Flaky zinc pigment particle size analysis and detection method and system

Abstract

The invention belongs to the technical field of detection, and discloses a flaky zinc pigment particle size analysis and detection method and a flaky zinc pigment particle size analysis and detection system. And on the basis, a polarization scattering characteristic value representing anisotropic scattering characteristics of the flaky pigment particles is obtained, so that the problem that the particle size detection result is distorted due to random orientation of the flaky zinc pigment particles is effectively solved, and the effect of providing detection data really reflecting the effective particle size state is achieved.

Description

Technical Field

[0001] This application relates to the field of detection technology, and more specifically, to a method and system for particle size analysis of flake zinc pigment. Background Technology

[0002] As an important heavy-duty anti-corrosion coating, the particle size, distribution, and morphology of the flake zinc pigment in zinc-rich primers are key factors determining the final coating's density, barrier properties, and anti-corrosion performance. To ensure batch-to-batch quality stability and timely adjustment of production process parameters, zinc-rich primer production lines are typically equipped with online particle size analysis systems. These systems utilize bypass sampling lines installed on the main feed pipeline to extract high-viscosity coating slurry from the main pipeline for testing.

[0003] However, there are significant problems with directly analyzing high-concentration raw slurries using existing technologies. The slurry contains extremely high concentrations of flaky zinc pigment and is opaque, making optical detection difficult. For example, when using image-based detectors, the pigment particles are severely stacked and overlapped in the microscopic field of view captured by the camera, making it impossible to effectively segment the outline of individual particles and thus impossible to accurately measure their size. Furthermore, when attempting to use laser diffraction, the excessively high particle concentration leads to multiple scattering effects, invalidating the relationship between the scattered light signal and particle size, resulting in significant deviations in the measurement results.

[0004] To address the challenge of detecting high-concentration slurries, some online detection systems have incorporated an automatic dilution unit between the sampling pipeline and the detection module. This unit consists of a small mixing chamber, a precision metering pump, and a solvent storage tank. The high-concentration slurry drawn from the main pipeline first enters the mixing chamber, while the metering pump precisely injects a specific proportion of compatible solvent. Rapid agitation dilutes the slurry to a concentration range permissible for optical detection before it enters the detection module. This allows for the acquisition and analysis of clear, resolvable individual particle signals.

[0005] However, this dilution process introduces new technical challenges. When this small stream of slurry enters the mixing chamber of the automatic dilution unit, the high-speed injection of diluent solvent generates intense local turbulence. This turbulence completely disrupts the original stable orientation of the flake-shaped pigment particles, causing them to exhibit a completely random tumbling posture in the mixing chamber and subsequent detection flow cell. This random orientation severely affects the particle size measurement results. Specifically, for a flake-shaped particle, its projected area is largest when its front side faces the detector, and it may be identified as a large-diameter particle; while when it faces the detector with its side or edge, its projected area is smallest, and it may be identified as a small-diameter particle. Due to the random tumbling introduced by the dilution process, the detector may capture multiple projected sizes of the same particle under different postures in a short period of time, or capture a large number of particles exhibiting non-representative postures. Ultimately, the particle size distribution curve output by the system becomes abnormally broad and contains a large number of "pseudo-small particle" signals generated by the side projection of particles, resulting in a deviation between the measured average particle size value and the actual value, and a distorted particle size distribution morphology. Such measurement results cannot accurately reflect the effective particle size of pigments in the main pipeline, nor can they be used to guide the precise control of the production process, rendering the entire online detection system worthless.

[0006] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0007] The purpose of this application is to provide a method and system for analyzing and detecting the particle size of flake zinc pigment, which can effectively solve the problem of particle size measurement distortion caused by the random orientation of flake pigment particles during dilution, thereby obtaining more accurate particle size data.

[0008] In a first aspect, this application provides a method for analyzing and detecting the particle size of flake zinc pigments, used in a zinc-rich primer production line to detect the particle size data of flake zinc pigment particles in a diluted slurry diluted by an automatic dilution unit. The method includes the following steps:

[0009] A1. An irradiation beam with a preset polarization direction is emitted into the diluted slurry flowing through the detection flow cell to form scattered light;

[0010] A2. At multiple scattering angles, the intensity of multiple polarization components of the scattered light is collected using a polarization-sensitive detector;

[0011] A3. Based on the polarization component intensity, obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles;

[0012] A4. Based on the polarization scattering characteristic value, the particle size data of the flake zinc pigment particles is determined using a preset mapping relationship between the polarization scattering characteristic value and the particle size.

[0013] Preferably, the irradiation beam is a linearly polarized light beam, and the preset polarization direction is a horizontal polarization direction, a vertical polarization direction, or a 45° polarization direction;

[0014] Step A2 includes:

[0015] At least five scattering angles within the range of 0-180 degrees, the intensity of the horizontal polarization component and the intensity of the vertical polarization component of the scattered light are simultaneously acquired.

[0016] Preferably, the at least five scattering angles include a forward angle less than 90°, a lateral angle equal to 90°, and a backward angle greater than 90°.

[0017] Preferably, step A3 includes:

[0018] A301. Evaluate the signal quality of the horizontal and vertical polarization component intensities at each scattering angle to determine whether they meet the preset effective measurement range and signal-to-noise ratio requirements.

[0019] A302. Based on the signal quality assessment results, the intensity of the horizontal polarization component and the intensity of the vertical polarization component that meet the requirements are normalized to eliminate the absolute intensity changes caused by fluctuations in the concentration of the diluted slurry or optical path attenuation.

[0020] A303. Based on the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity, determine the polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles; the polarization scattering characteristic values ​​include at least one of depolarization degree, polarization ratio, and polarization ellipsoid.

[0021] Preferably, step A303 includes:

[0022] B1. For each scattering angle, obtain time series data of the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity within a preset time period;

[0023] B2. Based on the time series data, calculate the instantaneous polarization scattering characteristic value corresponding to each time point to obtain the instantaneous polarization scattering characteristic value sequence;

[0024] B3. Perform wave pattern analysis on the instantaneous polarization scattering characteristic value sequence to identify abnormal wave patterns caused by instantaneous aggregation;

[0025] B4. Based on the abnormal fluctuation pattern identification results, the instantaneous polarization scattering feature values ​​are filtered to exclude the instantaneous polarization scattering feature values ​​corresponding to the abnormal fluctuation patterns;

[0026] B5. Statistical processing is performed on the selected instantaneous polarization scattering characteristic values ​​to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

[0027] Preferably, step B2 includes at least one of the following steps:

[0028] B201. For each time point in the time series data, calculate the ratio of the absolute value of the difference between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point to the sum of the two, and obtain the instantaneous depolarization degree.

[0029] B202. For each time point in the time series data, calculate the ratio of the normalized horizontal polarization component intensity to the normalized vertical polarization component intensity corresponding to that time point to obtain the instantaneous polarization ratio.

[0030] B203. For each time point in the time series data, analyze the relative relationship between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point, and determine the instantaneous polarization ellipsoid.

[0031] Preferably, step B3 includes:

[0032] B301. For each instantaneous polarization scattering characteristic value sequence at each scattering angle, calculate its fluctuation amplitude, fluctuation duration, and fluctuation rate within a preset time window;

[0033] B302. Analyze the instantaneous ratios or instantaneous correlations between instantaneous polarization scattering eigenvalues ​​at different scattering angles;

[0034] B303. Based on the fluctuation amplitude, the fluctuation duration, the fluctuation change rate, the instantaneous ratio, and the instantaneous correlation, compare them with a preset clustering pattern criterion to identify abnormal fluctuation patterns caused by instantaneous clustering.

[0035] Preferably, step B5 includes:

[0036] B501. Obtain the original horizontal polarization component intensity and the original vertical polarization component intensity corresponding to each filtered instantaneous polarization scattering feature value, as well as its acquisition timestamp;

[0037] B502. Calculate the signal strength and signal-to-noise ratio of each instantaneous polarization scattering characteristic value based on the original horizontal polarization component intensity and the original vertical polarization component intensity;

[0038] B503. Determine the weighting factor for each instantaneous polarization scattering feature value based on the signal strength, the signal-to-noise ratio, and the time interval between the acquisition timestamp and the current processing time;

[0039] B504. Using the weighting factor, the selected instantaneous polarization scattering characteristic values ​​are weighted and averaged to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

[0040] Preferably, the preset mapping relationship between polarization scattering characteristic values ​​and particle size includes the mapping relationship between reference polarization scattering characteristic values ​​and particle size under multiple sets of different reference environmental parameter conditions;

[0041] Step A4 includes:

[0042] A401. Obtain real-time environmental parameters;

[0043] A402. Select the mapping relationships that match the reference environmental parameter conditions with the real-time environmental parameters as candidate mapping relationships;

[0044] A403. Select candidate mapping relationships that match the reference polarization scattering feature value and the polarization scattering feature value as target mapping relationships;

[0045] A404. Determine the particle size data of the flake-shaped zinc pigment particles based on the particle size corresponding to the target mapping relationship.

[0046] Secondly, this application provides a particle size analysis and detection system for flake zinc pigments, used in a zinc-rich primer production line to detect the particle size data of flake zinc pigment particles in a diluted slurry diluted by an automatic dilution unit. The system includes:

[0047] An illumination light source is used to emit an illumination beam with a preset polarization direction onto the diluted slurry flowing through the detection flow cell to form scattered light;

[0048] Multiple detector arrays are arranged around the detection flow cell at different scattering angles. Each detector array includes multiple polarization-sensitive detectors corresponding to different polarization states. The detector arrays are used to collect the intensity of multiple polarization components of the scattered light.

[0049] The host computer is used to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles based on the polarization component intensity, and to determine the particle size data of the flake zinc pigment particles based on the polarization scattering characteristic values ​​and the preset mapping relationship between the polarization scattering characteristic values ​​and the particle size.

[0050] Beneficial effects: The method and system for analyzing and detecting the particle size of flaky zinc pigment provided in this application combine an irradiation beam with a preset polarization direction with a polarization-sensitive detector to collect the intensity of polarization components at multiple scattering angles, and obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of flaky pigment particles. This effectively solves the problem of distorted particle size detection results caused by the random orientation of flaky zinc pigment particles, and achieves the effect of providing detection data that truly reflects the effective particle size state. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating the particle size analysis and detection method for flake zinc pigments provided in this application embodiment.

[0052] Figure 2 This is a schematic diagram of the structure of the flake zinc pigment particle size analysis and detection system provided in the embodiments of this application.

[0053] Labeling explanations: 1. Illumination source; 2. Detector array; 3. Host computer; 90. Detection flow cell. Detailed Implementation

[0054] The technical model of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0055] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0056] refer to Figure 1 This application proposes a method for particle size analysis of flaky zinc pigments, used in a zinc-rich primer production line to detect the particle size data of flaky zinc pigment particles in a diluted slurry diluted by an automatic dilution unit. The method includes the following steps:

[0057] A1. An irradiation beam with a preset polarization direction is emitted into the diluted slurry flowing through the detection flow cell to form scattered light;

[0058] A2. At multiple scattering angles, the intensity of multiple polarization components of the scattered light is collected using a polarization-sensitive detector;

[0059] A3. Based on the polarization component intensity, obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles;

[0060] A4. Based on the polarization scattering characteristic value, the particle size data of the flake zinc pigment particles is determined using a preset mapping relationship between the polarization scattering characteristic value and the particle size.

[0061] Among them, emitting an illumination beam with a preset polarization direction means that the direction of vibration of the electric field vector of the beam is limited to a specific plane or direction. This can be achieved by using linearly polarized light, circularly polarized light, or elliptically polarized light. For example, the light emitted by the light source is polarized by using a polarizer or waveplate. The main purpose is to take advantage of the anisotropic scattering characteristics of the particles so that the scattered light carries the particle morphology and orientation information.

[0062] Among them, "at multiple scattering angles" refers to the observation positions set in different spatial directions around the detection flow cell. This can be achieved by setting discrete angle points or continuous angle ranges. For example, measurements can be taken at multiple specific angle points within the range of 0 to 180 degrees. The main purpose is to comprehensively capture the spatial distribution information of the scattered light, which includes the combined characteristics of the particle's shape, size, and current orientation.

[0063] Among them, acquiring the intensity of multiple polarization components of scattered light using a polarization-sensitive detector refers to using a detector capable of distinguishing and measuring the intensity of light in different polarization states to obtain the light intensity of scattered light in a specific polarization direction. This can be achieved using a photodetector containing a polarization filter, a polarization camera, or a Stokes vector measurement instrument. For example, by placing a polarization analyzer in front of the photodetector to measure the intensity of the horizontal polarization component and the intensity of the vertical polarization component respectively, the main purpose is to capture the change in polarization state of the scattered light and obtain the intensity of different polarization components, laying the data foundation for subsequent extraction of polarization scattering feature values.

[0064] Among them, obtaining the polarization scattering characteristic value that characterizes the anisotropic scattering properties of the flake pigment particles refers to the value calculated based on the collected polarization component intensity, which can reflect the difference in optical response of the flake particles in different directions. It can be achieved by using at least one of depolarization degree, polarization ratio or polarization ellipticity. For example, the ratio of the absolute value of the difference between the horizontal polarization component intensity and the vertical polarization component intensity to the sum of the two can be used as the depolarization degree. Its main purpose is to transform the original polarization component intensity data into characteristic values ​​that are robust to the instantaneous random orientation of the particles, and stably characterize the true size information of the particles.

[0065] The use of a pre-defined mapping relationship between polarization scattering eigenvalues ​​and particle size refers to a pre-established mathematical model, lookup table, or database that associates polarization scattering eigenvalues ​​with particle size. This can be established through numerical simulations based on Mie scattering theory or the discrete dipole approximation (DDA), or through standard particle experiments or machine learning models. For example, a database can be established by experimentally measuring standard flake zinc pigment slurries with known particle sizes. The main purpose is to achieve accurate inference from polarization scattering eigenvalues ​​to particle size and overcome the influence of random orientation on particle size measurement.

[0066] The core innovation of this application lies in combining an illumination beam with a preset polarization direction with a polarization-sensitive detector to collect the intensity of polarization components at multiple scattering angles, and on this basis, obtaining polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of flake pigment particles. This effectively solves the problem of distorted particle size detection results caused by the random orientation of flake zinc pigment particles, and achieves the effect of providing detection data that truly reflects the effective particle size state.

[0067] Specifically, this method begins by emitting an illumination beam with a preset polarization direction into the diluted slurry flowing through the detection flow cell. This beam interacts with the flake-like zinc pigment particles in the slurry, forming scattered light containing information about the particle morphology and orientation. Subsequently, at multiple scattering angles, a polarization-sensitive detector simultaneously acquires the intensity of multiple polarization components of the scattered light. This process captures the intensity variations of the scattered light in different spatial directions and polarization states, which encompass the combined characteristics of the particle shape, size, and current orientation. Next, based on these acquired polarization component intensities, the system further obtains polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake-like pigment particles. These characteristic values ​​are calculated based on the relative relationships between the intensities of different polarization components, and they have a certain robustness to the instantaneous random orientation of the particles, enabling a more stable characterization of the true size information of the flake-like particles. Finally, based on the acquired polarization scattering characteristic values, the particle size data of the flake-like zinc pigment particles is determined using a preset mapping relationship between the polarization scattering characteristic values ​​and the particle size. This mapping relationship is pre-established, which associates processed polarization scattering characteristic values ​​that are insensitive to particle orientation with the actual particle size. This allows for accurate inference of particle size based on stable polarization scattering characteristics, even when particles are randomly tumbling, thus enabling accurate analysis and detection of the particle size of flake zinc pigment particles.

[0068] Through the above-described solution, this application effectively solves the problem of distorted particle size detection results caused by the random orientation of flake zinc pigment particles during the dilution process in zinc-rich primer production lines. This method can provide detection data that accurately reflects the effective particle size state of flake zinc pigment particles, thereby enabling online detection systems to provide valuable particle size data to guide precise control of the production process and improve the quality stability between product batches.

[0069] Preferably, the irradiation beam is a linearly polarized light beam, and the preset polarization direction is a horizontal polarization direction, a vertical polarization direction, or a 45° polarization direction;

[0070] Step A2 includes:

[0071] At least five scattering angles within the range of 0-180 degrees, the intensity of the horizontal polarization component and the intensity of the vertical polarization component of the scattered light are simultaneously acquired.

[0072] Among them, a linearly polarized light beam refers to a light wave whose electric field vector vibrates within a fixed plane, which can be realized using optical components such as polarizers, prisms, or lasers.

[0073] Synchronous acquisition refers to acquiring multiple data points or signals simultaneously at the same time point or within a very short time interval. This can be achieved using a multi-channel data acquisition system or a high-speed parallel processing unit.

[0074] This application further optimizes the characteristics of the illumination beam and the method of collecting scattered light to obtain more accurate and comprehensive anisotropic scattering information of plate-like zinc pigment particles. Specifically, by limiting the illumination beam to a linearly polarized beam and presetting its polarization direction to horizontal, vertical, or 45°, a known and stable incident light polarization state is provided for subsequent analysis. For plate-like pigment particles, which exhibit significant anisotropic characteristics, the polarization state of their scattered light strongly depends on the polarization direction of the incident light and the spatial orientation of the particles themselves. Using linearly polarized light as the incident light and selecting these typical polarization directions ensures that the scattered light contains rich and resolvable polarization information, laying the foundation for subsequent analysis of the anisotropic scattering characteristics of the particles.

[0075] By applying the aforementioned limitations, this method can more effectively extract the true anisotropic scattering characteristics from randomly oriented flake-like pigment particles. When linearly polarized light is incident on randomly tumbling flake-like particles in a specific direction, the polarization state of the scattered light undergoes a unique change due to the instantaneous orientation of the particles. By simultaneously measuring the horizontal and vertical polarization components at multiple angles, the system can capture these subtle polarization changes, which contain information about the true size and shape of the particles, rather than just their projected size. This high-quality, high-reliability raw data is then used to calculate polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of flake-like pigment particles. This more refined and comprehensive data acquisition method enables subsequent characteristic value calculations and particle size determination processes to effectively distinguish between the true size of the particles and the "pseudo-small particle" signal caused by random orientation, thereby obtaining more accurate particle size data and overcoming the problem of inaccurate particle size measurement caused by random particle orientation in existing technologies.

[0076] Furthermore, the at least five scattering angles include a forward angle less than 90°, a lateral angle equal to 90°, and a backward angle greater than 90°. For example... Figure 2 In the diagram, the scattering angles corresponding to the two detector arrays 2 on the left are the forward angles, and the scattering angles corresponding to the two detector arrays 2 on the right are the backward angles.

[0077] Forward angles less than 90° are primarily used to capture information about light diffraction and forward scattering after passing through particles; this scattered light is typically related to the overall size and projected area of ​​the particle. Lateral angles equal to 90° are significant for understanding the anisotropic scattering characteristics of plate-like particles. In this direction, the interaction between light and particles is more complex, and its polarization characteristics are sensitive to the particle's shape, surface structure, and instantaneous orientation. Backward angles greater than 90° provide supplementary information about the particle's internal structure, surface roughness, and multiple scattering effects; this information is valuable for distinguishing plate-like particles of different shapes and orientations. By covering these representative angle ranges, sufficient angular diversity and information richness are ensured in the collected polarization scattering data.

[0078] By explicitly specifying that at least five scattering angles of the collected scattered light should cover a forward angle less than 90°, a lateral angle equal to 90°, and a backward angle greater than 90°, this application ensures that the collected polarization scattering data has sufficient angular diversity and information richness. This allows for a more comprehensive and accurate characterization of the anisotropic scattering properties of the flake-like zinc pigment particles, effectively addressing the measurement challenges posed by random particle tumbling. Consequently, the sensitivity of the subsequently calculated polarization scattering characteristic values ​​to the true shape, orientation, and particle size information of the particles is enhanced, thereby significantly improving the accuracy and robustness of particle size data determination and effectively avoiding measurement distortion caused by random tumbling of flake-like particles during dilution.

[0079] In a preferred embodiment, at least five scattering angles can be specifically set as follows: the forward angle can include 30° and 60°, the lateral angle can be 90°, and the backward angle can include 120° and 150°. In actual operation, multiple polarization-sensitive detector arrays can be arranged around the detection flow cell. For example, a detector array can be configured at each of the five scattering angle positions of 30°, 60°, 90°, 120°, and 150° (e.g., Figure 2 (As shown). Each detector array can contain polarization-sensitive detectors for simultaneously acquiring the horizontal and vertical polarization component intensities. When an illumination beam with a preset polarization direction passes through the diluted slurry and forms scattered light, these detector arrays located at different angles can simultaneously receive and acquire the horizontal and vertical polarization component intensities corresponding to the scattering angle. This ensures comprehensive capture of the scattering characteristics of the flake-like zinc pigment particles in different directions, providing rich and representative raw data for subsequent calculations of polarization scattering characteristic values.

[0080] In some implementations, step A3 includes:

[0081] A301. Evaluate the signal quality of the horizontal and vertical polarization component intensities at each scattering angle to determine whether they meet the preset effective measurement range and signal-to-noise ratio requirements.

[0082] A302. Based on the signal quality assessment results, the intensity of the horizontal polarization component and the intensity of the vertical polarization component that meet the requirements are normalized to eliminate the absolute intensity changes caused by fluctuations in the concentration of the diluted slurry or optical path attenuation.

[0083] A303. Based on the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity, determine the polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles; the polarization scattering characteristic values ​​include at least one of depolarization degree, polarization ratio, and polarization ellipsoid.

[0084] Signal quality assessment refers to judging the reliability of the acquired horizontal and vertical polarization component intensities using preset criteria. This can include checking whether the signal intensity is within the effective measurement range, for example, setting a minimum intensity threshold to exclude excessively weak signals, and / or setting a maximum intensity threshold to exclude saturated signals; simultaneously, the signal-to-noise ratio (SNR) can be evaluated to ensure that the effective components of the signal are much higher than the noise level, for example, by calculating the ratio of the signal mean to the noise standard deviation (which can be pre-calibrated).

[0085] The preset effective measurement range and signal-to-noise ratio (SNR) requirements refer to the specific values ​​or standards used when evaluating signal quality. The effective measurement range can be a set of upper and lower limits to define an acceptable range of signal strength; the SNR requirement can be a minimum ratio below which data is considered unreliable. These requirements can be preset based on experimental data, sensor characteristics, or application needs.

[0086] Intensity normalization refers to a data transformation performed on the horizontal and vertical polarization component intensities to meet signal quality requirements, aiming to eliminate absolute intensity variations unrelated to particle characteristics. This can be achieved in various ways, such as dividing the horizontal and vertical polarization component intensities at each scattering angle by their sum, or dividing by a preset reference intensity value, or using other mathematical transformations to make them comparable under different measurement conditions.

[0087] Among them, polarization scattering eigenvalues ​​refer to quantitative parameters that characterize the anisotropic scattering properties of flake-shaped pigment particles by analyzing the changes in the polarization state of scattered light. These parameters can reflect the shape, orientation, and interaction mode of the particles with light. They can include depolarization degree, which is a measure of the difference between the polarization state of the scattered light and the polarization state of the incident light; polarization ratio, which is the ratio between the intensities of different polarization components; and polarization ellipticity, which is the shape parameter of the polarization ellipse of the scattered light, such as the major-minor axis ratio or azimuth angle.

[0088] This application ensures the accuracy and reliability of subsequent polarization scattering characteristic value calculations by preprocessing the raw polarization component intensities. After acquiring the horizontal and vertical polarization component intensities of the scattered light, a signal quality assessment is first performed on the horizontal and vertical polarization component intensities at each scattering angle. This assessment aims to determine whether the acquired raw data meets the preset effective measurement range and signal-to-noise ratio requirements. This step effectively filters out high-quality raw data, eliminating data distortion caused by excessively weak, strong, or noisy signals, thereby avoiding the introduction of unreliable measurement results into subsequent calculations and ensuring the purity of the data source. Based on this, according to the signal quality assessment results, the horizontal and vertical polarization component intensities that meet the requirements are normalized. The key to this processing is to eliminate absolute intensity changes caused by fluctuations in the concentration of diluted slurry or optical path attenuation. Since these external factors can cause non-particle-related changes in the overall intensity of the scattered light signal, without normalization, the polarization component intensities measured at different time points or in different batches will be incomparable. By normalizing, this method ensures that the subsequently calculated polarization scattering eigenvalues ​​reflect only the anisotropic scattering characteristics of the particles themselves, unaffected by external environmental factors, thus improving the stability of the measurement results. Finally, based on the horizontal and vertical polarization component intensities after quality assessment and intensity normalization, polarization scattering eigenvalues ​​characterizing the anisotropic scattering properties of the flake-like pigment particles are determined. These eigenvalues ​​are parameters specifically used to quantify the change in polarization state when light interacts with anisotropic particles. Calculating these eigenvalues ​​using preprocessed, high-quality, and normalized intensity data ensures that they accurately and stably reflect the true shape and orientation information of the flake-like zinc pigment particles, providing reliable input for the subsequent accurate determination of particle size.

[0089] Through the synergistic effect of the above steps, this scheme, after acquiring the intensity of the polarization component of the scattered light, can effectively address potential signal quality issues and external environmental interference in actual testing, thereby obtaining more accurate and stable polarization scattering characteristic values. These optimized characteristic values, serving as the basis for subsequent particle size determination, significantly improve the accuracy and reliability of the entire method for analyzing and detecting the particle size of flake zinc pigments. This allows the final particle size data to more accurately reflect the actual state of the pigment particles, thus better guiding the production process of zinc-rich primers.

[0090] Preferably, step A303 may include:

[0091] B1. For each scattering angle, obtain time series data of the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity within a preset time period;

[0092] B2. Based on the time series data, calculate the instantaneous polarization scattering characteristic value corresponding to each time point to obtain the instantaneous polarization scattering characteristic value sequence;

[0093] B3. Perform wave pattern analysis on the instantaneous polarization scattering characteristic value sequence to identify abnormal wave patterns caused by instantaneous aggregation;

[0094] B4. Based on the abnormal fluctuation pattern identification results, the instantaneous polarization scattering feature values ​​are filtered to exclude the instantaneous polarization scattering feature values ​​corresponding to the abnormal fluctuation patterns;

[0095] B5. Statistical processing is performed on the selected instantaneous polarization scattering characteristic values ​​to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

[0096] The preset time period refers to a continuous time interval used to continuously collect polarization component intensity data. Its length can be set according to actual detection needs and particle flow rate to ensure that the dynamic behavior of particles can be captured.

[0097] Among them, time series data refers to the set of data in which the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity are continuously collected for each scattering angle within a preset time period and arranged in chronological order.

[0098] Instantaneous polarization scattering eigenvalues ​​refer to numerical values ​​characterizing the anisotropic scattering properties of flaky pigment particles, calculated based on the normalized horizontal and vertical polarization component intensities at each specific time point in the time series data. Examples include instantaneous depolarization degree, instantaneous polarization ratio, or instantaneous polarization ellipticity. A sequence of instantaneous polarization scattering eigenvalues ​​refers to a complete dataset composed of these instantaneous polarization scattering eigenvalues ​​calculated at different time points arranged in chronological order.

[0099] Among them, fluctuation pattern analysis refers to in-depth mathematical and statistical analysis of instantaneous polarization scattering characteristic value sequences to identify specific patterns or trends in the data. It can be implemented using time series analysis, signal processing, or pattern recognition algorithms. Abnormal fluctuation patterns refer to the abnormal fluctuation patterns identified in fluctuation pattern analysis that deviate from the normal, stable scattering behavior of flaky pigment particles and are caused by non-steady-state factors such as instantaneous agglomeration or violent particle tumbling.

[0100] In step B4, the filtering refers to removing data points that are identified as abnormal from the instantaneous polarization scattering feature value sequence based on the results of abnormal fluctuation pattern identification, so as to ensure the data quality of subsequent processing.

[0101] Statistical processing refers to performing mathematical operations on the selected instantaneous polarization scattering characteristic values ​​to extract their overall characteristics or representative values. This can be achieved by methods such as calculating the average, median, mode, or weighted average.

[0102] The overall operational logic of this solution lies in overcoming the abnormal fluctuations in polarization scattering characteristic values ​​caused by the instantaneous agglomeration or random tumbling of flaky pigment particles during online detection. Instead of relying solely on measurement data at a single moment, it introduces time-dimensional data acquisition and intelligent processing. First, for each scattering angle, the system continuously acquires time-series data of the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity within a preset time period. This continuous acquisition process captures the dynamically changing scattering information of particles in the fluid, laying the foundation for subsequent detailed analysis. Next, based on this time-series data, the system calculates the corresponding instantaneous polarization scattering characteristic value at each time point, thus forming a sequence of instantaneous polarization scattering characteristic values ​​reflecting the dynamic changes in particle scattering characteristics. Subsequently, fluctuation pattern analysis is performed on this instantaneous polarization scattering characteristic value sequence. This is a crucial step in identifying anomalies. By analyzing the fluctuation amplitude, frequency, and duration of the data, abnormal fluctuation patterns caused by non-steady-state factors such as instantaneous agglomeration or violent particle tumbling can be effectively identified. Once an abnormal pattern is identified, the system filters the instantaneous polarization scattering feature values ​​based on the identification results, excluding abnormal data points affected by transient interference to ensure the purity of data in subsequent processing. Finally, the filtered instantaneous polarization scattering feature values ​​are statistically processed, such as by calculating the average or median, to obtain a stable polarization scattering feature value that truly reflects the inherent anisotropic scattering characteristics of the flake pigment particles.

[0103] By employing the aforementioned technical methods, this solution effectively addresses the problem of abnormal fluctuations or unstable data in polarization scattering characteristic values ​​calculated directly from the instantaneously acquired polarization component intensity during online detection. This is caused by the instantaneous agglomeration or random tumbling of flaky zinc pigment particles in the diluted slurry. By acquiring time-series data within a preset time period and performing fluctuation pattern analysis and anomaly screening on the instantaneous polarization scattering characteristic value sequence, interference data caused by non-steady-state factors such as instantaneous agglomeration can be effectively identified and eliminated. Statistical processing of the screened data yields a more stable, accurate, and truly reflective polarization scattering characteristic value that accurately reflects the inherent anisotropic scattering characteristics of flaky pigment particles. This significantly improves the reliability of polarization scattering characteristic value determination, thus providing a solid foundation for the accuracy and stability of subsequent particle size data, making the online particle size detection results more representative and instructive.

[0104] Specifically, step B2 includes at least one of the following steps:

[0105] B201. For each time point in the time series data, calculate the ratio of the absolute value of the difference between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point to the sum of the two, and obtain the instantaneous depolarization degree.

[0106] B202. For each time point in the time series data, calculate the ratio of the normalized horizontal polarization component intensity to the normalized vertical polarization component intensity corresponding to that time point to obtain the instantaneous polarization ratio.

[0107] B203. For each time point in the time series data, analyze the relative relationship between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point, and determine the instantaneous polarization ellipsoid.

[0108] The instantaneous depolarization degree, i.e. the instantaneous value of the depolarization degree, is a quantitative indicator of the change in the polarization state of scattered light. It can be calculated based on the ratio of the absolute value of the difference between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity to the sum of the two.

[0109] The instantaneous polarization ratio, i.e. the instantaneous value of the polarization ratio, is the proportional relationship of the intensity distribution of scattered light in the horizontal and vertical polarization directions. It can be calculated based on the ratio of the normalized horizontal polarization component intensity to the normalized vertical polarization component intensity.

[0110] The instantaneous polarization ellipticity, i.e. the instantaneous value of the polarization ellipticity, is a complete description of the polarization state of the scattered light, including information such as its ellipticity and principal axis direction. It can be determined by analyzing the relative phase and amplitude relationship between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity using polarization measurement and analysis techniques such as the Stokes vector method, the Jones matrix method, or the Mueller matrix method.

[0111] Specifically, by calculating at least one of instantaneous depolarization degree, instantaneous polarization ratio, or instantaneous polarization ellipticity, this method can accurately capture the dynamic changes in the polarization state of scattered light caused by the random tumbling and instantaneous agglomeration of flake pigment particles in diluted slurry from multiple dimensions. When particles instantaneously agglomerate, their scattering characteristics change significantly, causing the polarization state of the scattered light to deviate from the expected behavior of individual particles. Instantaneous depolarization degree quantifies the degree of randomness in the polarization state of scattered light; multiple scattering caused by agglomeration increases the depolarization effect, thus exhibiting abnormal fluctuations in depolarization degree. The instantaneous polarization ratio directly reflects the intensity distribution of scattered light in different polarization directions; changes in the orientation of flake particles and the formation of agglomerates alter this ratio, providing a basis for distinguishing between normal orientation and agglomeration signals. Instantaneous polarization ellipticity provides a more complete description of the polarization state of scattered light, capable of capturing minute polarization state changes caused by complex orientation or agglomeration; these changes are a strong basis for identifying abnormal fluctuation patterns. By providing these instantaneous feature values ​​with clear physical meaning and sensitivity to changes in particle state, this scheme provides high-quality, high-discrimination input data for subsequent wave pattern analysis. This means that when the system performs wave pattern analysis on the instantaneous polarization scattering feature value sequence, it can more accurately identify abnormal wave patterns caused by instantaneous agglomeration, because these patterns have unique and identifiable signal characteristics in terms of depolarization degree, polarization ratio, or polarization ellipsoid. Subsequently, the system can effectively filter the instantaneous polarization scattering feature values ​​based on the identification results, eliminating abnormal data points affected by instantaneous agglomeration. Finally, statistical processing is performed on the filtered instantaneous polarization scattering feature values ​​to obtain more realistic and accurate polarization scattering feature values ​​that characterize the anisotropic scattering properties of flaky pigment particles, thereby ensuring the reliability of the finally determined particle size data. This refined feature value calculation enables the entire particle size analysis and detection method to effectively overcome measurement errors caused by instantaneous agglomeration when dealing with anisotropic particles in complex fluids, significantly improving the accuracy and stability of the detection results.

[0112] By clarifying the specific calculation methods for instantaneous polarization scattering characteristic values, including the calculation of instantaneous depolarization degree, instantaneous polarization ratio, or instantaneous polarization ellipticity, this scheme can more accurately and comprehensively reflect the anisotropic scattering characteristics of flake pigment particles and the instantaneous aggregation phenomenon that may occur during dilution. This provides a more reliable and discriminative data foundation for the subsequent identification and elimination of abnormal fluctuation patterns caused by instantaneous aggregation, thereby ensuring that the final determined particle size data has higher accuracy.

[0113] In one specific implementation, after acquiring time-series data of the normalized horizontal polarization component intensity (Ih) and normalized vertical polarization component intensity (Iv) for each scattering angle, the following calculations are performed: For the instantaneous depolarization degree (DOP), the corresponding instantaneous depolarization degree can be calculated for each time point in the time-series data, and the calculation formula can be expressed as: DOP = |Ih - Iv| / (Ih + Iv). For the instantaneous polarization ratio (PR), the corresponding instantaneous polarization ratio can be calculated for each time point in the time-series data, and the calculation formula can be expressed as: PR = Ih / Iv. For the instantaneous polarization ellipticity (E1), a Stokes vector S can be constructed for each time point in the time-series data based on the normalized horizontal polarization component intensity Ih and the normalized vertical polarization component intensity Iv, and then the parameters of the polarization elliptic, such as the ellipticity angle or azimuth angle, can be calculated based on the Stokes vector S as the instantaneous polarization ellipticity. For example, a polarization analysis algorithm library can be used to calculate and output the instantaneous polarization ellipticity in real time, taking into input the normalized horizontal and vertical polarization component intensities, as well as other possible polarization component intensities (such as the 45-degree polarization component intensity). These calculations can be performed by a dedicated digital signal processor (DSP) or a general-purpose processor (e.g., software running on a host computer), ensuring fast and accurate calculation of polarization scattering eigenvalues ​​at each time point, thereby generating a sequence of instantaneous polarization scattering eigenvalues ​​for subsequent analysis.

[0114] Preferably, step B3 may include:

[0115] B301. For each instantaneous polarization scattering characteristic value sequence at each scattering angle, calculate its fluctuation amplitude, fluctuation duration, and fluctuation rate within a preset time window;

[0116] B302. Analyze the instantaneous ratios or instantaneous correlations between instantaneous polarization scattering eigenvalues ​​at different scattering angles;

[0117] B303. Based on the fluctuation amplitude, the fluctuation duration, the fluctuation change rate, the instantaneous ratio, and the instantaneous correlation, compare them with a preset clustering pattern criterion to identify abnormal fluctuation patterns caused by instantaneous clustering.

[0118] The preset time window refers to a continuous time interval used to extract the instantaneous polarization scattering characteristic value sequence for local analysis during data acquisition and processing. It can be set according to factors such as the typical motion speed of particles in the fluid, the time scale of agglomeration and disintegration, and the data sampling frequency. For example, it can be set to a fixed duration of several milliseconds to hundreds of milliseconds, or it can be dynamically adjusted according to the characteristics of the real-time data stream.

[0119] Among them, the preset aggregation pattern criterion refers to a set of rules or thresholds used to determine whether the instantaneous polarization scattering feature value sequence conforms to the abnormal fluctuation characteristics caused by instantaneous aggregation. It can be established based on a large amount of experimental data or simulation models. For example, it can include the upper and lower limits of fluctuation amplitude, duration, and rate of change, as well as specific ranges or patterns of instantaneous ratios or correlations between different scattering angles. These criteria can be stored and applied in the form of lookup tables, decision trees, or machine learning models.

[0120] This scheme analyzes the fluctuation patterns of instantaneous polarization scattering feature value sequences. First, for each scattering angle, the fluctuation amplitude, duration, and rate of change within a preset time window are calculated. This process quantifies the dynamic characteristics of the signal at each angle in the time dimension, providing fundamental data for subsequent pattern recognition. The fluctuation amplitude captures the instantaneous and drastic changes in signal strength or feature values, the fluctuation duration distinguishes between transient noise and sustained events, and the rate of change describes the speed of cluster formation or disintegration. Next, the instantaneous ratios or correlations between instantaneous polarization scattering feature values ​​at different scattering angles are analyzed. This step introduces information in the spatial dimension, utilizing the anisotropic characteristics of sheet-like particle scattering to capture the coordinated changes in scattering signals at different angles during clustering. This cross-angle analysis enhances the robustness of recognition and avoids misjudgment. Finally, the acquired feature parameters are comprehensively utilized, and the fluctuation amplitude, duration, rate of change, instantaneous ratio, and instantaneous correlation are compared with preset clustering pattern criteria to identify abnormal fluctuation patterns caused by instantaneous clustering. This comprehensive discrimination based on multi-dimensional features makes the identification process more accurate and reliable, effectively eliminating interference caused by other non-clustering factors.

[0121] It is precisely because of the introduction of this refined and multi-dimensional analysis that this scheme no longer relies solely on a single or simple fluctuation analysis method. Instead, it constructs a multi-dimensional discrimination system by introducing refined quantification in the time dimension and analysis in the spatial dimension. This system enables the system to more comprehensively and deeply understand the dynamic behavior of the instantaneous polarization scattering characteristic value sequence. Thus, even in complex detection environments with random particle tumbling or other instantaneous interference, it can accurately distinguish abnormal fluctuations truly caused by instantaneous aggregation. This improvement in analysis method significantly enhances the accuracy and robustness of abnormal fluctuation pattern recognition, thereby ensuring the effectiveness of subsequent data screening and ultimately obtaining more realistic and reliable particle size data for flaky zinc pigments, solving the problem of particle size data distortion in previous schemes.

[0122] In a specific embodiment, for the instantaneous polarization scattering characteristic value sequence at each scattering angle, a sliding time window method can be used to calculate its fluctuation characteristics. For example, a preset time window of 50 milliseconds can be set. Within this time window, the fluctuation amplitude can be calculated as the difference between the maximum and minimum values ​​of the sequence; the fluctuation duration can be defined as the length of time during which the characteristic value continuously exceeds a certain preset threshold; and the fluctuation change rate can be calculated as the maximum rate of change of the characteristic value within the sliding time window, for example, by calculating the absolute value of the difference between characteristic values ​​at adjacent time points and taking the maximum value. Simultaneously, the instantaneous ratios or instantaneous correlations between instantaneous polarization scattering characteristic values ​​at different scattering angles can be analyzed. For example, the ratio of instantaneous polarization scattering characteristic values ​​(such as instantaneous depolarization degree) at a forward scattering angle (e.g., 10 degrees) to those at a side scattering angle (e.g., 90 degrees) can be calculated, or the Pearson correlation coefficient between them can be calculated. When aggregation occurs, these ratios or correlations can exhibit specific patterns different from the random tumbling of individual particles. Subsequently, based on the calculated fluctuation amplitude, fluctuation duration, fluctuation change rate, instantaneous ratio, and instantaneous correlation, they can be compared with preset aggregation mode criteria. These criteria can be stored in a lookup table. For example, if the fluctuation amplitude exceeds value A, the duration exceeds value B, the rate of change exceeds value C, and the instantaneous ratio between specific angles falls within the range of D to E, then it can be determined as an abnormal fluctuation pattern caused by instantaneous clustering. Alternatively, a machine learning-based classifier, such as a support vector machine or neural network, can be used to learn the features of clustering and non-clustering patterns through training, thereby identifying abnormal fluctuation patterns.

[0123] Preferably, step B5 may include:

[0124] B501. Obtain the original horizontal polarization component intensity and the original vertical polarization component intensity corresponding to each filtered instantaneous polarization scattering feature value, as well as its acquisition timestamp;

[0125] B502. Calculate the signal strength and signal-to-noise ratio of each instantaneous polarization scattering characteristic value based on the original horizontal polarization component intensity and the original vertical polarization component intensity;

[0126] B503. Determine the weighting factor for each instantaneous polarization scattering feature value based on the signal strength, the signal-to-noise ratio, and the time interval between the acquisition timestamp and the current processing time;

[0127] B504. Using the weighting factor, the selected instantaneous polarization scattering characteristic values ​​are weighted and averaged to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

[0128] Signal strength refers to the amplitude or energy of the measured signal, which can be expressed as the sum of the original horizontal polarization component strength and the original vertical polarization component strength, or the square root of the sum of their squares.

[0129] The signal-to-noise ratio (SNR) refers to the power ratio or amplitude ratio of the signal to the noise. It can be calculated by using the ratio of the average value of the signal to the standard deviation of the noise (which can be pre-calibrated), or by evaluating the purity of the signal through a specific algorithm.

[0130] The weighting factor refers to the relative importance coefficient assigned to each data point in the statistical processing. It can be determined by function mapping, lookup table or machine learning model based on the evaluation results of data quality and timeliness.

[0131] Weighted average processing refers to assigning different weights to each data point based on its importance when averaging a set of data points. This can be achieved by multiplying each data point by its corresponding weight, summing the results, and finally dividing by the sum of all weights.

[0132] The statistical processing method in this application provides a foundation for subsequent data quality and timeliness assessment by acquiring the original horizontal polarization component intensity, the original vertical polarization component intensity, and the acquisition timestamp corresponding to each filtered instantaneous polarization scattering feature value. Based on these original intensity data, the system can calculate the signal strength and signal-to-noise ratio (SNR) of each instantaneous polarization scattering feature value, thereby quantifying its data quality. Signal strength reflects the strength of the measured signal, while SNR directly indicates the reliability of the data, enabling the system to identify and distinguish data points of different qualities. Furthermore, the system comprehensively considers the signal strength, SNR, and the time interval between the acquisition timestamp and the current processing time to determine the weighting factor for each instantaneous polarization scattering feature value. This means that data points with higher data quality and stronger timeliness will be given greater weight, ensuring priority reflection of the current true state. Finally, using these determined weighting factors, the filtered instantaneous polarization scattering feature values ​​are weighted and averaged to obtain polarization scattering feature values ​​characterizing the anisotropic scattering properties of the flake pigment particles. This weighted averaging mechanism, combined with the aforementioned step of filtering instantaneous polarization scattering characteristic values ​​to eliminate abnormal fluctuation patterns, forms a more complete data processing workflow. By first eliminating abnormal data caused by instantaneous aggregation, and then performing weighted statistics on the remaining valid data based on quality and timeliness, this method can effectively reduce the impact of low-quality or outdated data on the final results, while highlighting the contribution of high-quality and timely data. This combination ensures that the final obtained polarization scattering characteristic values ​​not only eliminate aggregation interference but also significantly improve data quality and real-time performance, providing a more solid and reliable foundation for the accurate determination of subsequent particle size data.

[0133] In a specific embodiment, the statistical processing of the filtered instantaneous polarization scattering feature values ​​can be implemented as follows: First, for each filtered instantaneous polarization scattering feature value, the system can directly obtain the original horizontal polarization component intensity and the original vertical polarization component intensity corresponding to its generation from the data acquisition module, and simultaneously record the system timestamp when these original data were acquired. For example, these intensity values ​​can be the digital quantity of the voltage signal output by the photodetector after analog-to-digital conversion, and the timestamp can be the nanosecond-level count of the system's real-time clock. Next, the system can calculate the signal strength and signal-to-noise ratio of each instantaneous polarization scattering feature value based on the acquired original horizontal polarization component intensity and the original vertical polarization component intensity. The signal strength can be simply defined as the sum of the original horizontal polarization component intensity and the original vertical polarization component intensity, while the signal-to-noise ratio can be estimated based on a preset noise model or through real-time measurement of background noise, for example, it can be expressed as the ratio of the signal average value to the noise standard deviation. Then, the system can determine the weighting factor of each instantaneous polarization scattering feature value based on the calculated signal strength, signal-to-noise ratio, and the time interval between the acquisition timestamp and the current processing time. For example, a weighting function can be defined that assigns greater weight to data points with higher signal strength, better signal-to-noise ratio, and shorter time intervals. For instance, an exponential decay function can be used to reflect the impact of time intervals on weighting, combined with linear or nonlinear weighting of signal strength and signal-to-noise ratio. Finally, the system uses these determined weighting factors to perform a weighted average on the selected instantaneous polarization scattering characteristic values. Specifically, each selected instantaneous polarization scattering characteristic value is multiplied by its corresponding weighting factor, then all weighted values ​​are summed and divided by the sum of all weighting factors to obtain the final polarization scattering characteristic value characterizing the anisotropic scattering properties of the flake pigment particles.

[0134] In some implementations, the preset mapping relationship between polarization scattering characteristic values ​​and particle size includes the mapping relationship between reference polarization scattering characteristic values ​​and particle size under multiple sets of different reference environmental parameter conditions;

[0135] Step A4 includes:

[0136] A401. Obtain real-time environmental parameters;

[0137] A402. Select the mapping relationships that match the reference environmental parameter conditions with the real-time environmental parameters as candidate mapping relationships;

[0138] A403. Select candidate mapping relationships that match the reference polarization scattering feature value and the polarization scattering feature value as target mapping relationships;

[0139] A404. Determine the particle size data of the flake-shaped zinc pigment particles based on the particle size corresponding to the target mapping relationship.

[0140] The pre-defined mapping relationship between polarization scattering characteristic values ​​and particle size, including the mapping relationship between reference polarization scattering characteristic values ​​and particle size under multiple sets of different reference environmental parameters, refers to a series of mathematical models or lookup tables established under different environmental conditions that associate polarization scattering characteristic values ​​with the particle size of flake zinc pigment particles. This can be achieved by measuring the polarization scattering of flake zinc pigment samples of known particle sizes in a laboratory under various pre-defined combinations of reference environmental parameters such as temperature, pressure, humidity, solvent type, or concentration, and recording the corresponding polarization scattering characteristic values, thereby constructing multiple sets of mapping relationships. These mapping relationships can be stored as multidimensional lookup tables, regression model sets, or neural network models.

[0141] Real-time environmental parameters refer to the actual physical or chemical parameters (temperature, pressure, humidity, solvent type or concentration, etc.) in the current production line or testing environment during particle size detection. These parameters can be obtained in real time through sensors integrated into the detection system and from the control center of the production line.

[0142] Among them, the candidate mapping relationship refers to the set of mapping relationships that are initially selected from multiple preset mapping relationships based on real-time environmental parameters and are consistent with or close to the current environmental conditions. It can select mapping relationships with differences within a preset threshold range by comparing the differences between the real-time environmental parameters and the reference environmental parameters when each mapping relationship was established. For example, it can calculate the similarity value between the two. If the similarity value is higher than the preset similarity threshold, it is determined that the two match.

[0143] Among them, the target mapping relationship refers to the mapping relationship or set of mapping relationships that is most matched with the currently measured polarization scattering feature value after further screening from the candidate mapping relationships. It can be calculated by substituting the measured polarization scattering feature value into the candidate mapping relationship for inversion calculation, or by comparing the similarity P between the actual polarization scattering feature value and the reference polarization scattering feature value in the candidate mapping relationship, and selecting the mapping relationship or set of mapping relationships with the highest similarity P.

[0144] If the target mapping relationship is a single mapping relationship, then in step A404, the particle size corresponding to the mapping relationship is used as the particle size data of the flake zinc pigment particles; if the target mapping relationship is a set of mapping relationships, then the similarity P corresponding to these mapping relationships is used as the weight to calculate the weighted average of the particle sizes corresponding to these mapping relationships to obtain the particle size data of the flake zinc pigment particles.

[0145] This method introduces a mapping relationship between polarization scattering characteristic values ​​and particle size established under multiple sets of different reference environmental parameters when determining the particle size data of flake zinc pigment particles. This means that the influence of environmental parameter changes on polarization scattering characteristics has been fully considered during the system calibration phase, constructing a more comprehensive mapping relationship database. In the actual testing process, the system first acquires various environmental parameters in the current production environment in real time, such as temperature, pressure, humidity, or the solvent properties of the slurry. This real-time data provides accurate background information on the current testing environment. Subsequently, based on these real-time acquired environmental parameters, the system performs preliminary screening from the preset mapping relationship database, identifying those mapping relationships whose reference environmental parameter conditions at the time of establishment best match the current real-time environmental parameters. These screened mapping relationships are then used as candidate mapping relationships. This screening process ensures that the mapping relationships used for subsequent particle size determination are highly relevant to the environmental background, thereby effectively eliminating errors that may be caused by mapping relationships established under mismatched environments. Building upon this, the system further compares the currently measured polarization scattering characteristic values ​​(obtained by collecting the intensity of the polarization component of the scattered light generated by the interaction between the irradiated beam and the diluted slurry at multiple scattering angles, characterizing the anisotropic scattering properties of the flake-like pigment particles) with the corresponding reference polarization scattering characteristic values ​​in these candidate mapping relationships. Through this dual screening mechanism of environmental parameter matching and polarization scattering characteristic value matching, the system can accurately identify the mapping relationship that best reflects the current particle scattering characteristics and environmental conditions, determining it as the final target mapping relationship for particle size calculation. Finally, the system uses this dynamically selected target mapping relationship to convert the currently measured polarization scattering characteristic values ​​into corresponding particle size data, thereby determining the particle size data of the flake-like zinc pigment particles.

[0146] This method pre-defines the mapping relationship between polarization scattering characteristic values ​​and particle size under multiple sets of different reference environmental parameters. During detection, real-time environmental parameters are dynamically acquired, and candidate mapping relationships matching the real-time environmental parameters are selected. Further selection yields a target mapping relationship matching the actual polarization scattering characteristic values. Finally, the particle size data of the flake-like zinc pigment particles is determined based on this target mapping relationship. This approach overcomes the problem of inaccurate particle size detection caused by fluctuations in environmental parameters when using a single fixed mapping relationship. It ensures that even when environmental factors such as temperature, pressure, humidity, or slurry properties change in a zinc-rich primer production line, the particle size detection results remain accurate and reliable. This allows the detection data to truly reflect the actual particle size state of the pigment on the production line, effectively guiding the precise control of the production process and improving the quality control level of the production process.

[0147] refer to Figure 2This application provides a particle size analysis and detection system for flaky zinc pigments, used in a zinc-rich primer production line to detect the particle size data of flaky zinc pigment particles in a diluted slurry diluted by an automatic dilution unit. The system includes:

[0148] Irradiation light source 1 is used to emit an irradiation beam with a preset polarization direction to the diluted slurry flowing through the detection flow cell 90 to form scattered light (refer to step A1 above for details).

[0149] Multiple detector arrays 2 are arranged around the detection flow cell 90 at different scattering angles. Each detector array 2 includes multiple polarization-sensitive detectors corresponding to different polarization states. The detector array 2 is used to collect the intensity of multiple polarization components of the scattered light (collected by polarization-sensitive detectors corresponding to different polarization states).

[0150] The host computer 3 is used to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles based on the polarization component intensity, and to determine the particle size data of the flake zinc pigment particles based on the polarization scattering characteristic values ​​and the preset mapping relationship between the polarization scattering characteristic values ​​and the particle size (for details, please refer to steps A3 and A4 above).

[0151] The illumination source 1 can be a semiconductor laser, with a linear polarizer placed in front of it to form a linearly polarized beam with a preset polarization direction.

[0152] Each detector array 2 may contain two photodiode detectors, and an analyzer is placed in front of each photodiode detector. One analyzer is used to collect the intensity of the horizontal polarization component, and the other analyzer is used to collect the intensity of the vertical polarization component.

[0153] The host computer can be an industrial control computer, which runs specially developed particle size analysis software to execute steps A3 and A4.

[0154] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for analyzing and detecting the particle size of flaky zinc pigment, used in a zinc-rich primer production line to detect the particle size data of flaky zinc pigment particles in a diluted slurry diluted by an automatic dilution unit, characterized in that... The steps of this method include: A1. An irradiation beam with a preset polarization direction is emitted into the diluted slurry flowing through the detection flow cell to form scattered light; A2. At multiple scattering angles, the intensity of multiple polarization components of the scattered light is collected using a polarization-sensitive detector; A3. Based on the polarization component intensity, obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles; A4. Based on the polarization scattering characteristic value, the particle size data of the flake zinc pigment particles is determined using a preset mapping relationship between the polarization scattering characteristic value and the particle size.

2. The method for particle size analysis and detection of flake zinc pigment according to claim 1, characterized in that, The irradiation beam is a linearly polarized light beam, and the preset polarization direction is a horizontal polarization direction, a vertical polarization direction, or a 45° polarization direction. Step A2 includes: At least five scattering angles within the range of 0-180 degrees, the intensity of the horizontal polarization component and the intensity of the vertical polarization component of the scattered light are simultaneously acquired.

3. The method for particle size analysis and detection of flake zinc pigment according to claim 2, characterized in that, The at least five scattering angles include a forward angle less than 90°, a lateral angle equal to 90°, and a backward angle greater than 90°.

4. The method for particle size analysis and detection of flake zinc pigment according to claim 2, characterized in that, Step A3 includes: A301. Evaluate the signal quality of the horizontal and vertical polarization component intensities at each scattering angle to determine whether they meet the preset effective measurement range and signal-to-noise ratio requirements. A302. Based on the signal quality assessment results, the intensity of the horizontal polarization component and the intensity of the vertical polarization component that meet the requirements are normalized to eliminate the absolute intensity changes caused by fluctuations in the concentration of the diluted slurry or optical path attenuation. A303. Based on the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity, determine the polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles; the polarization scattering characteristic values ​​include at least one of depolarization degree, polarization ratio, and polarization ellipsoid.

5. The method for particle size analysis and detection of flake zinc pigment according to claim 4, characterized in that, Step A303 includes: B1. For each scattering angle, obtain time series data of the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity within a preset time period; B2. Based on the time series data, calculate the instantaneous polarization scattering characteristic value corresponding to each time point to obtain the instantaneous polarization scattering characteristic value sequence; B3. Perform wave pattern analysis on the instantaneous polarization scattering characteristic value sequence to identify abnormal wave patterns caused by instantaneous aggregation; B4. Based on the abnormal fluctuation pattern identification results, the instantaneous polarization scattering feature values ​​are filtered to exclude the instantaneous polarization scattering feature values ​​corresponding to the abnormal fluctuation patterns; B5. Statistical processing is performed on the selected instantaneous polarization scattering characteristic values ​​to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

6. The method for particle size analysis and detection of flake zinc pigment according to claim 5, characterized in that, Step B2 includes at least one of the following steps: B201. For each time point in the time series data, calculate the ratio of the absolute value of the difference between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point to the sum of the two, and obtain the instantaneous depolarization degree. B202. For each time point in the time series data, calculate the ratio of the normalized horizontal polarization component intensity to the normalized vertical polarization component intensity corresponding to that time point to obtain the instantaneous polarization ratio. B203. For each time point in the time series data, analyze the relative relationship between the normalized horizontal polarization component intensity and the normalized vertical polarization component intensity corresponding to that time point, and determine the instantaneous polarization ellipsoid.

7. The method for particle size analysis and detection of flake zinc pigment according to claim 5, characterized in that, Step B3 includes: B301. For each instantaneous polarization scattering characteristic value sequence at each scattering angle, calculate its fluctuation amplitude, fluctuation duration, and fluctuation rate within a preset time window; B302. Analyze the instantaneous ratios or instantaneous correlations between instantaneous polarization scattering eigenvalues ​​at different scattering angles; B303. Based on the fluctuation amplitude, the fluctuation duration, the fluctuation change rate, the instantaneous ratio, and the instantaneous correlation, compare them with a preset clustering pattern criterion to identify abnormal fluctuation patterns caused by instantaneous clustering.

8. The method for particle size analysis and detection of flake zinc pigment according to claim 5, characterized in that, Step B5 includes: B501. Obtain the original horizontal polarization component intensity and the original vertical polarization component intensity corresponding to each filtered instantaneous polarization scattering feature value, as well as its acquisition timestamp; B502. Calculate the signal strength and signal-to-noise ratio of each instantaneous polarization scattering characteristic value based on the original horizontal polarization component intensity and the original vertical polarization component intensity; B503. Determine the weighting factor for each instantaneous polarization scattering feature value based on the signal strength, the signal-to-noise ratio, and the time interval between the acquisition timestamp and the current processing time; B504. Using the weighting factor, the selected instantaneous polarization scattering characteristic values ​​are weighted and averaged to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles.

9. The method for particle size analysis and detection of flake zinc pigment according to claim 1, characterized in that, The pre-defined mapping relationship between polarization scattering eigenvalues ​​and particle size includes the mapping relationship between reference polarization scattering eigenvalues ​​and particle size under multiple sets of different reference environmental parameter conditions; Step A4 includes: A401. Obtain real-time environmental parameters; A402. Select the mapping relationships that match the reference environmental parameter conditions with the real-time environmental parameters as candidate mapping relationships; A403. Select candidate mapping relationships that match the reference polarization scattering feature value and the polarization scattering feature value as target mapping relationships; A404. Determine the particle size data of the flake-shaped zinc pigment particles based on the particle size corresponding to the target mapping relationship.

10. A particle size analysis and detection system for flaky zinc pigment, used in a zinc-rich primer production line to detect the particle size data of flaky zinc pigment particles in a diluted slurry diluted by an automatic dilution unit, characterized in that... The system includes: An illumination light source is used to emit an illumination beam with a preset polarization direction onto the diluted slurry flowing through the detection flow cell to form scattered light; Multiple detector arrays are arranged around the detection flow cell at different scattering angles. Each detector array includes multiple polarization-sensitive detectors corresponding to different polarization states. The detector arrays are used to collect the intensity of multiple polarization components of the scattered light. The host computer is used to obtain polarization scattering characteristic values ​​that characterize the anisotropic scattering properties of the flake pigment particles based on the polarization component intensity, and to determine the particle size data of the flake zinc pigment particles based on the polarization scattering characteristic values ​​and the preset mapping relationship between the polarization scattering characteristic values ​​and the particle size.

Images