Bamboo product continuous drying and paint spraying production method and system

Abstract

The invention provides a continuous drying and paint spraying production method and system for bamboo products, and relates to the technical field of bamboo product processing. Performing data analysis, and determining a product characteristic parameter table; the drying equipment is controlled to conduct drying according to the parameter table and monitor process data in real time; controlling balance equipment to perform balance cooling and monitoring data; controlling paint spraying equipment to spray paint, and monitoring the thickness of a paint film in real time through an online thickness gauge to obtain first paint spraying data; performing dynamic evaluation according to the first paint spraying data to obtain a thickness standard ratio, a non-standard ratio and a standard-exceeding ratio; and executing a corresponding production process according to an evaluation result. The problems that in the prior art, the bamboo product drying moisture content is uneven, the paint spraying thickness consistency is poor, and the production process depends on manual adjustment are solved, automation and intellectualization of the bamboo product production process are achieved, and the product quality and the production efficiency are improved.

Description

[Technical Field]

[0001] This invention relates to the field of bamboo product processing technology, specifically to a continuous drying and painting production method and system for bamboo products. [Background Technology]

[0002] Bamboo products, as a green and environmentally friendly material, are widely used in furniture, decorative materials, and handicrafts. The surface treatment of bamboo products typically involves drying, cooling, painting, and curing. However, existing production methods generally suffer from the following problems:

[0003] Unstable drying and moisture content control: Bamboo has a high and uneven natural moisture content. Traditional drying processes lack real-time monitoring and dynamic adjustment, resulting in some products having excessively high or low moisture content, which can cause cracking or deformation.

[0004] Inaccurate paint thickness control: Existing painting processes mostly rely on manual labor or fixed procedures, making it impossible to monitor and control the paint film thickness in real time, resulting in uneven paint film thickness and affecting the product's appearance and durability.

[0005] Loose process connections: Traditional processes lack data linkage between different stages, and drying, cooling, painting and curing operate independently, which can easily lead to mismatched process parameters, affecting production efficiency and quality consistency.

[0006] Therefore, there is an urgent need for a continuous drying and painting production method for bamboo products that can achieve full-process automation, closed-loop monitoring and dynamic control, so as to improve production efficiency and product quality stability. [Summary of the Invention]

[0007] To address the problems of unstable drying control, inaccurate paint thickness control, and lack of coordination in the production process in existing technologies, this invention provides a continuous drying and painting production method for bamboo products. This method achieves intelligent control and dynamic quality assessment throughout the entire process, effectively improving the quality consistency and production efficiency of bamboo products.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0009] A continuous drying and painting production method for bamboo products, the method being applied to a composite monitoring system for bamboo product production, the method comprising:

[0010] Obtain characteristic data for bamboo product production;

[0011] The feature data is parsed to determine the product feature parameter table, which includes the product number and the corresponding geometric dimensions, spraying area, and initial moisture content parameters.

[0012] The drying equipment is controlled to dry the bamboo products. The drying control program of the drying equipment is called according to the product characteristic parameter table and the target moisture content. The temperature, humidity and real-time moisture content during the drying process are monitored in real time as drying monitoring data.

[0013] The control balancing equipment performs balancing cooling on the dried bamboo products. Based on the drying monitoring data and the target temperature, the balancing cooling program is invoked to monitor the temperature, humidity, and real-time moisture content to obtain balancing cooling monitoring data.

[0014] The system controls the painting production equipment to paint the bamboo products after balanced cooling. The system calls the painting program based on the product characteristic parameter table and balanced cooling monitoring data, monitors the painting data in real time to obtain the first painting data, obtains the dynamic evaluation result based on the first painting data, and executes the corresponding production process based on the dynamic evaluation result.

[0015] Control the curing and drying equipment to cure and further dry the bamboo products that have entered the curing process after spraying paint, and then unload the materials.

[0016] Further optimized, the first paint spraying data includes paint film thickness; the dynamic evaluation result obtained based on the first paint spraying data specifically involves: comparing the paint film thickness distribution data with a preset thickness value and identifying: areas with acceptable thickness, areas with unacceptable thickness, and areas with excessive thickness, and calculating the corresponding thickness compliance ratio a, thickness non-compliance ratio b, and thickness excess ratio c respectively.

[0017] Further optimized calculation methods for thickness compliance rate (a), thickness non-compliance rate (b), and thickness exceeding standard (c) include:

[0018] The preset thickness value range [T0-ΔT, T0+ΔT] is obtained by calling the preset value T0 and the preset tolerance ΔT. All thickness data points are traversed. If a data point is within the preset thickness value range, the area where the point is located is the thickness-compliant area; if the data point is < T0-ΔT, the area where the point is located is the thickness-non-compliant area; if the data point is > T0+ΔT, the area where the point is located is the thickness-exceeding area.

[0019] Let the total number of measurement points be N; the number of points that meet the thickness standard is Na, then the thickness compliance ratio is a = Na / N; the number of points that do not meet the thickness standard is Nb, then the thickness non-compliance ratio is b = Nb / N; the number of points that exceed the thickness standard is Nc, then the thickness excess ratio is c = Nc / N.

[0020] Further optimization involves executing corresponding production processes based on dynamic evaluation results. Methods include: calling the preset value A_set for the compliance rate.

[0021] P1. When the thickness compliance ratio a ≥ A_set, execute the conveying command to enter the curing equipment;

[0022] P2. When the thickness compliance ratio a < A_set and b ≥ c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard, scan again with an online thickness gauge to detect the paint film thickness, and recalculate the corresponding thickness compliance ratio a2, thickness non-compliance ratio b2, and thickness exceeding the standard ratio c2. Repeat steps P1 and P2.

[0023] P3. When the thickness compliance ratio a < A_set and b < c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard and mark the bamboo product as a defective product, and execute the conveying instruction to enter the curing equipment.

[0024] Further optimization includes obtaining the characteristic data for producing bamboo products, including:

[0025] Product number obtained by entering or scanning;

[0026] Acquire color image data of bamboo products using image acquisition equipment;

[0027] Initial moisture content data of bamboo products were obtained using a near-infrared online moisture meter.

[0028] Further optimization involves parsing the feature data to determine a product feature parameter table, the method of which includes:

[0029] Receive product numbers obtained through manual input or automatic scanning identification;

[0030] The image data acquired by the image acquisition device is preprocessed and edge-enhanced, and the contour features of bamboo products are extracted.

[0031] Based on the aforementioned contour features, the geometric dimensions of the bamboo product are calculated using an image pixel calibration method.

[0032] Pixel statistics are performed on the region within the contour feature, and the spraying area of ​​the bamboo product is calculated by combining the pre-calibrated pixel-area conversion coefficient.

[0033] Receive initial moisture content data measured by the near-infrared online moisture detector;

[0034] The product number, geometric dimensions, spraying area, and initial moisture content data are associated and stored to generate the product characteristic parameter table.

[0035] A production system utilizing the above-mentioned continuous drying and painting method for bamboo products, the system comprising:

[0036] The data acquisition module is used to obtain characteristic data of bamboo products;

[0037] The data processing and control module is communicatively connected to the data acquisition module, receives the feature data, parses it, and outputs a product feature parameter table; obtains dynamic evaluation results based on the first painting data, and generates production process control instructions based on the dynamic evaluation results;

[0038] An execution module is communicatively connected to the data processing and control module. The execution module includes, but is not limited to, drying equipment, balancing equipment, spray painting production equipment, and curing and drying equipment, and is used to perform drying, balancing, spray painting, curing and / or secondary drying operations.

[0039] The online monitoring module includes an online monitoring device installed on the execution module, used to monitor production data in real time and send it to the data processing and control module;

[0040] In a further optimized manner, the data processing and control module also includes an image processing unit, which preprocesses and enhances the edges of the images captured by the industrial color camera, and extracts the contour features of the bamboo product; based on the contour features, the geometric dimensions and coating area of ​​the bamboo product are calculated using an image pixel calibration method.

[0041] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0042] By collecting multi-dimensional characteristic data such as geometric dimensions and initial moisture content during the bamboo product production process, precise and individualized initial state information can be obtained. This ensures that subsequent key processes such as drying and painting can be personalized based on accurate and complete data, enhancing the matching degree and reliability of the entire process parameters. Through data analysis and feature extraction, the collected raw data is organized into a structured product characteristic parameter table, enabling the key attributes of each bamboo product to be digitally calibrated, ensuring that the individual differences and process requirements of bamboo products are clearly and accurately reflected. By calling and optimizing the control programs of each piece of equipment in real time according to the product characteristic parameter table, the continuous production process is divided into multiple precisely controllable stages such as drying, balancing, painting, and curing. This allows for the adoption of the most suitable process parameters at each stage, avoiding the limitations of traditional fixed-program processing. Multi-stage collaborative control enables the system to achieve more precise and controllable results. The system can flexibly handle bamboo products of different specifications and initial states, adapting to the diverse needs of high-end bamboo product production. By connecting and intelligently controlling multiple execution devices such as drying, balancing, painting, and curing, and dynamically adjusting the working status of each device based on real-time monitoring data, it can automatically select the optimal process strategy (such as compensatory spraying) based on quality feedback at different stages, avoiding quality defects or resource waste, thereby improving production efficiency and product yield, and reducing unnecessary energy consumption and losses. Through real-time monitoring of paint film thickness by an online thickness gauge and dynamic evaluation and decision-making, it achieves closed-loop feedback control of painting quality. Based on the evaluation results, the production system can automatically trigger subsequent actions such as compensatory spraying, defect marking, or pass-through, significantly reducing reliance on external manual inspection and intervention, making the entire bamboo product production process more automated and intelligent, and ultimately achieving a stable output of high-end quality. [Attached Image Description]

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A schematic flowchart of a continuous drying and painting production method for bamboo products provided in an embodiment of this application;

[0045] Figure 2 A flowchart illustrating the execution of corresponding production processes based on dynamic evaluation results, provided for embodiments of this application;

[0046] Figure 3 This is a schematic diagram of the structure of the continuous drying and painting production system for bamboo products provided in the embodiments of this application.

Detailed Implementation Methods

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0049] Example 1

[0050] like Figure 1 As shown, this application provides a continuous drying and painting production method for bamboo products. The method is applied to a composite monitoring system for bamboo product production. The system includes a composite production line, and the method includes:

[0051] S101: Obtain characteristic data for producing bamboo products;

[0052] In this embodiment, the monitoring system is centered around a composite production line, which sequentially includes a feeding station, primary drying equipment, balancing and cooling equipment, painting equipment (including an online detection station), curing equipment, and an unloading station. It integrates multiple functional modules such as automated conveying, multimodal data acquisition, intelligent processing, precision machining, and closed-loop feedback control. After the bamboo products obtained in the previous process enter the continuous drying and painting production line, such as at the feeding station, they first pass through the data acquisition unit. The unit collects the product number of the bamboo product and further uses data on the geometric shape, spraying area, and initial moisture content of the bamboo product.

[0053] Furthermore, the product number is obtained by input or scanning; the product number can be manually entered or obtained by label scanning (such as through RFID or barcode identification). This embodiment uses manual input.

[0054] Color image data of bamboo products is acquired through image acquisition equipment. Further, images of bamboo products are acquired using an industrial color camera and a ring LED light source, specifically a Basler acA2440-75um industrial color camera and a CCS LDR2-50SW2 ring LED light source, including top-view and dual side-view images. In this embodiment, an industrial-grade color camera is used, equipped with a high-brightness LED light source to ensure clear, high-contrast images under different ambient lighting conditions. To comprehensively capture the three-dimensional shape of the product, a multi-angle shooting strategy is adopted. Specifically, an industrial camera is installed directly above the conveyor line to vertically capture the top view of the product, obtaining its length and width information. Simultaneously, side cameras are symmetrically arranged on both sides of the conveyor line to acquire side views of the product, thereby obtaining its thickness or height information. This multi-view imaging scheme effectively overcomes the information loss problem caused by a single viewpoint, providing a complete data foundation for subsequent three-dimensional dimension reconstruction and surface area calculation.

[0055] The initial moisture content data of bamboo products is obtained using a near-infrared online moisture meter. This initial moisture content data can be obtained by workers manually inputting data into the system during offline sampling using a portable needle-type moisture meter (e.g., the German Trotec T660); alternatively, a near-infrared (NIR) online moisture meter can be used for non-contact measurement of the bamboo products passing through (this embodiment uses the Japanese Kett PM-710 near-infrared online moisture meter).

[0056] S102: Analyze the feature data to determine the product feature parameter table, which includes the product number and the corresponding geometric dimensions, spraying area, and initial moisture content parameters.

[0057] Furthermore, it receives product numbers obtained through manual input or automatic scanning.

[0058] The image data acquired by the image acquisition device is preprocessed and edge-enhanced, and the contour features of bamboo products are extracted.

[0059] One of the preprocessing steps includes: converting the image to grayscale using the cv2.cvtColor function of the OpenCV library, performing Gaussian filtering (5×5 kernels) using the cv2.GaussianBlur function, and finally performing edge detection (threshold 50, 150) using the cv2.Canny function.

[0060] Based on the aforementioned contour features, the geometric dimensions of the bamboo product are calculated using an image pixel calibration method.

[0061] One specific calculation method is as follows: The system is calibrated in advance using a 100mm standard calibration block, and the pixel size coefficient K is measured to be 0.1mm / pixel; the size of the bounding rectangle of the outline is obtained through cv2.boundingRect, and the actual size = pixel size × K;

[0063] Pixel statistics are performed on the region within the contour feature, and the spraying area of ​​the bamboo product is calculated by combining the pre-calibrated pixel-area conversion coefficient.

[0064] Specific calculation method: Use cv2.countNonZero to count the number of pixels within the outline, and obtain the pixel area coefficient K_area = 0.08mm through calibration. 2 / pixel, actual area = number of pixels × K_area;

[0065] Receive initial moisture content data measured by the near-infrared online moisture detector;

[0066] The product number, geometric dimensions, spraying area, and initial moisture content data are associated and stored to generate the product characteristic parameter table.

[0067] The data processing unit of the production composite monitoring system analyzes and identifies feature data. This unit consists of one or more high-performance industrial computers, such as the Advantech UNO-2183G industrial computer, which serves as the data processing server. These computers possess powerful computing capabilities and stability, enabling them to adapt to the complex and harsh working environment of industrial sites. The data processing unit has built-in specialized image processing and data analysis software. In this embodiment, the industrial camera and moisture meter communicate with the IPC via Gigabit Ethernet protocol. Upon receiving image data from the industrial camera, the software runs a series of complex algorithms to analyze the 3D model, including image correction, edge detection, edge enhancement, contour extraction, and size calculation, to obtain the product's external dimensions (length, width, height, and thickness), ultimately generating the product's geometric dimensions. Pixel statistics are performed on the regions within the contour features, and Poisson surface reconstruction is performed using classes from the PCL library to generate a triangular mesh model of the product. Relevant functions are called to traverse all triangular faces and accumulate their areas. Combined with a pre-calibrated pixel-to-area conversion coefficient, the total sprayed area of ​​the fruit plate is finally calculated. Simultaneously, it also receives moisture content data from a near-infrared spectral sensor.

[0068] All these parsed parameters, such as product number, geometric dimensions (length, width, height), surface area, and initial moisture content, will be integrated into a product feature parameter table. An example product feature parameter table is shown in Table 1.

[0069] Table 1 Product Feature Parameters

[0070]

[0071] S103: Control the drying equipment to dry the bamboo products, call the drying control program of the drying equipment according to the product characteristic parameter table and the target moisture content, and monitor the temperature, humidity and real-time moisture content during the drying process as drying monitoring data.

[0072] When a bamboo product is about to enter the drying equipment, the system automatically extracts key parameters such as the initial moisture content and thickness, based on the target moisture content value entered by the technician for the product number and the product characteristic parameter table. It then calls upon the most suitable drying program for the product from a pre-established drying model database. This drying model is based on extensive experimental data and wood drying theory, describing the optimal drying temperature curve and time under different initial moisture contents, thicknesses, and target moisture contents. In this embodiment, the technician presets a target moisture content of 9-12%. Based on the initial moisture content (22%) and product thickness (12mm), the program calculates that the drying temperature should be set to 78℃. In this embodiment, a tunnel drying device is used, and the conveyor speed should be set to 0.5 meters per minute. Real-time monitoring: The PLC controls the operation of the drying equipment and reads data from the temperature and humidity sensors inside the equipment in real time (e.g., 78.5℃, 15% RH). Simultaneously, at the outlet of the drying equipment, a near-infrared moisture meter continuously monitors the real-time moisture content of the fruit trays and feeds back the data (e.g., 10.5%) to the PLC. All this data is recorded as drying monitoring data.

[0073] In a specific embodiment, the drying equipment is controlled by a Siemens S7-1200 PLC, which reads real-time data (e.g., 78.5°C, 15% RH) from the Heraeus M222 PT100 temperature sensor and Rotronic HC2-IM humidity sensor inside the drying equipment. Simultaneously, at the outlet of the drying equipment, a Kett PM-710 near-infrared moisture meter continuously monitors the real-time moisture content of the fruit trays and feeds back the data (e.g., 10.5%) to the PLC. All this data is recorded as drying monitoring data.

[0074] S104: Control the balancing equipment to perform balancing cooling on the dried bamboo products. Based on the drying monitoring data and the target temperature, call the balancing cooling program to monitor the temperature, humidity, and real-time moisture content to obtain balancing cooling monitoring data.

[0075] Balanced cooling is a crucial step connecting the two key processes of drying and painting. Its main purposes are twofold: first, to lower the temperature of the bamboo product after high-temperature drying to a suitable room temperature range for painting (typically 20-35℃), preventing excessively high product temperature from causing the solvent in the paint to evaporate too quickly, affecting the leveling and adhesion of the paint film; second, through the cooling process, to further release and balance the residual stress generated inside the product during drying, improving the product's dimensional stability and laying the foundation for achieving high-quality painting results.

[0076] The parameter settings for balanced cooling are also data-driven. In this embodiment, the balanced cooling equipment is a tunnel-type device. The product enters from one end of the balanced cooling equipment via a conveyor and exits from the other end to proceed to the next process. When the dried bamboo product enters the balanced cooling station, the system automatically calls the corresponding balanced cooling program based on the final product temperature recorded in the drying monitoring data and the target temperature set in the balanced cooling monitoring data (28℃ in this embodiment). For example, if the product temperature is high when it exits the oven (e.g., 70℃), the first half of the system will call a strong air cooling program to cool the product down with a faster airflow; if the product temperature is close to room temperature, the second half will call a weak air or natural cooling program to avoid condensation or new stress on the product surface due to excessively rapid cooling. The target cooling temperature and time are preset according to the characteristics of the paint used and the process requirements to ensure that the product enters the spray booth in the most ideal condition.

[0077] Monitoring: At the outlet of the balancing cooling equipment, a temperature sensor and a humidity sensor (such as the Rotronic HC2-IM temperature and humidity sensor) are installed to monitor the surface temperature and humidity of the product as it leaves the cooling zone in real time. This data is recorded as balancing cooling monitoring data and fed back to the production composite monitoring system.

[0078] S105: Control the painting production equipment to paint the bamboo products after balanced cooling, call the painting program according to the product characteristic parameter table and balanced cooling monitoring data, monitor the painting data in real time to obtain the first painting data, obtain the dynamic evaluation result based on the first painting data, and execute the corresponding production process according to the dynamic evaluation result.

[0079] The production monitoring system, based on the product characteristic parameter table (including geometric dimensions, spraying area, etc.) and the product's state after balanced cooling (temperature, humidity), retrieves a basic painting program matching the product type and size from a pre-set painting process database. This basic program includes the initial movement speed of the spray gun, spraying pressure, paint flow rate, and spraying path planning. If the product temperature is slightly high, the system may appropriately reduce the paint flow rate or increase the spray gun movement speed to prevent defects such as orange peel on the paint film. Once all parameters are ready, the PLC sends the final painting program instructions to the painting robot, which then waits for the product to enter the work area.

[0080] When bamboo products are transported to the painting station, a multi-axis painting robot begins automated painting operations based on received program instructions. The painting equipment typically consists of a multi-axis robotic arm and precision spray guns, capable of precise spraying along a preset three-dimensional path. The robotic arm carries the precision spray gun, moving at a constant speed across all surfaces of the product along the pre-defined three-dimensional path. The spray gun's trajectory ensures even paint coverage, avoiding excessively thick paint films or missed areas caused by overlapping spraying.

[0081] After a single spraying operation, the bamboo product is subjected to an online thickness gauge, such as laser triangulation, spectral confocal measurement, or eddy current measurement. In this embodiment, triangulation is used. The online thickness gauge is installed after the spray gun and continuously scans the freshly sprayed surface as the product moves, generating a two-dimensional or three-dimensional distribution map of the paint film thickness (5μm) in real time.

[0082] S106: Control the curing equipment to cure bamboo products that have entered the curing process after spraying paint, and unload the materials.

[0083] Curing is a crucial step in the paint coating process. Its purpose is to transform the liquid paint film sprayed onto the bamboo product surface into a solid film with good mechanical and protective properties through physical or chemical methods. The effectiveness of the curing process directly determines key indicators such as the final hardness, abrasion resistance, adhesion, and weather resistance of the coating. There are two main curing methods: thermal curing, and this embodiment uses thermal curing. The PLC initiates a predetermined program for the curing and drying equipment, such as 80°C in this embodiment, and maintains it for 30 minutes to ensure that the resin in the paint film can fully cross-link and cure. After curing, a near-infrared (NIR) online moisture meter measures the real-time moisture content. Based on the preset final moisture content control target, it is determined whether to activate the secondary drying equipment, and then the material is unloaded for the next production process, such as packaging.

[0084] Furthermore, the first paint spraying data includes the paint film thickness; the dynamic evaluation result obtained based on the first paint spraying data specifically involves: comparing the paint film thickness distribution data with the preset thickness value and identifying: areas with acceptable thickness, areas with unacceptable thickness, and areas with excessive thickness, and calculating the corresponding thickness compliance ratio a, thickness non-compliance ratio b, and thickness excess ratio c respectively.

[0085] A target coating thickness (e.g., 50 μm) and an allowable error range (e.g., ±5 μm) are preset. The actual thickness data measured by the online thickness gauge is compared with this standard in real time. Based on the comparison results, the system divides the product surface into "thickness compliant area", "thickness non-compliant area" (below 45 μm) and "thickness exceeding standard area" (above 55 μm).

[0086] Furthermore, the calculation methods for the thickness compliance ratio (a), thickness non-compliance ratio (b), and thickness excess ratio (c) include: calling the compliance preset value T0 and the preset tolerance ΔT to obtain the preset thickness value range [T0-ΔT, T0+ΔT]; traversing all thickness data points, if a data point is within the preset thickness value range, then the area where the point is located is the thickness compliance area; if the data point < T0-ΔT, then the area where the point is located is the thickness non-compliance area; if the data point > T0+ΔT, then the area where the point is located is the thickness excess area.

[0087] Let the total number of measurement points be N; the number of points that meet the thickness standard is Na, then the thickness compliance ratio is a = Na / N; the number of points that do not meet the thickness standard is Nb, then the thickness non-compliance ratio is b = Nb / N; the number of points that exceed the thickness standard is Nc, then the thickness excess ratio is c = Nc / N.

[0088] Assuming N = 1000 points are measured in this study, the calculation results are as follows:

[0089] a=880 / 1000=0.88, b=100 / 1000=0.10, c=20 / 1000=0.02.

[0090] The dynamic evaluation results are (a = 0.88, b = 0.10, c = 0.02).

[0091] Furthermore, such as Figure 2 As shown, the corresponding production process is executed based on the dynamic evaluation results. The method includes: calling the preset value A_set for the compliance ratio.

[0092] P1. When the thickness compliance ratio a ≥ A_set, execute the conveying command to enter the curing equipment;

[0093] P2. When the thickness compliance ratio a < A_set and b ≥ c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard, scan again with an online thickness gauge to detect the paint film thickness, and recalculate the corresponding thickness compliance ratio a2, thickness non-compliance ratio b2, and thickness exceeding the standard ratio c2. Repeat steps P1 and P2.

[0094] P3. When the thickness compliance ratio a < A_set and b < c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard and mark the bamboo product as a defective product, and execute the conveying instruction to enter the curing equipment.

[0095] Specifically, based on the paint film thickness distribution data provided by the online thickness gauge, the system will conduct dynamic evaluation. The core of the evaluation is to calculate three key proportional indicators and make corresponding production decisions according to preset rules.

[0096] The system will call a preset A_set (e.g., A_set is 90%). A_set can be adjusted; for example, when the product's quality requirements are high, A_set will be higher; similarly, when the product's coating quality requirements are low, the A_set value will be lower. The decision logic is as follows:

[0097] P1. Pass: If the thickness compliance ratio a is greater than or equal to A_set, the paint quality of the product is considered to be qualified, and the system executes the conveying instruction to send the product to the next curing process.

[0098] P2. Compensation Spraying: If the thickness compliance ratio 'a' is less than A_set, and the area of ​​the non-compliant region is greater than or equal to the area of ​​the over-compliant region (i.e., b ≥ c), the system will determine that the main defect is "thinning". In this case, the system will control the spray gun to perform a compensation spraying procedure on the area where the thickness is non-compliant. After compensation spraying, the system will scan and detect the same area again using an online thickness gauge, recalculate a2, b2, and c2, and then repeat the judgment steps of P1 and P2.

[0099] In this embodiment, the compensation spraying procedure is executed as follows: a spraying robot carrying a small-diameter touch-up paint spray gun (such as ANESTIWATAW-71, 1.0mm diameter) performs local spot spraying on areas where the thickness does not meet the standard. The spot spraying parameters are: spray gun moving speed: 200mm / s; paint output: 30mL / min; spraying distance: 150mm. After compensation spraying, the same area is scanned again by a laser thickness gauge. If a2≥95%, it passes; otherwise, the compensation spraying is repeated. The system can also limit the number of compensation sprays, such as a maximum of 3 repetitions. If it still does not meet the standard, it is marked as a defective product and enters the next procedure.

[0100] P3. Marking Defects: If the thickness compliance ratio a is less than the preset threshold and the area of the non-compliant region is smaller than the area of the over-standard region (i.e., b < c), the system will determine that the main defect is "thick spraying" or both "thin spraying" and "thick spraying" exist, but the "thick spraying" problem is more prominent. At this time, the system will mark the defective product (for example, by using an inkjet marking machine to mark on the back), and at the same time, in order to prevent the unsprayed area from affecting the product performance, the compensation spraying process will still be performed on the non-compliant region a, and then it will be conveyed to the curing process.

[0101] This intelligent evaluation and decision-making mechanism ensures that only high-quality products can enter the subsequent processes, and at the same time provides a clear identification for the subsequent processing of defective products.

[0102] For the product obtained in Example 1, the paint spraying consistency rate reaches more than 95%.

[0103] Example 2

[0104] As Figure 3 shown, a production system for the continuous drying and painting production method of bamboo products in Example 1, the system includes:

[0105] S201: A data acquisition module, used to obtain the characteristic data of bamboo products;

[0106] Furthermore, it includes industrial color cameras and near-infrared online moisture detectors, used to obtain the characteristic data of bamboo products;

[0107] In this embodiment, the industrial color cameras: 3 Hikvision MV-CA013-20GM (2 million pixels, GigE, global shutter), installed vertically and at ±30° on both sides respectively, with a 12mm lens and a field of view of 400mm × 300mm. Lighting: OPT-RI12060 ring-shaped LED, inner diameter of the light-emitting surface is 120mm, 24V / 30W, illuminance can be adjusted to 8500lx, stroboscopic is synchronized with the camera exposure, and the exposure time is 0.8ms to ensure no smear at a line speed of 1m / s.

[0108] One Japanese Kett PM-710 online moisture meter is adopted, installed behind the feeding station, and its sensor head is perpendicular to the conveyor belt and aligned with the bamboo products.

[0109] Other sensors: PT100 temperature sensors and capacitive humidity sensors are integrated inside the drying and curing equipment. Specifically, Heraeus M222 PT100 temperature sensors and Rotronic HC2-IM capacitive humidity sensors are integrated inside the drying and curing equipment.

[0110] S202: Data processing and control module, which is communicatively connected to the data acquisition module, receives the feature data, parses it, and outputs a product feature parameter table; obtains dynamic evaluation results based on the first paint spraying data, and generates production process control instructions based on the dynamic evaluation results;

[0111] This module is the "brain" of the system, employing an industrial-grade computer; this embodiment uses two computers. One is the host computer (industrial IPC): an Advantech UNO-2183G. It runs control software written in Python 3.8 and C++, and has the OpenCV 4.5.5 computer vision library and the PCL (Point Cloud Library) 1.11.1 point cloud library installed. This industrial PC is equipped with an Intel Core i7 processor, 16GB of RAM, and a 256GB SSD to ensure sufficient computing power.

[0112] The other unit is the lower-level machine (Programmable Logic Controller, PLC): a German Siemens SIMATIC S7-1200 (CPU 1215C) is used. It is responsible for receiving high-level instructions from the upper-level machine (such as "start drying" and "target temperature") and converting them into specific I / O control signals (such as activating the heating element contactor and adjusting the inverter frequency to control the conveyor belt speed). Simultaneously, it collects real-time data from all sensors. Communication between the PLC and the IPC is via Ethernet / IP protocol.

[0113] The product feature parameter table and the process of obtaining dynamic evaluation results are shown in Example 1.

[0114] S203: Execution module, which is communicatively connected to the data processing and control module. The execution module includes, but is not limited to: drying equipment, balancing equipment, spray painting production equipment, and curing and drying equipment, and is used to perform drying, balancing, spray painting, curing and / or secondary drying operations.

[0115] S204: Online monitoring module, including an online monitoring device installed on the execution module, used to monitor production data in real time and send it to the data processing and control module;

[0116] Furthermore, the data processing and control module also includes an image processing unit, which preprocesses and enhances the edges of the images captured by the industrial color camera, and extracts the contour features of the bamboo products; based on the contour features, the geometric dimensions and coating area of ​​the bamboo products are calculated using the image pixel calibration method.

[0117] Example 3

[0118] A computer device is provided, which can be a server, an industrial computer, or an embedded controller. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores bamboo product characteristic parameter tables, real-time monitoring data, process standard parameters, and historical production data. The network interface is used for communication with external data acquisition modules, execution modules, and online monitoring modules via a network connection. When the computer program is executed by the processor, it implements a continuous drying and painting production method for bamboo products.

[0119] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0120] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0121] Obtain characteristic data for bamboo product production;

[0122] The feature data is analyzed and identified to determine the product feature parameter table, which includes the product number and the corresponding geometric dimensions, spraying area, and initial moisture content parameters.

[0123] The drying equipment is controlled to dry the bamboo products. The drying control program of the drying equipment is called according to the product characteristic parameter table and the target moisture content. The temperature, humidity and real-time moisture content during the drying process are monitored in real time as drying monitoring data.

[0124] The control balancing equipment performs balancing cooling on the dried bamboo products. Based on the drying monitoring data and the target temperature, the balancing cooling program is invoked to monitor the temperature, humidity, and real-time moisture content to obtain balancing cooling monitoring data.

[0125] The system controls the painting production equipment to paint the bamboo products after balanced cooling. The system calls the painting program based on the product characteristic parameter table and balanced cooling monitoring data, monitors the painting data in real time to obtain the first painting data, obtains the dynamic evaluation result based on the first painting data, and executes the corresponding production process based on the dynamic evaluation result.

[0126] The curing equipment is controlled to cure bamboo products that have been painted and are then cured. Curing process data is monitored to obtain curing monitoring data.

[0127] Control the second drying equipment to perform secondary drying on the cured bamboo products and then unload them.

[0128] The above description is a detailed description of the preferred embodiments of the present invention. However, the embodiments are not intended to limit the scope of the patent application of the present invention. All equivalent changes or modifications made under the technical spirit of the present invention should fall within the patent scope covered by the present invention.

Claims

1. A method for continuous drying and painting of bamboo products, characterized in that, The method is applied to a composite monitoring system for bamboo product production, and the method includes: Obtain characteristic data for bamboo product production; The feature data is parsed to determine the product feature parameter table, which includes the product number and the corresponding geometric dimensions, spraying area, and initial moisture content parameters. The drying equipment is controlled to dry the bamboo products. The drying control program of the drying equipment is called according to the product characteristic parameter table and the target moisture content. The temperature, humidity and real-time moisture content during the drying process are monitored in real time as drying monitoring data. The control balancing equipment performs balancing cooling on the dried bamboo products. Based on the drying monitoring data and the target temperature, the balancing cooling program is invoked to monitor the temperature, humidity, and real-time moisture content to obtain balancing cooling monitoring data. The system controls the painting production equipment to paint the bamboo products after balanced cooling. The system calls the painting program based on the product characteristic parameter table and balanced cooling monitoring data, monitors the painting data in real time to obtain the first painting data, obtains the dynamic evaluation result based on the first painting data, and executes the corresponding production process based on the dynamic evaluation result. Control the curing and drying equipment to cure and further dry the bamboo products that have entered the curing process after spraying paint, and then unload the materials.

2. The method for continuous drying and painting of bamboo products according to claim 1, characterized in that, The first paint spraying data includes the paint film thickness; the dynamic evaluation result obtained based on the first paint spraying data specifically involves: comparing the paint film thickness distribution data with the preset thickness value and identifying: areas with acceptable thickness, areas with unacceptable thickness, and areas with excessive thickness, and calculating the corresponding thickness compliance ratio a, thickness non-compliance ratio b, and thickness excess ratio c respectively.

3. The method for continuous drying and painting of bamboo products according to claim 2, characterized in that, The calculation methods for thickness compliance rate (a), thickness non-compliance rate (b), and thickness exceeding standard (c) include: The preset thickness value range [T0-ΔT, T0+ΔT] is obtained by calling the preset value T0 and the preset tolerance ΔT. All thickness data points are traversed. If a data point is within the preset thickness value range, the area where the point is located is the thickness-compliant area; if the data point is < T0-ΔT, the area where the point is located is the thickness-non-compliant area; if the data point is > T0+ΔT, the area where the point is located is the thickness-exceeding area. Let the total number of measurement points be N; the number of points that meet the thickness standard is Na, then the thickness compliance ratio is a = Na / N; the number of points that do not meet the thickness standard is Nb, then the thickness non-compliance ratio is b = Nb / N; the number of points that exceed the thickness standard is Nc, then the thickness excess ratio is c = Nc / N.

4. The method for continuous drying and painting of bamboo products according to claim 2, characterized in that, Based on the dynamic evaluation results, corresponding production processes are executed. Methods include: calling the preset value A_set for the compliance ratio. P1. When the thickness compliance ratio a ≥ A_set, execute the conveying command to enter the curing equipment; P2. When the thickness compliance ratio a < A_set and b ≥ c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard, scan again with an online thickness gauge to detect the paint film thickness, and recalculate the corresponding thickness compliance ratio a2, thickness non-compliance ratio b2, and thickness exceeding the standard ratio c2. Repeat steps P1 and P2. P3. When the thickness compliance ratio a < A_set and b < c, then perform a compensation spraying procedure on the area where the thickness does not meet the standard and mark the bamboo product as a defective product, and execute the conveying instruction to enter the curing equipment.

5. The method for continuous drying and painting of bamboo products according to claim 1, characterized in that, The acquisition of characteristic data for bamboo product production includes: Product number obtained by entering or scanning; Acquire color image data of bamboo products using image acquisition equipment; Initial moisture content data of bamboo products were obtained using a near-infrared online moisture meter.

6. A continuous drying and painting production method for bamboo products according to claim 1 or 4, characterized in that, The method for parsing the feature data to determine the product feature parameter table includes: Receive product numbers obtained through manual input or automatic scanning identification; The image data acquired by the image acquisition device is preprocessed and edge-enhanced, and the contour features of bamboo products are extracted. Based on the aforementioned contour features, the geometric dimensions of the bamboo product are calculated using an image pixel calibration method. Pixel statistics are performed on the region within the contour feature, and the spraying area of ​​the bamboo product is calculated by combining the pre-calibrated pixel-area conversion coefficient. Receive initial moisture content data measured by the near-infrared online moisture detector; The product number, geometric dimensions, spraying area, and initial moisture content data are associated and stored to generate the product characteristic parameter table.

7. A production system utilizing the continuous drying and painting method for bamboo products as described in claim 1, characterized in that, The system includes: The data acquisition module is used to obtain characteristic data of bamboo products; The data processing and control module is communicatively connected to the data acquisition module, receives the feature data, parses it, and outputs a product feature parameter table; obtains dynamic evaluation results based on the first painting data, and generates production process control instructions based on the dynamic evaluation results; An execution module is communicatively connected to the data processing and control module. The execution module includes, but is not limited to, drying equipment, balancing equipment, spray painting production equipment, and curing and drying equipment, and is used to perform drying, balancing, spray painting, curing and / or secondary drying operations. The online monitoring module includes an online monitoring device installed on the execution module, used to monitor production data in real time and send it to the data processing and control module.

8. The production system for a continuous drying and painting method for bamboo products according to claim 7, characterized in that, The data processing and control module also includes an image processing unit, which preprocesses and enhances the edges of the images captured by the industrial color camera and extracts the contour features of the bamboo products. Based on the aforementioned contour features, the geometric dimensions and spraying area of ​​the bamboo product are calculated using an image pixel calibration method.

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