Automatic classification and identification system and method for regenerated high-quality metal based on LIBS (laser-induced breakdown spectroscopy) technology

Abstract

The invention discloses a system and a method for automatically classifying and identifying regenerated high-quality metal based on LIBS (laser-induced breakdown spectroscopy) technology, in the system, a material conveying module conveys materials to be detected along a classifying and identifying assembly line; the to-be-detected material pretreatment device is used for pretreating a to-be-detected material; the to-be-detected material information sensing system collects basic information of a to-be-detected material; the control system is used for controlling the LIBS multi-dimensional high-throughput detection system based on the basic information of the to-be-detected material; the LIBS multi-dimensional high-throughput detection system is used for detecting and analyzing the to-be-detected material based on an LIBS technology to obtain a classification recognition result of the to-be-detected material; and the material post-processing device is used for classifying and collecting different types of to-be-detected materials. According to the method, full-automatic online classification and recognition can be carried out on the regenerated high-quality metal of different types and different forms, the classification and recognition efficiency and accuracy of the regenerated high-quality metal are greatly improved, and the regenerated high-quality metal is effectively recycled.

Description

Technical Field

[0001] The present invention relates to the technical field of recycled metal classification and recovery, and in particular to a system and method for automatically classifying and identifying recycled high-quality metals based on LIBS technology. Background Art

[0002] The recycling of renewable resources can not only turn waste into treasure and reduce resource waste, but also reduce pollution to the environment; especially the recycling of high-quality and rare metals in recycled metals, such as stainless steel, titanium alloy, high-temperature alloy and other metal materials. Due to the scarcity of metal elements they contain, the smelting process is complex and the yield is low, if the recycled high-quality metals can be recycled, the waste of resources will be greatly reduced. Therefore, the recycling of recycled high-quality metals becomes more important; the main sources of recycled high-quality metals are scraps generated in the metal processing process, defective metal parts, and metal parts that have reached the service life. Due to their uncontrollable sources, there is a mixture of metal grades. If the recycled high-quality metals can be classified by grade before entering the smelting process, it can not only prevent the downgrading of high-value alloys, but also provide important guidance for subsequent smelting processes, reducing energy consumption and pollution in the smelting process.

[0003] Laser induced breakdown spectroscopy (LIBS) detection technology uses pulsed laser to perform non-contact high-energy excitation ablation on the surface of the material. The ablated material generates a large amount of plasma, and the spectral signal is collected and analyzed for the plasma signal, and finally the composition and content of the object being tested are obtained. LIBS technology does not require direct contact with the object being tested during testing, and can achieve online dynamic analysis. It is suitable for online, high-throughput, large-scale, and rapid classification and detection of recycled high-quality metal materials. Therefore, how to use LIBS technology to solve the recycling and classification problem of recycled metals has become a topic worthy of in-depth discussion by technicians in this field. Summary of the invention

[0004] The purpose of the present invention is to provide a system and method for automatic classification and identification of recycled high-quality metals based on LIBS technology, which can perform fully automatic online classification and identification of recycled high-quality metals of different categories and forms, greatly improve the classification and identification efficiency and accuracy of recycled high-quality metals, and enable the recycled high-quality metals to be effectively recycled.

[0005] To achieve the above object, the present invention provides the following solutions: A recycled high-quality metal automatic classification and identification system based on LIBS technology, comprising: a material transmission module, a pre-processing device for the material to be tested, an information sensing system for the material to be tested, a LIBS multi-dimensional high-throughput detection system, a control system, and a material post-processing device; The material transmission module is used to transmit the material to be tested along the classification and identification assembly line; the material to be tested is a recycled high-quality metal material; The material pre-treatment device is used to pre-treat the material to be tested so that the morphology and surface state of the material to be tested are relatively consistent; The material information sensing system to be tested is used to collect basic information of the material to be tested and transmit it to the control system; the basic information includes the presence, size, shape, height and position information of the material to be tested; The control system is used to control the LIBS multi-dimensional high-throughput detection system based on the basic information of the material to be tested; The LIBS multi-dimensional high-throughput detection system is used to detect and analyze the material to be tested based on the LIBS technology to obtain the classification and identification results of the material to be tested; The material post-processing device is used to receive the execution instruction of the control system and classify and collect different categories of materials to be tested according to the execution instruction; the control system generates the execution instruction according to the classification and identification results of the materials to be tested.

[0006] Furthermore, the pre-processing device for the material to be tested includes a shearing device and a cleaning device for impurity removal. The shearing device is used to shear and crush the material to be tested into materials with consistent shapes. The shapes of the material to be tested include: crumb-like materials with a shape and size of 3-15mm; flake-like materials with a shape and size of more than 15mm; The impurity removal and cleaning equipment includes at least one of ultrasonic, high temperature and laser ablation equipment, which is used to remove impurities and clean the surface of the material to be tested so that the surface state of the material to be tested is consistent.

[0007] Furthermore, the information perception system for the material to be tested includes an adjustable brightness lighting system, a variable focal length optical system and an adaptive height sensing system. The adjustable brightness lighting system is used to illuminate the surface of the material to be tested so as to distinguish the material to be tested from the conveyor belt of the material transmission module. The variable focal length optical system is used to dynamically adjust the focal length of the lens to adapt to the size and position changes of the material to be tested and the detection requirements, thereby ensuring the imaging quality and detail capture capability. The adaptive height sensing system is used to sense the height fluctuation of the material to be tested in real time and dynamically adjust the sensor posture.

[0008] Furthermore, the LIBS multi-dimensional high-throughput detection system includes multiple groups of single-path optical systems, and the single-path optical systems include lasers, excitation light paths, return light paths, and spectrometers; The LIBS multi-dimensional high-throughput detection system adopts laser-induced laser spectroscopy technology and is equipped with a fully automatic analysis program, which automatically calculates the start time and end time of excitation and the working state of the laser in the LIBS multi-dimensional high-throughput detection system according to the material identification state and the area of ​​the horizontal projection; The LIBS multi-dimensional high-throughput detection system excites the material to be tested through multiple sets of single-path optical systems to obtain the atomic emission spectrum information of the material, compares the obtained atomic emission spectrum information of the material with the material model database, and classifies and identifies the material to be tested in combination with a classification algorithm.

[0009] Furthermore, the material model database is constructed by using atomic emission spectrum information of recycled high-quality metals of multiple different grades as a training set, optimizing SVM parameters through GA iteration, training to obtain a classification model, and constructing a material model database based on the classification model.

[0010] Furthermore, the control system controls the start and stop time and scanning mode of the LIBS multi-dimensional high-throughput detection system; the control system displays the classification and recognition results on a visualization panel.

[0011] Furthermore, the material post-processing device includes a plurality of different material channels for collecting different types of materials to be tested.

[0012] The present invention also provides a method for automatically classifying and identifying recycled high-quality metals based on LIBS technology, which is applied to the above-mentioned system for automatically classifying and identifying recycled high-quality metals based on LIBS technology, and comprises the following steps: S1. Excitation area division: During the detection process, according to the position of the material to be tested on the material transmission module, the detection area of ​​the material to be tested is divided into a horizontal area and a vertical area. The horizontal area is the transmission direction of the material to be tested, and the detection area is divided into a front single-point scanning excitation area and a rear multi-point scanning excitation area; the vertical area division is perpendicular to the transmission direction of the material to be tested, and the detection area is divided into 1, 2, 3, ..., N areas; S2. Confirmation of detection mode and collection of material spectrum information: According to the detection requirements, the corresponding excitation mode is matched, the material to be tested is excited, and the material atomic emission spectrum information of the material to be tested is obtained; the excitation modes include single-point excitation mode, single-point and key material accumulation mode, line scan sampling mode, line scan sampling and regional multi-point accumulation mode; S3. Data processing of spectrum information of materials to be tested: It is used to detect and analyze the materials to be tested based on LIBS technology, obtain the detection information of the materials to be tested, and compare it with the model database to obtain the classification and identification results of the materials to be tested; S4. Output of classification and identification results of materials to be tested: The control system displays the classification and identification results on a visual panel; the material post-processing device classifies and collects different types of materials to be tested.

[0013] Furthermore, in S2, the single-point excitation mode implements single-point excitation for flake-like materials to obtain single-point material detection information; the single-point and key material accumulation mode, based on the single-point excitation mode, performs multi-point accumulation excitation on the materials to be tested with large information differences, so as to achieve accurate classification and identification of the materials to be tested; the line scan sampling mode, for chip-like materials, implements sampling scanning to obtain large-scale regional spectral information; the line scan sampling and regional multi-point accumulation mode, based on the line scan sampling mode, performs small-area multi-point accumulation excitation on areas with large information differences in a large area, so as to achieve accurate classification and identification of chip-like materials.

[0014] Compared with the traditional metal sorting technology in the existing technology, the automatic classification and identification system and method of recycled high-quality metals based on LIBS technology provided by the present invention integrates multiple system modules such as material transmission module, pre-treatment device of materials to be tested, information perception system of materials to be tested, LIBS multi-dimensional high-throughput detection system, control system, material post-processing device, etc., to realize the complete assembly line operation of material transmission, pre-treatment, basic information collection, LIBS technical analysis and classification collection, improve the efficiency of automatic classification and identification of high-quality metal materials, and realize the collection of high-quality metal materials of different categories, so as to facilitate the recycling and reuse of high-quality metals.

[0015] The present invention performs online fully automatic classification and identification of recycled high-quality metals based on LIBS technology. It does not require complicated manual operations and automatically matches the corresponding excitation mode according to the identification and classification requirements, greatly improving the efficiency and accuracy of classification and identification. It can perform fully automatic online classification and identification of recycled high-quality metals of different categories and forms (chips, flakes), and is suitable for online, high-throughput, large-scale, and rapid classification and detection of recycled high-quality metal materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 This is a schematic diagram of the overall structure of the automatic classification and identification system for recycled high-quality metals based on LIBS technology of the present invention; Figure 2It is a schematic diagram of the conveying direction of the material conveying module of the present invention; Figure 3 This is the workflow diagram of the automatic classification and identification system for recycled high-quality metals based on LIBS technology; Figure 4 Schematic diagram of the optical system of the LIBS multi-dimensional high-throughput detection system of the present invention; Figure 5 Schematic diagram of the automatic classification, identification and detection method for recycled high-quality metals based on LIBS technology of the present invention, (a) represents the division of the excitation area of ​​shavings, wherein A is the front single-point scanning excitation area, and B is the rear multi-point scanning excitation area; (b) represents the excitation mode of shavings, wherein the figure shows the line scanning sampling and regional multi-point accumulation mode, and the curve represents the excitation scanning path; (c) represents the division of the excitation area of ​​flake materials, wherein C is the front single-point scanning excitation area, and D is the rear multi-point scanning excitation area; (d) represents the excitation mode of flake materials, wherein the figure shows the single-point and key material accumulation mode, and the dots represent the excitation spots; Explanation of the accompanying drawings: 1. Material transmission module; 2. Pre-treatment device for materials to be tested; 3. Information perception system for materials to be tested; 4. LIBS multi-dimensional high-throughput detection system; 5. Control system; 6. Material post-treatment device; 7. Flake-shaped materials; 8. Excitation spots. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The purpose of the present invention is to provide a system and method for automatic classification and identification of recycled high-quality metals based on LIBS technology, which integrates six modules including a material transmission module, a pre-treatment device for materials to be tested, an information perception system for materials to be tested, a LIBS multi-dimensional high-throughput detection system, a control system, and a material post-processing device. It can realize fully automatic online classification and identification of recycled metal grades, greatly improve the classification and identification efficiency and classification and identification accuracy of recycled metal grades, and finally quickly classify and identify recycled high-quality metal grades.

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] Example 1 like Figure 1As shown, the automatic classification and identification system for recycled high-quality metals based on LIBS technology provided by the present invention includes: a material transmission module 1, a pre-processing device for materials to be tested 2, an information sensing system for materials to be tested 3, a LIBS multi-dimensional high-throughput detection system 4, a control system 5 and a material post-processing device 6; the specific introduction is as follows: like Figure 2 As shown, the material transmission module 1 is used to transmit the material to be tested along the classification and identification assembly line, and transmit the material to be tested to the corresponding positions of different systems and modules, so as to facilitate corresponding operations on the material to be tested; the material to be tested is a recycled high-quality metal material; the recycled high-quality metal includes metal and alloy materials with high-quality characteristics, and its sources include but are not limited to processing waste, defective metal parts, metal parts that have reached the service life, etc.; illustratively, the material transmission module 1 includes a conveyor belt and a motor connected to the conveyor belt drive, the material pre-processing device 2 to be tested, the material information perception system 3 to be tested, the LIBS multi-dimensional high-throughput detection system 4, the control system 5 and the material post-processing device 6 are arranged in sequence along the conveyor belt, and the motor is electrically connected to the controller of the control system 5.

[0022] The material pretreatment device 2 to be tested is used to pre-treat the material to be tested so that the morphology and surface state of the material to be tested are relatively consistent; for example, the material pretreatment device 2 to be tested includes a shearing device and an impurity removal and cleaning device, and the impurity removal and cleaning device removes impurities and cleans the surface of the material by means of ultrasound, high temperature, laser ablation, etc. For example, the shearing device can use a double-roll crusher, and the double rollers rotate relative to squeeze and crush, which is used to shear and crush the material to be tested into a material with consistent morphology; in the impurity removal and cleaning equipment, ultrasound: an industrial multi-tank ultrasonic cleaning device is used, and the multi-tank equipment realizes the automation of the entire process of degreasing-rinsing-drying; high temperature: a high-temperature water-based solvent is used to clean the oil on the surface of the material to be tested; laser ablation (high-temperature plasma driven cleaning): high-frequency pulses are used to excite the surface of the material, and high energy causes the surface of the material to be ablated, decomposing surface pollutants (such as metal oxides, organic residues); the shearing device and the impurity removal and cleaning device can select existing equipment with the above functions according to actual needs, and no specific limitation is made here.

[0023] The shapes of the materials to be tested include: crumb-like materials, with a shape and size of 3-15mm; flake-like materials, with a shape and size of more than 15mm; the impurity removal and cleaning equipment includes at least one of ultrasonic, high temperature and laser ablation equipment, which is used to remove impurities and clean the surface of the materials to be tested so that the surface state of the materials to be tested is consistent.

[0024] The material information sensing system 3 to be tested is used to collect basic information of the material to be tested and transmit it to the control system 5; the basic information includes the presence, size, shape, height and position information of the material to be tested; illustratively, the material information sensing system 3 to be tested includes an adjustable brightness lighting system, a variable focal length optical system and an adaptive height sensing system, the adjustable brightness lighting system adjusts the brightness of the LED light strip through a built-in adjustment circuit, the adjustable brightness lighting system is used to illuminate the surface of the material to be tested, so as to distinguish the material to be tested from the conveyor belt of the material transmission module, so as to capture material information more clearly and accurately; the variable focal length optical system is used to dynamically adjust the focal length of the lens, and the variable focal length optical system includes a variable focal length optical lens, which realizes the focal length of the zoom lens according to the clarity of the picture, adapts to the size, position changes and detection requirements of the material to be tested, and ensures the imaging quality and detail capture capability; the adaptive height sensing system uses a 3D line laser measuring instrument to sense the height fluctuation of the material to be tested in real time and dynamically adjust the sensor posture.

[0025] The material information sensing system 3 transmits the sensed basic information of the material to be tested to the control system 5 through the data communication line, and the control system 5 triggers the full-automatic analysis program of the LIBS multi-dimensional high-throughput detection system 4 to collect high-throughput spectral data for the material to be tested.

[0026] The control system 5 is used to control the LIBS multi-dimensional high-throughput detection system 4 based on the basic information of the material to be tested; for example, the control system includes a software operating system, an industrial computer, a display, a control circuit, etc. The control system 5 realizes the coordination between the system modules through data transmission, and displays the classification identification information on the visualization panel; the control system 5 is also used to control the start and stop time and scanning mode of the LIBS multi-dimensional high-throughput detection system 4; The LIBS multi-dimensional high-throughput detection system 4 can adapt to different heights and angles of the material, and realize multi-dimensional high-throughput detection from the dimensions of height, angle, superposition of height and angle, and multiple excitation modes; it is used to detect and analyze the material to be tested based on the LIBS technology to obtain the classification and identification results of the material to be tested; for example, the LIBS multi-dimensional high-throughput detection system 4 includes multiple groups of single-channel optical systems, and the single-channel optical system includes a laser, an excitation light path, a return light path, and a spectrometer. After receiving the signal of the control system 5, the laser emits light in a set excitation mode, and the excitation light path shapes, reflects, and focuses the laser emitted by the laser on the surface of the material to excite the material; after the material is excited by the high-energy laser, it emits an atomic emission spectrum, which is collected in the spectrometer through the return light path, and the spectrometer completes the photoelectric signal conversion and completes the material spectrum information collection; The LIBS multi-dimensional high-throughput detection system 4 adopts laser-induced laser spectroscopy technology and is equipped with a fully automatic analysis program, which automatically calculates the start time and end time of excitation and the working state of the laser in the LIBS multi-dimensional high-throughput detection system according to the material identification state and the area of ​​the horizontal projection; The LIBS multi-dimensional high-throughput detection system 4 excites the material to be tested through multiple sets of single-channel optical systems to obtain the atomic emission spectrum information of the material, compares the obtained atomic emission spectrum information of the material with the material model database, and classifies and identifies the material to be tested in combination with the classification algorithm; The material model database is constructed by using atomic emission spectrum information of recycled high-quality metals of multiple different brands as a training set, iteratively optimizing SVM (Support Vector Machine) parameters through GA (Genetic Algorithm), training to obtain a classification model, and constructing a material model database based on the classification model. The material model database contains the brand and its corresponding element type and content. The element composition of the material to be tested can be determined through the material atomic emission spectrum information, and the brand of the material to be tested can be confirmed by comparing it with the element type and content in the material model database.

[0027] For example, the LIBS multi-dimensional high-throughput detection system 4 is composed of 3 groups of single-channel optical systems, which include lasers, excitation optical paths, return optical paths, and spectrometers; the 3 groups of single-channel optical systems form a comprehensive optical system, which performs excitation scanning on 9 grades one by one in a sampling scanning mode, collects sample spectrum data of 9 different grades of titanium alloys, including TA3, TA7, TA15, TB2, TB13, TC1, TC4, TC6, and TC11, and uses G (Genetic Algorithm) to optimize SVM (Support Vector Machine) to construct a classification model algorithm. The SVM parameters are optimized through GA iteration, and the classification model is obtained through training.

[0028] The material post-processing device 6 is composed of multiple material channels, each of which is provided with a swing rod mechanism, which is pushed by a cylinder to realize the swinging action of the swing rod, and finally realizes the separation of materials. The controller of the material post-processing device 6 receives the execution instruction of the control system 5, and classifies and collects different types of materials to be tested according to the execution instruction; the control system 5 generates the execution instruction according to the classification and identification results of the materials to be tested; for example, the material post-processing device (6) includes multiple different material channels for collecting different types of materials to be tested. Multiple material collection buckets can also be provided under different material channels for collecting different materials to be tested. For example, for the classification of recycled titanium alloy materials, it includes: 9 different grades of recycled high-quality titanium alloy materials, TA3, TA7, TA15, TB2, TB13, TC1, TC4, TC6, and TC11, are provided with a swing rod mechanism, and different materials are assigned to different material channels to realize the final material identification and classification.

[0029] Example 2 like Figure 3-Figure 5 As shown, the present invention also provides a method for automatic classification and identification of recycled high-quality metals based on LIBS technology, which is applied to the above-mentioned automatic classification and identification system for recycled high-quality metals based on LIBS technology, and includes the following steps: S1. Division of excitation area: During the detection process, according to the position of the material to be tested on the material transmission module, the detection area of ​​the material to be tested is divided into a horizontal area and a vertical area. The horizontal area is the transmission direction of the material to be tested, and the detection area is divided into a front single-point scanning excitation area and a rear multi-point scanning excitation area. The vertical area division is perpendicular to the transmission direction of the material to be tested, and the detection area is divided into 1, 2, 3, ..., N areas; S2. Confirmation of detection mode and collection of material spectrum information: According to the detection requirements, the corresponding excitation mode is matched, the material to be tested is excited, and the material atomic emission spectrum information of the material to be tested is obtained; the excitation modes include single-point excitation mode, single-point and key material accumulation mode, line scan sampling mode, line scan sampling and regional multi-point accumulation mode; among them, the single-point excitation mode implements single-point excitation for flake-like materials to obtain single-point material detection information; the single-point and key material accumulation mode, based on the single-point excitation mode, performs multi-point cumulative excitation on the materials to be tested with large information differences, so as to achieve accurate classification and identification of the materials to be tested; the line scan sampling mode, for the crumb-like materials, implements sampling scanning to obtain large-scale regional spectral information; the line scan sampling and regional multi-point accumulation mode, based on the line scan sampling mode, performs small-area multi-point cumulative excitation on the areas with large information differences in a large area, so as to achieve accurate classification and identification of crumb-like materials; S3. Data processing of spectrum information of materials to be tested: It is used to detect and analyze the materials to be tested based on LIBS technology, obtain the detection information of the materials to be tested, and compare it with the model database to obtain the classification and identification results of the materials to be tested; S4. Output of classification and identification results of materials to be tested: The control system displays the classification and identification results on a visual panel; the material post-processing device classifies and collects different types of materials to be tested.

[0030] Example 2-1 Taking recycled titanium alloy materials as an example, the present invention provides a method for automatically classifying and identifying recycled high-quality metals based on LIBS technology, comprising the following steps: S1. Division of excitation area: For recycled titanium alloy chips, such as Figure 5 As shown in (a), since the scraps can cover the entire conveyor belt, the entire surface of the conveyor belt can be defined as the scraps, and the material detection area is divided into horizontal and vertical areas. The horizontal area is the material conveying direction. In this embodiment, the horizontal excitation area is divided into a front single-point scanning excitation area A and a rear multi-point scanning excitation area B; the vertical area division is perpendicular to the material conveying direction, and the detection area is divided into 1, 2, and 3 areas; S2. Confirmation of detection mode and collection of material spectrum information: For recycled titanium alloy chips, such as Figure 5 In (b), the detection mode is the line scan sampling and regional multi-point accumulation mode, in which the three areas of the material are linearly sampled and scanned in the front single-point scanning excitation area, and the average value of the spectral data of the three areas is used as the classification and identification information of the whole material; the multi-point accumulation mode can be used in the rear multi-point scanning excitation area, but no excitation is performed in this example; because the chips are spread all over the conveyor belt and the chips are moving along the conveyor belt, the frequency of the laser is relatively high, and the entire chip is scanned, forming a curved scanning path, Figure 5 The curve shown in (b) shows the path of the laser scanning the chip, and the density of the curve represents the different excitation modes; S3. Data processing of spectrum information of materials to be tested: The spectrum information of the recycled titanium alloy material is processed, and the average value of the spectrum in the three regions is used as the information of the material to be tested, which is compared with the model database to provide classification identification information; S4. Output of spectrum information of the material to be tested: According to the comparison results of S3 data, the material classification and identification information is given. For example, 9 different grades of recycled high-quality titanium alloy materials, including TA3, TA7, TA15, TB2, TB13, TC1, TC4, TC6, and TC11, are classified and identified. As shown in Table 1, the classification and identification accuracies are 96.70%, 96.40%, 95.90%, 96.81%, 96.86%, 96.79%, 95.86%, 95.72%, and 96.13%, respectively.

[0031]

[0032] Example 2-2 Taking the recycled high-quality stainless steel flakes and block materials as an example, the difference from Example 2-1 is that: for the recycled stainless steel flakes and block materials, such as Figure 5 In (c) and (d), in this embodiment, the front single-point scanning excitation area C and the rear multi-point scanning excitation area D are divided. The number of dots on a material represents different excitation modes. The detection mode of the front single-point scanning excitation area C is the single-point excitation mode, that is, single-point tracking excitation is performed on the three areas of the material. The detection mode of the rear multi-point scanning excitation area D is the single-point and key material accumulation mode, and no excitation is performed in this embodiment; Figure 5 The dots shown in (d) represent laser excitation spots, and the number of spots represents different excitation modes.

[0033] The average value of the spectral data of the three areas was used as the classification and identification information of the overall material. The grades of the tested stainless steel materials were 201, 301, 304, 309, 310, 316, 321, 410, and 430, and the test accuracy rates were 98.93%, 97.56%, 96.31%, 97.42%, 98.67%, 98.51%, 98.07%, 94.72%, and 94.72%, respectively.

[0034]

[0035] Compared with traditional metal sorting, the present invention utilizes LIBS technology to classify and identify recycled metals by elemental composition, and sets different classification and identification methods for different materials to be tested and classification and identification requirements. It integrates six modules, namely, material transmission module, material pre-treatment device to be tested, material information perception system to be tested, LIBS multi-dimensional high-throughput detection system, control system, and material post-processing device. It can realize fully automatic online classification and identification of recycled metal grades, greatly improve the classification and identification efficiency and accuracy of recycled metal grades, and finally quickly classify and identify recycled high-quality metal grades.

[0036] Matters not covered by the present invention are known technologies.

[0037] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A system for automatic classification and identification of recycled high-quality metals based on LIBS technology, characterized in that: include: A material transmission module (1), a material pre-processing device for testing (2), a material information sensing system for testing (3), a LIBS multi-dimensional high-throughput detection system (4), a control system (5), and a material post-processing device (6); The material transmission module (1) is used to transmit the material to be tested along the classification and identification assembly line; the material to be tested is a recycled high-quality metal material; The material pre-treatment device (2) is used to pre-treat the material to be tested so that the morphology and surface state of the material to be tested are relatively consistent; The material to be tested information sensing system (3) is used to collect basic information of the material to be tested and transmit it to the control system (5); the basic information includes the presence, size, shape, height and position information of the material to be tested; The control system (5) is used to control the LIBS multi-dimensional high-throughput detection system (4) based on the basic information of the material to be tested; The LIBS multi-dimensional high-throughput detection system (4) is used to detect and analyze the material to be tested based on the LIBS technology to obtain the classification and identification results of the material to be tested; The material post-processing device (6) is used to receive an execution instruction from the control system (5) and to perform classification and collection operations on different categories of materials to be tested according to the execution instruction; the control system (5) generates the execution instruction according to the classification and identification results of the materials to be tested.

2. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 1 is characterized in that: The material pre-processing device (2) includes a shearing device and a cleaning device. The shearing device is used to shear and crush the material to be tested into materials with a uniform shape. The shapes of the material to be tested include: crumb-like materials with a shape and size of 3-15 mm; flake-like materials with a shape and size of more than 15 mm. The impurity removal and cleaning equipment includes at least one of ultrasonic, high temperature and laser ablation equipment, which is used to remove impurities and clean the surface of the material to be tested so that the surface state of the material to be tested is consistent.

3. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 1 is characterized in that: The material information sensing system (3) comprises an adjustable brightness lighting system, a variable focal length optical system and an adaptive height sensing system. The adjustable brightness lighting system is used to illuminate the surface of the material to be tested so as to distinguish the material to be tested from the conveyor belt of the material transmission module (1). The variable focal length optical system is used to dynamically adjust the focal length of the lens to adapt to the size and position changes of the material to be tested and the detection requirements, thereby ensuring the imaging quality and detail capture capability. The adaptive height sensing system is used to sense the height fluctuation of the material to be tested in real time and dynamically adjust the sensor posture.

4. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 1 is characterized in that: The LIBS multi-dimensional high-throughput detection system (4) comprises a plurality of sets of single-path optical systems, wherein the single-path optical systems comprise a laser, an excitation optical path, a return optical path, and a spectrometer; The LIBS multi-dimensional high-throughput detection system (4) adopts laser-induced laser spectroscopy technology and is equipped with a fully automatic analysis program. The fully automatic analysis program automatically calculates the start time and end time of the excitation and the working state of the laser in the LIBS multi-dimensional high-throughput detection system according to the material identification state and the area of ​​the horizontal projection; The LIBS multi-dimensional high-throughput detection system (4) excites the material to be tested through multiple sets of single-path optical systems to obtain atomic emission spectrum information of the material, compares the obtained atomic emission spectrum information of the material with the material model database, and classifies and identifies the material to be tested in combination with a classification algorithm.

5. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 4 is characterized in that: The material model database is constructed by using atomic emission spectrum information of multiple recycled high-quality metals of different grades as a training set, optimizing SVM parameters through GA iteration, training to obtain a classification model, and constructing a material model database based on the classification model.

6. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 1 is characterized in that: The control system (5) controls the start and stop time and the scanning mode of the LIBS multi-dimensional high-throughput detection system (4); the control system (5) displays the classification and recognition results on a visualization panel.

7. The automatic classification and identification system for recycled high-quality metals based on LIBS technology according to claim 1 is characterized in that: The material post-processing device (6) comprises a plurality of different material channels, which are used to collect different types of materials to be tested.

8. A method for automatic classification and identification of recycled high-quality metals based on LIBS technology, applied to the automatic classification and identification system for recycled high-quality metals based on LIBS technology as described in any one of claims 1 to 7, characterized in that: The method comprises the following steps: S1, dividing the excitation area: During the detection process, according to the position of the material to be tested on the material transmission module, the detection area of ​​the material to be tested is divided into a horizontal area and a vertical area. The horizontal area is the transmission direction of the material to be tested, and the detection area is divided into a front single-point scanning excitation area and a rear multi-point scanning excitation area; the vertical area division is perpendicular to the transmission direction of the material to be tested, and the detection area is divided into 1, 2, 3, ..., N areas; S2. Confirmation of detection mode and collection of material spectrum information: According to the detection requirements, the corresponding excitation mode is matched, the material to be tested is excited, and the material atomic emission spectrum information of the material to be tested is obtained; the excitation modes include single-point excitation mode, single-point and key material accumulation mode, line scan sampling mode, line scan sampling and regional multi-point accumulation mode; S3. Data processing of spectrum information of materials to be tested: It is used to detect and analyze the materials to be tested based on LIBS technology, obtain the detection information of the materials to be tested, and compare it with the model database to obtain the classification and identification results of the materials to be tested; S4. Output of classification and identification results of materials to be tested: The control system displays the classification and identification results on a visual panel; the material post-processing device classifies and collects different types of materials to be tested.

9. The method for automatic classification and identification of recycled high-quality metals based on LIBS technology according to claim 8, characterized in that: In S2, the single-point excitation mode implements single-point excitation for flake-like materials to obtain single-point material detection information; the single-point and key material accumulation mode, based on the single-point excitation mode, performs multi-point accumulation excitation on the materials to be tested with large information differences, so as to achieve accurate classification and identification of the materials to be tested; the line scan sampling mode, for chip-like materials, implements sampling scanning to obtain large-scale regional spectral information; the line scan sampling and regional multi-point accumulation mode, based on the line scan sampling mode, performs small-area multi-point accumulation excitation on areas with large information differences in a large area, so as to achieve accurate classification and identification of chip-like materials.

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