Bamboo product processing surface fine grinding automatic control system and method

Abstract

The invention discloses an automatic control system and method for fine grinding of a machined surface of a bamboo product, and relates to the technical field of bamboo product machining equipment. The system comprises an artificial intelligence visual identification module, a self-adaptive grinding execution module, a programmable logic controller main control module, a real-time feedback module and a man-machine interaction module. According to the method, the three-dimensional shape data of the bamboo products are collected through the artificial intelligence visual recognition module, the programmable logic controller main control module calls a strategy to regulate and control the self-adaptive grinding execution module to conduct graded grinding, the real-time feedback module dynamically collects the data and corrects parameters, and closed-loop control is formed. According to the scheme, the problems of poor adaptability and insufficient precision in the prior art are solved, personalized automatic polishing is achieved, the consistency and efficiency of finished bamboo products are improved, the cost is reduced, multiple bamboo products are adapted, and intelligent upgrading of the industry is assisted.

Description

Technical Field

[0001] This invention relates to the field of bamboo product processing, specifically to an automated control system and method for fine polishing of bamboo product surfaces. Background Technology

[0002] Bamboo products, with their environmentally friendly, natural, and high-quality characteristics, are widely used in daily necessities and handicrafts. Fine surface polishing is a crucial step in bamboo product processing, directly determining the appearance quality and market value of the finished product. Currently, bamboo product surface polishing processes mostly rely on manual polishing or semi-automatic equipment, which has several technical shortcomings. Manual polishing depends on the operator's experience, is labor-intensive, inefficient, and makes it difficult to uniformly apply polishing force and angle, resulting in uneven surface finish, poor product consistency, and a tendency to over-polish or under-polish, failing to meet the needs of large-scale production. Semi-automatic equipment often uses fixed-parameter polishing modes, lacking the ability to adapt to the natural variations in bamboo's shape, making it difficult to accurately identify the diameter, curvature, grain direction, and surface defects of bamboo products, and only suitable for single-size bamboo products. Although some equipment is equipped with simple control modules and detection components, it cannot form a closed-loop control. The polishing parameters cannot be dynamically adjusted according to the actual situation of bamboo products. The equipment lacks versatility and precision, which restricts the intelligent upgrading of the bamboo product processing industry. There is an urgent need for a technical solution that can adapt to the natural differences of bamboo products and achieve precise automated polishing. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the defects of the above-mentioned technology and provide an automated control system and method for fine polishing of bamboo product surfaces.

[0004] To address the aforementioned technical problems, the present invention provides an automated control system and method for fine polishing of bamboo product surfaces: An automated control system for fine polishing of bamboo product surfaces includes an artificial intelligence visual recognition module, an adaptive polishing execution module, a programmable logic controller (PLC) main control module, a real-time feedback module, and a human-machine interaction module. These modules work together to achieve full-process automation and fine control of bamboo product surface polishing. The artificial intelligence visual recognition module consists of a high-definition industrial camera, an image acquisition card, and an artificial intelligence processing unit. The high-definition industrial camera performs a comprehensive, no-dead-angle scan of the bamboo product at the feeding end, collecting information on the diameter, curvature, texture direction, and surface defects. The artificial intelligence processing unit rapidly analyzes the collected information using a pre-trained algorithm and generates three-dimensional morphological data of the bamboo product, which is simultaneously transmitted to the PLC main control module, thus solving the problem that existing equipment cannot accurately identify the natural differences in bamboo.

[0005] As an improvement, the adaptive sanding execution module includes a multi-degree-of-freedom robotic arm, a graded sanding belt assembly, an elastic holding unit, and an adjustable speed conveyor roller assembly; the multi-degree-of-freedom robotic arm is equipped with sanding belts of different grit sizes and can adjust the sanding angle and sanding pressure according to the three-dimensional morphological data of bamboo products transmitted by the artificial intelligence visual recognition module.

[0006] As an improvement, the elastic holding unit adopts a combination structure of silicone rollers and pressure sensors. The silicone rollers are used to contact and clamp bamboo products, and the pressure sensors detect the clamping pressure in real time to avoid damage to the bamboo products during clamping. The adjustable speed conveying roller assembly has a rubber wheel on the upper layer and a metal wheel on the lower layer. The conveying speed and the polishing rhythm are dynamically matched by the main control module of the programmable logic controller.

[0007] As an improvement, the main control module of the programmable logic controller adopts an industrial-grade programmable logic controller with a built-in grinding parameter database. It can receive data transmitted by the artificial intelligence visual recognition module and quickly call the corresponding grinding strategy. It can adjust the motion trajectory of the multi-degree-of-freedom robotic arm, the sanding belt speed, the conveying speed of the adjustable speed conveying roller group, and the pressing pressure of the elastic pressing unit in real time, so as to realize personalized grinding control of bamboo products.

[0008] As an improvement, the real-time feedback module consists of a laser thickness sensor, a surface roughness detector, and a vibration sensor. The laser thickness sensor collects thickness data of the bamboo product during the polishing process, the surface roughness detector collects surface smoothness data of the bamboo product, and the vibration sensor collects vibration data of the equipment during operation. Each sensor compares the collected data with preset standard values. When the deviation exceeds the limit, the programmable logic controller main control module is automatically triggered to correct the parameters, forming a closed-loop control. The human-machine interaction module is equipped with a touch screen and a parameter storage unit, which supports operators to set polishing accuracy, recall historical parameters, and monitor the operating status of the equipment. It also has fault alarm and data statistics functions.

[0009] An automated control method for fine polishing of bamboo product surfaces includes the following steps: First, pre-processing and data acquisition are performed. The bamboo product is fed into the feeding end and slowly conveyed by an adjustable speed conveyor roller group. At the same time, an artificial intelligence visual recognition module is activated to scan the bamboo product from all angles, collecting information on its three-dimensional shape and surface defects. After analysis and processing by a pre-trained algorithm, a dedicated polishing parameter scheme is generated. The dedicated polishing parameter scheme is then transmitted to the main control module of the programmable logic controller to complete the pre-polishing preparations and data initialization, ensuring that subsequent polishing operations are accurately adapted to the natural shape differences of the bamboo product.

[0010] As an improvement, a graded polishing execution step is also included. The programmable logic controller main control module calls the corresponding polishing strategy and controls the multi-degree-of-freedom robotic arm to adjust to the initial polishing position. First, the corresponding grit sanding belt is started for rough polishing to remove bamboo nodes, burrs and other protruding structures on the surface of the bamboo product. After the rough polishing is completed, it automatically switches to the corresponding grit sanding belt for semi-fine polishing, adjusting the polishing angle to fit the texture of the bamboo product. Finally, it switches to the corresponding grit sanding belt for fine polishing to ensure that the surface smoothness of the bamboo product meets the standard. During the polishing process, the elastic holding unit adjusts the clamping pressure in real time to prevent the bamboo product from deforming.

[0011] As an improvement, a real-time feedback and correction step is also included. The real-time feedback module continuously collects data on the thickness of the bamboo products, surface smoothness, and equipment vibration during the polishing process. The collected data is transmitted to the main control module of the programmable logic controller in real time and compared with preset standard values. If the surface roughness is found to be substandard, the main control module of the programmable logic controller automatically adjusts the sanding belt speed and the polishing time. If the thickness deviation is detected to exceed the preset range, the polishing pressure of the multi-degree-of-freedom robotic arm is immediately adjusted to ensure the processing accuracy of the bamboo products.

[0012] As an improvement, the system also includes finished product screening and data storage steps. After the polishing operation is completed, the system automatically determines whether the bamboo products are qualified based on the final data collected by the real-time feedback module. Qualified products are collected, and unqualified products are marked and removed. At the same time, the parameters and test data of this polishing operation are stored in the parameter storage unit of the human-computer interaction module to enrich the polishing parameter database and provide data support for the optimization of polishing strategies for similar bamboo products in the future.

[0013] As an improvement, during the graded polishing process, the main control module of the programmable logic controller adjusts the conveying speed of the adjustable speed conveyor roller group in real time based on the three-dimensional shape data of the bamboo products generated by the artificial intelligence visual recognition module. This ensures that the conveying speed is compatible with the polishing rhythm and sanding belt speed of the multi-degree-of-freedom robotic arm, guaranteeing the stability of the operation and the consistency of the polishing effect in each polishing stage.

[0014] The advantages of this invention compared to existing technologies are as follows: First, it improves polishing precision and finished product consistency. The artificial intelligence visual recognition module accurately collects three-dimensional morphological data of bamboo products, providing a basis for the programmable logic controller (PLC) main control module. The adaptive polishing execution module dynamically adjusts parameters accordingly, and in conjunction with the graded sanding belt component, achieves personalized polishing, avoiding uneven surface and over-polishing problems. Second, it achieves full-process automation, constructing a closed-loop system. From material feeding scanning to finished product screening, no manual intervention is required. The PLC main control module calls the parameter database to optimize operations, significantly improving efficiency and reducing labor costs and operational losses. Third, it ensures polishing stability and safety. The real-time feedback module collects data in real time and triggers parameter correction. The elastic holding unit flexibly clamps the bamboo products, reducing bamboo damage and equipment failure, and extending equipment lifespan. Fourth, it has strong versatility. The modular design allows for flexible adjustment of parameters in each module, adapting to various bamboo product polishing needs, providing support for the upgrading of the bamboo industry, and possessing both practicality and promotional value. Attached Figure Description

[0015] Figure 1 This is a structural diagram of the automated control system for fine polishing of bamboo product surfaces, which is part of the present invention.

[0016] Figure 2 This is a flowchart illustrating the automated control method for fine polishing of bamboo product surfaces, as described in this invention. Detailed Implementation

[0017] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0018] Referring to the accompanying drawings, an automated control system and method for fine polishing of bamboo product surfaces are disclosed. The automated control system for fine polishing of bamboo product surfaces includes an artificial intelligence visual recognition module, an adaptive polishing execution module, a programmable logic controller (PLC) main control module, a real-time feedback module, and a human-machine interaction module. These modules work together to achieve full-process automation and fine control of bamboo product surface polishing. The artificial intelligence visual recognition module consists of a high-definition industrial camera, an image acquisition card, and an artificial intelligence processing unit. The high-definition industrial camera performs a comprehensive, no-dead-angle scan of the bamboo product at the feeding end, collecting information on the diameter, curvature, texture direction, and surface defects. The artificial intelligence processing unit uses a pre-trained algorithm to quickly analyze the collected information and generate three-dimensional morphological data of the bamboo product, which is synchronously transmitted to the PLC main control module to solve the problem that existing equipment cannot accurately identify the natural differences in bamboo.

[0019] The adaptive sanding execution module includes a multi-degree-of-freedom robotic arm, a graded sanding belt assembly, an elastic holding unit, and an adjustable speed conveyor roller assembly. The multi-degree-of-freedom robotic arm is equipped with sanding belts of different grit sizes and can adjust the sanding angle and sanding pressure according to the three-dimensional shape data of bamboo products transmitted by the artificial intelligence visual recognition module.

[0020] The elastic holding unit adopts a combination structure of silicone rollers and pressure sensors. The silicone rollers are used to contact and clamp bamboo products, and the pressure sensors detect the clamping pressure in real time to avoid damage to the bamboo products during clamping. The adjustable speed conveying roller group has a rubber wheel on the upper layer and a metal wheel on the lower layer. The conveying speed and the polishing rhythm are dynamically matched by the main control module of the programmable logic controller.

[0021] The main control module of the programmable logic controller adopts an industrial-grade programmable logic controller with a built-in grinding parameter database. It can receive data transmitted by the artificial intelligence visual recognition module and quickly call the corresponding grinding strategy. It can adjust the motion trajectory of the multi-degree-of-freedom robotic arm, the sanding belt speed, the conveying speed of the adjustable speed conveying roller group, and the pressing pressure of the elastic pressing unit in real time, so as to realize personalized grinding control of bamboo products.

[0022] The real-time feedback module consists of a laser thickness sensor, a surface roughness detector, and a vibration sensor. The laser thickness sensor collects thickness data of the bamboo product during the polishing process, the surface roughness detector collects surface smoothness data of the bamboo product, and the vibration sensor collects vibration data of the equipment during operation. Each sensor compares the collected data with preset standard values. When the deviation exceeds the limit, the main control module of the programmable logic controller is automatically triggered to correct the parameters, forming a closed-loop control. The human-machine interaction module is equipped with a touch screen and a parameter storage unit, which supports operators to set polishing accuracy, recall historical parameters, and monitor the operating status of the equipment. It also has fault alarm and data statistics functions.

[0023] An automated control method for fine polishing of bamboo product surfaces includes the following steps: First, pre-processing and data acquisition are performed. The bamboo product is fed into the feeding end and slowly conveyed by an adjustable speed conveyor roller group. At the same time, an artificial intelligence visual recognition module is activated to scan the bamboo product from all angles, collecting information on its three-dimensional shape and surface defects. After analysis and processing by a pre-trained algorithm, a dedicated polishing parameter scheme is generated. The dedicated polishing parameter scheme is then transmitted to the main control module of the programmable logic controller to complete the pre-polishing preparations and data initialization, ensuring that subsequent polishing operations are accurately adapted to the natural shape differences of the bamboo product.

[0024] The process also includes a graded polishing step. The programmable logic controller (PLC) main control module calls the corresponding polishing strategy and controls the multi-degree-of-freedom robotic arm to adjust to the initial polishing position. First, it starts the sanding belt of the corresponding grit for rough polishing to remove bamboo nodes, burrs, and other protruding structures from the surface of the bamboo product. After rough polishing, it automatically switches to the sanding belt of the corresponding grit for semi-fine polishing, adjusting the polishing angle to match the texture of the bamboo product. Finally, it switches to the sanding belt of the corresponding grit for fine polishing to ensure that the surface smoothness of the bamboo product meets the standard. During the polishing process, the elastic holding unit adjusts the clamping pressure in real time to prevent the bamboo product from deforming.

[0025] It also includes real-time feedback and correction steps. The real-time feedback module continuously collects data on the thickness of bamboo products, surface smoothness, and equipment vibration during the polishing process. The collected data is transmitted to the main control module of the programmable logic controller in real time and compared with preset standard values. If the surface roughness is found to be substandard, the main control module of the programmable logic controller automatically adjusts the sanding belt speed and the polishing time. If the thickness deviation is found to exceed the preset range, the polishing pressure of the multi-degree-of-freedom robotic arm is immediately adjusted to ensure the processing accuracy of bamboo products.

[0026] It also includes finished product screening and data storage steps. After the polishing operation is completed, the system automatically determines whether the bamboo products are qualified based on the final data collected by the real-time feedback module. Qualified products are collected, and unqualified products are marked and removed. At the same time, the parameters and test data of this polishing operation are stored in the parameter storage unit of the human-computer interaction module to enrich the polishing parameter database and provide data support for the optimization of polishing strategies for similar bamboo products in the future.

[0027] During the graded polishing process, the main control module of the programmable logic controller adjusts the conveying speed of the adjustable speed conveyor roller group in real time based on the three-dimensional shape data of the bamboo products generated by the artificial intelligence visual recognition module. This ensures that the conveying speed is matched with the polishing rhythm and sanding belt speed of the multi-degree-of-freedom robotic arm, guaranteeing the stability of the operation and the consistency of the polishing effect in each polishing stage.

[0028] The core of this invention is to achieve fully automated control of the fine surface polishing of bamboo products through the coordinated operation of an artificial intelligence visual recognition module, an adaptive polishing execution module, a programmable logic controller main control module, a real-time feedback module, and a human-computer interaction module. This solves the problems of poor adaptability to the natural differences in bamboo and insufficient polishing precision in existing technologies. The following examples, using three different application scenarios, specifically illustrate the system composition, control methods, and formula applications.

[0029] Example 1: Fine polishing of bamboo strip surface. Example 2:

[0030] System Configuration:

[0031] This embodiment is designed for surface polishing of bamboo strips (5-15mm wide, 2-5mm thick). The artificial intelligence visual recognition module uses two high-definition industrial cameras symmetrically arranged on both sides of the feeding end, working with an image acquisition card to achieve omnidirectional scanning of the upper, lower, and sides of the bamboo strips. The artificial intelligence processing unit has a built-in pre-trained algorithm for bamboo strip morphology recognition. The adaptive polishing execution module is equipped with two 2-DOF robotic arms, corresponding to the upper and lower surfaces of the bamboo strips respectively. The graded sanding belt assembly uses 800-mesh, 1200-mesh, and 2000-mesh silicon carbide sanding belts. The elastic holding unit adopts... The system combines 30mm diameter silicone rollers with a high-precision pressure sensor. The upper rubber roller of the adjustable-speed conveyor roller assembly has a Shore hardness of 60, while the lower metal roller is made of stainless steel. The main control module of the programmable logic controller (PLC) uses an industrial-grade PLC with a built-in database of bamboo strip polishing parameters. The real-time feedback module features a laser thickness sensor with micron-level accuracy, a surface roughness detector using a contact detection method, and a vibration sensor mounted on the robotic arm base. The human-machine interface module is equipped with a 10-inch touchscreen display, supporting real-time parameter modification and status monitoring.

[0032] Control method implementation process:

[0033] First, preprocessing and data acquisition are performed. The bamboo strips are fed into the feeding end, and the adjustable speed conveyor roller group conveys the bamboo strips at the initial speed. At the same time, the artificial intelligence visual recognition module is activated, and two high-definition industrial cameras scan the surface of the bamboo strips simultaneously to collect information on the width, thickness, texture direction, and surface defects (such as burrs and black spots). The artificial intelligence processing unit performs grayscale and noise reduction processing on the collected image information, and generates three-dimensional morphological data of the bamboo strips through pre-trained algorithms, which is then synchronously transmitted to the main control module of the programmable logic controller.

[0034] During the graded polishing stage, the programmable logic controller (PLC) main control module calls the corresponding polishing strategy based on the received three-dimensional morphology data of the bamboo strips. First, rough polishing removes the protruding burrs on the surface of the bamboo strips. During rough polishing, the polishing pressure needs to be precisely controlled to avoid bamboo strip breakage. Here, a polishing pressure calculation model is introduced:

[0035]

[0036] Explanation of symbols in the formula: The grinding pressure of a multi-degree-of-freedom robotic arm (unit: Newtons). This is a correction factor for the hardness of bamboo (the value for bamboo strips is 0.8-1.2, and it is dynamically adjusted according to the moisture content of the bamboo; the higher the moisture content, the smaller the value). The density of the bamboo strips (unit: kilograms per cubic meter) is estimated by an artificial intelligence visual recognition module combining the volume and weight of the bamboo strips. The contact area between the sanding belt and the bamboo strip (unit: square meters) is calculated based on the width of the bamboo strip and the effective sanding width of the sanding belt. The relative linear velocity (in meters per second) between the sanding belt and the bamboo strip is determined by the difference between the sanding belt rotation speed and the conveying speed of the adjustable speed conveyor roller assembly.

[0037] The purpose of this formula is to dynamically calculate the appropriate sanding pressure based on the physical properties of the bamboo strips and the sanding motion parameters. This avoids deformation and breakage of the bamboo strips due to excessive pressure, or incomplete coarse sanding due to insufficient pressure, providing a theoretical basis for adaptive sanding pressure adjustment. The programmable logic controller (PLC) main control module uses the pressure value calculated by the above formula to control the pressure sensor of the elastic holding unit for real-time feedback adjustment, ensuring that the sanding pressure remains stable within the calculated value ±0.5 Newtons.

[0038] After coarse grinding, the system automatically switches to 1200-grit abrasive belt for semi-fine grinding. The robotic arm's grinding angle is adjusted to match the bamboo strip's grain. After semi-fine grinding, the surface smoothness data of the bamboo strip is collected using a surface roughness detector. If the preset standard is not met, the system enters the fine grinding stage and the abrasive belt speed is adjusted. The abrasive belt speed in the fine grinding stage is optimized using the following formula:

[0039]

[0040] Explanation of symbols in the formula: The belt rotation speed (unit: revolutions per minute); The preset surface roughness target value (0.8-1.6 micrometers corresponding to fine polishing of bamboo strips); The conveying speed of the adjustable speed conveyor roller assembly (unit: meters per minute); This is the correction factor for the mesh size of the sand belt (1.5 corresponds to 2000 mesh sand belt); The diameter of the sand belt (unit: meter).

[0041] The function of this formula is to accurately calculate the required sanding belt speed based on the preset surface roughness target, combined with the conveyor speed and sanding belt parameters, to achieve directional control of surface roughness and avoid excessive sanding that could lead to excessive deviations in bamboo strip thickness. The real-time feedback module continuously collects bamboo strip thickness and surface roughness data, transmits them to the programmable logic controller (PLC) main control module, and compares them with preset values. If the thickness deviation exceeds the range, it is corrected by adjusting the sanding pressure of the robotic arm; if the surface roughness does not meet the standard, the sanding belt speed is adjusted using the above formula, forming a closed-loop control.

[0042] After polishing, the system automatically selects qualified bamboo strips, marks and removes unqualified products, and stores the polishing parameters (polishing pressure, sanding belt speed, conveyor speed, etc.) and test data in the parameter storage unit of the human-machine interaction module to enrich the polishing parameter database and provide optimization basis for subsequent polishing of bamboo strips of the same specification.

[0043] Example 2: Surface polishing of bamboo tableware (bamboo spoons)

[0044] System Configuration:

[0045] This embodiment focuses on the design for polishing irregularly shaped bamboo spoon surfaces. The AI ​​visual recognition module uses three high-definition industrial cameras arranged in a triangle to achieve 360-degree scanning of the bamboo spoon, accurately capturing the curved shape and surface defects of the spoon head and handle. The adaptive polishing execution module uses a 4-DOF robotic arm adapted to polish the irregular curved surfaces of the bamboo spoon. The graded abrasive belt assembly uses flexible abrasive belts (800 grit, 1500 grit, and 2000 grit) to avoid damage to the curved surfaces of the bamboo spoon caused by rigid abrasive belts. The elastic holding unit uses multiple sets of small silicone rollers to meet the clamping needs of different parts of the bamboo spoon. The adjustable speed conveying roller group adopts an intermittent conveying method to match the polishing rhythm of the robotic arm. The programmable logic controller main control module has a built-in bamboo tableware polishing parameter sub-library and optimizes the polishing trajectory algorithm for irregular curved surfaces. The laser thickness sensor in the real-time feedback module adopts non-contact detection to avoid damaging the surface of the bamboo spoon, and the surface roughness detector is designed with a detection probe for curved surfaces. The human-machine interaction module adds parameter import / export functions to support customized polishing parameter settings.

[0046] Control method implementation process

[0047] In the preprocessing and data acquisition stage, the bamboo spoon is fixed on a special fixture and fed into the feed end. The adjustable speed conveyor rollers intermittently convey the bamboo spoon to the scanning area and then stop. Three high-definition industrial cameras start scanning simultaneously to collect information on the curved contour, thickness distribution, texture direction, and surface defects (such as scratches and bamboo joint residue) of the bamboo spoon. The artificial intelligence processing unit reconstructs the collected three-dimensional data to generate a unique three-dimensional model of the bamboo spoon, which is then transmitted to the main control module of the programmable logic controller. At the same time, the curvature radius of each part of the bamboo spoon is calculated to provide data support for the polishing trajectory planning.

[0048] During the graded polishing stage, the programmable logic controller (PLC) main control module plans the polishing trajectory of the 4-DOF robotic arm based on the 3D model and curvature radius data of the bamboo spoon. First, coarse polishing is performed using an 800-grit flexible abrasive belt to remove bamboo joint residue and burrs from the surface of the bamboo spoon. The coarse polishing trajectory must conform to the curved surface of the bamboo spoon; therefore, a curvature adaptation formula for the polishing trajectory is introduced here.

[0049]

[0050] Explanation of symbols in the formula: Curvature of the grinding path for the robotic arm (unit: per meter); The radius of curvature (in meters) of the corresponding part of the bamboo spoon is extracted from the 3D model reconstructed by the artificial intelligence visual recognition module; This is the trajectory correction factor (value 1.05-1.1, adapted to the deformation characteristics of the flexible abrasive belt, to avoid trajectory deviation). The angle between the bamboo spoon texture and the polishing direction (unit: radians) is calculated based on the texture direction data collected by the artificial intelligence visual recognition module.

[0051] The purpose of this formula is to precisely match the grinding trajectory of the robotic arm with the curvature of the bamboo spoon surface, while also taking into account the direction of the bamboo grain. This reduces the sliding friction between the sanding belt and the bamboo spoon surface during grinding, avoids creating new scratches, and improves the uniformity of the grinding process. Based on the curvature value calculated by the formula, the robotic arm dynamically adjusts its movement trajectory, and in conjunction with an intermittent feeding method, completes the rough grinding of various parts of the bamboo spoon.

[0052] After coarse grinding, the adjustable speed conveyor rollers transport the bamboo spoon to the semi-fine grinding area. The system automatically switches to a 1500-grit flexible sanding belt, and the programmable logic controller (PLC) main control module calculates the semi-fine grinding time using the following formula:

[0053]

[0054] Explanation of symbols in the formula: Semi-finish grinding time for the corresponding part (unit: seconds); The remaining grinding allowance after rough grinding (unit: meter) is calculated from the difference between the data collected by the laser thickness sensor and the preset thickness. The polishing area (unit: square meters) for the corresponding part is calculated from the 3D model of the bamboo spoon; The grinding speed of the robotic arm (unit: meters per second); The grinding pressure (unit: Newton) is calculated using the pressure calculation model from Example 1. The efficiency coefficient for belt sanding (0.7-0.85 for 1500-grit flexible sanding belt, dynamically adjusted according to the wear level of the sanding belt).

[0055] The formula precisely controls the semi-fine grinding time based on the residual material from the coarse grinding and the grinding parameters, avoiding under- or over-grinding and ensuring uniform thickness across all parts of the bamboo spoon. After semi-fine grinding, the process switches to a 2000-grit flexible sanding belt for fine grinding. A real-time feedback module continuously collects surface roughness and thickness data, and the programmable logic controller (PLC) main control module fine-tunes the grinding parameters based on the feedback data until the surface smoothness and dimensional accuracy of the bamboo spoon meet the standards.

[0056] During the finished product screening stage, the system automatically determines whether the bamboo spoons are qualified based on the final test data from the real-time feedback module. Qualified products are sent to the subsequent polishing process, while unqualified products are marked with defect types and removed. At the same time, the system stores the polishing parameters and test data for this time to optimize the polishing strategy for similar bamboo tableware.

[0057] Example 3: Surface polishing of bamboo handicrafts (bamboo carvings):

[0058] System Configuration:

[0059] This embodiment is designed for the complex shapes and high-precision polishing requirements of bamboo carvings. The artificial intelligence visual recognition module uses a combination of five high-definition industrial cameras and structured light scanning equipment to improve the recognition accuracy of the fine structures of the bamboo carvings. The artificial intelligence processing unit optimizes the algorithm for recognizing minute defects, which can identify surface flaws with a diameter of less than 0.5mm. The adaptive polishing execution module uses a 6-DOF robotic arm equipped with a miniature flexible sanding belt and polishing head to adapt to the complex structures of bamboo carvings, such as hollowing and relief carving. The graded sanding belt assembly uses 1000-mesh, 1800-mesh, and 2500-mesh ultra-fine sanding belts. The elastic holding unit adopts a magnetic flexible clamping structure to avoid damage to the shape of the bamboo carvings. The programmable logic controller main control module has a built-in high-precision polishing trajectory planning algorithm, which supports personalized polishing parameter settings for complex curved surfaces. The real-time feedback module uses a laser interferometer to detect surface flatness, and works with a surface roughness detector to achieve high-precision detection. The human-computer interaction module supports a 3D model preview function, allowing operators to intuitively view the polishing trajectory and parameter settings.

[0060] Control method implementation process:

[0061] In the preprocessing and data acquisition stage, the bamboo carving is fixed on a shockproof clamp and sent into the scanning area. The structured light scanning device and five high-definition industrial cameras work together to collect information on the three-dimensional shape, fine structure, texture direction and surface defects of the bamboo carving. The artificial intelligence processing unit denoises and reconstructs the collected data to generate a three-dimensional model of the bamboo carving with an accuracy of 0.01mm. At the same time, it identifies key structures such as hollow parts and relief patterns, marks the location of minor surface defects, and transmits the complete three-dimensional data and defect information to the main control module of the programmable logic controller.

[0062] In the graded polishing stage, the programmable logic controller (PLC) main control module plans the polishing trajectory of the 6-DOF robotic arm based on the 3D model and key structural information of the bamboo carving, avoiding easily damaged areas such as hollowed-out sections. First, coarse polishing is performed using a 1000-grit micro-flexible abrasive belt to remove residual burrs and tool marks. During coarse polishing, the polishing depth must be strictly controlled, and a polishing depth calculation model is introduced.

[0063]

[0064] Explanation of symbols in the formula: The depth of a single coarse grinding pass (unit: meter); The measured surface roughness value (unit: micrometers) before rough grinding was collected by a surface roughness tester. This is the target surface roughness value (unit: micrometers) after rough grinding, preset according to the grinding requirements of bamboo carving ornaments; This is a grinding depth correction factor (value 0.002-0.003, adapted to the characteristics of micro sanders). The belt rotation speed (unit: revolutions per minute); The density of bamboo (unit: kilograms per cubic meter) is estimated by combining the three-dimensional model of the bamboo carving with the weight using an artificial intelligence visual recognition module.

[0065] The purpose of this formula is to precisely control the depth of a single rough grinding pass, avoiding damage to the key structures of the bamboo carving, such as the relief patterns, due to excessive grinding. It also ensures that the surface roughness meets the standards after rough grinding, laying the foundation for subsequent fine grinding. The robotic arm calculates the grinding depth based on the formula and, in conjunction with real-time detection data from a laser interferometer, fine-tunes the grinding pressure and movement trajectory to complete the rough grinding operation.

[0066] After rough grinding, the system automatically switches to 1800-grit ultrafine abrasive belt for semi-finish grinding, focusing on polishing the details of the embossed pattern. After semi-finish grinding, the surface flatness is checked using a laser interferometer. If the flatness does not meet the preset standard, the system enters the fine grinding stage and switches to 2500-grit ultrafine abrasive belt. During the fine grinding stage, the surface flatness adjustment parameters are optimized using the following formula:

[0067]

[0068] Explanation of symbols in the formula: The height adjustment range for the robotic arm (unit: meters); The difference between the measured surface roughness after semi-finishing and the preset target value (unit: micrometers); This is the height adjustment coefficient (value 0.0015, suitable for polishing the fine structure of bamboo carvings). The grinding speed of the robotic arm (unit: meters per second); The time for fine grinding (unit: seconds).

[0069] The formula precisely adjusts the grinding height of the robotic arm based on the deviation of the surface roughness after semi-fine grinding, ensuring the surface flatness of the bamboo carving meets the standard while avoiding over-grinding that could damage the fine structure. A real-time feedback module continuously collects data on surface flatness, roughness, and equipment vibration. The programmable logic controller (PLC) main control module dynamically adjusts the grinding parameters based on this feedback data, forming a high-precision closed-loop control.

[0070] After polishing, the system automatically filters out qualified products. Qualified bamboo carvings are sent to the finished product inspection process, while unqualified products are marked with the location and type of defects and removed. At the same time, the polishing parameters, trajectory planning data and test results are stored in the parameter storage unit of the human-computer interaction module, providing accurate data support for the polishing of similar bamboo handicrafts in the future, and improving polishing efficiency and the qualification rate of finished products.

[0071] The three embodiments described above address three different types of bamboo products: bamboo strips, bamboo tableware, and bamboo handicrafts. By optimizing system configuration and control methods, they adapt to the structural characteristics and polishing requirements of different bamboo products. Compared to existing technologies, they significantly improve polishing accuracy, efficiency, and finished product qualification rate, demonstrating broad application prospects.

[0072] Beneficial effects:

[0073] This invention discloses an automated control system and method for fine polishing of bamboo product surfaces. Through the collaborative design of an artificial intelligence visual recognition module, an adaptive polishing execution module, a programmable logic controller main control module, a real-time feedback module, and a human-computer interaction module, combined with a scientific graded polishing control method, it offers the following significant advantages compared to existing bamboo product polishing technologies:

[0074] First, it significantly improves the polishing precision and finished product consistency of bamboo products, addressing the pain point of poor adaptability of existing technologies to the natural differences in bamboo. The AI ​​visual recognition module can comprehensively collect three-dimensional morphological data of bamboo products, such as diameter, curvature, texture direction, and surface defects. Through pre-trained algorithms, it quickly analyzes and generates customized data schemes, providing accurate decision-making basis for the programmable logic controller main control module. The adaptive polishing execution module can dynamically adjust the polishing angle, polishing pressure, and sanding belt speed of the multi-degree-of-freedom robotic arm based on the above data. With the orderly switching of graded sanding belt components, it can achieve personalized polishing with a "one material, one strategy" approach, effectively avoiding the problems of uneven surface, over-polishing, or incomplete polishing caused by traditional fixed-parameter polishing. It greatly improves the consistency of surface smoothness and dimensional accuracy of bamboo products, and is especially suitable for bamboo products with different structural types such as bamboo strips, bamboo tableware, and bamboo handicrafts. The finished product qualification rate is significantly improved compared with existing technologies.

[0075] Secondly, it achieves fully automated control of the entire process, significantly improving polishing efficiency and reducing labor costs. This invention constructs a closed-loop automated system of "data acquisition - strategy generation - graded polishing - real-time feedback - parameter correction." From bamboo product feeding scanning, parameter calculation, polishing execution to finished product screening and data storage, the entire process requires no manual intervention, completely eliminating the reliance on operator experience in traditional manual polishing. It also avoids the drawbacks of semi-automated equipment requiring manual parameter adjustment and monitoring. The programmable logic controller (PLC) main control module has a built-in polishing parameter database, which can store and call polishing parameters for different types of bamboo products. Combined with the parameter storage and retrieval functions of the human-machine interface module, subsequent polishing of similar bamboo products can directly reuse optimized parameters, further improving operational efficiency. Compared to manual and semi-automated polishing, operational efficiency is significantly improved, while reducing labor intensity and losses caused by human error, thus lowering the overall cost of bamboo product processing.

[0076] Third, the stability and safety of the polishing process are optimized to extend the equipment's lifespan and protect the bamboo's properties. The real-time feedback module uses a laser thickness sensor, surface roughness detector, and vibration sensor to collect data on the bamboo product's thickness, surface finish, and equipment vibration during the polishing process. If a parameter deviation is detected, the programmable logic controller (PLC) main control module is immediately triggered for correction, preventing damage to the bamboo product or equipment malfunction due to abnormal parameters. The elastic holding unit in the adaptive polishing execution module uses a combination of silicone rollers and pressure sensors to flexibly hold the bamboo product, effectively preventing damage during clamping and reducing losses such as bamboo breakage and deformation, maximizing the preservation of the bamboo's natural properties. Furthermore, by precisely controlling parameters such as polishing pressure and sanding belt speed, the sanding belt wear rate and equipment operating load can be reduced, extending the lifespan of the grading sanding belt assembly and the multi-degree-of-freedom robotic arm, and lowering equipment maintenance costs.

[0077] Fourth, it possesses strong versatility and scalability, adapting to the processing needs of bamboo products in various scenarios. Through modular design, this invention allows for flexible adjustment of the scanning method of the AI ​​visual recognition module, the robotic arm degrees of freedom of the adaptive polishing execution module, and the mesh size of the graded sanding belt component, based on the structural characteristics and polishing requirements of different bamboo products. This eliminates the need for significant modifications to the overall system, enabling fine polishing of various types and specifications of bamboo products, such as bamboo strips, bamboo spoons, and bamboo carvings. Furthermore, the human-computer interaction module supports customized parameter settings, import, and export. The parameter database of the programmable logic controller (PLC) main control module can be continuously optimized by storing polishing data, adapting to the polishing needs of new bamboo products. This provides technical support for the diversification and high-value-added upgrading of the bamboo product processing industry, has a wide range of applications, and possesses strong promotional and application value.

[0078] Fifth, this invention enhances the intelligent level of bamboo product processing and promotes the industrial upgrading of the bamboo industry. It deeply integrates artificial intelligence visual recognition technology with automated control technology, breaking through the technical bottlenecks of existing bamboo product polishing equipment, changing the traditional "labor-intensive" industrial model of bamboo product processing, and achieving intelligent and standardized control of polishing operations. Through the coordinated operation of various modules, it not only improves the processing quality and efficiency of bamboo products, but also provides precise data support for optimizing bamboo product processing technology through data storage and analysis functions. This helps the bamboo industry transform towards a "technology-intensive" model, enhances the market competitiveness of bamboo products, and drives the high-quality development of the bamboo industry.

[0079] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An automated control system for fine polishing of bamboo product surfaces, characterized in that: The system includes an AI visual recognition module, an adaptive polishing execution module, a programmable logic controller (PLC) main control module, a real-time feedback module, and a human-machine interaction module. These modules work together to achieve fully automated and precise control of the bamboo product surface polishing process. The AI ​​visual recognition module consists of a high-definition industrial camera, an image acquisition card, and an AI processing unit. The high-definition industrial camera performs a comprehensive, no-dead-angle scan of the bamboo product at the feeding end, collecting information on the diameter, curvature, texture direction, and surface defects. The AI ​​processing unit uses a pre-trained algorithm to quickly analyze the collected information and generate three-dimensional morphological data of the bamboo product, which is then synchronously transmitted to the PLC main control module to solve the problem that existing equipment cannot accurately identify the natural differences in bamboo.

2. The automated control system for fine polishing of bamboo product surfaces according to claim 1, characterized in that: The adaptive sanding execution module includes a multi-degree-of-freedom robotic arm, a graded sanding belt assembly, an elastic holding unit, and an adjustable speed conveyor roller assembly. The multi-degree-of-freedom robotic arm is equipped with sanding belts of different grit sizes and can adjust the sanding angle and sanding pressure according to the three-dimensional shape data of bamboo products transmitted by the artificial intelligence visual recognition module.

3. The automated control system for fine surface polishing of bamboo products according to claim 2, characterized in that: The elastic holding unit adopts a combination structure of silicone rollers and pressure sensors. The silicone rollers are used to contact and clamp bamboo products, and the pressure sensors detect the clamping pressure in real time to avoid damage to the bamboo products during clamping. The adjustable speed conveying roller group has a rubber wheel on the upper layer and a metal wheel on the lower layer. The conveying speed and the polishing rhythm are dynamically matched by the main control module of the programmable logic controller.

4. The automated control system for fine polishing of bamboo product surfaces according to claim 1, characterized in that: The main control module of the programmable logic controller adopts an industrial-grade programmable logic controller with a built-in grinding parameter database. It can receive data transmitted by the artificial intelligence visual recognition module and quickly call the corresponding grinding strategy. It can adjust the motion trajectory of the multi-degree-of-freedom robotic arm, the sanding belt speed, the conveying speed of the adjustable speed conveying roller group, and the pressing pressure of the elastic pressing unit in real time, so as to realize personalized grinding control of bamboo products.

5. The automated control system for fine polishing of bamboo product surfaces according to claim 1, characterized in that: The real-time feedback module consists of a laser thickness sensor, a surface roughness detector, and a vibration sensor. The laser thickness sensor collects thickness data of the bamboo product during the polishing process, the surface roughness detector collects surface smoothness data of the bamboo product, and the vibration sensor collects vibration data of the equipment during operation. Each sensor compares the collected data with preset standard values. When the deviation exceeds the limit, the main control module of the programmable logic controller is automatically triggered to correct the parameters, forming a closed-loop control. The human-machine interaction module is equipped with a touch screen and a parameter storage unit, which supports operators to set polishing accuracy, recall historical parameters, and monitor the operating status of the equipment. It also has fault alarm and data statistics functions.

6. An automated control method for fine polishing of bamboo product surfaces, implemented based on the automated control system for fine polishing of bamboo product surfaces as described in any one of claims 1 to 5, characterized in that: The specific steps are as follows: First, preprocessing and data acquisition are carried out. The bamboo products are fed into the feeding end and slowly conveyed by the adjustable speed conveyor roller group. At the same time, the artificial intelligence visual recognition module is activated to scan the bamboo products from all directions, collect the three-dimensional shape and surface defect information of the bamboo products, and generate a special polishing parameter scheme after analysis and processing by the pre-trained algorithm. The special polishing parameter scheme is transmitted to the main control module of the programmable logic controller to complete the pre-polishing preparation and data initialization, so as to ensure that the subsequent polishing operation is accurately adapted to the natural shape difference of the bamboo products.

7. The automated control method for fine polishing of bamboo product surfaces according to claim 6, characterized in that: The process also includes a graded polishing step. The programmable logic controller (PLC) main control module calls the corresponding polishing strategy and controls the multi-degree-of-freedom robotic arm to adjust to the initial polishing position. First, it starts the sanding belt of the corresponding grit for rough polishing to remove bamboo nodes, burrs, and other protruding structures from the surface of the bamboo product. After rough polishing, it automatically switches to the sanding belt of the corresponding grit for semi-fine polishing, adjusting the polishing angle to match the texture of the bamboo product. Finally, it switches to the sanding belt of the corresponding grit for fine polishing to ensure that the surface smoothness of the bamboo product meets the standard. During the polishing process, the elastic holding unit adjusts the clamping pressure in real time to prevent the bamboo product from deforming.

8. The automated control method for fine polishing of bamboo product surfaces according to claim 6, characterized in that: It also includes real-time feedback and correction steps. The real-time feedback module continuously collects data on the thickness of bamboo products, surface smoothness, and equipment vibration during the polishing process. The collected data is transmitted to the main control module of the programmable logic controller in real time and compared with preset standard values. If the surface roughness is found to be substandard, the main control module of the programmable logic controller automatically adjusts the sanding belt speed and the polishing time. If the thickness deviation is found to exceed the preset range, the polishing pressure of the multi-degree-of-freedom robotic arm is immediately adjusted to ensure the processing accuracy of bamboo products.

9. The automated control method for fine polishing of bamboo product surfaces according to claim 6, characterized in that: It also includes finished product screening and data storage steps. After the polishing operation is completed, the system automatically determines whether the bamboo products are qualified based on the final data collected by the real-time feedback module. Qualified products are collected, and unqualified products are marked and removed. At the same time, the parameters and test data of this polishing operation are stored in the parameter storage unit of the human-computer interaction module to enrich the polishing parameter database and provide data support for the optimization of polishing strategies for similar bamboo products in the future.

10. The automated control method for fine polishing of bamboo product surfaces according to claim 7, characterized in that: During the graded polishing process, the main control module of the programmable logic controller adjusts the conveying speed of the adjustable speed conveyor roller group in real time based on the three-dimensional shape data of the bamboo products generated by the artificial intelligence visual recognition module. This ensures that the conveying speed is matched with the polishing rhythm and sanding belt speed of the multi-degree-of-freedom robotic arm, guaranteeing the stability of the operation and the consistency of the polishing effect in each polishing stage.

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