Online detection system and method for polishing solution particles in diamond polishing process

Abstract

The invention relates to the technical field of material detection, in particular to a polishing solution particle online detection system and method in the diamond polishing process, and the method comprises the following steps: identifying particle size information of particles in a polishing solution through a particle size identification model; the particles in the detection area are dynamically excited in combination with different optical excitation conditions; synchronously collecting a first excitation response, a second excitation response and a third excitation response generated after the particles are dynamically excited; setting a fourth excitation condition to perform static excitation on the particles, and detecting a fourth excitation response generated after the particles are subjected to static excitation; combining the first excitation response, the second excitation response, the third excitation response and the fourth excitation response to form a multi-modal particle feature vector; and matching the multi-modal particle feature vector with a preset diamond model, identifying diamond particles, distinguishing non-diamond impurity particles, and outputting the concentration and particle size distribution information of the diamond particles.

Description

Technical Field

[0001] The present invention relates to the technical field of material detection, and particularly to an on-line detection system and method for polishing liquid particles during diamond polishing. Background Technique

[0002] At present, the detection of the state of diamond particles in the polishing liquid mainly relies on off-line detection methods, such as laser particle size analyzers, dynamic light scattering instruments, etc. Although these methods can provide particle size information with a certain degree of accuracy, there are problems such as poor real-time performance, susceptibility to sample sedimentation and environmental interference, and inability to identify the particle material. Especially in the repeatedly used polishing liquid, non-diamond impurity particles such as silicon carbide and alumina may be mixed in. They are similar to diamond particles in terms of refractive index, particle size, morphology, etc., and conventional detection techniques are difficult to effectively distinguish, thereby affecting the quality evaluation and use effect of the polishing liquid.

[0003] In addition, although there are microscopic differences between diamond and other high-refractive-index particles in terms of light scattering behavior, polarization response, and spectral absorption characteristics, traditional detection methods often fail to make full use of these physical characteristics for high-precision identification. Therefore, there is an urgent need for a detection system that can realize on-line identification and quantitative analysis of different component particles in the polishing liquid based on the optical, scattering or other physical characteristics of the particles.

[0004] For this reason, an on-line detection system and method for polishing liquid particles during diamond polishing are proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide an on-line detection system and method for polishing liquid particles during diamond polishing to distinguish diamond particles from non-diamond impurities in the polishing liquid and ensure the identification and measurement of only diamond abrasive grains. The system includes: a particle size identification module that identifies the particle size information of the particles in the polishing liquid through a particle size identification model; a dynamic excitation module that dynamically excites the particles in the detection area under different optical excitation conditions; a dynamic excitation response acquisition module that synchronously acquires the first excitation response, the second excitation response, and the third excitation response generated by the particles after dynamic excitation; a static excitation and detection module that sets a fourth excitation condition to statically excite the particles and detects the fourth excitation response generated by the particles after static excitation; a feature analysis and identification module that combines the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; and matches the multi-modal particle feature vector with a preset diamond model to identify diamond particles and distinguish non-diamond impurity particles, and outputs the concentration and particle size distribution information of diamond particles.

[0006] To achieve the above object, the present invention provides the following technical solutions: An on-line detection system for polishing fluid particles during diamond polishing, comprising: A particle size recognition module, configured to guide the polishing fluid to a detection area at a preset rate, and recognize the particle size information of the particles in the polishing fluid through a particle size recognition model; A dynamic excitation module, configured to dynamically excite the particles in the detection area by combining different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; A dynamic excitation response acquisition module, configured to synchronously acquire a first excitation response, a second excitation response, and a third excitation response generated by the particles after the dynamic excitation; A static excitation and detection module, configured to set a fourth excitation condition to statically excite the particles, and detect a fourth excitation response generated by the particles after the static excitation; A feature analysis and recognition module, configured to combine the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; match the multi-modal particle feature vector with a preset diamond model to identify diamond particles and distinguish non-diamond impurity particles, and output the concentration and particle size distribution information of the diamond particles.

[0007] Preferably, the particle size recognition model includes: a particle information acquisition unit, a motion trajectory extraction unit, an edge detection and contour reconstruction unit, and a particle size information estimation and calibration unit; The particle information acquisition unit continuously acquires the particle information of the particles moving with the liquid flow in the polishing fluid to obtain a particle information sequence; The motion trajectory extraction unit calculates the particle velocity and relative residence time based on the movement trajectory of the particles in the particle information sequence; The edge detection and contour reconstruction unit extracts the edges of the particles based on the particle velocity and relative residence time, and fits the two-dimensional projection contour of the particles; The particle size information estimation and calibration unit calculates the edge contour area of the particles according to the two-dimensional projection contour, and combines preset optical calibration parameters to identify the particle size information of the particles.

[0008] Preferably, the first excitation condition is to irradiate with M different laser wavelengths; the second excitation condition is to irradiate with N different laser incident angles; the third excitation condition includes a first polarization angle, a second polarization angle, and a third polarization angle.

[0009] Preferably, the third excitation condition is dynamically adjusted based on the particle size information, specifically including: If the particle size information is less than a preset first threshold, select a first polarization angle; If the particle size information is greater than and / or equal to the preset first threshold and less than and / or equal to the preset second threshold, select a second polarization angle; If the particle size information is greater than the preset second threshold, select a third polarization angle.

[0010] Preferably, the fourth excitation condition is to continuously irradiate with an ultraviolet light source of a preset wavelength to excite the fluorescence response of the particles and obtain a fourth excitation response.

[0011] Preferably, the feature analysis and recognition module includes: a particle feature extraction unit, a multi-modal particle feature fusion unit, a model matching and classification unit, and a statistical output unit; The particle feature extraction unit is used to extract feature parameters characterizing the optical properties of the particles from the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to obtain the particle features; The multi-modal particle feature fusion unit performs weighted combination on the extracted particle features to form the multi-modal particle feature vector; The model matching and classification unit trains the preset diamond model based on known diamond particle and typical impurity particle data, and matches the input multi-modal particle feature vector with the diamond model, and outputs the classification results and confidence levels of the particles as diamonds and non-diamond impurities; The statistical output unit statistically outputs the concentration and particle size distribution information of diamond particles within the detection time period according to the classification results and confidence levels.

[0012] Preferably, an on-line detection method for polishing fluid particles during diamond polishing includes: Guide the polishing fluid to the detection area at a preset rate, and identify the particle size information of the particles in the polishing fluid through a particle size recognition model; Dynamically excite the particles in the detection area under different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; Synchronously collect the first excitation response, the second excitation response, and the third excitation response generated by the particles after the dynamic excitation; Set a fourth excitation condition to statically excite the particles, and detect the fourth excitation response generated by the particles after the static excitation; Combine the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; match the multi-modal particle feature vector with a preset diamond model to identify diamond particles and distinguish non-diamond impurity particles, and output the concentration and particle size distribution information of diamond particles.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention proposes a particle size recognition model, which combines multi-unit collaborative recognition mechanisms such as trajectory analysis, edge detection, and particle size estimation to achieve online and high-precision recognition of the particle size in the polishing liquid, providing pre-information support for the personalized setting of subsequent excitation conditions. Compared with the traditional method of inferring particle size based on a single scattering image or hydrodynamic inversion, the recognition error of the present invention is significantly reduced, and it has strong adaptability. Especially in a dynamic environment with a mixture of various particles and strong background interference, it can still maintain high resolution and recognition accuracy.

[0014] 2. By introducing a multi-channel excitation mechanism and setting a combination of a dynamic excitation module and a static excitation module, the present invention collects scattering responses under different wavelengths, incident angles, polarization conditions, and ultraviolet excitation conditions, significantly enhancing the optical feature dimension of particle recognition. It can dynamically adjust excitation parameters to adapt to the response characteristics of different particle sizes. Even in the presence of optical interference or high refractive index impurities, it can still efficiently identify diamond particles, effectively solving the problem that it is difficult to distinguish diamond from alumina and silicon carbide particles due to their similar optical properties in the existing solutions.

[0015] 3. The present invention constructs a multi-modal particle feature vector and introduces a preset diamond recognition model based on machine learning training, which can fuse and analyze the high-dimensional features of various excitation responses, thereby significantly improving the classification accuracy of diamonds and non-diamond impurities and the real-time response ability of the system. Compared with the existing solutions that rely on a single response parameter for pattern matching, the present invention achieves millisecond-level response output while maintaining high accuracy, and is particularly suitable for the on-line and continuous detection requirements of the polishing liquid state in industrial scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic structural diagram of an on-line detection system for polishing liquid particles during diamond polishing provided by an embodiment of the present invention; Figure 2 It is a schematic flow diagram of an on-line detection method for polishing liquid particles during diamond polishing provided by an embodiment of the present invention; Figure 3 It is a schematic structural diagram of a particle size recognition model provided by an embodiment of the present invention; Figure 4 It is a working principle diagram of a feature analysis and recognition module provided by an embodiment of the present invention. Detailed implementation manners

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Diamond polishing is a high-precision surface treatment technology, which is widely used in fields such as optics, electronics, and precision machinery. Its core lies in using diamond particles in the polishing liquid to grind the surface of the workpiece to achieve high-quality surface finish. The particle size and distribution of diamond particles in the polishing liquid directly affect the polishing effect and are the key factors determining the polishing quality. However, in actual operation, non-diamond impurity particles are often mixed into the polishing liquid, and these impurities will interfere with the polishing process, resulting in surface defects or quality degradation. Therefore, real-time and accurate detection of the concentration and particle size distribution of diamond particles in the polishing liquid, and at the same time effectively distinguishing non-diamond impurity particles, have become important technical requirements for ensuring polishing quality.

[0019] The present invention proposes an on-line detection system and method for polishing liquid particles during diamond polishing, which can effectively distinguish diamond particles and non-diamond impurities in the polishing liquid during on-line detection of polishing liquid particles during diamond polishing, and ensure that only diamond abrasive grains are identified and measured. In order to illustrate that the method of the present invention can play a role in distinguishing diamond particles and non-diamond impurities in the polishing liquid, the effectiveness of the present invention will be described below with reference to two embodiments.

[0020] Embodiment 1 In the embodiment of the present application, the method proposed by the present invention is used to elaborate on the process of effectively distinguishing diamond particles and non-diamond impurities in the polishing liquid. The embodiment of the present application is applicable to on-line and continuous detection of the state of the polishing liquid during diamond polishing in an industrial scenario. The following will elaborate on the on-line and continuous detection process of the state of the polishing liquid during diamond polishing according to Figure 1 the content; wherein, Figure 1Specific structural diagram of the system proposed by the present invention, including: a particle size recognition module, which recognizes the particle size information of particles in the polishing liquid through a particle size recognition model; a dynamic excitation module, which dynamically excites particles in the detection area under different optical excitation conditions; a dynamic excitation response acquisition module, which synchronously acquires the first excitation response, the second excitation response, and the third excitation response generated by the particles after dynamic excitation; a static excitation and detection module, which sets a fourth excitation condition to statically excite the particles and detects the fourth excitation response generated by the particles after static excitation; a feature analysis and recognition module, which combines the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; matches the multi-modal particle feature vector with a preset diamond model, identifies diamond particles and distinguishes non-diamond impurity particles, and outputs the concentration and particle size distribution information of diamond particles. Figure 2 Specific flowchart of the method proposed by the present invention. In combination with Figure 1 and Figure 2 the content in, the following description is made: The particle size recognition module is used to guide the polishing liquid to the detection area at a preset rate and recognize the particle size information of particles in the polishing liquid through a particle size recognition model; The particle size recognition model includes: a particle information acquisition unit, a motion trajectory extraction unit, an edge detection and contour reconstruction unit, and a particle size information estimation and calibration unit; The particle information acquisition unit continuously acquires the particle information of particles moving with the liquid flow in the polishing liquid to obtain a particle information sequence; The motion trajectory extraction unit calculates the particle velocity and relative residence time based on the movement trajectory of the particles in the particle information sequence; The edge detection and contour reconstruction unit extracts the edges of the particles and fits the two-dimensional projection contour of the particles based on the particle velocity and relative residence time; The particle size information estimation and calibration unit calculates the edge contour area of the particles according to the two-dimensional projection contour and combines preset optical calibration parameters to identify the particle size information of the particles.

[0021] Specifically, first, the polishing liquid containing the particles to be measured is guided to the transparent detection area through precise pump control at a stable and preset flow rate; in this detection area, the particle information acquisition unit, which includes a light source (such as an LED stroboscopic lamp) and a high-speed imaging device (such as a CMOS camera with a frame rate of hundreds to thousands of FPS), continuously captures the flowing particles to form an image sequence containing particle motion and morphological information, and obtains a particle information sequence; The motion trajectory extraction unit processes the particle information sequence. Using the particle image velocimetry algorithm, it identifies the positions of the same particle in different frames in the particle information sequence images, thereby accurately calculating the motion speed of each particle and its relative residence time within the camera's field of view; Based on the calculated particle velocity and relative residence time, the edge detection and contour reconstruction unit uses a multi-frame fusion algorithm (in this embodiment, aligning multi-frame images based on particle trajectories and performing weighted averaging) to improve image clarity; then, through an edge detection algorithm (such as the Canny operator, Sobel operator, or an edge detection model based on machine learning), it extracts the clear edges of the particles, and further obtains the two-dimensional projection contour of the particles through contour fitting techniques (such as the minimum circumscribed circle, ellipse fitting, or irregular contour reconstruction); The particle size information estimation and calibration unit calculates the particle size information of the particles based on the reconstructed two-dimensional projection contour of the particles, including geometric parameters such as area, equivalent diameter, major and minor axes. Combining the calibration parameters of the optical system previously obtained through standard particle size particles (such as NIST-traceable microspheres), it accurately estimates the particle size information of each particle.

[0022] Table 1 is a comparison table of particle size recognition errors based on different methods.

[0023] Table 1 Comparison Table of Particle Size Recognition Errors

[0024] The particle size recognition module of this embodiment can accurately measure the particle size information of the flowing particles in the polishing liquid online and in real time through dynamic tracking and multi-frame processing techniques. Even when the particles have a certain flow rate, it can effectively overcome motion blur and ensure the accuracy of particle size measurement. The obtained accurate particle size information is not only a key parameter for evaluating the state of the polishing liquid (such as whether the abrasive size is qualified and whether there are abnormally large particles), but also provides important input for subsequent other modules (such as the adaptive adjustment of the polarization angle in the dynamic excitation module), thereby improving the intelligence level and detection accuracy of the entire detection system.

[0025] Preferably, the dynamic excitation module is used to dynamically excite the particles in the detection area in combination with different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; The first excitation condition is to irradiate with M different laser wavelengths; the second excitation condition is to irradiate with N different laser incident angles; the third excitation condition includes a first polarization angle, a second polarization angle, and a third polarization angle.

[0026] Specifically, the first excitation condition is switched by a programmable light source or a filter wheel, and M (for example, M can be set to 5, such as 405 nm, 488 nm, 532 nm, 633 nm, 785 nm) different wavelengths of lasers are used to irradiate the particles one by one to obtain the scattering or absorption characteristics of the particles at different laser wavelengths; the second excitation condition is to adjust the mirrors in the laser optical path or use a spatial light modulator to set N (for example, N can be set to 3, such as 30 degrees, 45 degrees, 60 degrees) different laser incident angles to irradiate the particles to detect the anisotropic scattering characteristics of the particles; the third excitation condition uses a liquid crystal variable phase retarder or a combination of rotating polarizers to generate polarized light with a first polarization angle (for example, 0 degrees), a second polarization angle (for example, 45 degrees), and a third polarization angle (for example, 90 degrees) to irradiate the particles, and the specific selection of the polarization angle of this third excitation condition will be dynamically adjusted based on the particle size information previously obtained by the particle size recognition module.

[0027] By combining the use of multiple different wavelengths, different incident angles, and dynamically adjusted polarization angles for excitation, the optical properties of the particles can be detected from multiple dimensions. Particles of different substances and different morphologies have different responses to these excitation conditions. This multi-parameter, dynamic excitation method significantly enhances the system's ability to obtain particle characteristic information, provides a richer and more distinguishable data basis for accurately distinguishing diamond particles from non-diamond impurity particles subsequently, and improves the sensitivity and accuracy of the distinction.

[0028] Preferably, the third excitation condition is dynamically adjusted based on the particle size information, specifically including: If the particle size information is less than a preset first threshold, the first polarization angle is selected; If the particle size information is greater than and / or equal to the preset first threshold and less than and / or equal to the preset second threshold, the second polarization angle is selected; If the particle size information is greater than the preset second threshold, the third polarization angle is selected.

[0029] Specifically, the first threshold (for example, 1 μm) and the second threshold (for example, 5 μm); When the particle size recognition module detects that the particle size information of the current particle is less than the preset first threshold, the dynamic excitation module automatically selects the first polarization angle (0-degree linearly polarized light) for excitation. If the detected particle size information is greater than or equal to the preset first threshold and less than or equal to the preset second threshold, the second polarization angle (45-degree linearly polarized light) is selected for excitation. If the particle size information of the particle is greater than the preset second threshold, the third polarization angle (90-degree linearly polarized light) is selected for excitation.

[0030] In this embodiment, the polarization angle is dynamically adjusted for particles in different particle size ranges, which can more effectively detect their polarization-related optical properties, such as depolarization effects, etc. This adaptive excitation strategy ensures high-quality polarization scattering signals for particles of various sizes, thereby improving the effectiveness of feature extraction and further enhancing the accuracy of distinguishing diamond from impurity particles, especially particles with similar morphology or material but different particle sizes.

[0031] Preferably, a dynamic excitation response acquisition module is used to synchronously acquire the first excitation response, the second excitation response, and the third excitation response generated by the particles after the dynamic excitation. Specifically, the excitation response is a scattered light spot image or an angle-resolved scattering pattern generated by the particles under each specific excitation condition.

[0032] Preferably, a static excitation and detection module is used to set a fourth excitation condition to statically excite the particles and detect the fourth excitation response generated by the particles after the static excitation. The fourth excitation condition is to continuously irradiate the particles with an ultraviolet light source of a preset wavelength to excite the fluorescence response of the particles and obtain the fourth excitation response.

[0033] Specifically, a continuous ultraviolet light source with a wavelength of 365 nm is used to excite the particles to generate a stable fluorescence signal. The acquisition system captures the excitation image of the particles under ultraviolet light irradiation and detects the corresponding fluorescence signal as the fourth excitation response to supplement and verify the particle optical characteristics obtained under dynamic excitation conditions.

[0034] Table 2 is a comparison table of the recognition rates of diamond and impurities under different excitation conditions.

[0035] Table 2 Comparison table of the recognition rates of diamond and impurities under different excitation conditions

[0036] Introducing fluorescence detection based on the inherent spectral characteristics of the material as the fourth excitation response greatly enhances the identification ability of the system. The fluorescence characteristics (such as whether it emits light, emission wavelength, fluorescence efficiency, fluorescence lifetime, etc.) of diamond and many potential non-diamond impurities (such as certain polymer microparticles, organic pollutants, other mineral particles) under ultraviolet or specific visible light excitation often have significant differences. This supplementary detection method provides strong chemical or structural fingerprint information independent of scattering characteristics for distinguishing diamond from non-diamond impurities, thereby further improving the accuracy and robustness of system recognition, especially for complex particle mixtures that are difficult to distinguish only by scattering characteristics.

[0037] Preferably, the feature analysis and recognition module includes: a particle feature extraction unit, a multi-modal particle feature fusion unit, a model matching and classification unit, and a statistical output unit; The particle feature extraction unit is used to extract feature parameters characterizing the optical properties of particles from the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response, so as to obtain the particle features; The multi-modal particle feature fusion unit performs weighted combination on the extracted particle features to form the multi-modal particle feature vector; The model matching and classification unit trains the preset diamond model based on the data of known diamond particles and typical impurity particles, and matches the input multi-modal particle feature vector with the diamond model, and outputs the classification results and confidence levels of the particles as diamond and non-diamond impurities; The statistical output unit statistically outputs the concentration and particle size distribution information of diamond particles within the detection time period according to the classification results and confidence levels.

[0038] Specifically, the particle feature extraction unit is responsible for deeply processing the three dynamic excitation responses obtained from the scattering image acquisition module and the fourth excitation response obtained from the static excitation and detection module. Total scattering intensity, integral of scattering intensity within a specific angular range, statistical moments (mean, variance, skewness, kurtosis) of the scattering angle distribution, image texture features (such as contrast, energy, entropy based on the gray-level co-occurrence matrix), degree of polarization, depolarization ratio, particle projection shape descriptors (such as roundness, elongation ratio), etc. are extracted from the first excitation response, the second excitation response, and the third excitation response; Feature parameters such as average fluorescence intensity, peak wavelength of the fluorescence spectrum, and peak area are extracted from the fourth excitation response; These parameters together constitute the particle features characterizing the multi-dimensional optical properties of a single particle; The multi-modal particle feature fusion unit first normalizes or standardizes features with different dimensions and numerical ranges, then uses feature selection algorithms (such as principal component analysis PCA, mutual information, model-based feature importance ranking) to eliminate redundant or low-contribution features, and performs intelligent weighted combination according to the discrimination ability of each feature for distinguishing diamond and impurities (adaptive learning through machine learning training), and finally forms a multi-modal particle feature vector; The model matching and classification unit first constructs a preset diamond model based on the multi-modal feature databases of a large number of labeled known diamond particles and various typical non-diamond impurity particles; then performs matching operations on the multi-modal particle feature vector and the preset diamond model through supervised machine learning algorithms (such as deep neural network DNN, support vector machine SVM, random forest RF, gradient boosting decision tree GBDT, etc.), and outputs the classification results and confidence levels of the particles being determined as diamond or non-diamond impurities.

[0039] By systematically extracting and intelligently integrating multi-source heterogeneous optical features, and using advanced data-driven machine learning models for matching and classification, not only the accurate identification of individual particle types (diamond or impurities) in the polishing fluid is achieved, but also the high-confidence particle identification results can be output in real time, realizing the effective distinction between diamond particles and impurity particles, and meeting the high-performance requirements of industrial-grade polishing fluid state monitoring. The final real-time statistical information of diamond concentration and particle size distribution provides key online quality control parameters for the production process, helping to promptly detect changes in the performance of the polishing fluid, optimize the polishing process parameters, and ensure the high quality and consistency of the final product.

[0040] An on-line detection system for polishing fluid particles during diamond polishing provided by the present invention has the ability to work in coordination with multiple modules, and can effectively distinguish diamond particles and non-diamond impurities in the polishing fluid during on-line detection of polishing fluid particles in the diamond polishing process, ensuring that only diamond abrasive grains are identified and measured. The particle size information of the particles is obtained through the particle size recognition module, and the excitation conditions are dynamically adjusted based on this, so that particles with different particle sizes obtain the optimal excitation response. The dynamic excitation module combines multiple laser wavelengths, incident angles, and polarization angles to excite the particles in multiple dimensions, and the dynamic excitation response acquisition module synchronously acquires the response data under multiple excitation conditions; the static excitation and detection module uses a specific ultraviolet laser to irradiate and excite the fluorescence response to further enrich the optical feature information of the particles. Subsequently, the feature analysis and recognition module performs in-depth feature extraction and fusion on the first to fourth excitation responses, constructs a multi-modal particle feature vector, and realizes the accurate classification and recognition of diamond particles and non-diamond impurities by matching with a preset diamond model. The system finally outputs the particle concentration and particle size distribution information, providing data support for process optimization and quality control. This system can effectively improve the intelligent level of particle recognition in the polishing fluid, reduce the influence of impurity interference on the polishing quality, and is widely applicable to the diamond polishing process in high-end fields such as optics, electronics, and precision manufacturing.

[0041] Example Two In Example One, the system proposed by the present invention successfully realized the on-line and continuous detection of the state of the polishing fluid during diamond polishing by effectively distinguishing diamond particles and non-diamond impurities in the polishing fluid in an industrial scenario. To further verify the effectiveness of the present invention, an on-line detection method for polishing fluid particles during diamond polishing is also proposed in the embodiments of this application, and the polishing fluid particles in another diamond polishing experiment are detected on-line and continuously.

[0042] The polishing fluid is guided to the detection area at a preset rate, and the particle size information of the particles in the polishing fluid is identified through the particle size recognition model; The particle size recognition model includes: a particle information acquisition unit, a motion trajectory extraction unit, an edge detection and contour reconstruction unit, and a particle size information estimation and calibration unit; The particle information acquisition unit continuously acquires the particle information of the particles moving with the liquid flow in the polishing liquid to obtain a particle information sequence; The motion trajectory extraction unit calculates the particle velocity and relative residence time based on the movement trajectory of the particles in the particle information sequence; The edge detection and contour reconstruction unit extracts the edges of the particles and fits the two-dimensional projection contour of the particles based on the particle velocity and relative residence time; The particle size information estimation and calibration unit calculates the edge contour area of the particles according to the two-dimensional projection contour, and combines preset optical calibration parameters to identify the particle size information of the particles.

[0043] Preferably, the particles in the detection area are dynamically excited under different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; The first excitation condition is to irradiate with M different laser wavelengths; the second excitation condition is to irradiate with N different laser incident angles; the third excitation condition includes a first polarization angle, a second polarization angle, and a third polarization angle.

[0044] Preferably, the third excitation condition is dynamically adjusted based on the particle size information, specifically including: If the particle size information is less than a preset first threshold, then select the first polarization angle; If the particle size information is greater than and / or equal to the preset first threshold and less than and / or equal to the preset second threshold, then select the second polarization angle; If the particle size information is greater than the preset second threshold, then select the third polarization angle.

[0045] Preferably, the first excitation response, the second excitation response, and the third excitation response generated after the particles are dynamically excited are synchronously acquired.

[0046] Preferably, a fourth excitation condition is set to statically excite the particles, and the fourth excitation response generated after the particles are statically excited is detected; The fourth excitation condition is to continuously irradiate with an ultraviolet light source of a preset wavelength to excite the fluorescence response of the particles to obtain a fourth excitation response.

[0047] Preferably, the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response are combined to form a multi-modal particle feature vector; the multi-modal particle feature vector is matched with a preset diamond model to identify diamond particles and distinguish non-diamond impurity particles, and the concentration and particle size distribution information of the diamond particles are output.

[0048] The feature analysis and recognition module includes: a particle feature extraction unit, a multi-modal particle feature fusion unit, a model matching and classification unit, and a statistical output unit; The particle feature extraction unit is used to extract feature parameters characterizing the optical properties of the particles from the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response, to obtain the particle features; The multi-modal particle feature fusion unit performs weighted combination on the extracted particle features to form the multi-modal particle feature vector; The model matching and classification unit trains the preset diamond model based on the data of known diamond particles and typical impurity particles, and matches the input multi-modal particle feature vector with the diamond model, and outputs the classification results and confidence levels of the particles as diamond and non-diamond impurities; The statistical output unit statistically outputs the concentration and particle size distribution information of the diamond particles within the detection time period according to the classification results and confidence levels.

[0049] Table 3 is a comparison table of the recognition accuracies of different methods.

[0050] Table 3 Comparison Table of Recognition Accuracies

[0051] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirits of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An on-line detection system for polishing fluid particles during the diamond polishing process, characterized in that, Including: A particle size recognition module, configured to guide the polishing liquid to a detection area at a preset rate and recognize the particle size information of the particles in the polishing liquid through a particle size recognition model; A dynamic excitation module, configured to dynamically excite the particles in the detection area by combining different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; A dynamic excitation response acquisition module, configured to synchronously acquire a first excitation response, a second excitation response, and a third excitation response generated by the particles after the dynamic excitation; A static excitation and detection module, configured to set a fourth excitation condition to statically excite the particles and detect a fourth excitation response generated by the particles after the static excitation; A feature analysis and recognition module, configured to combine the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; match the multi-modal particle feature vector with a preset diamond model to identify diamond particles and distinguish non-diamond impurity particles, and output the concentration and particle size distribution information of the diamond particles.

2. The on-line detection system for polishing liquid particles during diamond polishing according to claim 1, wherein: The particle size recognition model includes: a particle information acquisition unit, a motion trajectory extraction unit, an edge detection and contour reconstruction unit, and a particle size information estimation and calibration unit; The particle information acquisition unit continuously acquires the particle information of the particles moving with the liquid flow in the polishing liquid to obtain a particle information sequence; The motion trajectory extraction unit calculates the particle velocity and the relative residence time based on the movement trajectory of the particles in the particle information sequence; The edge detection and contour reconstruction unit extracts the edges of the particles and fits the two-dimensional projection contour of the particles based on the particle velocity and the relative residence time; The particle size information estimation and calibration unit calculates the edge contour area of the particles according to the two-dimensional projection contour and combines preset optical calibration parameters to identify the particle size information of the particles.

3. The on-line detection system for polishing liquid particles during diamond polishing according to claim 1, wherein: The first excitation condition is to irradiate with M different laser wavelengths; the second excitation condition is to irradiate with N different laser incident angles; the third excitation condition includes a first polarization angle, a second polarization angle, and a third polarization angle.

4. The on-line detection system for polishing liquid particles during diamond polishing according to claim 1, wherein: The third excitation condition is dynamically adjusted based on the particle size information, specifically including: If the particle size information is less than a preset first threshold, then select the first polarization angle; If the particle size information is greater than and / or equal to the preset first threshold and less than and / or equal to the preset second threshold, then select the second polarization angle; If the particle size information is greater than the preset second threshold, then select the third polarization angle.

5. The on-line detection system for polishing liquid particles during diamond polishing according to claim 1, wherein: The fourth excitation condition is to continuously irradiate with an ultraviolet light source of a preset wavelength to excite the fluorescence response of the particles and obtain a fourth excitation response.

6. The on-line detection system for polishing fluid particles during diamond polishing according to claim 1, wherein: The feature analysis and recognition module includes: a particle feature extraction unit, a multi-modal particle feature fusion unit, a model matching and classification unit, and a statistical output unit; The particle feature extraction unit is used to extract feature parameters characterizing the optical properties of the particles from the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to obtain the particle features; The multi-modal particle feature fusion unit performs weighted combination on the extracted particle features to form the multi-modal particle feature vector; The model matching and classification unit trains the preset diamond model based on the data of known diamond particles and typical impurity particles, and matches the input multi-modal particle feature vector with the diamond model, and outputs the classification results and confidence levels of the particles as diamond and non-diamond impurities; The statistical output unit statistically outputs the concentration and particle size distribution information of diamond particles within the detection time period according to the classification results and confidence levels.

7. An on-line detection method for polishing fluid particles during diamond polishing, characterized in that, Including: Guiding the polishing fluid to the detection area at a preset rate, and identifying the particle size information of the particles in the polishing fluid through a particle size recognition model; Dynamically exciting the particles in the detection area under different optical excitation conditions; the optical excitation conditions include a first excitation condition, a second excitation condition, and a third excitation condition; the third excitation condition is dynamically adjusted based on the particle size information; Synchronously collecting the first excitation response, the second excitation response, and the third excitation response generated after the particles are dynamically excited; Setting a fourth excitation condition to statically excite the particles, and detecting the fourth excitation response generated after the particles are statically excited; Combining the first excitation response, the second excitation response, the third excitation response, and the fourth excitation response to form a multi-modal particle feature vector; matching the multi-modal particle feature vector with a preset diamond model, identifying diamond particles and distinguishing non-diamond impurity particles, and outputting the concentration and particle size distribution information of diamond particles.

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