Image processing system and method for salt mist particle size detection

Abstract

The invention discloses an image processing system and method for salt mist particle size detection, and relates to the technical field of salt mist tests, the system captures salt mist particle images and acquires multi-dimensional information through a multi-spectral imaging technology by using light sources with different wavelengths and high-resolution imaging equipment, and establishes an image information set in combination with environment temperature and humidity data. Through image preprocessing and multispectral image fusion, salt mist particle features are extracted, and a comprehensive data set is constructed. And calculating a salt mist particle size distribution coefficient and a particle concentration coefficient according to the comprehensive data set to ensure that experimental conditions meet preset requirements and avoid experimental errors. Further analyzing the motion change and the form change of the particles, and calculating a dynamic change coefficient to ensure the stable behavior of the particles. And finally, training and screening the data by using a convolutional neural network, automatically identifying the salt mist particles conforming to the standard, and optimizing the accuracy and efficiency of the salt mist experiment.

Description

Technical Field

[0001] The present invention relates to the technical field of salt spray testing, in particular to an image processing system and method for detecting salt spray particle size. Background Art

[0002] The salt spray test is a common experimental method used to simulate the corrosion behavior of materials or products in a salt spray environment. It is widely used in fields such as metals, coatings, and electronic devices to test their corrosion resistance in salt spray environments. However, the results of salt spray tests can be affected by the particle size distribution, concentration, movement behavior, and particle morphology of the salt spray particles. If these factors are not adequately controlled or monitored, the test results may be erroneous, affecting the actual corrosion resistance evaluation of the material.

[0003] Currently, common monitoring methods used in salt spray testing rely primarily on traditional salt spray particle observation and physical analysis. Traditional methods, such as microscopic observation, manual screening, and manual testing, often suffer from low monitoring accuracy, low automation, complex data processing, and an inability to comprehensively assess particle behavior. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides an image processing system and method for salt spray particle size detection to solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an image processing system and method for detecting salt spray particle size, an image processing system for detecting salt spray particle size, comprising a multispectral imaging module, an image processing module, a salt spray particle size monitoring module, a salt spray particle size dynamic tracking module and an intelligent screening model module;

[0006] The multispectral imaging module is used to use light sources of different wavelengths, including visible light, ultraviolet light, and infrared light, to image and collect salt spray particles through high-resolution imaging equipment, capture salt spray particle images under different spectra, obtain multi-dimensional information of salt spray particles, and establish an image information set; the ambient temperature and humidity values ​​of the salt spray environment simulation box are collected in real time through temperature sensors and humidity sensors;

[0007] The image processing module is used to pre-process the image by adopting histogram equalization technology and Gaussian filtering denoising technology, and then perform multispectral image fusion processing to perform weighted synthesis on images of different bands to obtain salt spray particle image information data; use image segmentation technology and edge image processing technology to extract the salt spray particle image information data, and combine the collected ambient temperature and ambient humidity values ​​of the salt spray environment simulation box to establish a comprehensive data set;

[0008] The salt spray particle size monitoring module is used to monitor the particle size distribution and concentration of particles in the salt spray environment, calculate the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx respectively, and perform comparative analysis through thresholds to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, thereby avoiding the risk of inaccurate corrosion effects and uneven simulated environment due to unqualified salt spray particles;

[0009] The salt spray particle size dynamic tracking module is used to monitor the motion changes and morphological changes of salt spray particles in real time, calculate the motion change coefficient YBx and the morphological change coefficient XBx respectively, and then comprehensively calculate the dynamic change coefficient DTBH. By comparing the threshold value, the dynamic behavior of the salt spray particles in the experimental environment is comprehensively analyzed to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of the salt spray particles that do not meet expectations;

[0010] The intelligent screening model module is used to use a convolutional neural network to construct an initial convolutional neural network model, and use the trained initial convolutional neural network model as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

[0011] Preferably, the multispectral imaging module includes a deployment unit and a collection unit;

[0012] The deployment unit is used to deploy several spectral cameras on the salt spray environment simulation box; install a temperature sensor and a humidity sensor inside the salt spray environment simulation box; and evenly distribute several light sources including visible light, ultraviolet light, and infrared light inside the salt spray environment simulation box to ensure uniform illumination of the entire detection area so that all salt spray particles are fully illuminated;

[0013] The acquisition unit is used to use a spectral camera in conjunction with a light source to simultaneously image salt spray particles in multiple bands, collect appearance information and position information of the salt spray particles, and establish an image information set; and use a temperature sensor and a humidity sensor to collect the ambient temperature and humidity values ​​of the salt spray environment simulation box in real time.

[0014] Preferably, the image processing module includes an image enhancement unit, a multispectral image fusion unit and a data extraction unit;

[0015] The image enhancement unit is used to adjust the image of the image information set by using a histogram equalization technique, adjust the pixel distribution of the image, make the grayscale distribution of the image tend to be uniform, and convert the equalized grayscale value into the grayscale value of the original image; and use a Gaussian filter denoising technique to remove noise from the image of the image information set;

[0016] The multispectral image fusion unit is used to perform multispectral image fusion processing on the enhanced image according to image data under different spectra, perform weighted synthesis on images of different bands, and obtain salt spray particle image information data;

[0017] The data extraction unit is used to extract salt spray particle image information data by using image segmentation technology and edge image processing technology, including the particle size, area and thickness of the salt spray particles, and establish a comprehensive data set in combination with the ambient temperature value and the ambient humidity value.

[0018] Preferably, the salt spray particle size monitoring module includes a particle size distribution monitoring unit and a salt spray particle concentration monitoring unit;

[0019] The particle size distribution monitoring unit comprises a particle size distribution calculation subunit and a particle size distribution analysis subunit, which are used to monitor the particle size distribution state of the salt spray;

[0020] The particle size distribution calculation subunit is used to calculate the salt spray particle size distribution coefficient FBx by dimensionlessly processing the data of the comprehensive data set. The formula is as follows:

[0021]

[0022] Where n represents the total number of salt spray particles, d i represents the particle size of the i-th salt spray particle, μ represents the average particle size;

[0023] The particle size distribution analysis subunit is used to preset a first threshold value Q1 in advance, and compare and analyze the particle size distribution coefficient FBx with the first threshold value Q1 to obtain a first evaluation result including:

[0024] When the salt spray particle size distribution coefficient FBx is less than or equal to the first threshold Q1, it indicates that the particle size distribution of the salt spray particles is qualified and there is no risk of inaccurate corrosion effects. No adjustment is made and continuous monitoring is performed.

[0025] When the salt spray particle size distribution coefficient FBx is greater than the first threshold value Q1, it indicates that the particle size distribution of the salt spray particles is unqualified, and there is a risk of inaccurate corrosion effects. The first warning instruction is triggered, and the first strategy is generated: pneumatic screening and centrifugal separation technology are used to screen the salt spray particles, and only salt spray particles with a salt spray particle size distribution coefficient FBx ≤ the first threshold value Q1 are retained.

[0026] Preferably, the salt spray particle concentration monitoring unit includes a salt spray particle concentration calculation subunit and a salt spray particle concentration analysis subunit, which are used to divide the salt spray particle distribution area into several sub-areas and monitor the concentration distribution state of the salt spray particles in different areas;

[0027] The salt spray particle concentration calculation subunit is used to calculate the salt spray particle concentration coefficient NDx by dimensionlessly processing the data of the comprehensive data set. The formula is as follows:

[0028]

[0029] Where m represents the total number of regions, C j represents the salt spray particle concentration in the jth region, C0 represents the ideal concentration value of salt spray particles, Ak represents the number of salt spray particles in the region, and Aq represents the area of ​​the region;

[0030] The salt mist particle concentration analysis subunit is used to preset a second threshold value Q2 in advance, and compare and analyze the salt mist particle concentration coefficient NDx with the second threshold value Q2 to obtain a second evaluation result including:

[0031] When the salt mist particle concentration coefficient NDx is less than or equal to the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is qualified and there is no risk of causing inhomogeneity in the simulated environment. No adjustment is made and continuous monitoring is performed.

[0032] When the salt mist particle concentration coefficient NDx is greater than the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is unqualified and there is a risk of causing non-uniformity in the simulated environment. The second warning instruction is triggered and the second strategy is generated: reduce the spray particle size of the sprayer by 20% and increase the spray pressure by 10%.

[0033] Preferably, the salt spray particle size dynamic tracking module includes a salt spray particle motion change unit, a salt spray particle morphology change unit, a comprehensive salt spray particle dynamic change unit and a salt spray particle change analysis unit;

[0034] The salt spray particle motion change unit is used to monitor the position change of salt spray particles during the motion process. Combined with the comprehensive data set data, after dimensionless processing, the motion change coefficient YBx is calculated and obtained. The formula is as follows:

[0035]

[0036] Where M represents the number of observation cycles, Δx b Indicates the displacement change of salt spray particles in the x-axis direction in the bth time period, Δy b Indicates the displacement change of salt spray particles in the y-axis direction in the bth time period, Δz b It represents the displacement change of salt spray particles in the z-axis direction in the bth time period, t b represents the time difference of the bth time period, f(wd b ) represents the effect of ambient temperature change on the movement of salt spray particles in the bth time period, f(sd b) represents the effect of the change in ambient humidity on the movement of salt spray particles in the bth time period.

[0037] Preferably, the salt spray particle morphology change unit is used to monitor the morphology change of salt spray particles during movement, and calculates the morphology change coefficient XBx after dimensionless processing based on the comprehensive data set data, as follows:

[0038]

[0039] Where M represents the number of observation cycles, A b A represents the area of ​​salt spray particles in the bth cycle, o represents the initial area of ​​salt spray particles, H b represents the thickness of salt spray particles in the bth cycle, H o Indicates the initial thickness of salt spray particles, g(wd b ) represents the effect of ambient temperature change on the morphology of salt spray particles in the bth time period, g(sd b ) represents the effect of the change in ambient humidity on the morphology of salt spray particles in the bth time period.

[0040] Preferably, the comprehensive salt spray particle dynamic change unit is used to obtain the motion change coefficient YBx and the morphology change coefficient XBx by calculation, and comprehensively calculate the dynamic change coefficient DTBH, and the formula is as follows:

[0041] DTBH=w1*YBx+w2*XBx;

[0042] Where w1 and w2 are weight coefficients;

[0043] The salt mist particle change analysis unit is used to preset a third threshold value Q3 in advance, and compare and analyze the dynamic change coefficient DTBH with the third threshold value Q3. Obtaining a third evaluation result includes:

[0044] When the dynamic change coefficient DTBH ≤ the third threshold Q3, it means that the movement change of salt spray particles is within the expected range, the behavior of salt spray particles is stable, there is no risk of affecting the experimental results, and continuous monitoring is required;

[0045] When the dynamic change coefficient DTBH is greater than the third threshold Q3, it indicates that the movement change of the salt spray particles does not conform to the expected range, the behavior of the salt spray particles is unstable, and there is a risk of affecting the experimental results. The third early warning instruction is triggered and the third strategy is generated: reduce the temperature value by 10%, reduce the spray particle size of the sprayer by 25%, and reduce the ambient humidity value by 15%, until the dynamic change coefficient DTBH ≤ the third threshold Q3.

[0046] Preferably, the intelligent screening model module is used to use a convolutional neural network to construct an initial model of the convolutional neural network, and train and test the initial model of the convolutional neural network with comprehensive data set data, and use the trained initial model of the convolutional neural network as the intelligent screening model, while using the intermediate layer output of the salt spray particle size distribution coefficient FBx, the salt spray particle concentration coefficient NDx and the dynamic change coefficient DTBH as feature vectors to identify feature information, and train and test the intelligent screening model through the acquired feature information, and run the trained intelligent screening model as data to automatically screen out salt spray particles that meet standard specifications.

[0047] Preferably, an image processing method for detecting salt spray particle size comprises the following steps:

[0048] Step 1: Using light sources of different wavelengths, high-resolution imaging equipment is used to image and collect salt spray particles, capture images of salt spray particles under different spectra, collect multi-dimensional information of salt spray particles, and establish an image information set; collect the ambient temperature and humidity values ​​of the salt spray environment simulation box;

[0049] Step 2: Preprocess the image, perform multispectral image fusion processing, and perform weighted synthesis on images of different bands to obtain salt spray particle image information data; then extract the salt spray particle image information data, and combine it with the ambient temperature and humidity values ​​collected in the salt spray environment simulation box to establish a comprehensive data set;

[0050] Step 3: Calculate the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx using the comprehensive data set data, and perform comparative analysis using thresholds to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, avoiding the risk of inaccurate corrosion effects and uneven simulated environments due to unqualified salt spray particles;

[0051] Step 4: Calculate the motion change coefficient YBx and the morphological change coefficient XBx respectively through the comprehensive data set data, and then calculate the dynamic change coefficient DTBH. Through threshold comparison, comprehensively analyze the dynamic behavior of salt spray particles in the experimental environment to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of salt spray particles that do not meet expectations;

[0052] Step 5: By using the convolutional neural network, an initial convolutional neural network model is constructed, and the trained initial convolutional neural network model is used as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

[0053] The present invention provides an image processing system and method for detecting salt spray particle size. It has the following beneficial effects:

[0054] (1) This image processing system and method for detecting salt spray particle size uses multispectral image fusion technology and efficient image processing algorithms to extract clearer and more accurate particle information from salt spray particle images of different wavelengths, including characteristics such as particle size, morphology, and area. This high-quality image data can improve the detection accuracy of salt spray particles and ensure data reliability.

[0055] (2) The image processing system and method for detecting salt spray particle size can detect problems such as unqualified particles or uneven concentration distribution through the salt spray particle size monitoring module, trigger early warning instructions, and avoid experimental data deviation and the risk of uneven simulation environment caused by unqualified salt spray particles;

[0056] (3) The image processing system and method for detecting salt spray particle size can accurately evaluate the dynamic behavior of particles in the experimental environment by tracking the movement and morphological changes of salt spray particles in real time, combined with the influence of changes in ambient temperature and humidity, to ensure that the experimental conditions meet the requirements, thereby reducing experimental errors caused by unstable particle behavior and enhancing the reliability of experimental results;

[0057] (4) This image processing system and method for salt spray particle size detection, combined with a convolutional neural network intelligent screening model, can automatically screen salt spray particles that meet the standards, reduce manual intervention, and improve experimental efficiency. At the same time, real-time monitoring of the dynamic change coefficient and threshold comparison help automatically adjust the experimental environment parameters to ensure the stability of salt spray particles and their expected behavior during the experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flow chart of an image processing system for detecting salt spray particle size according to the present invention;

[0059] Figure 2 The figure is a schematic diagram of an image processing method for detecting salt spray particle size according to the present invention. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present invention are clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0061] Example 1

[0062] See also Figure 1, the present invention provides an image processing system for salt spray particle size detection, including a multispectral imaging module, an image processing module, a salt spray particle size monitoring module, a salt spray particle size dynamic tracking module and an intelligent screening model module;

[0063] The multispectral imaging module is used to use light sources of different wavelengths, including visible light, ultraviolet light, and infrared light, to image and collect salt spray particles through high-resolution imaging equipment, capture images of salt spray particles under different spectra, obtain multi-dimensional information of salt spray particles, and establish an image information set; the ambient temperature and humidity values ​​of the salt spray environment simulation box are collected in real time through temperature sensors and humidity sensors;

[0064] The image processing module is used to pre-process the image by using histogram equalization technology and Gaussian filtering denoising technology, and then perform multispectral image fusion processing to perform weighted synthesis of images of different bands to obtain salt spray particle image information data; the image information data of salt spray particles is extracted using image segmentation technology and edge image processing technology, and combined with the ambient temperature and humidity values ​​collected from the salt spray environment simulation box to establish a comprehensive data set;

[0065] The salt spray particle size monitoring module is used to monitor the particle size distribution and concentration of particles in the salt spray environment. It calculates the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx, and performs comparative analysis based on threshold values ​​to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, thereby avoiding the risk of inaccurate corrosion effects and uneven simulated environments due to unqualified salt spray particles.

[0066] The salt spray particle size dynamic tracking module is used to monitor the movement and morphological changes of salt spray particles in real time, calculate the movement change coefficient YBx and the morphological change coefficient XBx respectively, and then comprehensively calculate the dynamic change coefficient DTBH. Through threshold comparison, it comprehensively analyzes the dynamic behavior of salt spray particles in the experimental environment to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of salt spray particles that do not meet expectations;

[0067] The intelligent screening model module is used to use convolutional neural networks to build an initial convolutional neural network model, and use the trained initial convolutional neural network model as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

[0068] In this embodiment, by utilizing a convolutional neural network within the intelligent screening model module, the system can automatically identify and screen salt spray particles that meet standard specifications. This trained and optimized neural network model accurately extracts feature information from large amounts of salt spray particle image data, significantly improving screening efficiency and accuracy. This automated screening not only reduces manual intervention and potential errors but also significantly increases the screening speed of salt spray particles while ensuring experimental consistency, thereby enhancing the overall effectiveness and reliability of salt spray environment simulation experiments.

[0069] Example 2: This example is explained in Example 1. Please refer to Figure 1 ,Specifically, the multispectral imaging module includes a deployment unit and an ,acquisition unit;

[0070] The deployment unit is used to deploy several spectral cameras on the salt spray environment simulation chamber; install temperature sensors and humidity sensors inside the salt spray environment simulation chamber; and evenly distribute several light sources including visible light, ultraviolet light, and infrared light inside the salt spray environment simulation chamber to ensure uniform lighting across the entire detection area, so that all salt spray particles are fully illuminated.

[0071] The acquisition unit is used to use a spectral camera in conjunction with a light source to simultaneously image salt spray particles in multiple bands, collect appearance information and position information of salt spray particles, and establish an image information set; the ambient temperature and humidity values ​​of the salt spray environment simulation box are collected in real time through temperature sensors and humidity sensors.

[0072] In this embodiment, the deployment and acquisition units within the multispectral imaging module enable the system to achieve omnidirectional, uniform illumination and high-precision imaging within the salt spray environment simulation chamber. This design ensures that salt spray particles are fully captured across different spectral bands, providing rich, multidimensional image information that facilitates precise analysis of the morphology, distribution, and movement of salt spray particles. Furthermore, the real-time acquisition of temperature and humidity data makes image data analysis more environmentally adaptable, improves the control precision of the experimental environment, and provides a reliable foundation for subsequent particle size monitoring and dynamic tracking.

[0073] Example 3, this example is explained in Example 2, please refer to Figure 1 ,Specifically, the image processing module includes an image enhancement unit, a ,multispectral image fusion unit and a data extraction unit;

[0074] The image enhancement unit is used to adjust the image of the image information set by using the histogram equalization technology, adjust the pixel distribution of the image, make the gray level distribution of the image tend to be uniform, and convert the equalized gray value into the gray value of the original image; use the Gaussian filter denoising technology to remove noise from the image of the image information set;

[0075] The multispectral image fusion unit is used to perform multispectral image fusion processing on the enhanced image according to the image data under different spectra, perform weighted synthesis on the images of different bands, and obtain salt spray particle image information data;

[0076] The data extraction unit is used to extract salt spray particle image information data by using image segmentation technology and edge image processing technology, including the particle size, area and thickness of salt spray particles, and establish a comprehensive data set in combination with the ambient temperature value and the ambient humidity value.

[0077] In this embodiment, the image processing module effectively improves image quality through histogram equalization and Gaussian filtering denoising techniques, enhancing the contrast and detail clarity of salt spray particles and providing more accurate image data for subsequent analysis. The multispectral image fusion unit further integrates information from different spectral bands, ensuring that the images of salt spray particles maintain high quality and consistency under different environmental conditions, ensuring more comprehensive information capture. The data extraction unit accurately extracts particle size, area, and thickness data through image segmentation and edge processing techniques, and creates a comprehensive data set based on environmental parameters, thus providing accurate and reliable data support for subsequent particle size monitoring and dynamic behavior analysis.

[0078] Example 4: This example is explained in Example 3. Figure 1 ,Specifically, the salt spray particle size monitoring module includes a ,particle size distribution monitoring unit and a salt spray particle concentration ,monitoring unit;

[0079] The particle size distribution monitoring unit includes a particle size distribution calculation subunit and a particle size distribution analysis subunit, which are used to monitor the particle size distribution state of salt spray;

[0080] The particle size distribution calculation subunit is used to calculate the salt spray particle size distribution coefficient FBx through the data of the comprehensive data set after dimensionless processing. The formula is as follows:

[0081]

[0082] Where n represents the total number of salt spray particles, d i represents the particle size of the i-th salt spray particle, μ represents the average particle size;

[0083] The particle size distribution analysis subunit is used to preset a first threshold value Q1 in advance, and compare and analyze the particle size distribution coefficient FBx with the first threshold value Q1. Obtaining a first evaluation result includes:

[0084] When the salt spray particle size distribution coefficient FBx is less than or equal to the first threshold Q1, it indicates that the particle size distribution of the salt spray particles is qualified and there is no risk of inaccurate corrosion effects. No adjustment is made and continuous monitoring is performed.

[0085] When the salt spray particle size distribution coefficient FBx is greater than the first threshold value Q1, it indicates that the particle size distribution of the salt spray particles is unqualified, and there is a risk of inaccurate corrosion effects. The first warning instruction is triggered, and the first strategy is generated: pneumatic screening and centrifugal separation technology are used to screen the salt spray particles, and only salt spray particles with a salt spray particle size distribution coefficient FBx ≤ the first threshold value Q1 are retained.

[0086] In this embodiment, the salt spray particle size monitoring module effectively monitors the particle size distribution of salt spray particles by accurately calculating the particle size distribution coefficient of salt spray particles and comparing and analyzing it with a preset first threshold. When the particle size distribution coefficient exceeds the threshold, the system automatically triggers an alert and takes screening measures, using pneumatic screening and centrifugal separation technology to remove unqualified salt spray particles. This ensures that the particle size distribution in the experimental environment meets the requirements and avoids inaccurate corrosion effects caused by unqualified particle size. This not only improves experimental reliability and data accuracy, but also reduces the experimental risks caused by unqualified particles.

[0087] Example 5: This example is explained in Example 4. Please refer to Figure 1 Specifically, the salt spray particle concentration monitoring unit includes a salt spray particle concentration calculation subunit and a salt spray particle concentration analysis subunit, which are used to divide the salt spray particle distribution area into several sub-areas and monitor the concentration distribution state of salt spray particles in different areas;

[0088] The salt spray particle concentration calculation subunit is used to calculate the salt spray particle concentration coefficient NDx through the data of the comprehensive data set after dimensionless processing. The formula is as follows:

[0089]

[0090]

[0091] Where m represents the total number of regions, C j represents the salt spray particle concentration in the jth region, C0 represents the ideal concentration value of salt spray particles, Ak represents the number of salt spray particles in the region, and Aq represents the area of ​​the region;

[0092] The salt mist particle concentration analysis subunit is used to preset a second threshold value Q2 in advance, and compare and analyze the salt mist particle concentration coefficient NDx with the second threshold value Q2 to obtain a second evaluation result including:

[0093] When the salt mist particle concentration coefficient NDx is less than or equal to the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is qualified and there is no risk of causing inhomogeneity in the simulated environment. No adjustment is made and continuous monitoring is performed.

[0094] When the salt mist particle concentration coefficient NDx is greater than the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is unqualified and there is a risk of causing non-uniformity in the simulated environment. The second warning instruction is triggered and the second strategy is generated: reduce the spray particle size of the sprayer by 20% and increase the spray pressure by 10%.

[0095] In this embodiment, the salt spray particle concentration monitoring unit calculates and analyzes the concentration of salt spray particles in different sub-areas, enabling real-time monitoring of the uniformity of the simulated environment. When the salt spray particle concentration coefficient exceeds a preset threshold, the system automatically triggers an alert and adjusts the sprayer's spray particle size and pressure accordingly to balance the salt spray particle concentration distribution and ensure uniformity in the simulated environment. This feature effectively avoids deviations in experimental results caused by uneven concentration, improves experimental accuracy and reliability, and ensures the stability of the experimental environment.

[0096] Example 6: This example is explained in Example 1. Please refer to Figure 1 ,The salt spray particle size dynamic tracking module includes a salt spray particle motion change unit, a salt spray particle morphology change unit, a comprehensive salt spray particle dynamic change unit, and a salt spray particle change analysis unit;

[0097] The salt spray particle motion change unit is used to monitor the position change of salt spray particles during movement. Combined with the data of the comprehensive data set, after dimensionless processing, the motion change coefficient YBx is calculated and obtained. The formula is as follows:

[0098]

[0099] Where M represents the number of observation cycles, Δx b Indicates the displacement change of salt spray particles in the x-axis direction in the bth time period, Δy b Indicates the displacement change of salt spray particles in the y-axis direction in the bth time period, Δz b It represents the displacement change of salt spray particles in the z-axis direction in the bth time period, t b represents the time difference of the bth time period, f(wd b ) represents the effect of ambient temperature change on the movement of salt spray particles in the bth time period, f(sd b ) represents the effect of the change in ambient humidity on the movement of salt spray particles in the bth time period.

[0100] In this embodiment, the salt spray particle motion change unit accurately calculates the motion change coefficient by monitoring the displacement of salt spray particles and the impact of environmental changes on their motion in real time, ensuring that the dynamic behavior of salt spray particles during the experiment meets predetermined requirements. By incorporating the effects of temperature and humidity, the system can track the movement of particles in real time, avoiding inaccurate experimental results caused by unstable salt spray particle behavior or deviation from the expected trajectory. This improves the reliability and accuracy of the experiment and ensures that the simulated environment is highly consistent with actual corrosion conditions.

[0101] Example 7, this example is explained in Example 6, please refer to Figure 1 The salt spray particle morphology change unit is used to monitor the morphology change of salt spray particles during movement. Combined with the comprehensive data set data, after dimensionless processing, the morphology change coefficient XBx is calculated and obtained. The formula is as follows:

[0102]

[0103] Where M represents the number of observation cycles, A b A represents the area of ​​salt spray particles in the bth cycle, o represents the initial area of ​​salt spray particles, H b represents the thickness of salt spray particles in the bth cycle, H o Indicates the initial thickness of salt spray particles, g(wd b ) represents the effect of ambient temperature change on the morphology of salt spray particles in the bth time period, g(sd b ) represents the effect of the change in ambient humidity on the morphology of salt spray particles in the bth time period.

[0104] In this embodiment, the salt spray particle morphology change unit monitors the morphological changes of salt spray particles during their motion and, in combination with the effects of temperature and humidity variations, calculates the morphology change coefficient in real time, accurately tracking the particle morphological evolution. This function effectively prevents experimental data errors caused by unstable particle morphology, ensuring that salt spray particles in the simulated environment always remain within the predetermined ideal morphology range, thereby improving experimental reliability and consistency and avoiding the risk of inaccurate corrosion test results or uneven environmental simulation caused by abnormal morphological changes.

[0105] Example 8: This example is explained in Example 7. Please refer to Figure 1 The comprehensive salt spray particle dynamic change unit is used to obtain the motion change coefficient YBx and the morphological change coefficient XBx by calculation, and to comprehensively calculate the dynamic change coefficient DTBH. The formula is as follows:

[0106] DTBH=w1*YBx+w2*XBx;

[0107] Where, w1 and w2 represent weight coefficients, which are set by the user, 0 < w1 < 1, 0 < w2 < 1, and w1 + w2 = 1;

[0108] The salt spray particle change analysis unit is used to preset a third threshold Q3 in advance, and compare and analyze the dynamic change coefficient DTBH with the third threshold Q3 to obtain the third evaluation result, including:

[0109] When the dynamic change coefficient DTBH ≤ the third threshold Q3, it indicates that the movement change of the salt spray particles is within the expected range, the behavior of the salt spray particles is stable, there is no risk of affecting the experimental results, and continuous monitoring is carried out;

[0110] When the dynamic change coefficient DTBH > the third threshold Q3, it indicates that the movement change of the salt spray particles does not conform to the expected range, the behavior of the salt spray particles is unstable, there is a risk of affecting the experimental results, trigger the third warning instruction, and generate the third strategy: reduce the temperature value by 10%, reduce the spray particle size of the atomizer by 25%, and reduce the environmental humidity value by 15% until the dynamic change coefficient DTBH ≤ the third threshold Q3.

[0111] In this embodiment, the comprehensive salt spray particle dynamic change unit calculates the dynamic change coefficient by comprehensively calculating the movement change coefficient and the morphological change coefficient, and monitors the movement and morphological changes of the salt spray particles in real time. When the dynamic change coefficient exceeds the preset threshold, it can automatically trigger an alarm and adjust the environmental conditions, such as temperature, humidity and spray particle size, to ensure the stable behavior of the salt spray particles and avoid affecting the experimental results due to unstable particle movement or morphological changes. This mechanism effectively improves the accuracy and reliability of the experimental data.

[0112] Embodiment 9. This embodiment is an explanatory description carried out in Embodiment 8. Please refer to Figure 1 The intelligent screening model module is used to use a convolutional neural network to construct an initial convolutional neural network model, train and test the initial convolutional neural network model with the comprehensive dataset data, and use the initial convolutional neural network model after training as the intelligent screening model. At the same time, the intermediate layer outputs of the salt spray particle size distribution coefficient FBx, the salt spray particle concentration coefficient NDx and the dynamic change coefficient DTBH are used as feature vectors to identify the feature information, and the intelligent screening model is trained and tested with the obtained feature information, and the intelligent screening model after training is used as data operation to automatically screen out the salt spray particles that meet the standard specifications.

[0113] In this example, the intelligent screening model module uses a convolutional neural network (CNN) to train and test a comprehensive dataset. By incorporating key characteristic information such as the salt spray particle size distribution coefficient, salt spray particle concentration coefficient, and dynamic change coefficient, it can automatically screen out salt spray particles that meet standard specifications. This automated screening process effectively improves screening accuracy and efficiency, reduces errors caused by manual intervention, and ensures the consistency and stability of salt spray particles during the experiment.

[0114] Example 10. An image processing method for detecting salt spray particle size, see Figure 2 , including the following steps:

[0115] Step 1: Using light sources of different wavelengths, high-resolution imaging equipment is used to image and collect salt spray particles, capture images of salt spray particles under different spectra, collect multi-dimensional information of salt spray particles, and establish an image information set; collect the ambient temperature and humidity values ​​of the salt spray environment simulation box;

[0116] Step 2: Preprocess the image, perform multispectral image fusion processing, and perform weighted synthesis on images of different bands to obtain salt spray particle image information data; then extract the salt spray particle image information data, and combine it with the ambient temperature and humidity values ​​collected in the salt spray environment simulation box to establish a comprehensive data set;

[0117] Step 3: Calculate the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx using the comprehensive data set data, and perform comparative analysis using thresholds to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, avoiding the risk of inaccurate corrosion effects and uneven simulated environments due to unqualified salt spray particles;

[0118] Step 4: Calculate the motion change coefficient YBx and the morphological change coefficient XBx respectively through the comprehensive data set data, and then calculate the dynamic change coefficient DTBH. Through threshold comparison, comprehensively analyze the dynamic behavior of salt spray particles in the experimental environment to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of salt spray particles that do not meet expectations;

[0119] Step 5: By using the convolutional neural network, an initial convolutional neural network model is constructed, and the trained initial convolutional neural network model is used as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

[0120] In this embodiment, through the implementation of the above steps, the system is able to comprehensively and accurately collect and process image data of salt spray particles, and analyze it in conjunction with environmental parameters. By integrating multi-dimensional information and establishing a comprehensive dataset, the particle size distribution, concentration, and dynamic changes of salt spray particles are ensured to meet predetermined standards, effectively avoiding the unevenness and instability in the experimental environment. This not only improves the accuracy of salt spray particle screening, but also enhances the reliability and reproducibility of the experiment.

[0121] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0122] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by those skilled in the art according to actual conditions. The above are only preferred specific implementation methods of the present invention, but the protection scope of the present invention is not limited to this. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solution and inventive concept of the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An image processing system for detecting salt spray particle size, characterized in that: It includes multispectral imaging module, image processing module, salt spray particle size monitoring module, salt spray particle size dynamic tracking module and intelligent screening model module; The multispectral imaging module is used to use light sources of different wavelengths, including visible light, ultraviolet light, and infrared light, to image and collect salt spray particles through high-resolution imaging equipment, capture salt spray particle images under different spectra, obtain multi-dimensional information of salt spray particles, and establish an image information set; the ambient temperature and humidity values ​​of the salt spray environment simulation box are collected in real time through temperature sensors and humidity sensors; The image processing module is used to pre-process the image by adopting histogram equalization technology and Gaussian filtering denoising technology, and then perform multispectral image fusion processing to perform weighted synthesis on images of different bands to obtain salt spray particle image information data; use image segmentation technology and edge image processing technology to extract the salt spray particle image information data, and combine the collected ambient temperature and ambient humidity values ​​of the salt spray environment simulation box to establish a comprehensive data set; The salt spray particle size monitoring module is used to monitor the particle size distribution and concentration of particles in the salt spray environment, calculate the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx respectively, and perform comparative analysis through thresholds to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, thereby avoiding the risk of inaccurate corrosion effects and uneven simulated environment due to unqualified salt spray particles; The salt spray particle size dynamic tracking module is used to monitor the motion changes and morphological changes of salt spray particles in real time, calculate the motion change coefficient YBx and the morphological change coefficient XBx respectively, and then comprehensively calculate the dynamic change coefficient DTBH. By comparing the threshold value, the dynamic behavior of the salt spray particles in the experimental environment is comprehensively analyzed to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of the salt spray particles that do not meet expectations; The intelligent screening model module is used to use a convolutional neural network to construct an initial convolutional neural network model, and use the trained initial convolutional neural network model as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

2. The image processing system for detecting salt spray particle size according to claim 1, wherein: The multispectral imaging module includes a deployment unit and a collection unit; The deployment unit is used to deploy several spectral cameras on the salt spray environment simulation box; install a temperature sensor and a humidity sensor inside the salt spray environment simulation box; and evenly distribute several light sources including visible light, ultraviolet light, and infrared light inside the salt spray environment simulation box to ensure uniform illumination of the entire detection area so that all salt spray particles are fully illuminated; The acquisition unit is used to use a spectral camera in conjunction with a light source to simultaneously image salt spray particles in multiple bands, collect appearance information and position information of the salt spray particles, and establish an image information set; and use a temperature sensor and a humidity sensor to collect the ambient temperature and humidity values ​​of the salt spray environment simulation box in real time.

3. The image processing system for detecting salt spray particle size according to claim 2, wherein: The image processing module includes an image enhancement unit, a multispectral image fusion unit and a data extraction unit; The image enhancement unit is used to adjust the image of the image information set by using a histogram equalization technique, adjust the pixel distribution of the image, make the grayscale distribution of the image tend to be uniform, and convert the equalized grayscale value into the grayscale value of the original image; and use a Gaussian filter denoising technique to remove noise from the image of the image information set; The multispectral image fusion unit is used to perform multispectral image fusion processing on the enhanced image according to image data under different spectra, perform weighted synthesis on images of different bands, and obtain salt spray particle image information data; The data extraction unit is used to extract salt spray particle image information data by using image segmentation technology and edge image processing technology, including the particle size, area and thickness of the salt spray particles, and establish a comprehensive data set in combination with the ambient temperature value and the ambient humidity value.

4. The image processing system for detecting salt spray particle size according to claim 3, wherein: The salt spray particle size monitoring module includes a particle size distribution monitoring unit and a salt spray particle concentration monitoring unit; The particle size distribution monitoring unit comprises a particle size distribution calculation subunit and a particle size distribution analysis subunit, which are used to monitor the particle size distribution state of the salt spray; The particle size distribution calculation subunit is used to calculate the salt spray particle size distribution coefficient FBx by dimensionlessly processing the data of the comprehensive data set. The formula is as follows: Where n represents the total number of salt spray particles, d i represents the particle size of the i-th salt spray particle, μ represents the average particle size; The particle size distribution analysis subunit is used to preset a first threshold value Q1 in advance, and compare and analyze the particle size distribution coefficient FBx with the first threshold value Q1 to obtain a first evaluation result including: When the salt spray particle size distribution coefficient FBx is less than or equal to the first threshold Q1, it indicates that the particle size distribution of the salt spray particles is qualified and there is no risk of inaccurate corrosion effects. No adjustment is made and continuous monitoring is performed. When the salt spray particle size distribution coefficient FBx is greater than the first threshold value Q1, it indicates that the particle size distribution of the salt spray particles is unqualified, and there is a risk of inaccurate corrosion effects. The first warning instruction is triggered, and the first strategy is generated: pneumatic screening and centrifugal separation technology are used to screen the salt spray particles, and only salt spray particles with a salt spray particle size distribution coefficient FBx ≤ the first threshold value Q1 are retained.

5. The image processing system for detecting salt spray particle size according to claim 4, wherein: The salt spray particle concentration monitoring unit includes a salt spray particle concentration calculation subunit and a salt spray particle concentration analysis subunit, which are used to divide the salt spray particle distribution area into several sub-areas and monitor the concentration distribution state of salt spray particles in different areas; The salt spray particle concentration calculation subunit is used to calculate the salt spray particle concentration coefficient NDx by dimensionlessly processing the data of the comprehensive data set. The formula is as follows: Where m represents the total number of regions, C j represents the salt spray particle concentration in the jth region, C0 represents the ideal concentration value of salt spray particles, Ak represents the number of salt spray particles in the region, and Aq represents the area of ​​the region; The salt mist particle concentration analysis subunit is used to preset a second threshold value Q2 in advance, and compare and analyze the salt mist particle concentration coefficient NDx with the second threshold value Q2 to obtain a second evaluation result including: When the salt mist particle concentration coefficient NDx is less than or equal to the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is qualified and there is no risk of causing inhomogeneity in the simulated environment. No adjustment is made and continuous monitoring is performed. When the salt mist particle concentration coefficient NDx is greater than the second threshold Q2, it indicates that the salt mist particle concentration in the current sub-area is unqualified and there is a risk of causing non-uniformity in the simulated environment. The second warning instruction is triggered and the second strategy is generated: reduce the spray particle size of the sprayer by 20% and increase the spray pressure by 10%.

6. The image processing system for detecting salt spray particle size according to claim 1, wherein: The salt spray particle size dynamic tracking module includes a salt spray particle motion change unit, a salt spray particle morphology change unit, a comprehensive salt spray particle dynamic change unit and a salt spray particle change analysis unit; The salt spray particle motion change unit is used to monitor the position change of salt spray particles during the motion process. Combined with the comprehensive data set data, after dimensionless processing, the motion change coefficient YBx is calculated and obtained. The formula is as follows: Where M represents the number of observation cycles, Δx b Indicates the displacement change of salt spray particles in the x-axis direction in the bth time period, Δy b Indicates the displacement change of salt spray particles in the y-axis direction in the bth time period, Δz b It represents the displacement change of salt spray particles in the z-axis direction in the bth time period, t b represents the time difference of the bth time period, f(wd b ) represents the effect of ambient temperature change on the movement of salt spray particles in the bth time period, f(sd b ) represents the effect of the change in ambient humidity on the movement of salt spray particles in the bth time period.

7. The image processing system for detecting salt spray particle size according to claim 6, wherein: The salt spray particle morphology change unit is used to monitor the morphology change of salt spray particles during movement. Combined with the comprehensive data set data, after dimensionless processing, the morphology change coefficient XBx is calculated and obtained. The formula is as follows: Where M represents the number of observation periods, A b A represents the area of ​​salt spray particles in the bth cycle, o represents the initial area of ​​salt spray particles, H b represents the thickness of salt spray particles in the bth cycle, H o Indicates the initial thickness of salt spray particles, g(wd b ) represents the effect of ambient temperature change on the morphology of salt spray particles in the bth time period, g(sd b ) represents the effect of the change in ambient humidity on the morphology of salt spray particles in the bth time period.

8. The image processing system for detecting salt spray particle size according to claim 7, wherein: The comprehensive salt spray particle dynamic change unit is used to obtain the motion change coefficient YBx and the morphology change coefficient XBx by calculation, and comprehensively calculate the dynamic change coefficient DTBH. The formula is as follows: DTBH=w1*YBx+w2*XBx; Where w1 and w2 are weight coefficients; The salt mist particle change analysis unit is used to preset a third threshold value Q3 in advance, and compare and analyze the dynamic change coefficient DTBH with the third threshold value Q3. Obtaining a third evaluation result includes: When the dynamic change coefficient DTBH ≤ the third threshold Q3, it means that the movement change of salt spray particles is within the expected range, the behavior of salt spray particles is stable, there is no risk of affecting the experimental results, and continuous monitoring is required; When the dynamic change coefficient DTBH is greater than the third threshold Q3, it indicates that the movement change of the salt spray particles does not conform to the expected range, the behavior of the salt spray particles is unstable, and there is a risk of affecting the experimental results. The third early warning instruction is triggered and the third strategy is generated: reduce the temperature value by 10%, reduce the spray particle size of the sprayer by 25%, and reduce the ambient humidity value by 15%, until the dynamic change coefficient DTBH ≤ the third threshold Q3.

9. The image processing system for detecting salt spray particle size according to claim 8, wherein: The intelligent screening model module is used to use a convolutional neural network to construct an initial convolutional neural network model, and train and test the initial convolutional neural network model with comprehensive data set data, and use the trained initial convolutional neural network model as the intelligent screening model. At the same time, the intermediate layer output of the salt spray particle size distribution coefficient FBx, the salt spray particle concentration coefficient NDx and the dynamic change coefficient DTBH is used as a feature vector to identify feature information, and the intelligent screening model is trained and tested through the acquired feature information. The trained intelligent screening model is run as data to automatically screen out salt spray particles that meet standard specifications.

10. An image processing method for detecting salt spray particle size, comprising an image processing system for detecting salt spray particle size according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Using light sources of different wavelengths, high-resolution imaging equipment is used to image and collect salt spray particles, capture images of salt spray particles under different spectra, collect multi-dimensional information of salt spray particles, and establish an image information set; collect the ambient temperature and humidity values ​​of the salt spray environment simulation box; Step 2: Preprocess the image, perform multispectral image fusion processing, and perform weighted synthesis on images of different bands to obtain salt spray particle image information data; then extract the salt spray particle image information data, and combine it with the ambient temperature and humidity values ​​collected in the salt spray environment simulation box to establish a comprehensive data set; Step 3: Calculate the salt spray particle size distribution coefficient FBx and the salt spray particle concentration coefficient NDx using the comprehensive data set data, and perform comparative analysis using thresholds to ensure that the experimental conditions of the salt spray environment meet the predetermined requirements, avoiding the risk of inaccurate corrosion effects and uneven simulated environments due to unqualified salt spray particles; Step 4: Calculate the motion change coefficient YBx and the morphological change coefficient XBx respectively through the comprehensive data set data, and then calculate the dynamic change coefficient DTBH. Through threshold comparison, comprehensively analyze the dynamic behavior of salt spray particles in the experimental environment to ensure that the salt spray particles meet the predetermined experimental requirements during the movement process, and avoid inaccurate experimental results due to unstable behavior and changes of salt spray particles that do not meet expectations; Step 5: By using the convolutional neural network, an initial convolutional neural network model is constructed, and the trained initial convolutional neural network model is used as an intelligent screening model. The intelligent screening model is then trained and tested to automatically screen out salt spray particles that meet standard specifications.

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