skilled in the art can make adaptive adjustments according to actual conditions, which will not be repeated here.

[0103] Step S42, determining the vibration fine grinding amplitude according to the average height of the isolated main burrs, the average height of the continuous secondary burrs, and the average height of the tearing burrs;

[0104] In practice, the calculation formula for the vibration fine grinding amplitude is specifically:

[0105] ,

[0106] Among them, A is the vibration fine grinding amplitude, the unit is mm, and 2mm≤A≤5mm; α is the isolated main burr amplitude coefficient, preferably 15-20; β is the tearing type burr amplitude coefficient, preferably 20-30; γ is the continuous secondary burr amplitude coefficient, preferably -0.5 to -1.

[0107] It is understandable that burrs with higher heights need to be given higher weights, and the fracture energy that meets the most demanding burrs should be taken to quantify the energy requirements for long burr removal and avoid root residues caused by insufficient amplitude. At the same time, continuous secondary burrs are essentially wrinkles formed by plastic deformation of the material surface, and their removal process conforms to the law of metal plastic forming. At the same time, when the applied stress is close to the yield strength of the material, orderly plastic flow occurs in the burr area, and the wrinkles are stretched and removed. When the applied stress is much greater than the yield strength of the material, the base material will yield twice and generate new surface defects. Therefore, when the height of continuous secondary burrs is high, the amplitude should be reduced to suppress the generation of tertiary burrs (appearing as wavy series wrinkles).

[0108] Step S43, determining a burr volume equivalent according to the number of isolated main burrs, the length of continuous secondary burrs, the length of tearing burrs, the average height of isolated main burrs, the average height of continuous secondary burrs, and the average height of tearing burrs;

[0109] In practice, the calculation formula for the burr volume equivalent is specifically:

[0110] ,

[0111] Where V is the burr volume equivalent, in mm 3 ; k1 is the volume coefficient of isolated main burrs, preferably, it is 0.02; k2 is the volume coefficient of tearing burrs, preferably, it is 0.15; k3 is the volume coefficient of continuous secondary burrs, preferably, it is 0.25.

[0112] It is understandable that the k1, k2 and k3 are determined through calibration experiments (measuring the actual burr volume through 3D scanning and determining the k value through regression analysis). This is a prior art and will not be described in detail here.

[0113] Step S44, determining the vibration fine grinding time according to the total burr volume, the vibration fine grinding frequency, and the vibration fine grinding amplitude;

[0114] In practice, the calculation formula for the vibration fine grinding time is specifically:

[0115] ,

[0116] Where t is the vibration grinding time, unit is s; η is the efficiency coefficient, unit is Hz·s·mm -2 , determined according to the abrasive type and workpiece hardness, preferably 0.8Hz·s·mm -2 ~1Hz·s·mm -2 .

[0117] It can be understood that the essence of burr removal is volume reduction, and the processing time depends on the volume removal rate, which is positively correlated with the frequency and amplitude of vibration grinding. Among them, the frequency can approximately reflect the sliding distance of the abrasive, and the amplitude can approximately reflect the contact pressure of the abrasive.

[0118] Step S45 , judging whether to perform a super-finishing process and determining the time of the super-finishing process according to the number of the micro-burrs.

[0119] In practice, for a single workpiece, when N2 ≥ 10, a super-fine grinding process is performed after the fine grinding process, the abrasive is replaced, and the super-fine grinding process is performed at a vibration frequency of 80 Hz and a vibration amplitude of 1 mm. The calculation formula for the super-fine grinding process is specifically:

[0120] ,

[0121] Among them, t c is the time of the super-fine grinding process, in seconds; t0 is the basic time of the super-fine grinding process, in seconds, preferably, 600 seconds; k4 is the time coefficient of the super-fine grinding process, preferably, 10 seconds / piece.

[0122] It is understandable that micro-burrs are usually residues from abrasive micro-cutting. When the number of micro-burrs is large, an additional low-amplitude, high-frequency polishing process is required to remove them.

[0123] Step S5, based on the fine grinding process parameters, fine grinding the rough ground workpiece to remove the secondary burrs, including:

[0124] The grinding acoustic emission signal of the fine grinding is collected in real time during the fine grinding process, and the vibration fine grinding time is adjusted based on the energy entropy in the grinding acoustic emission signal;

[0125] adjusting the vibration fine grinding frequency based on a frequency offset in the grinding acoustic emission signal;

[0126] adjusting the vibration fine grinding amplitude based on the energy rise angle of the pulse signal in the grinding acoustic emission signal to obtain a finely ground workpiece;

[0127] Please continue reading Figure 4 As shown, it is a flow chart of step S5 of the precision manufacturing deburring method based on vibration grinding according to an embodiment of the present invention. Specifically, step S5 includes:

[0128] The time window for collecting the grinding acoustic emission signal during the fine grinding process is determined according to the number of the isolated main burrs and the length of the tearing burrs.

[0129] In implementation, the calculation formula of the time window is specifically:

[0130] ,

[0131] Among them, w is the duration of the time window, the unit is s; w0 is the basic duration of the time window, the unit is s, preferably, it is 0.05s; p1 is the isolated burr time coefficient, the unit is s·piece, preferably, it is 0.05s·piece; p2 is the tearing type burr time coefficient, the unit is s / mm, preferably, it is 0.05s / mm~0.1s / mm.

[0132] It is understandable that the breakage of isolated main glitches produces high-frequency transient pulses (duration <1ms). The more there are, the denser the pulses. When there are many isolated main glitches, shortening the window can avoid signal aliasing caused by pulse overlap and improve the resolution of transient events. The stress release of tearing-type glitches is a low-frequency gradual process (lasting hundreds of milliseconds to several seconds). The longer the length, the slower the frequency shift process. When the tearing-type glitches are long, extending the window can fully capture the frequency drift trajectory and prevent distortion in frequency domain analysis.

[0133] During implementation, when fine grinding the rough-ground workpiece in step S5, it also includes adding grinding fluid to the vibration grinder to form a layer of liquid as an interface between the grindstone and the workpiece to prevent abrasive powder from adhering to the workpiece. At the same time, it can play the role of lubrication, softening hard water, cleaning abrasives and workpieces, corrosion prevention and rust removal. The type and amount of the grinding fluid are selected according to the existing technology and will not be repeated here.

[0134] Step S51, using a piezoelectric acoustic emission sensor to collect the original grinding acoustic emission signal during the fine grinding process;

[0135] Step S52, filtering out low-frequency mechanical noise in the original grinding acoustic emission signal through a bandpass filter to obtain an acoustic emission signal;

[0136] In implementation, preferably, the bandpass filter adopts 100kHz to 800kHz.

[0137] Step S53, performing wavelet packet transform on the acoustic emission signal to calculate the energy entropy of the acoustic emission signal to detect and determine the degree of discreteness of energy distribution during the vibration grinding process;

[0138] Specifically, step S53 includes:

[0139] Step S531, performing wavelet packet transform on the acoustic emission signal to decompose the acoustic emission signal into several sub-bands;

[0140] In implementation, preferably, the number of decomposition layers is 5 Daubechies wavelet basis (DB4) to generate several sub-bands.

[0141] Step S532, calculating the energy of each of the sub-frequency bands;

[0142] In implementation, the calculation formula of the energy of the sub-band is specifically:

[0143] ,

[0144] Among them, W i (m) reflects the energy intensity of the signal at a specific frequency sub-band i and a specific time point m. It is generated by the wavelet packet decomposition algorithm and will not be described in detail here. m is the index of the coefficient within the sub-band, representing the position in the time series and corresponding to the time point of the original signal (equally spaced sampling). M is the length of the sub-band signal, and its calculation formula is as follows:

[0145] ,

[0146] Wherein, N is the total number of sampling points in the time window, that is, the product of the time window length w and the sampling frequency of the piezoelectric acoustic emission sensor. Preferably, the sampling frequency is 2 MHz; N 分解层数 The number of decomposition layers used for wavelet packet transform of the acoustic emission signal is preferably N 分解层数 =5; where M is an integer.

[0147] Step S533: Calculate the energy entropy of the acoustic emission signal according to the energy of each sub-frequency band.

[0148] In practice, the energy entropy calculation formula is specifically as follows:

[0149] ,

[0150] Among them, H w is the energy entropy.

[0151] It can be understood that energy entropy describes the degree of disorder in the distribution of acoustic emission signal energy in different frequency sub-bands.

[0152] Step S54, tracking the resonance peak in the acoustic emission signal, and calculating a frequency offset based on the sampling frequency of the piezoelectric acoustic emission sensor to detect and determine the frequency migration caused by stress release or structural resonance inside the workpiece;

[0153] Specifically, step S54 includes:

[0154] Step S541, constructing an autoregressive model of the acoustic emission signal;

[0155] In implementation, the expression of the autoregressive model is specifically:

[0156] ,

[0157] Among them, x(n) represents the signal amplitude of the nth sampling point among the N sampling points of the acoustic emission signal in the time window, r1~r p is the autoregressive coefficient, and e(n) is white noise (unpredictable random disturbance).

[0158] Preferably, the order p of the autoregressive model is 12.

[0159] It can be understood that the autoregressive model is a mathematical model used for time series analysis. Its core idea is that the current signal value can be predicted by a linear combination of several past signal values. Therefore, by fitting historical data, the regular components in the acoustic emission signal (such as vibrations of a specific frequency) can be extracted.

[0160] Step S542, solving the characteristic equation of the autoregressive model to calculate and obtain a number of frequency components;

[0161] In practice, the characteristic equation root of the autoregressive model is solved to obtain the frequency component, which is denoted as f k , unit is Hz.

[0162] It can be understood that the roots of the equation correspond to poles on the complex plane, and each pole corresponds to a frequency component f k The frequency component f k The value of is the product of the number of cycles obtained by dividing the phase angle of the corresponding pole by 2π and the sampling frequency; the solution of the characteristic equation roots of the autoregressive model is a prior art and will not be repeated here.

[0163] Step S543, identifying a main resonance peak among the frequency components;

[0164] In practice, the calculation formula of the main resonance peak is specifically:

[0165] ,

[0166] Among them, f peak is the main resonance peak, in Hz.

[0167] It can be understood that during the grinding process, the size of the main resonance peak in the acoustic emission signal corresponds to the state of material removal. Specifically, when the micro crack expands, the main resonance peak is the high-frequency peak (>400kHz); when the burr breaks, the main resonance peak is the medium-frequency peak (50kHz~400kHz); when the abrasive collides with the workpiece, the main resonance peak is the low-frequency peak (<50kHz).

[0168] Step S544 : Calculate the frequency offset based on the main resonance peak and the reference frequency of the vibration grinder when it is unloaded.

[0169] In implementation, the frequency offset is calculated as follows:

[0170] ,

[0171] Where △f is the frequency offset, in Hz; f base is the reference frequency of the vibration grinder when it is no-load, in Hz.

[0172] It can be understood that the frequency offset △f has the dual functions of resonance risk warning and burr removal status judgment. Among them, when a burr exists, the stress is concentrated at the root of the burr, and the energy released when it breaks causes high-frequency vibration, which is manifested as a gradual increase in the frequency offset △f. After the burr is removed, the stress is released and the vibration returns to the medium and low frequencies, which is manifested as the frequency offset △f reaching a peak and then falling back.

[0173] Step S55, calculating the energy rise angle of the pulse signal in the acoustic emission signal to detect and determine the impact strength of the abrasive during the vibration grinding process;

[0174] Specifically, step S55 includes:

[0175] Step S551, calculating a pulse detection threshold according to the ambient noise during non-vibration grinding;

[0176] In implementation, the calculation formula of the pulse detection threshold is specifically:

[0177] ,

[0178] Among them, V th is the pulse detection threshold; V 噪 is the RMS value of noise without grinding.

[0179] It can be understood that in acoustic emission signals, a pulse refers to a transient signal generated by a single physical event (such as abrasive impact or burr breakage), and its amplitude is much higher than the background noise.

[0180] Step S552, determining whether the signal amplitude in the acoustic emission signal is greater than the pulse detection threshold, and obtaining a pulse signal;

[0181] In an implementation, the signal amplitude within the time window exceeds the pulse detection threshold V th The signal is determined to be the pulse signal.

[0182] Specifically, the step S552 further includes: calculating a ring count according to the number of times the signal amplitude exceeds a threshold within a unit time.

[0183] In implementation, the calculation formula for the ring count is specifically:

[0184] ,

[0185] Among them, N c is the ringing count, that is, the signal amplitude per unit time exceeds the pulse detection threshold V th times.

[0186] Step S553, calculating the energy rise angle of the pulse signal according to the rise time of the pulse signal and the voltage peak of the pulse signal;

[0187] In implementation, the calculation formula of the energy rise angle of the pulse signal is specifically:

[0188] ,

[0189] Where RA is the energy rise angle, in μs / V; t ra is the rise time of the pulse signal, that is, the time from when the pulse signal exceeds the pulse detection threshold to when the pulse signal reaches the peak value, in μs; V ra is the peak voltage of the pulse signal, in V.

[0190] It can be understood that the energy rise angle RA is essentially the inverse of the slope, which describes how fast the acoustic emission pulse amplitude rises and is used to characterize the material fracture mode.

[0191] Step S554, determining the pulse signal exceeding threshold value according to the material of the workpiece;

[0192] In practice, the calculation formula for the pulse signal exceeding the threshold value is specifically:

[0193] ,

[0194] Among them, RA c is the pulse signal exceeding threshold, in μs / V; HRC is the hardness of the workpiece material; E is the elastic modulus of the workpiece material, in GPa; k ra is the pulse signal exceeding threshold coefficient, with the unit being μs·GPa / V. Preferably, it is 1.15 μs·GPa / V.

[0195] When RA>RA c When , the pulse signal is recorded as an exceeding-standard pulse signal.

[0196] It can be understood that when the energy rise angle is less than or equal to the pulse signal exceeding the threshold, it indicates that the energy is released quickly, which is a brittle fracture. When the energy rise angle is greater than the pulse signal exceeding the threshold, it indicates that the energy is released slowly, which is plastic flow.

[0197] Step S555 , calculating the proportion of pulse signals exceeding the standard and the concentration of high energy rise angles within the time window according to the pulse signal exceeding the standard threshold and the energy rise angle.

[0198] In implementation, the proportion of excessive pulse signals The calculation formula is as follows:

[0199] ,

[0200] It can be understood that the proportion of the exceeding-standard pulse signal is used to avoid false triggering of individual interference pulses.

[0201] In practice, high energy rise angle concentration The calculation formula is as follows:

[0202] ,

[0203] The number of consecutive pulses exceeding the standard within the time window is preferably defined as when three consecutive pulse signals among all pulse signals within the time window are greater than the pulse signal exceeding the standard threshold, it is recorded as one consecutive pulse exceeding the standard.

[0204] It is understandable that only continuous plastic deformation can be judged as over-wear.

[0205] Step S56 , adjusting the fine grinding process parameters in real time according to the energy entropy, the frequency offset, and the energy rise angle in the acoustic emission signal to obtain a finely ground workpiece.

[0206] Specifically, in step S56,

[0207] The burr removal state during the fine grinding process is determined according to the energy entropy and the frequency offset, wherein:

[0208] If the energy entropy is within the first threshold range and the frequency offset continues to increase, it is determined that the fine grinding process is in the continuous burr removal stage, and the process parameters of the fine grinding process are maintained;

[0209] If the energy entropy is within the second threshold range and the frequency offset reaches a peak value and then begins to decrease, it is determined that the isolated main burr is completely removed and the fine grinding process is at a fine grinding transition point, and the vibration fine grinding amplitude is reduced and the vibration fine grinding frequency is increased;

[0210] In implementation, the first threshold interval is preferably [1.8, 2.5]; the second threshold interval is preferably (2.5, 3.5).

[0211] It can be understood that the physical meaning of the energy entropy is the degree of distribution disorder of the signal energy in the frequency domain, which characterizes the degree of discreteness of the energy distribution during the fine grinding process; the physical meaning of the frequency offset is the offset of the main vibration frequency relative to the reference, which characterizes the frequency migration caused by the internal stress release of the material during the fine grinding process. When the energy entropy is in the first threshold range, it indicates that the energy is concentrated in a few sub-bands; at the same time, the frequency offset continues to increase, indicating that the stress is fully released (significant frequency shift), which further indicates that the process state is efficiently removing burrs.

[0212] When the energy entropy is in the second threshold range, it indicates that the energy is multi-band coordinated; at the same time, the frequency offset reaches a peak and then begins to decline, indicating that stress release begins to decrease, which further indicates that the process status is that large burrs (isolated main burrs and tearing-type burrs) have been basically removed.

[0213] In implementation, preferably, the vibration fine grinding amplitude is reduced to 80% of the original vibration fine grinding amplitude, and the vibration fine grinding frequency is increased to 120% of the original vibration fine grinding frequency.

[0214] It is understandable that after the isolated main burrs and tearing burrs are basically removed, the amplitude should be reduced and the frequency should be increased to focus on removing continuous secondary burrs and micro burrs.

[0215] If the energy entropy is greater than the first danger threshold, the abrasive is determined to be ineffective and an alarm is issued;

[0216] In implementation, the first danger threshold is preferably 3.5.

[0217] It can be understood that when the energy entropy is greater than the first danger threshold, it indicates that the energy is dispersed and the noise ratio increases, indicating that the process state is abrasive passivation or abrasive is stuck in the hole.

[0218] If the frequency offset is within the third threshold range, it is determined that the burrs are completely removed and vibration fine grinding is stopped;

[0219] In implementation, the third threshold interval is preferably [5 Hz, 20 Hz].

[0220] It can be understood that the frequency offset being in the third threshold range indicates that the frequency offset only leaves the background vibration of the equipment, which further indicates that the process state is no-load or no burr removal.

[0221] determining whether the vibration grinder has a resonance risk based on the frequency offset and the ring count, and reducing the vibration fine grinding amplitude and issuing an alarm when it is determined that the vibration grinder has a resonance risk;

[0222] In implementation, when the frequency offset Δf is less than 5 Hz, or the ring count Nc is greater than 200 times, it is determined that the vibration grinder has a resonance risk, the vibration fine grinding amplitude is reduced to 60% of the original vibration fine grinding amplitude, and an alarm is issued.

[0223] Preferably, when the vibration grinding machine is detected to have a resonance risk in three consecutive time windows, grinding is stopped immediately to prevent damage to the equipment.

[0224] It is understandable that when the vibration grinder resonates, the system enters the resonance lock frequency zone, and the frequency offset is abnormally reduced; at the same time, the resonance causes the structure to reverberate repeatedly, and the density of ringing events suddenly increases.

[0225] Based on the proportion of the exceeding pulse signals and the concentration of the high-energy rising angles within the time window, it is determined whether the vibration grinder has an over-grinding risk. When it is determined that there is an over-grinding risk, the vibration fine grinding amplitude is reduced and an alarm is issued.

[0226] In practice, the rule for determining the proportion of pulse signals exceeding the standard is:

[0227] ,

[0228] In practice, the determination rule of the high energy rise angle concentration is:

[0229] ,

[0230] During implementation, when either the excessive pulse signal ratio and the high energy rise angle concentration are judged as over-grinding or when both the excessive pulse signal ratio and the high energy rise angle concentration are judged as warnings, it is determined that the vibration grinder has a risk of over-grinding, the vibration fine grinding amplitude is reduced to 60% of the original vibration fine grinding amplitude, and an alarm is issued.

[0231] Step S6: detecting the residual burrs of the finely ground workpiece by a machine vision mechanism, and adjusting the size threshold of the secondary burrs according to the residual amount of the burrs.

[0232] In implementation, when residual burrs exist in more than or equal to 10% of the total number of workpieces of the finely ground workpieces, preferably, the height threshold in the size threshold is increased to 150% of the original height threshold, and the length threshold is increased to 150% of the original length threshold, and the burr feature parameters are re-determined with the adjusted size threshold and the above steps S2 to S6 are re-executed until the number of finely ground workpieces with residual burrs is less than 5% of the total number of workpieces.

[0233] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A precision manufacturing deburring method based on vibration grinding, characterized in that: include: Step S1, obtaining a rough-ground workpiece after rough grinding by a vibration grinder, and basic parameters of the rough-ground workpiece, wherein the basic parameters include the number of workpieces, the hardness of the workpiece, and the weight of the workpiece; Step S2, visually inspecting secondary burrs generated on the rough-ground workpiece after rough grinding, and constructing a three-dimensional secondary burr model of the rough-ground workpiece; Step S3, based on the size threshold of the secondary burr, identifying isolated main burrs, continuous secondary burrs, tearing burrs and micro burrs in the three-dimensional secondary burr model, and obtaining burr characteristic parameters of the rough-ground workpiece; Step S4, determining the fine grinding process parameters according to the burr characteristic parameters, including vibration fine grinding frequency, vibration fine grinding amplitude and vibration fine grinding time; Step S5, based on the fine grinding process parameters, fine grinding the rough ground workpiece to remove the secondary burrs, including: During the fine grinding process, a grinding acoustic emission signal of the fine grinding is collected in real time, and the vibration fine grinding time is adjusted based on the energy entropy in the grinding acoustic emission signal; adjusting the vibration fine grinding frequency based on a frequency offset in the grinding acoustic emission signal; adjusting the vibration fine grinding amplitude based on the energy rise angle of the pulse signal in the grinding acoustic emission signal to obtain a finely ground workpiece; Step S6: visually inspecting the residual burrs on the finely ground workpiece, and adjusting the size threshold according to the removal percentages of the isolated main burrs and the continuous secondary burrs.

2. The precision manufacturing deburring method based on vibration grinding according to claim 1, characterized in that: The step S3 comprises: Step S31, judging the type of each burr according to the size threshold to determine the number of isolated main burrs and the number of micro burrs; Step S32, calculating an average height of the isolated main burrs according to the number of the isolated main burrs and the height of each isolated main burr; Step S33, determining the length of the continuous secondary burrs and the length of the tearing burrs according to the size threshold; Step S34: Calculate the average height of continuous secondary burrs and the average height of tearing-type burrs based on the length of the continuous secondary burrs and the length of the tearing-type burrs to obtain the burr characteristic parameters, wherein the burr characteristic parameters include: the number of isolated main burrs, the average height of isolated main burrs, the length of the continuous secondary burrs, the average height of the continuous secondary burrs, the length of the tearing-type burrs, the average height of the tearing-type burrs, and the number of micro-burrs.

3. The precision manufacturing deburring method based on vibration grinding according to claim 2, characterized in that: The step S4 comprises: Step S41, determining the vibration fine grinding frequency according to the number of isolated main burrs, the length of continuous secondary burrs and the length of tearing burrs; Step S42, determining the vibration fine grinding amplitude according to the average height of the isolated main burrs, the average height of the continuous secondary burrs, and the average height of the tearing burrs; Step S43, determining a burr volume equivalent according to the number of isolated main burrs, the length of continuous secondary burrs, the length of tearing burrs, the average height of isolated main burrs, the average height of continuous secondary burrs, and the average height of tearing burrs; Step S44, determining the vibration fine grinding time according to the total burr volume, the vibration fine grinding frequency, and the vibration fine grinding amplitude; Step S45 , judging whether to perform a super-finishing process and determining the time of the super-finishing process according to the number of the micro-burrs.

4. The precision manufacturing deburring method based on vibration grinding according to claim 3 is characterized in that: The step S5 comprises: Step S51, using a piezoelectric acoustic emission sensor to collect the original grinding acoustic emission signal during the fine grinding process; Step S52, filtering out low-frequency mechanical noise in the original grinding acoustic emission signal through a bandpass filter to obtain an acoustic emission signal; Step S53, performing wavelet packet transform on the acoustic emission signal to calculate the energy entropy of the acoustic emission signal to detect and determine the degree of discreteness of energy distribution during the vibration grinding process; Step S54: tracking the resonance peak in the acoustic emission signal and calculating a frequency offset based on the sampling frequency of the piezoelectric acoustic emission sensor to detect and determine the frequency shift caused by stress release or structural resonance inside the workpiece; Step S55, calculating the energy rise angle of the pulse signal in the acoustic emission signal to detect and determine the impact strength of the abrasive during the vibration grinding process; Step S56 , adjusting the fine grinding process parameters in real time according to the energy entropy, the frequency offset, and the energy rise angle in the acoustic emission signal to obtain a finely ground workpiece.

5. The precision manufacturing deburring method based on vibration grinding according to claim 4, characterized in that: Before step S51 , the following step is further provided: determining a time window for collecting grinding acoustic emission signals during the fine grinding process according to the number of the isolated main burrs and the length of the tearing burrs.

6. The precision manufacturing deburring method based on vibration grinding according to claim 5, characterized in that: The step S53 includes: Step S531, performing wavelet packet transform on the acoustic emission signal to decompose the acoustic emission signal into several sub-bands; Step S532, calculating the energy of each of the sub-frequency bands; Step S533: Calculate the energy entropy of the acoustic emission signal according to the energy of each sub-frequency band.

7. The precision manufacturing deburring method based on vibration grinding according to claim 6, characterized in that: The step S54 includes: Step S541, constructing an autoregressive model of the acoustic emission signal; Step S542, solving the characteristic equation of the autoregressive model to calculate and obtain a number of frequency components; Step S543, identifying a main resonance peak among the frequency components; Step S544 : Calculate the frequency offset based on the main resonance peak and the reference frequency of the vibration grinder when it is unloaded.

8. The precision manufacturing deburring method based on vibration grinding according to claim 7, characterized in that: The step S55 includes: Step S551, calculating a pulse detection threshold according to the ambient noise during non-vibration grinding; Step S552, determining whether the signal amplitude in the acoustic emission signal is greater than the pulse detection threshold, and obtaining a pulse signal; Step S553, calculating the energy rise angle of the pulse signal according to the rise time of the pulse signal and the voltage peak of the pulse signal; Step S554, determining the pulse signal exceeding threshold value according to the material of the workpiece; Step S555 , calculating the proportion of pulse signals exceeding the standard and the concentration of high energy rise angles within the time window according to the pulse signal exceeding the standard threshold and the energy rise angle.

9. The precision manufacturing deburring method based on vibration grinding according to claim 8, characterized in that: The step S552 further includes: calculating a ring count based on the number of times the signal amplitude exceeds a threshold within a unit time.

10. The precision manufacturing deburring method based on vibration grinding according to claim 1, characterized in that: In the step S2, the morphological feature data of the secondary burr is acquired by multi-angle image acquisition, and based on the morphological feature data, the three-dimensional secondary burr model is generated by a three-dimensional point cloud reconstruction algorithm.

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