Material antifouling performance evaluation system and method for simulating marine environment

Abstract

The invention relates to the technical field of marine environment material science, and provides a material antifouling performance evaluation system and method for simulating a marine environment, the system at least comprises an environment simulation device and a visual evaluation system, the environment simulation device is used for constructing and maintaining a simulated marine environment containing coexistence of multiple organisms; the visual evaluation system is provided with a sample detection chamber, a plurality of to-be-detected samples are fixed in the sample detection chamber, and the sample detection chamber is in fluid communication with the environment simulation device, so that a simulated water body in the environment simulation device circularly flows through the surfaces of the to-be-detected samples; the visual evaluation system further comprises an image acquisition module and an image processing and analyzing module, the image acquisition module is used for performing image acquisition on the surface of the to-be-detected sample in the sample detection chamber, and the image processing and analyzing module is used for processing and analyzing the acquired image so as to evaluate the antifouling performance of the to-be-detected sample. Through the arrangement, in-situ and continuous dynamic monitoring and performance evaluation of the antifouling performance of the material can be realized.

Description

Technical Field

[0001] This invention relates to the field of marine environmental materials science and technology, and in particular to a system and method for evaluating the antifouling performance of materials in a simulated marine environment. Background Technology

[0002] Marine biofouling is a global problem facing marine facilities such as ships, offshore platforms, and pipelines. Biofouling organisms increase drag, accelerate structural corrosion, and clog pipelines, leading to significant economic losses and ecological risks. Therefore, developing effective antifouling materials is crucial, and accurate and efficient performance evaluation methods are a key aspect of antifouling material research and development.

[0003] Currently, the performance evaluation of antifouling materials mainly relies on two methods: First, real-sea tarpaulin testing, which involves placing material samples in a real marine environment for months or even years, evaluating the material by periodically observing and statistically analyzing the adhesion of fouling organisms. While this method reflects the real environment, it is extremely time-consuming, highly susceptible to geographical and climatic conditions, has poor repeatability, and is very costly, severely hindering research and development efficiency. Second, laboratory single-bioadhesion testing, which uses a single species (such as specific bacteria, algae, or barnacle larvae) in a controlled laboratory environment for adhesion testing. Although this method is rapid and controllable, it often misses the complex competition, symbiosis, and other interactions among various organisms in the marine fouling environment, resulting in evaluation results that significantly deviate from the material's performance in the actual marine environment, thus lacking reliability. Summary of the Invention

[0004] To address at least one of the shortcomings in the aforementioned background technology, the present invention provides a material antifouling performance evaluation system simulating a marine environment. This system includes at least an environmental simulation device and a visual evaluation system. The environmental simulation device is used to construct and maintain a simulated marine environment containing multiple coexisting organisms. The visual evaluation system includes a sample testing chamber containing multiple samples to be tested, which is fluidly connected to the environmental simulation device so that simulated water within the device circulates over the surface of the samples. The visual evaluation system further includes an image acquisition module and an image processing and analysis module. The image acquisition module acquires images of the surface of the samples to be tested within the sample testing chamber, and the image processing and analysis module processes and analyzes the acquired images to evaluate the antifouling performance of the samples.

[0005] In one embodiment, the sample testing chamber is provided with an inlet and an outlet, which are respectively connected to the environmental simulation device to form a circulating water path.

[0006] In one embodiment, the image acquisition module includes an image acquisition device and a displacement mechanism drivenly connected to the image acquisition device and / or the sample detection chamber; the displacement mechanism is used to drive relative motion between the image acquisition device and the surface of the sample to be tested, thereby acquiring an image of the surface of the sample to be tested in the sample detection chamber.

[0007] This invention also provides a method for evaluating the antifouling performance of materials in a simulated marine environment, comprising the following steps: The environmental construction and maintenance steps involve constructing and maintaining a simulated marine environment in which multiple organisms coexist within an environmental simulation device; fixing multiple test samples in the sample detection chamber of a visual evaluation system, and circulating simulated water from the environmental simulation device over the surface of the test samples. The image acquisition step involves using an image acquisition module to periodically and automatically acquire images of the surface of the sample to be tested within the sample detection chamber. The image processing and analysis steps, including image stitching, stain identification, and performance evaluation, are used to process the acquired images and evaluate the stain resistance of each of the test samples.

[0008] In one embodiment, for the same sample to be tested, the image acquisition device acquires multiple local images, which together cover the entire surface of the sample to be tested, and there is an overlapping area between adjacent local images.

[0009] In one embodiment, the image stitching operation includes: extracting and matching feature points from multiple local images of the same test sample, estimating the geometric transformation relationship between the images based on the matched feature points, and aligning and fusing the local images according to the geometric transformation relationship to generate the complete image.

[0010] In one embodiment, the soiling identification operation includes: Spatial alignment of the complete images of the same sample under test at different time points; The newly added areas of fouling bioattachment are identified by calculating the image differences between the aligned complete images; Mathematical morphology processing is performed on the identified contaminated areas to optimize the region contours.

[0011] In one embodiment, the formula for calculating the image difference is: ΔI(t1,t2)=|I(t2)-I(t1)|; In the formula, I(t1) and I(t2) are the complete images acquired at time t1 and time t2, respectively, and ΔI(t1,t2) is the change region obtained by image difference during time t1 to t2.

[0012] In one embodiment, the mathematical morphological processing includes erosion, dilation, opening, and closing operations; The corrosion operation is expressed as follows: ; The expansion operation is represented as: ; The opening operation is a combination of erosion followed by dilation, expressed as: ; The closing operation is a combination of dilation followed by erosion, expressed as: ; In the formula, The input is a binarized image of the contaminated area. As a structural element, Let z be the position of the structuring element B after translation. structural element Regarding reflection at the origin, The structure element is translated after reflection. .

[0013] In one embodiment, the performance evaluation operation includes calculating the coverage of the contaminated bioattachment area, wherein the coverage calculation formula is: (N_fouling / N_total)×100%; where N_fouling is the total number of pixels in the identified contaminated area, and N_total is the total number of pixels in the effective area of ​​the sample surface to be tested.

[0014] Based on the above, compared with the prior art, the material antifouling performance evaluation system and method for simulating a marine environment provided by the present invention has at least the following technical effects: 1. Through the design of a circulating water circuit between an independent sample testing chamber and an environmental simulation device, multiple samples can be monitored in situ for a long time without interfering with the simulated environment. Combined with automatic image acquisition and analysis, this greatly improves testing efficiency and result consistency.

[0015] 2. By constructing a simulated marine environment in which multiple fouling organisms coexist and interact, the limitations of traditional single-organism testing are overcome, making the assessment results closer to real marine scenarios and more predictive.

[0016] 3. From environmental control, image acquisition, stitching and recognition to performance evaluation and early warning, the entire process is automated, which significantly reduces human error and cost, and ensures the repeatability of experiments and the reliability of results.

[0017] Other features and beneficial effects of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other beneficial effects of the invention can be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Unless otherwise specified, the positional relationships shown in the drawings in the following description are based on the direction in which the components are drawn in the figure.

[0019] Figure 1 This is a schematic diagram of the structure of the material antifouling performance evaluation system for simulating a marine environment provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of an image acquisition device acquiring images of the sample under test. Figure 3 This is a flowchart of a method for evaluating the antifouling performance of materials in a simulated marine environment, provided in Embodiment 2 of the present invention. Figure 4 A flowchart illustrating the image processing and analysis steps; Figure 5 A flowchart of the image stitching operation; Figure 6 A flowchart for the contamination identification and performance evaluation operations.

[0020] Figure label: 1. Water tank; 2. Automatic water replenishment device; 3. Simulated water body; 4. Substrate; 5. Lighting device; 6. Isolation device; 7. Primary attachment substrate; 8. Biological attachment substrate; 9. Protein separator; 10. Filtration device; 11. Wave generator; 12. Heating device; 13. Visual assessment system; 14. Inlet; 15. Outlet. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. The technical features designed in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] In the description of this invention, it should be noted that all terms used in this invention (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains, and should not be construed as limiting the invention; it should be further understood that the terms used in this invention should be understood to have the same meaning as those in the context of this specification and in the relevant field, and should not be understood in an idealized or overly formal sense, except as expressly defined in this invention.

[0023] Example 1 Please see Figures 1-2 This invention provides a material antifouling performance evaluation system that simulates a marine environment. The core design of this system combines laboratory environment simulation with automated visual evaluation, and it mainly consists of an environmental simulation device and a visual evaluation system 13. The environmental simulation device is used to construct and maintain a complex ecosystem containing various typical marine fouling organisms coexisting and interacting under controlled laboratory conditions, highly replicating the formation process and attachment environment of real marine fouling organism communities. The visual evaluation system 13 is used to perform in-situ, non-invasive, and periodic surface image acquisition on multiple test samples immersed in the simulated environment. Through an integrated intelligent image processing and analysis module, it achieves dynamic monitoring of the entire process of fouling organism attachment and growth on the surface of the test samples and quantitative evaluation of antifouling performance. The environmental simulation device and the visual evaluation system 13 are interconnected and coupled through a circulating water system, forming a unified and fully functional testing platform, thereby achieving high-throughput evaluation of the material's antifouling performance.

[0024] It should be noted that the large fouling organisms involved in the embodiments of the present invention include, but are not limited to, barnacles, mussels, oysters, sea squirts, tube worms, etc. The above are merely exemplary examples and are not intended to limit the types of organisms.

[0025] Specifically, the main body of the environmental simulation device is a water tank 1, which serves as the core container for cultivating and housing the entire simulated ecosystem. The water tank 1 contains simulated water 3, preferably pretreated natural seawater. This natural seawater retains its inherent natural microbial community, including bacteria and microalgae, providing an initial and diverse source of basic organisms for the entire simulation system. At the bottom of the water tank 1, a substrate 4, such as natural sea sand, is laid to simulate a real seabed sedimentary interface, providing a physical base for the colonization of benthic microorganisms and the formation of biofilms.

[0026] To construct a hierarchical bioattachment environment, the system incorporates multiple complementary attachment substrates. Specifically, these include a primary attachment substrate 7 and a bioattachment substrate 9. The primary attachment substrate 7 is uniformly distributed in the simulated water body 3, providing an initial attachment interface for planktonic fouling organism larvae. The bioattachment substrate 9 has a surface pre-attached with specific types of mature fouling organisms, serving as a stable biological source and a reproduction source. This bioattachment substrate 8 can be pre-cultivated using marine hanging boards or inoculated in a laboratory.

[0027] Based on this design, the interior of the tank is divided into different functional zones: large adult fouling organisms remain largely immobile after attachment, while the biofouling substrates 9, carrying different species of adults, are placed independently within the environmental simulation device, allowing for spatial independence among the different species. Preferably, the simulated water body 3 remains connected between the zones, allowing for the free exchange of planktonic larvae, spores, and chemical substances. Through this setup, precise simulation and flexible control of the composition and spatial distribution of multi-species adult communities are achieved. These adult communities constitute the basic biological load and reproductive source in the simulated environment, and can continuously release gametes or larvae into the water according to their natural reproductive cycles, thus providing stable and realistic biofouling pressure for the entire testing system.

[0028] In one embodiment, after the primary biological community in the simulated environment has stabilized, larvae, spores, or adults of selected target fouling organisms are introduced into the simulated water body 3 according to a predetermined plan. The species and quantity introduced are determined according to the experimental design, typically selecting 4-5 representative fouling organisms. During operation, appropriate amounts of nutrients are added periodically to maintain biological growth. In this way, multiple fouling organisms are allowed to naturally attach, grow, and interact on the surface of the sample under test and within the device, thereby simulating the real process of fouling community formation and succession. The entire cultivation or testing cycle is set according to the specific research objectives and the growth rate of the fouling organisms.

[0029] It should be noted that the primary attachment substrate 7 and the biological attachment substrate 8 mentioned above can be made of materials with rough surfaces and stable chemical properties, such as stones or special ceramic slabs, and their specific materials are not limited to these.

[0030] Optionally, the tank 1 may also be equipped with an isolation device 6, such as a suspended culture box with a microporous mesh cover. The isolation device 6 is used for the temporary isolation culture of newly introduced organisms, or for conducting research on specific inter-organism interactions under controlled conditions.

[0031] Furthermore, to ensure the long-term stability of the simulated environment and the high repeatability of the experimental process, the environmental simulation device also performs independent and coordinated precise control of key physical parameters such as water temperature, salinity, light intensity, and hydraulics to ensure the long-term steady state of the simulated marine environment.

[0032] Specifically, in terms of temperature control, a heating device 12, such as a heating rod, immersed in the water is used in combination with an external high-precision temperature controller to maintain the temperature of the simulated water body 3 at about 25°C, which is suitable for the optimal physiological and attachment activities of most fouling organisms.

[0033] In one embodiment, salinity stability is achieved by an automatic water replenishment device 2, which has a built-in water level sensor that continuously monitors water loss due to evaporation and controls the salinity at around 30‰ by automatically replenishing fresh water, thereby avoiding osmotic pressure stress on aquatic organisms caused by salinity changes.

[0034] Preferably, the lighting conditions are provided by a lighting device 5, which is equipped with an automatic power switch at its power source. This device can accurately simulate the natural day-night rhythm of alternating 12 hours of light and 12 hours of darkness to regulate the photosynthesis of algae and the life cycle of other organisms in the system.

[0035] Furthermore, the hydraulic conditions are achieved by a wave-generating device 11, for example, using an adjustable-speed circulation pump, which generates a uniform, gentle, and directionally controllable water flow within the tank 1. The flow velocity can be adjusted and stabilized within the range of 0.1-0.3 m / s. This is intended to simulate natural ocean currents, promoting the uniform distribution of dissolved oxygen, nutrients, and larvae in the water, while preventing the deposition of solid particles and eliminating stagnant areas, thereby creating environmental conditions that conform to the characteristics of real ocean dynamics for the attachment behavior of fouling organism larvae.

[0036] Furthermore, water purification and ecological stability maintenance rely on the coordinated operation of the protein separator 9 and the filtration device 10. The protein separator 9 operates based on the principle of air flotation, generating numerous microbubbles to adsorb and separate organic suspended solids and some dissolved proteins from the water, effectively reducing the organic load on the water. In one embodiment, the filtration device 10 is a multi-stage composite filtration system, which sequentially includes a physical filtration layer, a chemical adsorption layer, and a biological filtration layer. The physical filtration layer can use filter media such as cashmere cotton, primarily used to intercept large suspended impurities in the water; the chemical adsorption layer can use materials such as activated carbon to adsorb dissolved organic matter and pigments; and the biological filtration layer can use porous carriers such as bacterial houses and biospheres to cultivate a rich community of nitrifying bacteria and other microorganisms. These three filtration layers work together to establish and maintain a stable nitrogen cycle, continuously degrading harmful substances such as ammonia nitrogen and nitrite produced by biological metabolism.

[0037] In a preferred embodiment, to ensure the long-term operational stability of the simulated ecosystem, regular monitoring can be employed. Regarding basic environmental parameters, water samples can be collected at fixed sampling points, and key indicators such as salinity, temperature, dissolved oxygen, and pH can be rapidly measured using a portable multi-parameter water quality analyzer. For monitoring water nutrients and microorganisms, a spectrophotometric method is used to systematically analyze the concentrations of ammonia nitrogen, nitrite, nitrate, phosphate, and silicate to assess the nutrient cycle status of the system. Simultaneously, chlorophyll a concentration spectrophotometry is used to assess algal biomass, and water samples and attached biofilm samples are collected, stained with fluorescence, and counted under a microscope to determine the total active microbial biomass.

[0038] Preferably, monitoring of fouling organism communities is divided into dynamic populations and sessile communities. For planktonic larval populations of large fouling organisms, a standardized planktonic net is used to filter a quantitative amount of water regularly, and the species, density, and developmental stage of barnacles, mussels, and other larvae are identified under a microscope. For sessile adult organisms such as barnacles and mussels, images are periodically acquired in a pre-designed observation area (such as marked rocks or substrates), and image analysis software is used to calculate their attachment coverage, individual density, and size changes. Sampling measurements can be combined to assess biomass growth and survival rate. This comprehensive monitoring system provides quantitative evidence for assessing the ecological stability of the simulated environment and the reproducibility of the experiment.

[0039] To ensure the accuracy and comparability of monitoring data and the repeatability of experiments, it should be noted that all the above monitoring methods strictly follow a pre-established standardized procedure. The core of this standardized procedure lies in clearly defining the fixed sampling locations, uniform sampling frequency, and standardized testing methods.

[0040] To further enhance the ecological realism of the simulated environment and increase the monitoring dimensions of system stability, a small number of non-fouling marine organisms such as fish and crustaceans (e.g., crabs) can be introduced into the tank 1. The activities of these organisms help simulate a more complete marine ecosystem, and their behavior and physiological state can also serve as auxiliary indicators for assessing the overall environmental health.

[0041] In one embodiment, the visual evaluation system 13 includes a sample testing chamber. Multiple samples to be tested are fixed within this chamber, and the samples can be selected from various antifouling performance evaluation materials according to experimental needs. The sample testing chamber has an inlet 14 and an outlet 15, which are respectively connected to a water tank 1 via pipes to form a circulating water path, allowing the simulated water 3 within the environmental simulation device to circulate over the surface of the samples to be tested and then return to the environmental simulation device.

[0042] Specifically, this circulating water circuit is used to maintain a constant and continuously updated water volume in the sample testing chamber. Through the circulating water circuit, the water flowing over the surface of the sample to be tested maintains dynamic consistency with the simulated water in the environmental simulation device in terms of temperature, salinity, nutrients, and biological population composition, and provides a continuously updated fluid environment for the attachment and growth of fouling organisms on the surface of the sample to be tested.

[0043] Furthermore, the visual evaluation system also includes an image acquisition module positioned above the sample testing chamber for acquiring images of the sample to be tested within the chamber. The area of ​​the sample testing chamber corresponding to the image acquisition module is transparent to facilitate unobstructed optical imaging.

[0044] Specifically, the image acquisition module mainly includes a displacement mechanism and an image acquisition device. The displacement mechanism is preferably a programmable servo-driven electric slide rail, connected to the image acquisition device or the sample detection chamber, thereby creating relative motion between the image acquisition device and the surface of the sample to be tested. Preferably, the displacement mechanism drives the image acquisition device to move along a preset path, and the preset path covers all positions of the sample to be tested. Preferably, the preset path is a serpentine trajectory. The displacement mechanism is configured to stay at the image acquisition point for a preset time to ensure clear image acquisition. Optionally, the preset dwell time is between 0.5s and 2s, preferably set to 1s. The image acquisition device is an industrial camera equipped with an autofocus lens and an adjustable aperture to adapt to the different reflective characteristics of the sample surface.

[0045] In one embodiment, the image acquisition module further includes an illumination device, preferably an LED array light source, which is synchronously controlled with the displacement mechanism or the image acquisition device so that it is lit during the image acquisition period and turned off or dimmed during the non-acquisition period.

[0046] Optionally, for test samples whose size exceeds the field of view of a single image acquisition device, the system employs a multi-point shooting strategy, controlling the image acquisition device to capture images at multiple predetermined points on the surface of the test sample, thereby acquiring multiple local images covering the entire surface of the test sample. In one embodiment, adjacent local images acquired for the same test sample have a 30%-50% overlap area to facilitate accurate image identification during subsequent evaluation.

[0047] In a preferred embodiment, the visual evaluation system 14 further includes an image processing and analysis module. This module is used to process and analyze the acquired images to evaluate the anti-fouling performance of the sample under test.

[0048] Specifically, this module integrates an image stitching unit, a contamination recognition unit, and a performance evaluation unit. The image stitching unit employs a feature point matching algorithm based on Scale Invariant Feature Transform (SIFT) to automatically stitch together multiple local images of the same sample into a complete image of the sample's surface. The contamination recognition unit spatially registers and aligns complete images of the same sample acquired at different time points, calculates image differences, identifies newly added biofouling areas, and optimizes the identified areas using mathematical morphology methods (such as corrosion, dilation, opening, and closing operations). The performance evaluation unit quantifies the degree of contamination by calculating the percentage of contaminated pixels on the sample's surface (contamination coverage rate) and automatically determines the material's antifouling performance level based on preset multi-level thresholds.

[0049] Example 2 This invention also provides a method for evaluating the antifouling performance of materials in a simulated marine environment, the method comprising the following steps: S1, Environment Construction and Maintenance Steps: Within the environmental simulation device, a simulated marine environment in which multiple organisms coexist is constructed and maintained; and multiple test samples are fixed in the sample detection chamber of the visual evaluation system, and simulated water from the environmental simulation device is circulated over the surface of the test samples.

[0050] S2, Image Acquisition Step: The image acquisition module performs periodic automated image acquisition on the surface of the sample to be tested in the sample detection chamber.

[0051] The image acquisition module uses a displacement mechanism to move the image acquisition device sequentially along a preset path to each sample to be tested for image acquisition. Preferably, for each sample, the image acquisition device acquires multiple local images covering its surface, with adjacent local images having a 30%-50% overlap.

[0052] S3. Image processing and analysis step: The acquired images are processed by the image processing and analysis module to evaluate the anti-fouling performance of each of the samples to be tested.

[0053] Specifically, the image processing and analysis step includes image stitching operation, fouling recognition operation and performance evaluation operation.

[0054] Among them, the image stitching operation includes: extracting and matching feature points for multiple partial images of the same sample to be tested, estimating the geometric transformation relationship between images based on the matched feature points, and aligning and fusing the partial images according to the geometric transformation relationship to generate a complete image.

[0055] In specific implementation, multiple partial images of the same sample to be tested are read, and the partial images are preprocessed. For example, image denoising is achieved through Gaussian filtering, and histogram equalization is used to enhance the image contrast to improve the accuracy of subsequent feature matching and stitching effect.

[0056] Specifically, the image stitching operation includes Scale-Invariant Feature Transform (SIFT) feature point extraction. This feature point extraction includes constructing a Difference of Gaussian (DoG) scale space, and detecting local extreme points in the scale space as candidate feature points. Among them, the DoG function for constructing the DoG scale space is: ; In the formula, represents the Difference of Gaussian value at the image position with scale σ, represents the Gaussian convolution kernel, represents the scale parameter, represents the input image, represents the scale multiplier. This formula detects key points in the image that are significant for scale changes by calculating the difference between two Gaussian blurred images with different scales.

[0057] Furthermore, the image stitching operation also includes feature point matching. This feature point matching uses the k-Nearest Neighbor (KNN) algorithm to find the matching points with the closest and the second-closest descriptor distances for the feature points in one image in another image. And the distance ratio test is used to eliminate incorrect matches. The acceptance condition for the match is ratio = d1 / d2 < T, where d1 represents the nearest neighbor distance, d2 is the second-nearest neighbor distance, and T is the threshold. Only when this ratio is less than the threshold, the match pair is accepted.

[0058] Preferably, the method also includes geometric transformation estimation. A Random Sample Consensus (RANSAC) algorithm is used to robustly estimate the homography transformation matrix describing the geometric relationship between the two images from the matched feature point pairs. This algorithm calculates the model by iteratively sampling a small number of matched point pairs and finding the transformation matrix with the largest number of interior points consistent with the model, thereby effectively eliminating interference from erroneous matches.

[0059] In one embodiment, the image stitching operation includes local image fusion. The overlapping areas of the aligned images are weighted and blended using a fade-in / fade-out fusion algorithm to eliminate stitching gaps and brightness differences, achieving a smooth and seamless stitching effect. The formula is expressed as follows: ; In the formula, The merged pixel values and Let be the pixel values ​​in the overlapping region of the two images to be merged. and The corresponding weight coefficients, and satisfying The weights change linearly based on the position of pixels within the overlapping area, thus achieving a natural transition from one image to another, effectively eliminating stitching gaps and brightness differences, and ultimately generating a complete image of the sample under test.

[0060] Furthermore, the contamination identification operation employs an analysis method based on time-series image comparison, which is used to identify contamination bioattachment areas on the surface of the sample by comparing complete images of the same sample at different time points.

[0061] In a specific implementation, complete images of the same sample at different time points are read and precisely spatially aligned. The absolute difference between complete images at adjacent time points is calculated using an image difference algorithm, expressed by the following formula: ΔI(t1,t2)=|I(t2)-I(t1)|; In the formula, I(t1) and I(t2) are the complete images acquired at times t1 and t2, respectively, and ΔI(t1,t2) is the change region obtained by image difference during the period from time t1 to t2. By performing threshold segmentation on this difference image, the newly added contamination and bioattachment areas on the surface of the sample under test during the period from time t1 to t2 can be preliminarily identified.

[0062] In a preferred embodiment, to optimize the initial identification results, a series of mathematical morphological processing steps are applied to the obtained binarized contaminated area image to refine the contours, separate adhered individuals, and fill internal holes. Specifically, this includes: The erosion operation is represented as: ; In the formula This is represented as the input binary image of the contaminated area, i.e., the foreground region in the binary image. Represents a structural element. Represents structural element Translation The position after that, through this operation, retains all the structural elements. The position that is still completely contained within the foreground region A after translation z This operation can eliminate edge burrs and small isolated points.

[0063] Specifically, structural elements A is defined as a small binary matrix or a set of pixels with a specific geometry, whose origin is located at its center or some specified reference point. This structuring element... The shape can be selected based on the morphological characteristics of the target fouling organisms and the purpose of image processing, including but not limited to circular or elliptical, rectangular or square, and linear or cross-shaped. Preferably, the structural elements... The size is determined based on the image resolution and the expected physical size (in pixels) of the contaminated organism in the image.

[0064] The expansion operation is represented as: ; In the formula Represents structural element The reflection (symmetric about the origin). The structure element is translated after reflection. This operation preserves all structural elements. reflection set Translation Back and foreground areas Intersecting positions This operation can fill small holes inside an area and connect adjacent areas.

[0065] In one embodiment, a combined erosion-dilation operation is performed. First, the binarized image of the contaminated area is processed. (i.e., foreground region A) Perform corrosion operation This process eliminates small objects and sharp protrusions, causing the main contours to converge inwards. Subsequently, an expansion operation is immediately performed on the etched results. This process restores the main dimensions and approximate shape of the affected areas, which were lost due to corrosion. This combined operation smooths the outer contours of the affected areas, removes minute details, and separates adhered fragments, aiding in accurate identification and counting of individual affected fragments.

[0066] In another embodiment, the reverse order is used, performing a combined operation of dilation followed by erosion. First, the original binarized image of the contaminated area is processed. Perform expansion operation This process fills the pores and breaks in the connections, reconnecting fragments that might have belonged to the same fouling organism but were separated. Subsequently, a corrosion process is immediately performed on the expanded area. This process counteracts the overall expansion of the area caused by the previous step, restoring the main size and general outline of the contaminated area, while retaining the hole filling and broken connection effects achieved in the previous step. This combined operation smooths the internal structure of the area, fills internal voids, and ensures the integrity of the same contaminated individual, which helps improve the accuracy of subsequent morphological parameter calculations.

[0067] In one embodiment, by reasonably setting structural elements By taking into account the size and shape of the organisms and combining the above operations, the system can effectively separate slightly clump-together soiled organisms and ensure the integrity of each individual soiled area.

[0068] Furthermore, for the morphologically optimized soiled areas, the system calculates quantitative parameters of their morphological characteristics. These parameters are key to identifying biological types and assessing growth status, and mainly include roundness, aspect ratio, area, and perimeter.

[0069] Preferably, by continuously performing the above-described identification, optimization, and feature extraction processes on image sequences acquired at different time points for the same sample under test, the system can construct a dynamic dataset of the evolution of morphological parameters of each contaminated area over time. Analyzing the trends of these parameters, such as the growth rate of area and perimeter, the evolution of roundness over time, and the stability or change of aspect ratio, can not only help distinguish the types of contaminants coexisting on the surface of the sample under test, but also provide a deeper assessment of the growth stage, health status, and spread pattern of individual contaminants on the material surface, thus providing deeper temporal dimension information for a refined evaluation of antifouling performance.

[0070] Optionally, the performance evaluation operation is based on the optimized fouled area data obtained from the aforementioned fouling identification operation. By quantitatively calculating the degree of fouling bioattachment, an objective and graded evaluation of the material's antifouling performance can be achieved.

[0071] Specifically, the performance evaluation operation includes calculating the coverage of biofouled areas on the surface of the test sample. This coverage is the percentage of pixels in biofouled areas relative to the total number of pixels on the test sample surface. The formula is (N_fouling / N_total) × 100%, where N_fouling represents the total number of pixels in the identified biofouled areas, and N_total represents the total number of pixels in the effective area of ​​the test sample surface. This calculation converts the degree of biofouling into a precise numerical indicator.

[0072] Furthermore, the system automatically determines the antifouling performance status of the material based on preset multi-level failure thresholds. In one embodiment, a three-level threshold standard can be set. When the fouling coverage is greater than 5%, the system determines that the surface of the sample under test has initial fouling, and the antifouling performance is beginning to show inadequacy, issuing an initial warning. When the coverage is greater than 10%, it is determined that the antifouling performance of the sample under test has significantly decreased, and the antifouling effect is unsatisfactory. When the coverage is greater than 20%, it is determined that the antifouling performance of the sample under test has completely failed under the current simulated environment.

[0073] It should be noted that the specific values ​​of the above-mentioned thresholds at each level can be customized according to the expected performance of different antifouling materials, the severity of the application scenario, or industry standards, in order to achieve flexible and targeted assessment.

[0074] As a preferred embodiment, this performance evaluation operation also features trend analysis and early warning functions. Specifically, the system continuously records the fouling coverage data of the same test sample at multiple consecutive time points and calculates the rate of change of coverage over time. The calculation formula is (C_t2-C_t1) / (t2-t1), where C_t2 and C_t1 represent the coverage at time t2 and time t1, respectively. By analyzing this rate of change, the speed and trend of fouling development can be determined. When the coverage growth rate of the test sample exceeds a preset rate threshold, the system will issue an early warning signal and generate a final comprehensive report, indicating that the antifouling performance of the material may accelerate its decline in the short term, providing researchers with a forward-looking judgment basis.

[0075] Optionally, to ensure the reliability, consistency, and traceability of the evaluation results, the image processing and analysis module is also equipped with multiple quality control mechanisms, including automatic image quality checking, stitching quality assessment, recognition result verification, and data consistency checking. Through the above performance evaluation operations and their supporting quality control mechanisms, this embodiment of the invention can achieve high-throughput, automated, quantitative, and traceable dynamic evaluation of the antifouling performance of multiple material samples.

[0076] It should be noted that the specific structure, function, and purpose of the material antifouling performance evaluation system for simulating a marine environment can be found in the aforementioned Example 1, and will not be repeated here.

[0077] Furthermore, those skilled in the art should understand that although many problems exist in the prior art, each embodiment or technical solution of the present invention can be improved in only one or a few aspects, without necessarily solving all the technical problems listed in the prior art or the background art simultaneously. Those skilled in the art should understand that any content not mentioned in a claim should not be construed as a limitation on that claim.

[0078] Although this document frequently uses terms such as environmental simulation device, visual assessment system, primary attachment substrate, and biological attachment substrate, the possibility of using other terms is not excluded. These terms are used merely for the convenience of describing and explaining the essence of the invention; interpreting them as any additional limitation would contradict the spirit of the invention.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A material antifouling performance evaluation system simulating a marine environment, characterized in that, include: An environmental simulation device used to construct and maintain a simulated marine environment in which multiple organisms coexist; A visual evaluation system is provided, comprising a sample testing chamber containing multiple samples to be tested, which is fluidly connected to an environmental simulation device to allow simulated water within the device to circulate over the surface of the samples. The system further includes an image acquisition module and an image processing and analysis module. The image acquisition module acquires images of the sample surface within the testing chamber, while the image processing and analysis module processes and analyzes the acquired images to evaluate the antifouling performance of the samples.

2. The material antifouling performance evaluation system for simulating a marine environment according to claim 1, characterized in that: The sample testing chamber is equipped with a water inlet and a water outlet, which are respectively connected to the environmental simulation device to form a circulating water path.

3. The material antifouling performance evaluation system for simulating a marine environment according to claim 1, characterized in that: The image acquisition module includes an image acquisition device and a displacement mechanism driven and connected to the image acquisition device and / or the sample detection chamber; the displacement mechanism is used to drive the image acquisition device to generate relative motion between itself and the surface of the sample to be tested, thereby acquiring an image of the surface of the sample to be tested within the sample detection chamber.

4. A method for evaluating the antifouling performance of materials in a simulated marine environment, characterized in that, Includes the following steps: The environmental construction and maintenance steps involve constructing and maintaining a simulated marine environment in which multiple organisms coexist within an environmental simulation device; fixing multiple test samples in the sample detection chamber of a visual evaluation system, and circulating simulated water from the environmental simulation device over the surface of the test samples. The image acquisition step involves using an image acquisition module to periodically and automatically acquire images of the surface of the sample to be tested within the sample detection chamber. The image processing and analysis steps, including image stitching, stain identification, and performance evaluation, are used to process the acquired images and evaluate the stain resistance of each of the test samples.

5. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 4, characterized in that: For the same sample to be tested, the image acquisition device acquires multiple local images, which together cover the entire surface of the sample to be tested, and there is an overlapping area between adjacent local images.

6. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 5, characterized in that: The image stitching operation includes: extracting and matching feature points from multiple local images of the same test sample, estimating the geometric transformation relationship between the images based on the matched feature points, and aligning and fusing the local images according to the geometric transformation relationship to generate the complete image.

7. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 6, characterized in that: The soiling identification operation includes: Spatial alignment of the complete images of the same sample under test at different time points; The newly added areas of fouling bioattachment are identified by calculating the image differences between the aligned complete images; Mathematical morphology processing is performed on the identified contaminated areas to optimize the region contours.

8. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 7, characterized in that: The formula for calculating the image difference is: ΔI(t1,t2)=|I(t2)-I(t1)|; In the formula, I(t1) and I(t2) are the complete images acquired at time t1 and time t2, respectively, and ΔI(t1,t2) is the change region obtained by image difference during time t1 to t2.

9. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 7, characterized in that: The mathematical morphological processing includes erosion, dilation, opening, and closing operations; The corrosion operation is expressed as follows: ; The expansion operation is represented as: ; The opening operation is a combination of erosion followed by dilation, expressed as: ; The closing operation is a combination of dilation followed by erosion, expressed as: ; In the formula, The input is a binarized image of the contaminated area. As a structural element, structural element Translation The position after, structural element Regarding reflection at the origin, The structure element is translated after reflection. .

10. The method for evaluating the antifouling performance of materials in a simulated marine environment according to claim 7, characterized in that: The performance evaluation operation includes calculating the coverage of the fouled bio-attached area. The coverage calculation formula is: (N_fouling / N_total)×100%; where N_fouling is the total number of pixels in the identified fouled area, and N_total is the total number of pixels in the effective area of ​​the sample surface to be tested.

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