PCB grinding and polishing method and device

Abstract

The invention provides a PCB grinding and polishing method which is characterized by comprising the following steps that a PCB is preliminarily cleaned, an initial image is obtained, and the initial image is used for reflecting feature information of the PCB after the PCB is preliminarily cleaned; classifying according to the feature information to obtain classification information, and feeding the PCB into a corresponding grinding device or polishing device for processing according to the classification information; consumable information of the polishing device is obtained, wherein the consumable information comprises information used for reflecting the type and use records of consumables; obtaining initial consumption according to the consumable information, wherein the initial consumption is used for reflecting a difference value between the current size of the consumable and the service life of an unused new consumable; obtaining an initial pressing parameter according to the initial consumption; and controlling the polishing device to polish the PCB according to the initial pressing parameter.

Description

Technical Field

[0001] The present application relates to the technical field of PCB circuit boards, and in particular to a method for grinding and polishing PCB circuit boards. Background Art

[0002] During the PCB production process, burrs, oxide layers, and various impurities often appear on the surface due to processes like cutting and drilling. These defects not only affect the PCB's appearance but can also impair circuit connectivity, leading to poor soldering and signal transmission issues. Therefore, polishing and removing these defects to achieve a smooth and even PCB surface is crucial for ensuring PCB performance and reliability.

[0003] In the traditional PCB grinding and polishing process, mechanical grinding is mainly used. This method uses grinding tools such as grinding wheels and sandpaper to grind the PCB surface to remove burrs and impurities. However, traditional mechanical grinding has problems such as low grinding accuracy and unstable surface quality, which makes it difficult to meet the production needs of high-precision PCBs. The traditional grinding and polishing process lacks process control and intelligent compensation, which not only makes it difficult to improve the processing quality of PCBs, but also makes it difficult to control the use of consumables. In view of this, this application is proposed. Summary of the Invention

[0004] The present invention proposes a PCB circuit board grinding and polishing method, which can solve the problem that the current grinding and polishing process lacks process control and intelligent compensation, which not only makes it difficult to improve the processing quality of the PCB, but also makes it difficult to control the use of consumables.

[0005] In a first aspect, an embodiment of the present application provides a method for grinding and polishing a PCB circuit board, comprising the following steps:

[0006] Cleaning the PCB and acquiring image information, wherein the image information is used to reflect characteristic information of the PCB after cleaning;

[0007] Classify the PCBs according to the characteristic information to obtain classification information, and send the PCBs to a corresponding grinding device or polishing device for processing according to the classification information;

[0008] Obtaining consumables information, including information reflecting the model and usage history of the consumables;

[0009] Analyze the consumables information to obtain a downward pressure parameter;

[0010] The grinding device or the polishing device is controlled according to the pressing parameter to process the PCB.

[0011] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0012] The PCB grinding and polishing method provided in this application can grasp the state and defects of the PCB before processing by acquiring image information that reflects characteristic information of the PCB after cleaning; then classifying it based on the characteristic information to obtain classification information, and sending the PCB to the corresponding grinding device or polishing device for processing based on the classification information; then acquiring consumable information that reflects the model and usage of the consumables; analyzing the consumable information to obtain a downward pressure parameter, and finally controlling the grinding device or polishing device to polish the PCB based on the downward pressure parameter. This method can classify the defects of the PCB before processing into the corresponding grinding device or polishing device, classifying larger defects into the grinding device and those that meet the polishing standard into the polishing device. During grinding and polishing, the consumable information helps adjust the parameters, and using the most suitable parameters for polishing not only improves the grinding and polishing quality of the product but also maximizes the use of consumables.

[0013] In a possible implementation of the first aspect, the classifying according to the feature information to obtain the classification information includes:

[0014] Obtaining PCB undulation information based on the characteristic information;

[0015] determining whether to perform polishing according to the undulation information;

[0016] If polishing is required, the corresponding PCB will be sorted into the polishing device;

[0017] If polishing is not required, the corresponding PCB will be sorted into the polishing device.

[0018] In a possible implementation of the first aspect, classifying the corresponding PCBs into polishing devices includes:

[0019] establishing a material removal rate model based on the characteristic information;

[0020] Obtaining curvature information according to the undulation information, and acquiring the curvature information in real time;

[0021] Performing adaptive compensation according to the curvature information;

[0022] The material removal rate model is combined to perform collaborative compensation.

[0023] In a possible implementation of the first aspect, obtaining consumables information includes:

[0024] Build a sensor network and synchronize data to obtain data information;

[0025] The analyzing the consumables information to obtain the pressing parameters includes:

[0026] Establishing a dynamic parameter adjustment model based on the data information;

[0027] The model is adjusted according to the dynamic parameters to perform dynamic path correction.

[0028] In a possible implementation of the first aspect, controlling the grinding device or the polishing device to process the PCB according to the pressing parameter includes:

[0029] Get the temperature data of PCB;

[0030] If the temperature data exceeds the safety threshold, the following adjustments are performed: immediately reduce the spindle speed, turn on the coolant, and make the actual pressure quickly converge to the target value;

[0031] Get updated image information;

[0032] The polishing path is updated according to the updated image information.

[0033] In a possible implementation of the first aspect, the method further includes:

[0034] Establishing a life prediction model based on the consumables information;

[0035] Compensation control is performed according to the life prediction model.

[0036] In a possible implementation of the first aspect, establishing the life prediction model according to the consumables information includes:

[0037] establishing a wear dynamics model based on the consumables information;

[0038] A life prediction model is established based on the wear dynamics model.

[0039] In a possible implementation of the first aspect, performing compensation control according to the life prediction model includes:

[0040] Obtaining wear stage information of consumables according to the life prediction model;

[0041] Compensation information is obtained according to the wear stage information.

[0042] In a second aspect, an embodiment of the present application provides a PCB circuit board grinding and polishing device, characterized by comprising:

[0043] A first acquisition module is used to acquire an initial image, where the initial image is used to reflect characteristic information of the PCB after preliminary cleaning;

[0044] A classification module is used to classify the PCBs according to the characteristic information to obtain classification information, and send the PCBs to a corresponding grinding device or polishing device for processing according to the classification information;

[0045] A second acquisition module is used to obtain consumables information of the polishing device, wherein the consumables information includes information reflecting the model of the consumables and usage records;

[0046] An analysis module, configured to analyze the consumables information to obtain a pressing parameter;

[0047] A control module, configured to control the polishing device to polish the PCB according to the initial pressing parameter;

[0048] A prediction module, configured to establish a life prediction model based on the consumables information;

[0049] A compensation module is used to perform compensation control according to the life prediction model.

[0050] In a third aspect, an embodiment of the present application provides a PCB circuit board grinding and polishing device, comprising:

[0051] A grinding device, a polishing device, and a control device; the grinding device and the polishing device are electrically connected to the control device; the control device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements any one of the methods described in the first aspect when executing the computer program.

[0052] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above-mentioned first aspects is implemented.

[0053] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a PCB circuit board grinding and polishing device, the PCB circuit board grinding and polishing device performs the PCB circuit board grinding and polishing method described in any one of the first aspects above.

[0054] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a process for grinding and polishing a PCB circuit board provided in an embodiment of the present application;

[0056] Figure 2Schematic diagram of the implementation process of step S200 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0057] Figure 3 Schematic diagram of the implementation process of step S300 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of the implementation flow of step S400 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0059] Figure 5 Schematic diagram of the implementation process of step S500 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0060] Figure 6 Schematic diagram of the implementation process of step S600 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0061] Figure 7 Schematic diagram of the implementation process of step S700 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0062] Figure 8 Schematic diagram of the implementation process of step S230 of the PCB circuit board grinding and polishing method provided in an embodiment of the present application;

[0063] Figure 9 A schematic diagram of the structure of a PCB circuit board grinding and polishing device provided in an embodiment of the present application;

[0064] Figure 10 A schematic diagram of the structure of the control device of the PCB circuit board grinding and polishing equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0066] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0067] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0068] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0069] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0070] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0071] Traditional PCB grinding and polishing primarily utilizes mechanical grinding. This method uses abrasive tools such as grinding wheels and sandpaper to grind the PCB surface, removing burrs and impurities. However, traditional mechanical grinding suffers from low grinding accuracy and unstable surface quality, making it difficult to meet the production requirements of high-precision PCBs. Traditional grinding and polishing processes also lack process control and intelligent compensation, making it difficult to improve PCB processing quality and manage consumables.

[0072] To solve the above-mentioned technical problems, an embodiment of the present application provides a method and apparatus for grinding and polishing a PCB circuit board. In this method, by acquiring image information that reflects characteristic information of the PCB after cleaning, the state and defects of the PCB before processing can be determined. Then, classification is performed based on the characteristic information to obtain classification information, and the PCB is sent to a corresponding grinding device or polishing device for processing based on the classification information. Then, consumable information that reflects the model of the consumables and the recorded information is acquired. The consumable information is analyzed to obtain a downward pressure parameter, and finally, the polishing device is controlled to polish the PCB based on the downward pressure parameter. This method can classify the defects of the PCB before processing into the corresponding grinding device or polishing device. Defects with larger defects are classified into a large grinding device, and those that meet the polishing standards are classified into a polishing device. During polishing, the consumable information helps adjust the parameters. Polishing with the most suitable parameters is beneficial to improving the polishing quality of the product and maximizing the use of consumables.

[0073] The PCB circuit board grinding and polishing method provided in the embodiment of the present application can be applied to a PCB circuit board grinding and polishing device. In this case, the PCB circuit board grinding and polishing device is the executor of the PCB circuit board grinding and polishing method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of PCB circuit board grinding and polishing device.

[0074] For example, the PCB circuit board grinding and polishing equipment may include a grinding device, a polishing device, a cleaning device, a sorting device, a cooling device, and a control device; the grinding device, the polishing device, the cleaning device, the sorting device, and the cooling device can all be electrically connected to the control device. The grinding device is used to grind PCB circuit boards with large defects that do not meet the polishing requirements. The polishing device polishes PCB circuit boards with defects that meet the polishing conditions. After being polished by the grinding device, those that meet the conditions will also enter the polishing device for polishing; the cleaning device is used to clean the PCB circuit boards to facilitate subsequent acquisition of image information. It can be water washing or vacuum cleaning, as long as the PCB surface is clean; the sorting device is used to sort the PCB circuit boards and send them to the corresponding grinding device or polishing device. The cooling device is arranged in the grinding device and the polishing device, and can cool the PCB circuit boards when necessary for processing. It can be air-cooled or liquid-cooled, and there is no restriction here; the control device monitors and controls the entire grinding process, polishing process, cleaning process, sorting process, and cooling process.

[0075] For example, the control device can be a mobile phone, a tablet computer, a wearable device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a smart screen, a smart TV, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, customer premise equipment (CPE) and / or other devices for communicating on a wireless system and a next-generation communication system, such as a mobile terminal in a 5G network or a mobile terminal in a future evolved public land mobile network (PLMN) network.

[0076] In order to better understand the PCB circuit board grinding and polishing method provided in the embodiment of the present application, the specific implementation process of the PCB circuit board grinding and polishing method provided in the embodiment of the present application is exemplarily introduced below.

[0077] Figure 1 The schematic flow chart of the PCB circuit board grinding and polishing method provided in the embodiment of the present application is shown. The PCB circuit board grinding and polishing method includes:

[0078] S100, cleaning the PCB and acquiring image information, where the image information is used to reflect characteristic information of the PCB after cleaning;

[0079] It is understood that after the PCB is cleaned, a camera or other optical device is used to capture the appearance of the PCB circuit board, or a high-precision laser sensor or optical scanning imaging system is used to obtain three-dimensional data of the PCB circuit board and then generate an electronic image, or a multi-axis industrial camera array is used to shoot the cleaned PCB from multiple angles to generate a high-resolution three-dimensional topology map, or a laser scanning module is used to scan and extract surface texture information using multispectral imaging. Image features are analyzed through a deep convolutional neural network (DCNN): 20+ dimensional feature vectors such as surface undulation, copper foil thickness gradient, solder mask layer concave depth, etc. are extracted; hidden defects such as microcracks (<50μm), oxidation spots, and residual colloid are identified; and a material hardness distribution heat map (based on the spectral reflectance characteristics of materials in different regions) is generated.

[0080] S200, classifying according to the characteristic information to obtain classification information, and sending the PCB to a corresponding grinding device or polishing device for processing according to the classification information;

[0081] As you can see, based on the previously acquired feature information, we can determine the physical characteristics and defects of each PCB circuit board, and then classify them based on the characteristics. The classification model can include mappings between different substrates (FR-4, aluminum substrate, etc.), defect types, and treatment methods. This mapping can be obtained by training the extracted features using machine learning or deep learning models (such as support vector machines and neural networks). Historical cases can also be used for training, thereby establishing a historical case library.

[0082] As an optional embodiment of this application, please refer to Figure 2 In step S200, classification is performed based on the feature information, and the obtained classification information includes:

[0083] S210, obtaining PCB undulation information based on the characteristic information;

[0084] It can be understood that after the image information is processed, various features of the PCB can be extracted, including the undulation information. The undulation information can reflect the PCB's height, thickness, and curvature radius. Based on these geometric features, the corresponding PCB status can be determined to determine how to perform the corresponding processing.

[0085] S220, judging whether to perform polishing based on the fluctuation information;

[0086] It can be understood that the undulation information can reflect the PCB's undulation height H, thickness D, and curvature radius R. The undulation height H refers to the height of the maximum protrusion of the PCB, the thickness D refers to the thickness of the PCB base part, and the curvature radius R refers to the curvature of the protrusion or depression 1 / R. The corresponding critical value can be set to distinguish whether to polish. Take the undulation height H as an example: set the critical undulation height to h. If H is greater than h, then it is judged that polishing is required, otherwise it is judged that polishing is not required. Taking the thickness D as an example, set the basic thickness to d. If D exceeds d by a certain percentage, such as 8%, then it is judged that polishing is required, otherwise it is judged that polishing is not required. The specific judgment conditions can be set according to the product processing requirements. The judgment conditions can be one or multiple common constraints. This is only an example and is not limited.

[0087] S230, if polishing is required, the corresponding PCB is classified into a polishing device;

[0088] It can be understood that through the above judgment process, the size of the PCB defect can be judged. If the judgment condition exceeds the critical value or the set value, it can indicate that the flatness defect of the PCB is large and needs to be polished first.

[0089] S240, if polishing is not required, the corresponding PCB will be sorted into the polishing device

[0090] It can be understood that through the above judgment process, the size of the PCB defect can be judged. If the judgment condition does not exceed the critical value or the set value, it can be shown that the flatness defect of the PCB is small and there is no need to grind it first, and polishing can be performed directly.

[0091] As an optional embodiment of this application, please refer to Figure 8 In step S230, classifying the corresponding PCB into a polishing device includes:

[0092] S231, establishing a material removal rate model based on the feature information;

[0093] As you can understand, material removal rate is often used to measure the amount of material removed per unit time, which is very important for processing efficiency and process optimization. In PCB grinding and polishing, controlling the removal rate can ensure uniform surface treatment and avoid over- or under-polishing. Based on this, the material removal rate model is as follows:

[0094]

[0095] Where: K: material characteristic coefficient (unit: mm 3 / (N^α·rpm^β·μm^γ)), which is determined by the PCB material type (such as FR-4, aluminum substrate) and surface treatment (gold plating, OSP, etc.).

[0096] F: Applied normal pressure (unit: N).

[0097] V: Grinding and polishing tool speed (unit: rpm).

[0098] D: average diameter of abrasive particles (unit: μm).

[0099] α, β, γ: empirical indexes, reflecting the nonlinear effect of each parameter on the removal rate (calibrated through experiments).

[0100] The material coefficient K characterizes the "removability" of the material itself and is related to hardness, toughness, and adhesion.

[0101] For example:

[0102] Copper foil (soft metal): K≈0.05~0.1

[0103] FR-4 fiberglass substrate (hard and brittle): K≈0.02~0.04

[0104] The calibration method is to determine the copper foil removal depth h by combining nanoindentation experiments with actual processing tests. For example, when F = 50N, V = 300rpm, and D = 20μm, the following is obtained:

[0105]

[0106] (A: polishing area, t: time)

[0107] Pressure index α; typical value: α≈1.0~1.5; physical mechanism:

[0108] α>1 indicates that the effect of pressure on the removal rate increases superlinearly, reflecting that the abrasive particles are embedded in the matrix and the shearing effect is enhanced under high pressure.

[0109] For copper foil: α≈1.2 (easy to plastically deform); for hard substrate: α≈0.8 (dominated by brittle fracture).

[0110] Speed index β; typical value: β≈0.6~0.9; physical mechanism:

[0111] β<1 indicates that when the rotation speed increases, the effective cutting times of the abrasive particles per unit time increase, but the single cutting depth decreases.

[0112] For fine areas (line width <100μm): β≈0.6 (to avoid abrasive slippage caused by excessively high rotation speed); for large surfaces: β≈0.8.

[0113] Abrasive particle diameter index γ; typical value: γ≈1.5~2.0; physical mechanism:

[0114] γ>1 reflects that when the abrasive size increases, the cutting volume of a single abrasive particle increases significantly.

[0115] However, in practical applications, it is necessary to balance the relationship between D and surface roughness (large abrasive particles have high efficiency but poor roughness).

[0116] S232, obtaining curvature information according to the undulation information, and acquiring the curvature information in real time;

[0117] It can be understood that the curvature radius R refers to the curvature of the convex or concave part, which is 1 / R. The curvature and curvature radius can be used to determine whether the corresponding area is a high curvature area, such as when the curvature is greater than 0.15mm. -1 When the corresponding surface radius R is less than 6.67mm, it belongs to the high curvature area. According to the above steps, the PCB circuit boards determined to need grinding all have serious surface flatness issues and may have multiple areas with different undulations. Therefore, finding and adjusting the areas with different curvatures in real time will enable the selection of the most suitable processing mode.

[0118] S233, performing adaptive compensation according to curvature information;

[0119] It is understandable that the material removal depth is predicted first:

[0120]

[0121] For areas with a thickness deviation greater than 10%, a spiral progressive path is generated to gradually correct the height difference.

[0122] For precision areas such as BGA pads, high-frequency, low-amplitude vibration polishing is used (to reduce F and D).

[0123] It can be understood that the spiral involute path is established:

[0124]

[0125] Where: a: initial radius (usually the distance from the center to the edge of the processing area)

[0126] b: Pitch coefficient (here the pitch is 0.2mm, corresponding to b = 0.2 / π)

[0127] θ: rotation angle

[0128] This can avoid residual tool marks on the curved surface caused by the straight path, and the involute expansion can adapt to different curvature radii.

[0129] Furthermore, the compensation pressure can be set according to different curvatures, such as: when the curvature increases by 0.1mm -1 , the pressure is increased by 5%, compensating for the normal pressure loss caused by the inclination of the curved surface.

[0130] Furthermore, to avoid pressure oscillations in linear compensation when curvature changes suddenly, a curvature adaptive pressure field is set:

[0131] F normal =F base ×(1+e -0.1R )

[0132] Among them: F normal : Adjusted normal pressure (unit: N)

[0133] F base : Basic pressure (standard value preset according to material type, unit: N)

[0134] R: radius of curvature (unit: mm), when convex, R>0, when concave, R<0

[0135] e -0.1R : Curvature compensation factor (exponential function form)

[0136] The origin of the exponential coefficient of 0.1: Through experimental calibration, it is found that in a typical PCB processing scenario (curvature range R = -10mm to +10mm):

[0137] When |R|<10mm, the pressure adjustment range is significant (compensation effect is obvious);

[0138] When |R|>20mm, the pressure approaches the baseline value (to avoid excessive response).

[0139] In actual systems, upper and lower pressure limits are set, such as: 0.5F base ≦F normal ≦3F base Prevent equipment damage caused by extreme values calculated by formulas.

[0140] Convex surfaces are those with outward projections, such as the edge of a BGA package or a bump on a solder pad. This reduces the actual contact area between the grinding tool and the surface, and excessive pressure can lead to localized over-polishing. Concave surfaces are those with inward depressions, such as drilled areas or grooves on a PCB. In these cases, the grinding tool may not fully contact the bottom of the depression, requiring increased pressure to ensure uniform material removal.

[0141] When R→+∞(flat region): e -0.1R →0, at this time F normal ≈F base ; When R = 0 (sharp edge): e 0 =1, F normal =2F base ; When R→-∞(deep concave area): e -0.1R →+∞, but due to the limited curvature in actual processing, the formula needs to be combined with physical constraints (such as the maximum pressure threshold).

[0142] Nonlinear pressure compensation is achieved through exponential functions: rapid response to high curvature (small curvature radius) areas; maintaining stable pressure in flat areas; and avoiding pressure oscillations caused by sudden changes in curvature during linear compensation.

[0143] S234, synergistic compensation combined with material removal rate model;

[0144] Understandably, during PCB polishing, different surface areas can experience uneven removal rates due to the following factors: Geometric differences: For example, the contact pressure between raised areas (BGA pads) and recessed areas (drilled holes) varies. Material differences: The hardness difference between copper foil (soft metal) and FR-4 substrate (hard and brittle) is significant. Tool wear: Localized wear of the polishing pad / grinding head causes variations in pressure distribution. Therefore, by dynamically adjusting the pressure P to compensate for these variations, uniform removal is achieved across the entire surface.

[0145] Real-time surface status perception through sensors:

[0146] Nano-displacement sensor: monitors the downward pressure of the grinding head in real time and calculates the actual contact pressure.

[0147] Infrared thermal imager: Captures surface temperature distribution and corrects for the effect of temperature on removal rate (K varies with temperature).

[0148] Acoustic emission sensor: detects abrasive particle shedding events and determines the wear status of the tool.

[0149] Build a dynamic pressure adjustment model:

[0150]

[0151] MRR target : Target removal rate set according to process requirements;

[0152] MRR actual : Actual removal rate calculated in real time through sensor data.

[0153] If the actual removal rate in a certain area is lower than the target value (e.g. due to high material hardness or insufficient pressure), the pressure in that area is increased proportionally. If the removal rate is too high (e.g. due to tool wear or excessive pressure), the pressure is reduced to avoid over-throwing.

[0154] Introducing the effects of temperature T and tool wear w, the model is expanded:

[0155] MRR=K(T)·P·V·f(w)

[0156] Here: Temperature correction term (E a is the activation energy).

[0157] Wear decay function.

[0158] First, obtain the current state of the area, calculate the corrected K value, calculate the target pressure, and adjust the actuator pressure. Through dynamic pressure distribution, the uneven removal caused by material and geometric differences is eliminated, and interference factors such as tool wear and temperature changes are responded to in real time to avoid "over-designed" global high pressure, reduce energy consumption, and process more complex heterogeneous material combinations (such as metal-ceramic substrates). Take practical applications as an example: due to the difference in hardness, the junction of copper (soft) and FR-4 (hard) is prone to step effect. Within the 3mm range of the junction area, the pressure is linearly reduced from 80N in the copper area to 120N in the substrate area, and the substrate area rotation speed (V FR-4 =1.2V Cu ) to compensate for the reduction in removal rate caused by reduced pressure. Another example: localized polishing pad wear compensation uses acoustic emission signals to identify worn areas (frequency <50kHz). In the worn area, the pressure is proportionally increased while the rotational speed is reduced to avoid overheating caused by sudden pressure increases.

[0159] S300, obtaining consumables information, the consumables information including information reflecting the model of the consumables and usage records;

[0160] It can be understood that intelligent consumables design can be achieved through digital modeling of consumables, and embedded RFID chips can be used to store consumables identity information and usage records, such as: recording the cumulative number of revolutions (integral of speed and time) and pressure spectrum (historical pressure distribution).

[0161] Various sensors can be integrated into the grinding and polishing devices, and the sensors can be used to collect various information, including various information about consumables, to obtain real-time changes in physical quantities during the processing and ensure control accuracy.

[0162] This can be achieved by establishing an acoustic emission feature library: through experiments, a database of spectrum features of different wear stages can be established, for example: initial wear: 80-120kHz high-frequency signal (micro-detachment of abrasive particles); mid-term wear: 30-50kHz medium-frequency signal (base material wear); final wear: low-frequency signal below 10kHz (structural fatigue).

[0163] As an optional embodiment of this application, please refer to Figure 3 In step S300, obtaining the consumables information of the polishing device includes:

[0164] S310, building a sensor network and performing data synchronization to obtain data information;

[0165] It is understood that the following sensors are integrated into the polishing device: a nano-displacement sensor for real-time tracking of surface topography, installed above the polishing head, to monitor in real time the change in the distance between the polishing head and the PCB surface; a piezoelectric force sensor for closed-loop control of contact pressure, integrated into the support arm of the polishing head, to measure the actual contact pressure; an infrared thermal imager for thermal damage warning, fixed above the processing area, to capture the surface temperature field distribution at a frame rate of 60Hz; an acoustic emission sensor for monitoring abrasive particle shedding, installed inside the polishing pad, to capture the high-frequency vibration signal when abrasive particles fall off, etc. It is understood that the above are key sensors listed by way of example, and of course other sensors can also be included to collect various other data signals. In this embodiment, this is not a limitation.

[0166] The signals collected by various sensors are then synchronized, using, for example, a sliding window alignment method: all sensor data is aligned within a 10ms time window. For example, force sensor data is mean filtered within the window, thermal imager data is spatially averaged, and displacement data is subjected to a Kalman filter to eliminate noise. Hardware acceleration uses an FPGA to preprocess high-sampling-rate data (such as 5kHz displacement signals) to reduce the load on the main control system. Data information is then generated through data synchronization.

[0167] S400: Analyze the consumables information to obtain the pressing parameters:

[0168] It can be understood that consumables information can reflect the model, material, processing history, physical changes in real-time processing, etc. of the consumables. Based on the above information, the processing parameters of the polishing device, such as pressure, speed, temperature warning, etc., can play a good control role.

[0169] As an optional embodiment of this application, please refer to Figure 4 In step S400, the pressing parameters obtained by analyzing the consumables information include:

[0170] S410, establishing a dynamic parameter adjustment model based on the data information;

[0171] Coupling equations of the dynamic parameter adjustment model:

[0172]

[0173] Where: F: optimal pressure value;

[0174] K: material hardness coefficient (calibrated by nanoindentation test, unit N / μm);

[0175] Δh: the difference between the current displacement and the target displacement (unit: μm);

[0176] α: Thermal expansion compensation coefficient (empirical value 0.0035℃ -1 );

[0177] T: real-time surface temperature, T0: reference temperature (usually 25°C).

[0178] A micro-indentation test was performed on a non-functional area of the PCB using a diamond indenter (curvature radius 5 μm), with a loading curve of 0-50 mN and a loading rate of 5 mN / s. Hardness calculation:

[0179]

[0180] P max : Maximum indentation load;

[0181] A c : Contact area (through indentation depth h c calculate).

[0182] Spatial interpolation: Generate hardness distribution map based on Kriging interpolation method:

[0183]

[0184] Weight w i Determined by the semivariogram model.

[0185] S420, dynamically correcting the path according to the dynamic parameter adjustment model;

[0186] It can be understood that the above dynamic parameter adjustment model can calculate the optimal pressure value according to the physical changes in the real-time processing process, thereby dynamically adjusting the downforce during the polishing process.

[0187] S500, controlling the polishing device to process the PCB according to the pressing parameter;

[0188] It can be understood that based on the obtained downward pressure parameters, the processing setting values can be obtained, so that the automation and intelligent setting of parameters can be improved when the PCB is polished.

[0189] As an optional embodiment of this application, please refer to Figure 5 In step S500, controlling the polishing device to polish the PCB according to the pressure parameter includes:

[0190] S510, obtaining temperature data of the PCB;

[0191] It can be understood that the data information after the infrared thermal imager is synchronized can be used to grasp the stable distribution of the PCB circuit board during the processing process in real time.

[0192] S520: If the temperature data exceeds the safety threshold, perform the following adjustments: immediately reduce the spindle speed, turn on the coolant, and quickly converge the actual pressure to the target value;

[0193] It is understandable that a temperature safety threshold can be set, such as 85°C. If it is detected that the local temperature exceeds the safety threshold, the spindle speed is immediately reduced by 10% and the coolant is turned on to avoid processing damage to the PCB circuit board caused by excessive temperature.

[0194] S530, obtaining updated image information;

[0195] It can be understood that the processing progress and the status of each area can be grasped in real time every 2ms based on the latest 3D topography data (from the displacement sensor).

[0196] S550, updating the polishing path according to the updated image information;

[0197] It can be understood that the current processing status of each area can be understood based on the updated image, and updating the polishing path based on the updated image information is conducive to more uniform processing of each area.

[0198] As an optional embodiment of this application, please refer to Figure 5 In step S600, establishing a life prediction model based on consumables information includes:

[0199] S610, establishing a wear dynamics model based on consumables information;

[0200] It can be understood that the pressure term characterizes the dominant influence of mechanical pressure on wear; the relative speed between the consumables and the PCB circuit board also affects the wear state; the temperature term can quantify the promoting effect on material softening and chemical reactions, such as: high temperature softening: increased temperature reduces material hardness and accelerates wear; oxidation reaction: certain materials (such as copper) oxidize faster at high temperatures, forming an easily peelable oxide layer. Different materials have different activation energies, such as: diamond abrasive: Q≈85kJ / molQ≈85kJ / mol (high activation energy, high temperature resistance). Resin-based polishing pad: Q≈25kJ / molQ≈25kJ / mol (significant softening at low temperatures). Therefore, based on the above influencing factors, the model is established as follows:

[0201]

[0202] Where: dw / dt: wear rate (unit: μm / s), which indicates the wear amount of consumables per unit time;

[0203] k: Material wear coefficient (unit: μm / (N^{1.2}·m^{0.8} / s^{0.8})), determined by the combined characteristics of the consumables and the PCB material;

[0204] P: contact pressure (unit: N);

[0205] V: relative motion speed (unit: m / s);

[0206] Q: activation energy (unit: kJ / mol), reflecting the sensitivity of material wear to temperature;

[0207] R: gas constant (8.314 J / (mol·K));

[0208] T: Real-time temperature of the processing interface (unit: K).

[0209] Experiments show that the effect of pressure on wear is superlinear (exponent > 1). A power of 1.2 means that for every 10% increase in pressure, the wear rate increases by approximately 12.6%. This reflects the phenomenon that under high pressure, abrasive particles embed into the matrix, accelerating material separation. A power of speed < 1 indicates that as speed increases, the number of friction events per unit time increases, but the duration of a single contact decreases. The overall effect is that the wear rate gradually slows with increasing speed, avoiding unlimited growth.

[0210] Calibrate the above parameters:

[0211] Through the orthogonal experimental method, in a controlled environment, multi-level combination tests of P, V, and T were conducted, and the wear data were recorded, as shown in Table 1:

[0212]

[0213]

[0214] Use the least squares method to fit the experimental data and solve for k and Q:

[0215]

[0216] S620, establishing a life prediction model based on the wear dynamics model;

[0217] It can be understood that based on the current wear state and historical data, the remaining service life or the number of times the consumable can be processed before failure is predicted. The cumulative wear amount w(t) is obtained by integrating the wear rate:

[0218]

[0219] The accumulated wear amount is updated in real time through numerical integration (such as the trapezoidal method), the maximum wear amount is preset, and the remaining life is determined based on the ratio between the accumulated wear amount and the preset maximum wear amount.

[0220] As an optional embodiment of this application, please refer to Figure 5 In step S700, performing compensation control according to the life prediction model includes:

[0221] S710, obtaining wear stage information of the consumables according to the life prediction model;

[0222] It can be understood that the above life prediction model can provide real-time information on the remaining life of consumables. For example, if the maximum wear is set to 1.0mm and the cumulative wear reaches 0.5mm, the remaining life of the consumable is (1-0.5) / 1 = 50%. Therefore, based on the remaining life percentage, wear stage information can be obtained, such as: 0-30% is the initial stage, 30%-50% is the middle stage, 50%-80% is the final stage, and exceeding 80% is the warning stage. Of course, other percentages can also be set. This is only an example and not a limitation.

[0223] S720, obtaining compensation information according to the wear stage information;

[0224] As you can understand, consumables' performance varies at different stages of wear, so compensating adjustments can help maintain consistent polishing. For example: in the initial stage, increase the speed by 5% and the time by 3%; in the mid-stage, increase the pressure by 0.2mm and the pressure by 8%; in the final stage, mark the machine for replacement; and in the warning stage, force the machine to stop. Of course, other proportional settings are possible; these are examples only and are not intended to be limiting.

[0225] In addition, data can also be corrected through the LSTM neural network: the residual of the theoretical prediction value of the wear dynamics equation and the actual sensor monitoring value is used as the input feature, and the LSTM model is trained to correct the prediction error. The LSTM inputs time series data (the error sequence of the past 60 seconds) and outputs the corrected remaining life prediction value, which helps to improve the accuracy of life prediction.

[0226] Regarding the PCB circuit board grinding and polishing method described in the above embodiment, the embodiment of the present application also provides a PCB circuit board grinding and polishing device, and each module of the device can implement each step of the PCB circuit board grinding and polishing method. Figure 9 A structural block diagram of a PCB circuit board grinding and polishing device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0227] Reference Figure 9 , the PCB circuit board grinding and polishing device includes:

[0228] The first acquisition module is used to acquire an initial image, where the initial image is used to reflect characteristic information of the PCB after preliminary cleaning;

[0229] The classification module is used to classify according to the feature information, obtain classification information, and send the PCB to the corresponding grinding device or polishing device for processing according to the classification information;

[0230] The second acquisition module is used to obtain the consumables information of the polishing device, the consumables information including the model of the consumables and the information of the usage record;

[0231] An analysis module is used to analyze the consumables information and obtain the pressing parameters;

[0232] A control module, configured to control the polishing device to polish the PCB according to the initial pressing parameters;

[0233] Prediction module, used to establish a life prediction model based on consumables information;

[0234] The compensation module is used to perform compensation control according to the life prediction model.

[0235] It should be noted that the information interaction, execution process and other contents between the above modules are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0236] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above modules is used as an example for illustration. In actual applications, the above functions can be distributed and completed by different modules as needed, that is, the internal structure of the device can be divided into different modules to complete all or part of the functions described above. The modules in the embodiment can be integrated into one processing unit, or each module can exist physically alone, or two or more modules can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of the modules are only for the convenience of distinguishing each other and are not used to limit the scope of protection of this application. The specific working process of the modules in the above device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0237] An embodiment of the present application also provides a PCB circuit board grinding and polishing device, including a grinding device, a polishing device, and a control device; the grinding device, the polishing device and the control device are electrically connected. Figure 10 This is a schematic diagram of the structure of the PCB circuit board grinding and polishing equipment provided in an embodiment of the present application.

[0238] For example, the computer program 82 may be divided into one or more modules / units, one or more of which are stored in the memory 81 and executed by the processor 80 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 82 in the control device 8.

[0239] The control device 8 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The PCB circuit board polishing device may include, but is not limited to, a processor 80 and a memory 81. It will be understood by those skilled in the art that Figure 10 This is merely an example of the control device 8 and does not constitute a limitation on the control device 8. The control device 8 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, buses, etc.

[0240] The processor 80 may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0241] In some embodiments, the memory 81 may be an internal storage unit of the control device 8, such as a hard disk or memory of the control device 8. In other embodiments, the memory 81 may also be an external storage device of the control device 8, such as a plug-in hard disk equipped on the control device 8, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Furthermore, the memory 81 may include both an internal storage unit of the control device 8 and an external storage device. The memory 81 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of a computer program. The memory 81 may also be used to temporarily store data that has been output or is about to be output.

[0242] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of any of the above method embodiments are implemented.

[0243] An embodiment of the present application provides a computer program product. When the computer program product is run on a PCB circuit board grinding and polishing device, the PCB circuit board grinding and polishing device implements the steps of any of the above-mentioned method embodiments.

[0244] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the PCB circuit board grinding and polishing equipment, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electric carrier signal and a telecommunication signal.

[0245] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0246] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0247] In the embodiments provided in this application, it should be understood that the disclosed PCB circuit board grinding and polishing device / equipment and method can be implemented in other ways. For example, the PCB circuit board grinding and polishing device / equipment embodiments described above are merely schematic. For example, the division of modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or module, which can be electrical, mechanical or other forms.

[0248] Modules described as separate components may or may not be physically separate, and 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 elements. Some or all of these modules may be selected to achieve the purpose of this embodiment based on actual needs.

[0249] It should be understood that the above-described specific embodiments of the present invention are merely illustrative or illustrative of the principles of the present invention and do not constitute limitations of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the scope of protection of the present invention. In addition, the appended claims are intended to cover all variations and modifications that fall within the scope and metes and bounds of the appended claims, or equivalents thereof.

Claims

1. A PCB circuit board grinding and polishing method, characterized in that: The following steps are involved: Cleaning the PCB and acquiring image information, wherein the image information is used to reflect characteristic information of the PCB after cleaning; Classify the PCBs according to the characteristic information to obtain classification information, and send the PCBs to a corresponding grinding device or polishing device for processing according to the classification information; Obtaining consumables information, including information reflecting the model and usage history of the consumables; Analyze the consumables information to obtain a downward pressure parameter; The grinding device or the polishing device is controlled according to the pressing parameter to process the PCB.

2. A PCB circuit board grinding and polishing method according to claim 1, characterized in that: The classification is performed based on the feature information to obtain classification information including: Obtaining PCB undulation information based on the characteristic information; determining whether to perform polishing according to the undulation information; If polishing is required, the corresponding PCB will be sorted into the polishing device; If polishing is not required, the corresponding PCB will be sorted into the polishing device.

3. A PCB circuit board grinding and polishing method according to claim 2, characterized in that: The classifying of the corresponding PCBs into the polishing device includes: establishing a material removal rate model based on the characteristic information; Obtaining curvature information according to the undulation information, and acquiring the curvature information in real time; Performing adaptive compensation according to the curvature information; The material removal rate model is combined to perform collaborative compensation.

4. A PCB circuit board grinding and polishing method according to claim 1, characterized in that: The obtaining of consumables information includes: Build a sensor network and synchronize data to obtain data information; The analyzing the consumables information to obtain the pressing parameters includes: Establishing a dynamic parameter adjustment model based on the data information; The model is adjusted according to the dynamic parameters to perform dynamic path correction.

5. A PCB circuit board grinding and polishing method according to claim 4, characterized in that: The controlling the polishing device to process the PCB according to the pressing parameter includes: Get the temperature data of PCB; If the temperature data exceeds the safety threshold, the following adjustments are performed: immediately reduce the spindle speed, turn on the coolant, and make the actual pressure quickly converge to the target value; Get updated image information; The polishing path is updated according to the updated image information.

6. A PCB circuit board grinding and polishing method according to claim 1, characterized in that: Also includes: Establishing a life prediction model based on the consumables information; Compensation control is performed according to the life prediction model.

7. A PCB circuit board grinding and polishing method according to claim 6, characterized in that: The establishing of a life prediction model according to the consumables information includes: establishing a wear dynamics model based on the consumables information; A life prediction model is established based on the wear dynamics model.

8. A PCB circuit board grinding and polishing method according to claim 6, characterized in that: The compensation control according to the life prediction model includes: Obtaining wear stage information of consumables according to the life prediction model; Compensation information is obtained according to the wear stage information.

9. A PCB circuit board grinding and polishing device, characterized in that: include: A first acquisition module is used to acquire an initial image, where the initial image is used to reflect characteristic information of the PCB after preliminary cleaning; A classification module is used to classify the PCBs according to the characteristic information to obtain classification information, and send the PCBs to a corresponding grinding device or polishing device for processing according to the classification information; A second acquisition module is used to acquire consumables information, wherein the consumables information includes information reflecting the model of the consumables and usage records; An analysis module, configured to analyze the consumables information to obtain a pressing parameter; a control module, configured to control the grinding device or the polishing device to process the PCB according to the initial pressing parameter; A prediction module, configured to establish a life prediction model based on the consumables information; A compensation module is used to perform compensation control according to the life prediction model.

10. A PCB circuit board grinding and polishing device, characterized in that: include: Grinding device, polishing device, control device; The grinding device and the polishing device are electrically connected to the control device; The control device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

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