T-shaped cold-bending metal decorative profile and composite manufacturing process

Abstract

The invention discloses a T-shaped cold-bending metal decoration profile and a composite manufacturing process, and relates to the technical field of metal material recycling and regeneration machining.The process comprises the steps that spectral data collection is conducted on the surface of a waste profile through multi-spectral scanning equipment, meanwhile, the thickness of a coating is accurately measured by combining a laser thickness gauge, and the thickness of the coating is measured; generating a comprehensive analysis report containing coating component characteristic peak values and thickness data; according to the T-shaped cold-bending metal decorative profile and the composite manufacturing process, efficient and intelligent closed-loop recycling of waste profiles is achieved, the purity and uniformity of recycled materials are improved, and a foundation is laid for large-scale recycling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of metal material recycling and regeneration processing, and particularly relates to a T-shaped cold-bending metal decorative profile and a composite manufacturing process. BACKGROUND

[0002] As a core material in modern industry and construction fields, the production and consumption scale of metal profiles continues to expand, and resource recycling has become a decisive factor for the sustainable development of the industry. With the intensification of global resource constraints and the improvement of environmental protection requirements, the recycling of profiles not only relates to the control of raw material costs, but also directly affects the environmental responsibility and economic benefits of the entire industry chain.

[0003] Current profile recycling mainly relies on traditional sorting and rough processing methods, which are inefficient in dealing with complex alloy components and cannot effectively remove surface treatment layers and impurities, resulting in unstable quality of recycled materials. At the same time, the existing recycling system mostly adopts an open process, lacking organic connection with the production end, resulting in a large amount of available resources being lost to low-value application fields. The problem of material purity control during the recycling process of waste profiles directly restricts the feasibility of re-melting. Since profiles will attach various coatings, oxides and pollutants during use, the presence of these impurities makes simple physical treatment unable to meet the purity standards required for re-melting. Insufficient material purity further leads to significant quality differences between production scrap and waste recycling materials, making it difficult to achieve uniform processing standards and recycling processes. When production scrap and waste materials cannot be recycled using the same path, production enterprises cannot establish a unified and efficient internal recycling system, and different sources of waste materials need to be treated and stored separately, significantly increasing the complexity of operation and cost burden. SUMMARY

[0004] The purpose of the present application is to provide a T-shaped cold-bending metal decorative profile and a composite manufacturing process, by developing a unified treatment technology suitable for waste materials of different sources, so that both waste profiles and production scrap can meet the quality requirements for direct recycling and reuse, thereby building a complete closed-loop process from waste material generation to re-entry into production.

[0005] To achieve the above purpose, the present application provides the following technical solution: a T-shaped cold-bending metal decorative profile, comprising: a T-shaped body for constituting the main structure and providing support; a first connecting flange fixed to the first side of the T-shaped body for providing lateral stability and a decorative surface; a second connecting flange fixed to the second side of the T-shaped body for providing lateral stability and a decorative surface; a node connecting plate detachably assembled at the end region of the T-shaped body for simplifying node connection and transferring load; a fastening bolt penetrating through the node connecting plate and the adjacent profile for applying fastening force; The node connecting plate includes a preformed array of holes for enabling quick alignment and field bolting.

[0006] A T-shaped cold bending metal decorative profile composite manufacturing process, using the profile, the process comprises: The surface of the waste profile is scanned by a multispectral scanning device to collect spectral data, and a laser thickness gauge is used to accurately measure the coating thickness to generate a comprehensive analysis report containing coating composition characteristic peaks and thickness data; According to the quality evaluation data report, a material classification database is constructed, and the unified quality recycled profiles are classified and marked according to the metal purity grade and alloy composition ratio, and a corresponding smelting process parameter configuration table is generated, including smelting temperature, time and additive ratio, and a quality control index data set is generated; According to the composition requirements in the smelting process parameter configuration table, different grades of unified quality recycled profiles are mixed in a preset ratio by an automatic batching system to form a standardized recycled raw material batch; an online quality monitoring system is applied to perform continuous spectral detection and composition stability verification on the batch, and a quality qualified mark and traceable batch code are generated to complete the closed-loop recycling process.

[0007] Preferably, the quality evaluation data report generated according to the comprehensive analysis report includes applying a multispectral composition identification algorithm to process the coating composition characteristic peaks and thickness data in the comprehensive analysis report, if the coating thickness exceeds a preset threshold, the waste profile needs to be treated for coating separation; if the thickness is below the threshold, it directly enters the subsequent element composition detection link, and a coating composition characteristic data set is generated.

[0008] Preferably, the quality evaluation data report generated according to the comprehensive analysis report further includes calculating and generating corresponding solvent formula parameters including solvent type and concentration ratio according to the coating composition characteristic data set through a chemical solvent proportioning system, and an automatic chemical treatment device performs coating dissolution operation on the surface of the waste profile according to the formula parameters to obtain a preliminary purified profile, and records the solvent consumption and processing time data.

[0009] Preferably, the quality evaluation data report generated according to the comprehensive analysis report further includes applying an X-ray fluorescence spectrometer to detect the element composition of the preliminary purified profile to obtain the content percentage data of each metal element and the pollutant element distribution information, if the purity of the main metal element meets the preset smelting standard, it is marked as qualified recycled profile; if it does not meet the standard, a pollutant element distribution data set is generated and enters the deep purification process.

[0010] Preferably, the quality evaluation data report generated according to the comprehensive analysis report further comprises dynamically adjusting the vibration frequency and magnetic field strength parameters of the physical separation equipment according to the pollutant element distribution data set, removing non-metallic impurities and foreign metal particles through a combined process of magnetic separation and gravity separation, obtaining a deeply purified profile, and generating an updated element content data set, by using an adaptive separation optimization algorithm.

[0011] Preferably, the quality evaluation data report generated according to the comprehensive analysis report further comprises performing secondary element composition detection on the deeply purified profile, obtaining updated metal element content percentage data, evaluating the composition uniformity of the profile through a composition stability analysis algorithm, and if the uniformity meets the preset fluctuation threshold standard, marking it as a unified quality recycling profile, and generating a quality evaluation data report.

[0012] Preferably, the multi-spectral scanning device performs synchronous scanning in combination with ultraviolet, visible light and near-infrared spectral channels when performing spectral data collection, and realizes identification and separation of metal oxides, organic residues and heavy metal ions in the coating by comparing with a reference spectrum library.

[0013] Preferably, the material grading database and the melting process parameter configuration table are linked and constructed through a data modeling engine, the modeling engine optimizes material grading rules by using a machine learning method based on historical melting data, target alloy ratio and quality stability standards, and generates melting temperature, holding time, types and doses of de-impurity additives process parameters matched with each recycling grade, so that recycled profiles of different sources can achieve high consistency in regenerative quality under a unified control framework.

[0014] Preferably, the online quality monitoring system is equipped with a tunable laser light source and a multi-channel photoelectric receiving array when performing continuous spectral detection, calculates the concentration change trend of each main metal element in the raw material batch in combination with a real-time data fitting algorithm, and automatically triggers a discharge mechanism and a feedback correction program when detecting abnormal fluctuations.

[0015] From the above technical solutions, the present application has the following beneficial effects: The T-shaped cold-bent metal decorative profile and composite manufacturing process analyzes the profile surface through multi-spectrum scanning and laser thickness measurement, judges whether the coating needs to be separated by combining with the composition recognition algorithm. For the profile that needs to be separated, the application automatically generates a solvent formula and performs coating dissolution, and then performs X-ray element detection. If the purity does not meet the standard, the adaptive separation optimization algorithm is used for deep purification, and the composition uniformity is evaluated again. The application also establishes a material grading database, generates smelting process parameters, and mixes different grade profiles through an automatic batching system to form standardized recycled raw materials. Finally, online quality monitoring is performed, and traceable batch codes are generated to realize efficient and intelligent closed-loop recycling of waste profiles, improve the purity and uniformity of recycled materials, and lay the foundation for large-scale reuse. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is a schematic diagram of the overall structure of the application. Figure 2 It is a process flow diagram of the application.

[0017] In the figure: 1, T-shaped body; 2, first connecting flange; 3, second connecting flange; 4, node connecting plate; 4a, multi-hole array; 5, fastening bolt. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the application.

[0019] As Figure 1 shown, the application provides a technical solution: a T-shaped cold-bent metal decorative profile, comprising: a T-shaped body 1 for forming the main structure and providing support; a first connecting flange 2 fixed to the first side of the T-shaped body 1 for providing lateral stability and decorative surface; a second connecting flange 3 fixed to the second side of the T-shaped body 1 for providing lateral stability and decorative surface; a node connecting plate 4 detachably assembled at the end region of the T-shaped body 1 for simplifying node connection and transferring load; a fastening bolt 5 penetrating the node connecting plate 4 and the adjacent profile for applying fastening force; wherein the node connecting plate 4 comprises a prefabricated multi-hole array 4a for realizing quick alignment and on-site bolt installation.

[0020] The T-shaped cold-formed metal decorative profile is designed to balance load-bearing capacity, installation convenience, and decorative function. The T-shaped body 1 is formed by cold bending of metal materials such as galvanized steel, stainless steel, or aluminum alloy, resulting in a main structure with a cross-section in the shape of an inverted "T". The T-shaped body 1 has high longitudinal bending stiffness, with the vertical section providing vertical support and the horizontal section expanding the platform with connecting flanges 2 and 3 to increase the force-bearing area.

[0021] The first connecting flange 2 and the second connecting flange 3 are fixed on both sides of the T-shaped body 1 by welding, screwing, or buckling, etc. This arrangement makes the overall profile more stable under lateral load and provides a smooth and continuous decorative surface, facilitating the attachment or covering of stone, aluminum plate, glass, or other decorative materials. In addition, the double-sided flanges also help to form regular partition lines in curtain wall or ceiling structures, improving visual effects and installation accuracy.

[0022] The node connecting plate 4, as a structural connector, is detachably installed at the end of the T-shaped body 1, with specific installation methods including screw hole alignment installation, slot sliding fixation, etc. The node connecting plate 4 is usually a flat metal component with an installation interface matching the geometric structure of the end of the T-shaped body 1, capable of transmitting axial and shear loads. The node connecting plate 4 is provided with a plurality of pre-prepared multi-hole arrays 4a, arranged in a consistent manner (such as a quincunx or rectangular grid) with the hole standard of the fastening bolt 5, ensuring quick alignment of the connecting holes on site without the need for additional positioning tools or re-drilling.

[0023] During installation, the node connecting plate 4 is fitted or attached to the end of the T-shaped body 1, and then the fastening bolt 5 is inserted through the pre-aligned holes to achieve mechanical locking with the adjacent profile (which can be of the same structure or other connecting components). The fastening bolt 5 generates axial clamping force when tightened, achieving firm connection at the node and effectively transmitting longitudinal load and shear force, preventing structural performance degradation due to loose connections. This design not only improves connection strength but also simplifies on-site construction processes, enhancing the reliability and modularity of the structural system.

[0024] The T-shaped cold-formed metal decorative profile has a compact design and good mechanical properties, effectively improving the installation convenience and connection stability of building decorative components. The use of pre-prepared multi-hole arrays 4a allows for quick and accurate positioning, avoiding on-site drilling, improving assembly efficiency, and reducing construction errors; the high-strength connection provided by the fastening bolt 5 improves overall load-bearing performance; and the detachable node connecting plate 4 improves the flexibility of the structure, facilitating later replacement or maintenance. The double-flange structure not only provides stability but also serves as an aesthetic decoration, suitable for various curtain wall, ceiling, partition, and other building construction scenarios, with wide applicability and engineering value.

[0025] In the above embodiments, the multi-hole array 4a of the node connecting plate 4 can be designed as round holes, long holes or special-shaped holes according to the construction requirements, and the hole spacing can also be customized according to the actual size of the fittings; the connection mode of the T-shaped body 1 and the connecting flanges 2 and 3 can also be riveting, bolt connection or buckle structure in addition to welding, so as to adapt to different structural strength and disassembly requirements; the node connecting plate 4 can also be made of stainless steel, aluminum alloy or high-strength engineering plastic and other materials to balance the strength, corrosion resistance and cost; the fastening bolt 5 can be an internal hexagonal bolt, an external hexagonal bolt or a self-tapping screw, and the connection mode can also be adjusted to a lock type or a quick locking device according to the load requirements, so as to improve the construction flexibility and connection firmness.

[0026] As Figure 2 shown, a T-shaped cold-bent metal decorative profile composite manufacturing process is also provided, which adopts the profile of claim 1, and the process comprises: The surface of the waste profile is scanned by a multi-spectral scanning device to collect spectral data, and a laser thickness gauge is used to accurately measure the coating thickness to generate a comprehensive analysis report containing coating composition characteristic peak values and thickness data; A quality evaluation data report is generated according to the comprehensive analysis report, a material grading database is constructed according to the quality evaluation data report, the unified quality recycled profiles are classified and marked according to the metal purity grade and alloy composition ratio, a corresponding smelting process parameter configuration table is generated, including smelting temperature, time and additive ratio, and a quality control index data set is generated; According to the composition requirements in the smelting process parameter configuration table, different grades of unified quality recycled profiles are mixed in a predetermined ratio by an automatic batching system to form a standardized recycled raw material batch; an online quality monitoring system is applied to perform continuous spectral detection and composition stability verification on the batch to generate a quality qualified identification and a traceable batch code, and the closed-loop recycling process is completed.

[0027] The process flow focuses on the recycling and remanufacturing links of the T-shaped cold-bent metal decorative profile, and uses intelligent means throughout the chain to realize automatic identification, data evaluation, graded mixing and quality control of the material from recycling to re-production. The core principle is to quickly and accurately analyze the coating residue and alloy composition in the recycled profile through high-precision multi-spectral detection and laser thickness measurement technology, and to develop a differentiated smelting and quality control scheme accordingly, so as to realize the stabilization of raw material performance and the consistency of remanufactured products.

[0028] Firstly, in the material pretreatment stage, a multi-spectral scanning device (such as a high-resolution detector integrating ultraviolet-visible-near infrared bands) is used to scan the surface of the waste metal profile point by point, extract the reflection and absorption characteristics of the coating and metal substrate at each band, and perform spectral identification to identify the composition characteristic peak of common coating materials such as epoxy coating, fluorocarbon coating, and powder spraying layer. At the same time, a laser thickness gauge (such as based on laser triangulation or time-of-flight principle) is used to measure the coating thickness of the profile surface in real time, and multi-point thickness distribution data is obtained. The collected spectral and thickness data are processed by an algorithm processing module (such as PCA principal component analysis, KNN classifier) to generate a comprehensive analysis report.

[0029] Subsequently, the system conducts quality assessment on the report, evaluates the purity of the metal matrix, the residual situation of the coating, and the types of potential pollutants. Based on these evaluation results, a quality assessment data report is generated, and the profile is labeled according to the alloy system (such as aluminum-silicon system, aluminum-zinc system), purity level (such as 99%, 95%), and surface residual type. The classification data enters the hierarchical database being constructed, forming a structured information set based on the properties of metal materials. On this basis, the system automatically matches the melting process parameter template, generates a melting parameter configuration table, including the recommended melting temperature (such as 660°C for aluminum alloy), duration (such as 2 hours for removing inclusions), and the addition amount of different metal impurities or adjusting agents (such as silicon, manganese, etc.), and defines a quality control index data set (such as Fe content <0.3%, impurity content <1%).

[0030] In the batching stage, the automatic batching system retrieves the ratio requirements of each classified material in the configuration table, and extracts the corresponding metal profile from different storage bins according to the set ratio. Each level of profile is first crushed and then enters the mixing hopper. The system confirms whether the mixing ratio meets the set target based on weight sensors, visual recognition, or barcode scanning. The standardized recycled raw material batch formed subsequently enters the melting process and is continuously monitored for composition by an online quality monitoring system (such as an online laser spectrum analyzer), which determines the composition fluctuation by comparing it with the target value in the configuration table in real time.

[0031] If the detection data meets the target interval, the system marks the batch as qualified and assigns a corresponding traceability code, which is written into the batch label through a two-dimensional code or RFID. All process data is uploaded to the quality management platform simultaneously to establish a complete batch file, achieving closed-loop management and quality traceability from recycling, classification, mixing, melting, to finished product.

[0032] The composite manufacturing process realizes efficient recycling and precise reuse of waste profiles, effectively improving resource recycling rate and reducing dependence on raw materials. Through multi-spectral scanning and laser thickness measurement technology, high-throughput and non-destructive detection of recycled materials can be realized, greatly improving the accuracy of raw material screening. The data-driven grading and batching strategy introduced in the process significantly improves the consistency and performance stability of recycled metals, reducing the risk of quality fluctuations in subsequent products. The online monitoring and batch tracking mechanism throughout the process ensures the traceability and quality transparency of the products, especially suitable for the building decoration industry with strict quality control requirements. Systematic process design further improves production efficiency, supporting large-scale continuous operation, which is conducive to achieving green manufacturing goals and closed-loop management of the industrial chain.

[0033] According to the quality evaluation data report generated by the comprehensive analysis report, the coating composition characteristic peaks and thickness data in the comprehensive analysis report are processed by a multi-spectral composition recognition algorithm. If the coating thickness exceeds the preset threshold standard, it is determined that the waste profile needs to be separated for coating; if the thickness is below the threshold, it directly enters the subsequent element composition detection link and generates a coating composition characteristic data set.

[0034] In this process, the comprehensive analysis report serves as the basic input data, containing a large amount of raw data collected through multi-spectral scanning and laser thickness measurement, including the composition characteristic peaks of the profile surface coating (i.e. the energy absorption or reflection positions of typical elements in the spectrum) and the corresponding thickness information. The system uses a multi-spectral composition recognition algorithm to analyze and process the above information to intelligently determine whether the coating affects the subsequent metallurgical process.

[0035] The multi-spectral composition recognition algorithm is based on a database model of typical metal coatings (such as polyester, fluorocarbon, and acrylic acid), which identifies the spectral response characteristics of different materials through algorithm modules (such as support vector machine SVM or random forest RF). The algorithm first normalizes and removes noise from the spectral data, then identifies the waveband characteristic peak matching the target material in the feature extraction stage, and finally uses a spectral-thickness coupling model to comprehensively judge the physical properties and material influence level of the coating.

[0036] Coating thickness, as another key evaluation basis, is compared with the set thickness threshold (e.g. 40 μm for aluminum profiles). The system sets a double-layer judgment logic: on the one hand, it determines whether the thickness absolute value meets the stripping intervention standard, and on the other hand, it further improves the judgment accuracy by combining the composition complexity (such as fluorine element and organic polymer types).

[0037] If the system detects that the coating thickness exceeds the set threshold and there are components that interfere with the metal recycling process, the profile is immediately marked as "to be separated" and the automated conveying device is instructed to transfer it to the coating treatment line. Common coating separation methods include: 1) alkali immersion combined with heat treatment to cause the organic layer to soften and fall off; 2) using plasma treatment to remove the residual layer at low temperature; 3) using mechanical polishing or sandblasting equipment for physical peeling. This step ensures that the profile surface is free of interfering components before entering the melting process.

[0038] On the contrary, if the determination result shows that the thickness is lower than the standard and there are no key interfering components, the system directly skips the separation step and sends the profile to the next stage of element detection process. At this time, the system automatically establishes a coating composition feature data set, records the identified main elements of the coating, residual thickness and spectral pattern, and binds them to the unique identification code of the profile, facilitating subsequent quality traceability and statistical analysis.

[0039] This method uses intelligent decision logic to determine whether the waste profile needs to be processed based on big data and algorithm analysis, greatly improving the scientificity and operation efficiency of classification and processing, and ensuring the performance stability of the regenerated profile.

[0040] Through the automatic recognition and judgment mechanism in this process, intelligent diversion of the coating treatment path of the waste profile is realized, avoiding the waste of resources caused by uniform treatment of all profiles, improving the processing efficiency and equipment utilization. At the same time, the influence of non-compliant coating residues on the purity of alloy components is effectively controlled, and the controllability of the quality of recycled raw materials is improved. The generation of coating feature data set also provides data support for subsequent process parameter adjustment and product quality traceability. The overall process logic is clear and efficient, suitable for metal remanufacturing enterprises of various scales, and has good generalizability.

[0041] According to the quality evaluation data report generated by the comprehensive analysis report, the coating composition feature data set is used to calculate and generate the corresponding solvent formula parameters through a chemical solvent proportioning system, including the type and concentration ratio of the solvent. The automatic chemical treatment device performs coating dissolution operation on the surface of the waste profile according to the formula parameters to obtain a preliminary purified profile, and records the solvent consumption and processing time data.

[0042] This composite manufacturing process further introduces a data-driven chemical treatment step after completing the coating thickness and composition analysis, aiming to achieve efficient, accurate and controllable coating removal operation. The core principle is to use the coating composition feature data set as input, combine with a pre-set solvent formula database, and dynamically generate the most suitable chemical solvent combination for targeted dissolution treatment of the surface of the waste profile, thereby achieving the preliminary purification and standardization of the raw material.

[0043] Specifically, the system first extracts key information parameters from the coating composition feature dataset, such as the main organic polymer class (e.g. polyester, polyurethane, fluorocarbon, epoxy), auxiliary components (such as pigments, fillers, plasticizers), swelling response type and molecular weight distribution, etc. These data are input into the calculation module of the chemical solvent proportioning system through a standardized interface. The system pre-sets response models for multiple typical solvent systems, including single-component solvents (such as toluene, acetone, isopropyl alcohol) and complex solvent systems (such as NMP / ethanol mixture, ethyl acetate / ammonia aqueous two-phase system), and performs multivariate matching based on coating dissolution parameters (such as solubility parameter, interfacial energy, diffusion coefficient).

[0044] Subsequently, the calculation module calculates the solvent types and their concentration ratios based on coating thickness information, processing time expectations and environmental constraints, and outputs a set of precise solvent formulation parameters. These parameters are directly transmitted to the solvent batching unit in the automatic chemical treatment device, which controls the precise pump and stirrer through electromagnetic valves to proportion multiple solvents into the treatment tank to form a treatment liquid with stable reaction activity.

[0045] In the actual operation phase, the treatment device uses immersion, circulating spray or ultrasonic synergistic action to apply the prepared solvent to the surface of the waste profile, and the treatment temperature is controlled by a constant temperature module within a pre-set range (such as 25°C~70°C) to ensure uniformity and efficiency of the reaction. To improve the control accuracy of the treatment, the system is equipped with a stripping process state detection unit, such as an infrared reflection change recognition module or a solution conductivity dynamic measurement device, which can evaluate the coating dissolution degree in real time. When the dissolution reaction reaches the set threshold, the system will interrupt the solvent spraying or stop the immersion and enter the cleaning process.

[0046] Throughout the process, the system continuously monitors key parameters such as solvent flow, treatment time, liquid temperature changes, etc., and forms a complete set of data records, including solvent consumption (such as in ml or g), single piece processing time (such as accurate to seconds), etc., for subsequent process optimization, solvent recycling and reuse, and environmental emission management.

[0047] In addition, the surface state of the treated profile can be photographed by the image recognition module and compared with the standard template to ensure complete removal and no corrosion marks, and then enter the subsequent element analysis or remelting process to ensure product quality from the source.

[0048] By introducing a chemical solvent proportioning system and an automated dissolution treatment device, the intelligence and precision levels of the surface coating treatment of waste profiles are significantly improved. The system can automatically generate the optimal chemical formula based on the specific coating characteristics, avoiding manual experience errors, improving dissolution efficiency, and reducing solvent waste and environmental risks. The data monitoring and recording mechanism during the treatment process provides reliable support for quality control and subsequent traceability, which is conducive to building a visual and controllable remanufacturing process chain. This scheme has strong adaptability and is suitable for waste profiles of different batches and different sources, improving the robustness and large-scale processing capacity of the recycling process.

[0049] According to the comprehensive analysis report, the quality evaluation data report also includes element composition detection of the preliminary purified profile by X-ray fluorescence spectrometer to obtain the content percentage data of each metal element and the pollutant element distribution information. If the purity of the main metal elements reaches the preset smelting standard, it is marked as a qualified recycled profile. If it does not meet the standard, a pollutant element distribution dataset is generated and enters the deep purification process.

[0050] After the preliminary purification treatment is completed, the residual coating on the surface of the waste profile has been basically removed. To ensure that it can be used as a qualified recycled metal in the subsequent smelting process, this process sets a key step of in-depth detection and evaluation of the element composition based on the X-ray fluorescence spectrometer (XRF). XRF is a non-destructive detection technology whose core principle is to use high-energy X-rays to irradiate the sample to excite the internal atoms, causing them to transition and release characteristic fluorescent X-rays. By analyzing the energy and intensity of these fluorescent X-rays, the element types are identified and their content percentages are calculated.

[0051] In operation, the preliminary purified profile is numbered and sent to the automatic conveying device, which guides it to the detection platform. The platform is equipped with a precision positioning module to ensure that the XRF probe accurately focuses on the profile surface and can perform repeated detection at multiple points through a two-dimensional scanning mechanism to form a full-surface coverage or high-density analysis graph of a specific area. The detection system identifies typical metal elements (such as Al, Mg, Fe, Zn, Mn) and impurity elements (such as Pb, Cd, S, Cl, Na) one by one and compares them in real time based on the standard concentration values in the database.

[0052] For each detection area, the system converts the fluorescent intensity into mass percentage through a calibration curve, automatically generates an analysis report containing the main element content, total impurity amount, and regional distribution, and applies internal judgment logic to evaluate the "smelting suitability" of the profile. If the purity of its main metal elements meets the preset smelting standard (e.g., Al ≥ 98.5%, Fe ≤ 0.4%, total impurities ≤ 1.0%), it is marked as a "qualified recycled profile" and included in the next batch of ingredient list with a unique tracking identification code. This data is simultaneously recorded in the MES system and the material quality database.

[0053] Conversely, if the analysis finds that the content of certain pollutants exceeds the set limit, especially non-metallic elements (such as Cl, S) or heavy metal elements (such as Pb, Cd) with negative metallurgical effects, the profile will be judged as "unqualified", and the system will automatically start the pollutant analysis module to generate a pollutant element distribution dataset. This dataset lists the types, concentration values, and spatial distribution heat map of impurity elements in detail, and evaluates their sources (such as from residual coating, environmental corrosion, or inclusions).

[0054] This type of profile is sent to a deep purification process, which may include electrolytic refining (for removing impurities with strong electrochemical activity), vacuum heat treatment (for evaporating volatile pollutants), selective chemical extraction or plasma treatment, etc. The specific process is automatically recommended and scheduled by the system according to the type and distribution density of pollutants. After purification, XRF re-inspection is performed again to ensure that the composition meets the standard before it can be included in the smeltable raw material system, ensuring the stability of the performance and chemical composition of the final product.

[0055] By detecting non-contact, high-sensitivity, and non-destructive analysis methods through X-ray fluorescence spectrometers, the accuracy and detection efficiency of recycled profile composition identification are greatly improved. Systematic acquisition of metal purity and impurity distribution information provides an objective standard for recycled raw material grade evaluation, facilitating batch management and classified utilization. The construction of pollutant element distribution dataset not only helps targeted purification treatment, but also improves resource utilization efficiency and reduces performance instability problems caused by impurities in the smelting stage, thereby enhancing the quality control capability and market competitiveness of the final product.

[0056] The quality evaluation data report generated according to the comprehensive analysis report also includes the use of adaptive separation optimization algorithms to dynamically adjust the vibration frequency and magnetic field strength parameters of physical separation equipment based on the pollutant element distribution dataset, removing non-metallic impurities and foreign metal particles through a combination of magnetic separation and gravity separation processes, obtaining deeply purified profiles, and generating an updated element content dataset.

[0057] After completing the preliminary purification and element content analysis, this process introduces an adaptive physical separation treatment module driven by the pollutant element distribution dataset for waste profiles that still have impurities exceeding the standard, aiming to improve the separation accuracy through dynamic parameter adjustment and achieve more thorough deep purification results.

[0058] The pollutant element distribution dataset is derived from the upstream X-ray fluorescence analysis and pattern calculation module, and the data includes the types, distribution areas, average particle size, magnetic response characteristics, and density intervals of impurity elements. The system first uses these data to model and parameter match through the built-in adaptive separation optimization algorithm, which integrates an expert rule base and a trained decision engine to determine the best separation strategy based on the physical differences between pollutant types and the main metal.

[0059] The specific parameter adjustment logic is as follows: Vibration frequency matching: according to the particle size range (such as 0.12.0mm) and density characteristics of the pollutants, the algorithm matches the vibration frequency (such as 1050 Hz) of the gravity separation platform to maximize the particle size layering effect and improve the non-metallic impurity floating separation efficiency.

[0060] Magnetic field strength regulation: when the system detects the presence of magnetic impurities (such as iron, nickel), it automatically adjusts the magnetic flux density (such as 300-1000 Gauss) on the surface of the magnetic roller, so that the impurity particles are adsorbed when passing through the magnetic separation belt, and the main metal profile is normally output due to weak magnetic response.

[0061] Inclination and air flow coupling: for mixtures with similar particle density but large particle size difference, the inclination angle of the inclined separation belt and the air pressure of the air flow assisted stripping device are dynamically adjusted to enhance the sinking tendency of high-density particles and assist in improving the clarity of gravity separation.

[0062] After the system receives the pollutant data set, all control parameters will be loaded into the physical separation controller in real time, and the device will enter the adjustment state. After the waste profile is crushed into particles, it is transported to the vibrating gravity separation module by the feeding device. First, the density difference is used to separate floating impurities such as paint scraps and high molecular substances, then the magnetic roller system is used to adsorb foreign magnetic metal particles, and finally the main material purification particles are output.

[0063] During the entire process, infrared sensors and high-definition camera modules perform online identification on the discharged particles. If abnormal particles (such as reflective, color difference, and abnormal appearance) are identified, the system can automatically trigger a backflow operation and feed back to the algorithm module for correction of the next parameters.

[0064] After processing is complete, the deeply purified profile particles are again sent to the analysis module for retesting by XRF or ICP-OES. The system updates the element content data set, which includes the main element content percentage, residual impurity level, each processing parameter, and processing batch number, to ensure that the material quality meets the requirements of the remanufacturing process standard.

[0065] The present application improves the impurity identification and separation accuracy by linking the pollutant distribution information with dynamic physical separation parameters, and is particularly suitable for processing recycled profiles with high impurity content and complex structure. Compared with traditional fixed parameter separation, the self-adaptive separation optimization algorithm can adjust the device parameters according to the actual material state, significantly improving the processing efficiency and separation accuracy. The combined design of magnetic separation and gravity separation covers the removal needs of various impurity forms, providing pure and composition stable metal raw materials for subsequent alloy preparation. At the same time, the updated element data set can form a complete material tracking chain, meeting the high requirements of quality control and traceability in industrial production.

[0066] According to the comprehensive analysis report generation quality evaluation data report also includes for deep purification profile, perform secondary element composition detection, get updated metal element content percentage data, evaluate the composition uniformity of the profile by composition stability analysis algorithm, if the uniformity meets the preset fluctuation threshold standard, mark as unified quality recycling profile, and generate quality evaluation data report.

[0067] After completing deep purification and excluding main impurities, to further ensure the quality stability of the recycled profile, the present application specially sets two key steps of "secondary element composition detection" and "composition uniformity evaluation" before the material enters the smelting link, aiming to verify the consistency and eligibility of the profile in overall composition, so as to form a closed-loop quality control chain.

[0068] The secondary element composition detection link adopts a multi-point and multi-region sampling strategy. The processed deep purification profile is processed into granular or small slice samples, which are respectively conveyed to the X-ray fluorescence spectrometer (XRF) and ICP-OES analyzer by the sample feeding robot for element detection. The detection method can combine rotary scanning, surface uniform sampling and internal cross-section sampling to avoid the representativeness deviation caused by relying on single-point data. Each detection point will generate mass percentage values of multiple main elements (such as Al, Fe, Mg, Zn, etc.) and impurity elements (such as Pb, Cd, S, Cl, etc.), and form a two-dimensional or three-dimensional data matrix structure, constructing a comprehensive composition map.

[0069] The obtained data is input into the composition stability analysis algorithm module, which integrates various statistical methods, including but not limited to: Coefficient of variation analysis: measures the dispersion degree of the element content data, and evaluates its fluctuation stability; Range analysis: calculates the maximum and minimum value difference of the same element in different point detection, reflecting the distribution uniformity; Standard deviation analysis: compares the standard deviation of each element in the sample group with the set mean interval to judge the fluctuation amplitude; Principal component analysis (PCA) and cluster analysis: auxiliary identification of some sample groups with potential abnormal clusters in composition characteristics.

[0070] The system presets the fluctuation threshold standard, such as the CV value of the main metal elements not greater than 2%, the single-point deviation from the center value not more than ±0.5%, and the high-risk impurities not appearing local peak aggregation, as the judgment basis of unified quality evaluation. If the detection data meets all the standards, the system automatically marks the batch of profile as "unified quality recycling profile", which represents that it has the qualification to enter the standardized smelting and precise alloy manufacturing.

[0071] At the same time, the system generates a "quality evaluation data report", including but not limited to the following: detection sampling cloth point map, element composition distribution map, fluctuation analysis map, quality assessment result, qualified label number and recommended use level, etc. The report is uploaded to the data management platform at the same time, and is bound with the tracking number corresponding to the batch of profiles, realizing the quality traceability from raw material recycling to finished product production.

[0072] If the analysis result shows that the fluctuation of a certain element exceeds the threshold value, the system will mark this batch as "abnormal fluctuation", and recommend adjusting the processing method according to the type of abnormal element, such as increasing the mixing uniformity step, re-screening purification or entering the secondary use recycling path, to ensure that the subsequent process quality is not affected.

[0073] This embodiment introduces the "composition uniformity" evaluation dimension, builds a more rigorous quality judgment system than single-point detection, effectively guarantees the performance consistency and alloy standard compatibility of recycled profiles in subsequent remanufacturing. Cooperate with the secondary detection mechanism to ensure the chemical composition stability between and within product batches, reduce the risk of composition segregation, and improve the controllability of material quality. At the same time, through the digital report to support the whole process quality tracking, it is convenient for enterprises to build material quality database and data docking of intelligent smelting platform.

[0074] The multi-spectral scanning device performs synchronous scanning by combining ultraviolet, visible and near-infrared spectral channels when performing spectral data acquisition, and realizes the identification and separation of metal oxides, organic residues and heavy metal ions in the coating by comparing with the reference spectrum library.

[0075] This embodiment introduces multi-channel multi-spectral scanning technology at the initial stage of material analysis, integrates the information of ultraviolet (200-400 nm), visible light (400-700 nm) and near-infrared (700-2500 nm) three spectral bands, and realizes high-resolution synchronous identification of complex coating components. The scanning device is equipped with a multi-channel spectral receiving module, and the three bands of scanning heads are time and space aligned through a synchronous trigger, ensuring unified analysis of the same scanning area.

[0076] During the detection process, the device emits a wide-spectrum illumination beam to irradiate the surface of the profile, and the components in the coating show specific absorption or reflection characteristics to different bands. For example: Metal oxides (such as Fe2O3, TiO2) show strong absorption peaks in the ultraviolet region; Organic residues (such as epoxy resin, polyurethane) have characteristic reflection or scattering peaks in the visible to near-infrared region; Heavy metal ions (such as Pb 2＋ , Cd 2＋ ) form complexes with surface ligands, which have typical absorption spectra.

[0077] The collected continuous spectrum is compared with a preset reference spectrum library, the spectrum library contains spectrum fingerprints of different coating materials under standard conditions, supports spectrum resolution and deconvolution operation when multiple components coexist. Principal component analysis (PCA) or partial least squares regression (PLSR) algorithm is used for identification enhancement, so as to accurately separate the spectrum contribution value of each type of material.

[0078] The final output result is the main material category in the coating and its relative intensity value, and a classification identification label is formed, which respectively marks the metal oxide area, the organic residual area and the heavy metal pollution area. The data provides a decision basis for whether to perform chemical stripping, selective solvent treatment or pollution control subsequently, and is also included in the comprehensive analysis report as one of the original data sources.

[0079] The present application realizes the synchronous identification of the fine components of the composite coating without damaging the material structure by fusing the multi-band spectrum acquisition and reference library comparison algorithm, greatly improving the information acquisition integrity and identification accuracy in the raw material sorting stage. The efficient separation and determination of metal oxides, organic residues and heavy metal pollution provide scientific basis for subsequent batching and purification decision, avoid misjudgment and resource waste, improve the overall recycling efficiency and product stability. The system also has rapid response capability and meets the industrial application needs of large-scale continuous processing.

[0080] The material grading database and the melting process parameter configuration table are linked and constructed through a data modeling engine, the modeling engine optimizes the material grading rules based on historical melting data, target alloy ratio and quality stability standards, and generates melting temperature, holding time, types and doses of additives process parameters matched with each recycling grade, so that recycled profiles from different sources can achieve high consistency of recycled quality under unified control framework.

[0081] This embodiment introduces a data modeling engine to establish a dynamic linkage mechanism between material grading and process parameter setting, breaking through the limitations of traditional experience-dependent melting parameter setting, and realizing high-precision formula management based on data-driven.

[0082] The specific operation process is as follows: first, the material grading database records the basic physical and chemical characteristic data of various recycled profiles, such as metal purity grade, alloy system, residual impurity type and content, composition fluctuation level, etc.; at the same time, the system summarizes a large amount of historical melting process data, including batching composition, heating curve, holding time, actual output alloy composition, impurity removal rate, physical property test results, etc.

[0083] The data modeling engine adopts a supervised machine learning method (such as random forest, gradient boosting decision tree GBDT, support vector machine SVM, etc.) to establish an input-output mapping model, the input is the material classification information and the target alloy type, and the output is the optimal smelting control parameter combination, including smelting temperature (such as 660-780 DEG C), holding time (such as 30-120 min), impurity removal additive type (such as fluoride salt, lime, refining agent, etc.) and recommended additive dosage (such as 0.5~2% mass ratio).

[0084] During the model training process, quality stability standards are also introduced as constraint conditions, such as component fluctuation rate less than ±0.5%, strength float less than 5%, and qualified rate greater than 98%, etc., to ensure that the recommended process parameter combination not only meets the component standard, but also has long-term consistency and industrial replicability.

[0085] The modeling engine is linked with the database and the process parameter management system through an interface, and when the actual batch recycled profile enters the batching stage, the system automatically calls the parameter model corresponding to the classification section of the current batch, quickly generates a smelting process configuration table and synchronously pushes it to the on-site control platform, ensuring the automation and precision of process execution.

[0086] The present application establishes a data modeling closed-loop mechanism between material classification and smelting control, realizing the whole-process intelligent optimization from recycled data driving process parameter development. Through machine learning model, the mapping relationship between recycled materials and target performance is systematically modeled, avoiding the uncertainty in manual decision-making, and improving the material utilization rate and product consistency. This method has good adaptability and expandability, and can quickly generate matching strategies according to different regions and different industry recycling sources, significantly improving the quality control level of recycled materials and the operation efficiency of production line.

[0087] The online quality monitoring system is equipped with a tunable laser light source and a multi-channel photoelectric receiving array when performing continuous spectrum detection, and combines a real-time data fitting algorithm to calculate the concentration variation trend of each main metal element in the raw material batch, and automatically triggers the discharge mechanism and feedback correction program when abnormal fluctuations are detected.

[0088] In the remanufacturing process, in order to ensure the quality stability of the recycled profile after mixed smelting, the present application realizes real-time monitoring and dynamic regulation of the composition of the raw material batch by deploying an online quality monitoring system. The core of the system includes a high-performance tunable laser light source, a multi-channel photoelectric receiving array and a real-time data fitting analysis module, which cooperatively complete continuous spectrum analysis and intelligent decision-making.

[0089] The tunable laser light source adopts an external cavity laser structure, can realize high-precision wavelength scanning in a specific wavelength range (such as 400-800 nm), and irradiate the surface of a metal melt or a high-temperature mixture area to excite the characteristic spectral lines of each metal element in the material. The released fluorescent signals are captured by a multi-channel photoelectric receiving array, which includes multiple waveband detectors (such as Si and InGaAs) to cover the spectral ranges corresponding to different elements.

[0090] The real-time data fitting algorithm inversely calculates the concentration values of the corresponding elements by fitting the spectral intensity at each time with the element characteristic peak values in the preset standard spectral library. This process combines Kalman filtering, moving average and other time series algorithms to form a trend analysis spectrum of the element concentration data, so as to capture the sharp fluctuations or long-term drift changes in a short period of time.

[0091] When the system detects that the concentration fluctuation amplitude of a certain main element (such as aluminum, magnesium, zinc, etc.) exceeds a set threshold (for example, ±1.0% or the standard deviation exceeds the confidence interval), it is automatically determined as an abnormal state. At this time, the controller will start the discharging mechanism, such as activating the electromagnetic valve to separate the abnormal batch from the main smelting flow to the waiting tank to prevent the abnormal batch from entering the finished product system and causing pollution. At the same time, the system uploads the real-time data to the feedback correction program, which combines the original batching data, the current element distribution and the historical deviation model to recalculate the recommended adjustment parameters (such as supplementing high-purity metals, adjusting the smelting temperature or adding a decontamination agent), and generates a “process correction instruction” for reference by the operator or directly pushed to the automatic control module.

[0092] The embodiment effectively solves the problems of uncontrollable element fluctuation and large quality fluctuation in the traditional recycling smelting process by constructing a continuous and closed-loop real-time spectral monitoring and reaction mechanism. The tunable laser combined with the multi-channel receiving array forms a high-sensitivity detection system, so that the composition deviation can be captured and responded within seconds, significantly improving the stability, safety and quality consistency of the production process. The feedback correction function enhances the adaptive ability of the system, reduces the frequency of human intervention, improves the level of intelligent manufacturing, and is particularly suitable for high-end metal decorative profile production scenarios with strict composition control requirements.

[0093] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A T-shaped cold-bent metal decorative profile, characterized in that: include: A T-shaped body (1) is used to form a main structure and provide support; a first connecting flange (2) is fixed to a first side of the T-shaped body (1) and is used to provide lateral stability and a decorative surface; a second connecting flange (3) is fixed to a second side of the T-shaped body (1) and is used to provide lateral stability and a decorative surface; a node connecting plate (4) is detachably assembled on an end region of the T-shaped body (1) and is used to simplify node connection and transmit load; a fastening bolt (5) passes through the node connecting plate (4) and an adjacent profile and is used to apply a fastening force; The node connection plate (4) comprises a prefabricated multi-hole array (4a) for achieving rapid alignment and on-site bolt installation.

2. A composite manufacturing process for T-shaped cold-bent metal decorative profiles, using the profile according to claim 1, characterized in that: The process comprises: Use multi-spectral scanning equipment to collect spectral data on the surface of waste profiles, and use a laser thickness gauge to accurately measure the coating thickness, generating a comprehensive analysis report containing characteristic peak values ​​of coating composition and thickness data; Generate a quality assessment data report based on the comprehensive analysis report. Based on the quality assessment data report, build a material classification database, classify and label uniform quality recycled profiles according to metal purity level and alloy composition ratio, generate a corresponding smelting process parameter configuration table, including smelting temperature, duration and additive ratio, and generate a quality control indicator data set; Based on the composition requirements in the smelting process parameter configuration table, recycled profiles of uniform quality of different grades are mixed in preset proportions through an automatic batching system to form standardized batches of recycled raw materials; an online quality monitoring system is used to perform continuous spectral detection and component stability verification on the batches, generate quality certification marks and traceable batch codes, and complete the closed-loop recycling process.

3. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 2, characterized in that: Generating a quality assessment data report based on the comprehensive analysis report includes applying a multi-spectral component recognition algorithm to process the coating component characteristic peak and thickness data in the comprehensive analysis report. If the coating thickness exceeds a preset threshold standard, it is determined that the waste profile needs to be separated from the coating. If the thickness is lower than the threshold, it will directly enter the subsequent element composition detection link and generate a coating composition feature data set.

4. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 3, characterized in that: The quality assessment data report generated based on the comprehensive analysis report also includes calculating and generating corresponding solvent formula parameters, including solvent type and concentration ratio, based on the coating composition characteristic data set through a chemical solvent ratio system. The automatic chemical processing device performs a coating dissolution operation on the surface of the waste profile according to the formula parameters to obtain a preliminary purified profile, and records the solvent consumption and processing time data.

5. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 4, characterized in that: The generation of a quality assessment data report based on the comprehensive analysis report also includes the use of an X-ray fluorescence spectrometer to perform elemental composition testing on the preliminary purified profiles to obtain the content percentage data of each metal element and the distribution information of the pollutant elements. If the purity of the main metal elements meets the preset smelting standard, it will be marked as a qualified recycled profile; if it does not meet the standard, a pollutant element distribution data set will be generated and the deep purification process will be entered.

6. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 5, characterized in that: The generation of a quality assessment data report based on the comprehensive analysis report also includes dynamically adjusting the vibration frequency and magnetic field strength parameters of the physical separation equipment based on the pollutant element distribution data set using an adaptive separation optimization algorithm, removing non-metallic impurities and foreign metal particles through a combined process of magnetic separation and gravity separation to obtain deeply purified profiles, and generating an updated element content data set.

7. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 6, characterized in that: The generation of a quality assessment data report based on the comprehensive analysis report also includes performing secondary element composition detection on the deeply purified profiles, obtaining updated metal element content percentage data, and evaluating the composition uniformity of the profiles through a composition stability analysis algorithm. If the uniformity meets the preset fluctuation threshold standard, it is marked as a uniform quality recycled profile and a quality assessment data report is generated.

8. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 2, characterized in that: The multi-spectral scanning device combines ultraviolet, visible light and near-infrared spectral channels for synchronous scanning when performing spectral data acquisition, and realizes the identification and separation of metal oxides, organic residues and heavy metal ions in the coating by comparing with the reference spectral library.

9. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 2, characterized in that: The material grading database and the smelting process parameter configuration table are constructed in conjunction with each other through a data modeling engine. Based on historical smelting data, target alloy ratios, and quality stability standards, the modeling engine utilizes machine learning methods to optimize material grading rules and generate smelting temperature, holding time, and impurity removal additive type and dosage process parameters that match each recycling grade. This allows recycled profiles from different sources to achieve highly consistent regeneration quality under a unified control framework.

10. The composite manufacturing process for a T-shaped cold-bent metal decorative profile according to claim 2, characterized in that: The online quality monitoring system is equipped with a tunable laser light source and a multi-channel photoelectric receiving array when performing continuous spectral detection. It combines a real-time data fitting algorithm to calculate the concentration change trend of each major metal element in the raw material batch, and automatically triggers the discharge mechanism and feedback correction program when abnormal fluctuations are detected.

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