Testing methods, devices, equipment, and storage media for anti-corrosion spraying operations on bridge piers and columns.

Abstract

This invention discloses a testing method, apparatus, equipment, and storage medium for anti-corrosion spraying operations on bridge pier columns, relating to the field of anti-corrosion spray coating testing technology. The method includes: pre-spraying testing of the surface of the bridge pier column to be sprayed; cleaning residues using appropriate removal methods; testing the moisture content and performing drying treatment or anti-corrosion coating spraying; and post-spraying testing and corresponding repairs. Pre-spraying testing identifies residues on the concrete surface and cleans them accordingly, followed by surface moisture content testing to ensure the effectiveness of the anti-corrosion coating. Post-spraying testing identifies uncovered areas, minor leaks, and areas with excessively thin or thick coatings, and repairs are made accordingly, ensuring a complete and uniform coverage of the silane anti-corrosion coating, allowing for good penetration into the concrete surface, ultimately guaranteeing the performance of the anti-corrosion coating. High-precision acceptance using modern methods ensures construction quality and safety.

Description

Technical Field

[0001] This invention relates to the field of anti-corrosion spray coating testing technology, and in particular to a testing method, apparatus, equipment and storage medium for anti-corrosion spray coating operations on bridge piers. Background Technology

[0002] During the construction of large bridges, such as cross-sea bridges, it is often necessary to perform anti-corrosion treatment on the bridge piers. This is done by spraying anti-corrosion materials, such as silane, onto the concrete surface of the piers. Due to the large scale of cross-sea bridges and the large dimensions of the piers, robotic or mechanical methods can be used instead of manual spraying for anti-corrosion coating. This not only improves efficiency and saves labor costs but also reduces the risks associated with working at heights.

[0003] Due to the large size of the bridge piers, prefabrication can be used for casting, followed by anti-corrosion coating application. Because of this size, the distance between the prefabrication yard and the construction site of the cross-sea bridge should not be too far. However, since cross-sea bridge construction sites are often located along the coast, construction operations are significantly affected by the marine climate. Therefore, the anti-corrosion coating process is crucial for the durability of the cross-sea bridge, especially after the coating is applied. Ensuring the anti-corrosion coating meets performance requirements is a key aspect of the acceptance process. However, due to the large size of the piers and the complex and variable marine climate, comprehensive and detailed testing of the surface anti-corrosion coating is difficult. Reliable methods are needed to ensure the quality of the anti-corrosion coating during acceptance. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and storage medium for detecting anti-corrosion spraying operations on bridge pier columns, in order to solve the technical problem that it is difficult to accurately test the performance of the sprayed silane anti-corrosion coating.

[0005] In a first aspect, embodiments of the present invention provide a method for detecting anti-corrosion spraying operations on bridge pier columns, including:

[0006] S101, Pre-spraying test is performed on the surface of the bridge pier column to be sprayed to analyze the residual condition of the concrete surface of the bridge pier column.

[0007] S102. Based on the results of the pre-spraying test and the type of residue on the concrete surface of the bridge pier column, the surface of the bridge pier column to be sprayed is cleaned using the appropriate cleaning method.

[0008] S103, conduct a moisture content test on the cleaned and qualified bridge pier column surface to be sprayed, and perform surface drying treatment or anti-corrosion coating spraying based on the moisture content test results.

[0009] S104. After the bridge pier column surface has been sprayed, an inspection is carried out, and corresponding repairs are made based on the inspection results.

[0010] Furthermore, S104 includes:

[0011] Microwave near-field scanning and laser-induced fluorescence were used to detect the coverage of the sprayed bridge pier column surface;

[0012] Multispectral imager, infrared thermal imager and laser displacement meter were used to detect the uniformity of the sprayed bridge pier surface and identify the parts where the thickness of the silane anti-corrosion coating exceeded the upper and lower limits of the design.

[0013] Furthermore, the use of a multispectral imager, infrared thermal imager, and laser displacement meter to detect the uniformity of the sprayed bridge pier surface and identify areas where the silane anti-corrosion coating thickness exceeds the design upper and lower limits includes:

[0014] The surface of the bridge pier after spraying was scanned using a multispectral imager, an infrared thermal imager, and a laser displacement meter to obtain multispectral data, thermal image data, and laser morphology data after spraying.

[0015] Water absorption and scattering features are extracted from the multispectral data after spraying; temperature rise rate and steady-state temperature difference features are extracted from the thermal imaging data after spraying; roughness and local curvature features are extracted from the laser morphology data after spraying.

[0016] The water absorption characteristics, scattering characteristics, temperature rise rate characteristics, steady-state temperature difference characteristics, roughness characteristics, and local curvature characteristics are fused to obtain the post-spraying fused characteristics;

[0017] Shared features are extracted from the post-coating fusion characteristics, and thinness and thickness detection heads are used to identify areas where the thickness of the silane anti-corrosion coating exceeds the design upper and lower limits.

[0018] Furthermore, S103 includes:

[0019] The moisture content of the bridge pier surface to be sprayed was detected by using a multispectral imager and an infrared thermal imager.

[0020] If the surface moisture content of the bridge pier exceeds the requirements for anti-corrosion coating application, the surface of the bridge pier shall be dried, and the moisture content shall be tested again after the drying process is completed.

[0021] If the moisture content of the bridge pier surface meets the requirements for anti-corrosion coating spraying, then the anti-corrosion coating spraying construction shall be carried out.

[0022] Furthermore, the method of using a multispectral imager and an infrared thermal imager to detect the moisture content of the surface of the bridge pier column to be sprayed, and obtaining the moisture content of the bridge pier column surface, includes:

[0023] The surface of the bridge pier was scanned using a multispectral imager and an infrared thermal imager to collect multispectral and thermal data of the bridge pier surface, and the data was preprocessed accordingly.

[0024] The thermal imaging data is used to compensate the multispectral data to form compensated spectral data;

[0025] Feature extraction is performed on the compensated spectral data and thermal imaging data to obtain spectral features and temperature features;

[0026] The spectral and temperature features are used to perform feature fusion, and the surface moisture content of the bridge pier column is regressed and output.

[0027] Furthermore, S101 includes:

[0028] Oil residue testing was performed on the surface of the bridge pier column to be sprayed.

[0029] Test for residual release agent on the surface of the bridge pier column to be sprayed;

[0030] Detection of residual laitance on the surface of the bridge pier column to be sprayed.

[0031] Furthermore, S102 includes:

[0032] Based on the pre-coating test results, the corresponding residues on the surface of the bridge pier column to be coated are cleaned.

[0033] After cleaning is completed, a pre-coating test is conducted again. Based on the test results, it is determined whether to continue cleaning until the anti-corrosion coating spraying construction requirements are met.

[0034] Secondly, embodiments of the present invention provide a detection device for anti-corrosion spraying operations on bridge piers, comprising:

[0035] The pre-coating detection module is used to perform pre-coating detection on the surface of the bridge pier column to be coated, and to analyze the residual condition of the concrete surface of the bridge pier column.

[0036] The surface cleaning module is used to clean the surface of the bridge pier column to be sprayed based on the results of the pre-spraying test and the type of residue on the concrete surface of the bridge pier column.

[0037] The moisture content detection module is used to detect the moisture content of the cleaned bridge pier column surface to be sprayed, and to carry out surface drying treatment or anti-corrosion coating spraying based on the moisture content detection results.

[0038] The post-coating inspection module is used to inspect the surface of the bridge pier after coating and to carry out corresponding repairs based on the inspection results.

[0039] Thirdly, embodiments of the present invention provide an electronic device, including:

[0040] One or more processors;

[0041] Storage device for storing one or more programs.

[0042] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described detection method for anti-corrosion spraying operations on bridge piers.

[0043] Fourthly, embodiments of the present invention provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the above-mentioned detection method for anti-corrosion spraying of bridge pier columns.

[0044] This invention provides a method, apparatus, equipment, and storage medium for inspecting anti-corrosion spraying operations on bridge piers. The method involves pre-spraying and inspecting the surface of the bridge pier before applying the silane anti-corrosion coating. This identifies residual oil, release agent, and laitance on the concrete surface and cleans them accordingly. Following this, the surface moisture content is tested to ensure the effectiveness of the subsequent silane anti-corrosion coating application. Post-spraying inspection of the bridge pier surface identifies uncovered areas, minor leaks, and areas with excessively thin or thick coatings, and repairs are made accordingly. This ensures a complete and uniform silane anti-corrosion coating coverage, allowing for good penetration into the concrete surface and ultimately guaranteeing the performance of the anti-corrosion coating to meet the durability and safety requirements of cross-sea bridges. This modern approach enables high-precision acceptance of the bridge pier anti-corrosion spraying operation, ensuring construction quality and subsequent related support requirements. Attached Figure Description

[0045] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0046] Figure 1 This is a flowchart of a detection method for anti-corrosion spraying operation of bridge pier columns as described in Embodiment 1 of the present invention;

[0047] Figure 2 This is a flowchart of a detection method for anti-corrosion spraying operation of bridge pier columns as described in Embodiment 2 of the present invention;

[0048] Figure 3 This is a flowchart of a detection method for anti-corrosion spraying operation of bridge pier columns as described in Embodiment 3 of the present invention;

[0049] Figure 4 This is a schematic diagram of a detection device for anti-corrosion spraying operation of bridge pier columns as described in Embodiment 4 of the present invention;

[0050] Figure 5 This is a structural diagram of the electronic device described in Embodiment 5 of the present invention. Detailed Implementation

[0051] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0052] Example 1

[0053] Figure 1 This is a flowchart of a detection method for anti-corrosion spraying operation of bridge pier columns according to Embodiment 1 of the present invention. This embodiment involves detecting and cleaning residues on the surface of the bridge pier columns, ensuring the spraying conditions of the anti-corrosion coating through moisture content testing, and conducting post-spraying testing on the completed anti-corrosion coating to ensure that its performance meets relevant requirements. Specifically, the method includes the following steps:

[0054] S101, Pre-spraying test is performed on the surface of the bridge pier column to be sprayed to analyze the residual condition of the concrete surface of the bridge pier column.

[0055] When precast bridge piers, steel formwork is used to create molds, which are then used to pour concrete to form the desired piers or columns. To facilitate demolding, release agents are often applied to the inside of the molds for easy removal. However, excessive application of the release agent, poor quality release agent, or improper demolding timing can leave residue on the concrete surface. During construction, lubricating oil and machine oil may splash onto the concrete surface, leaving oil residue. Improper pouring techniques, such as excessively fast pouring speed, improper vibration methods, or incorrect water-cement ratios or admixture formulations, can also lead to laitance residue on the concrete surface. This laitance residue can affect the penetration rate of the silane anti-corrosion coating, causing it to peel off and ultimately resulting in loss of anti-corrosion performance. Before spraying the silane anti-corrosion coating onto the concrete surface of the bridge pier, a pre-spraying test is required to check for residual oil, release agent, and laitance on the concrete surface of the bridge pier to ensure the effectiveness of the subsequent silane anti-corrosion coating spraying.

[0056] S102. Based on the results of the pre-coating test and the type of residue on the concrete surface of the bridge pier column, the surface of the bridge pier column to be coated shall be cleaned using the appropriate cleaning method.

[0057] Based on the type and condition of residues on the concrete surface of the bridge pier columns obtained after pre-coating inspection, corresponding methods are used for residue cleaning. For example, oil residues can be cleaned using high-pressure water jets or chemical solvents; release agent residues can be cleaned using alkaline hot water, mechanical grinding, or specialized release agent cleaning agents; and laitance residues can be cleaned using dry ice blasting, controlled pressure sandblasting, or high-frequency water jetting. After cleaning, acceptance testing is still required. If the results are unsatisfactory, cleaning must continue until the coating meets the requirements for the silane anti-corrosion coating application.

[0058] S103, conduct a moisture content test on the cleaned and qualified bridge pier column surface to be sprayed, and perform surface drying treatment or anti-corrosion coating spraying based on the moisture content test results.

[0059] The moisture content of the concrete surface has a crucial impact on the anti-corrosion effect of silane anti-corrosion coatings. If the moisture content of the concrete surface is greater than 8%, water molecules fill the capillary pores of the concrete, hindering the penetration of silane. This makes it difficult for silane to penetrate deep into the concrete, resulting in shallow penetration, uneven film formation, and insufficient performance of its anti-corrosion function. This leads to problems such as poor adhesion, reduced durability, and easy aging and cracking. Only when the moisture content of the concrete surface is less than 8% is the capillary pores inside the concrete relatively dry. Silane can penetrate deeper into the concrete under capillary action, evenly distributing on the concrete surface and forming a continuous film. This effectively forms a stable and dense protective layer with good weather resistance and durability, effectively protecting the concrete structure from corrosion for a longer period of time. Multispectral imagers and infrared thermal imagers can be used to collect multispectral and thermal data of the concrete surface. By analyzing the different spectral reflectance of concrete surfaces with different moisture contents at different temperatures, the moisture content of the bridge pier column surface to be sprayed can be calculated for subsequent construction reference. If the moisture content meets the requirements, the anti-corrosion coating will be applied; otherwise, the surface will be dried.

[0060] S104. After the bridge pier column surface has been sprayed, an inspection is carried out, and corresponding repairs are made based on the inspection results.

[0061] After applying silane anti-corrosion spraying to the concrete surface of bridge piers, coverage and uniformity tests are required. These tests identify defects caused by factors such as parameter control, environmental climate, and special treatment of specific areas during construction, including incomplete coverage of the concrete surface, and coatings that are too thin or too thick. Appropriate repairs are then carried out to ensure the performance of the silane anti-corrosion coating. For coverage testing, a preliminary large-scale inspection of the bridge pier surface can be conducted to eliminate larger uncovered defects, followed by a more detailed inspection to eliminate minor gaps and ensure complete coating coverage. For uniformity testing, the thickness and surface shape of the anti-corrosion coating are examined to identify areas where the silane anti-corrosion coating is too thin or too thick. This prevents insufficient anti-corrosion effect due to an insufficiently thin coating, and stress unevenness, reduced adhesion, cracking, peeling, and flaking caused by an excessively thick coating.

[0062] This embodiment involves pre-spraying and testing the surface of the bridge piers before applying the silane anti-corrosion coating. This identifies and removes residual oil, release agent, and laitance from the concrete surface, followed by cleaning. Surface moisture content is then measured to ensure the effectiveness of the subsequent silane anti-corrosion coating application. Post-spraying inspection of the bridge pier surfaces identifies uncovered areas, minor leaks, and areas with excessively thin or thick coatings, allowing for appropriate repairs. This ensures a complete and uniform silane anti-corrosion coating coverage, enabling good penetration into the concrete surface and ultimately guaranteeing the coating's performance to meet the durability and safety requirements of the cross-sea bridge. Modern methods are used for high-precision acceptance testing of the bridge pier anti-corrosion spraying operation, ensuring construction quality and subsequent support requirements.

[0063] In one optional implementation of this embodiment, step S101 includes:

[0064] Oil residue testing was performed on the surface of the bridge pier column to be sprayed.

[0065] At the prefabrication site of bridge piers, mechanical equipment is often used for construction. During operation, lubricating oil, machine oil, and other oil contaminants may splash onto the concrete surface, leaving oil residue. Fluorescent ultraviolet imaging, utilizing the principle that aromatic hydrocarbons in the oil fluoresce under ultraviolet light excitation, can be used to detect oil residue on the surface of the bridge pier to be coated. If the oil layer on the surface of the bridge pier appears thick to the naked eye, infrared thermography can also be used, utilizing the difference in heat capacity between oil and concrete, to detect oil residue on the surface of the bridge pier to be coated.

[0066] Release agent residue was tested on the surface of the bridge pier column to be sprayed.

[0067] Bridge piers can be prefabricated using molds by pouring concrete. During prefabrication, a release agent is needed to facilitate separation between the mold and the concrete. If the release agent is applied in excessive amounts, of poor quality, or the release time is inappropriate, it can leave residue on the concrete surface. Fourier transform infrared spectroscopy can be used to detect the presence of silicone-based or polymer-based release agent residues on the surface of the bridge pier to be coated. It can also be used to detect the presence of inorganic wax-based release agent residues on the surface. The appropriate testing method should be selected based on the type of release agent used.

[0068] Detection of residual laitance on the surface of the bridge pier column to be sprayed.

[0069] When casting precast concrete bridge piers, improper pouring speed or vibration methods, or incorrect water-cement ratio or admixture formulation in the concrete, can lead to laitance residue on the concrete surface. This residue hinders silane penetration, and its expansion stress after absorbing water is significant, easily causing freeze-thaw damage. It also increases chloride ion diffusion, severely impacting the splash zone, ultimately leading to the failure and peeling of the silane protective layer, loss of corrosion resistance, and reduced service life of the bridge pier, thus affecting the safety of the cross-sea bridge. The acoustic impedance method can be used, utilizing the principle that the acoustic impedance of the laitance layer is much lower than that of the concrete, to detect laitance residue on the surface of the bridge pier to be coated.

[0070] Optionally, S102 includes:

[0071] Based on the pre-coating test results, the corresponding residues on the surface of the bridge pier column to be coated are cleaned.

[0072] Based on the type of residue detected on the surface of the bridge pier column to be sprayed during pre-coating inspection, appropriate methods are used to clean the residue. For example, for oil residue, high-pressure water jet cleaning can be used, or chemical solvents can be used to precisely clean small areas of small amounts of oil residue. The appropriate cleaning method can be selected according to the actual situation. For release agent residue, alkaline hot water can be used to clean silicone oil-based release agents, or mechanical grinding can be used to clean wax-based or other cured release agent residues. Alternatively, a special release agent remover can be used depending on the actual situation. For laitance residue, dry ice blasting cleaning can be used to remove laitance through tiny dry ice particles. This method is highly efficient, environmentally friendly, and produces no wastewater. The surface roughness after cleaning is suitable for the ideal penetration conditions of silane. Alternatively, controlled pressure sandblasting, high-frequency water jetting, or other methods can be used to clean laitance residue depending on the actual situation.

[0073] After cleaning is completed, a pre-coating test is conducted again. Based on the test results, it is determined whether to continue cleaning until the anti-corrosion coating spraying construction requirements are met.

[0074] To ensure thorough cleaning and guarantee the corrosion resistance of the subsequent silane anti-corrosion coating, a pre-coating test must be conducted again after cleaning all residues from the surface of the bridge pier column to be sprayed. The same method is used to test the surface of the bridge pier column to be sprayed for various residues. If any residues are still present, the appropriate methods are used to clean them again until the pre-coating test results are qualified and meet the requirements for anti-corrosion coating spraying.

[0075] Example 2

[0076] Figure 2 This is a flowchart of a detection method for anti-corrosion spraying of bridge pier columns according to Embodiment 2 of the present invention. This embodiment is based on the above embodiment and optimized. In this embodiment, S104 is specifically optimized as follows:

[0077] Microwave near-field scanning and laser-induced fluorescence were used to detect the coverage of the sprayed bridge pier column surface;

[0078] Multispectral imager, infrared thermal imager and laser displacement meter were used to detect the uniformity of the sprayed bridge pier surface and identify the parts where the thickness of the silane anti-corrosion coating exceeded the upper and lower limits of the design.

[0079] Accordingly, the detection method for anti-corrosion spraying of bridge pier columns provided in this embodiment specifically includes:

[0080] S201, Pre-spraying test is performed on the surface of the bridge pier column to be sprayed to analyze the residual condition of the concrete surface of the bridge pier column.

[0081] S202. Based on the results of the pre-coating test and the type of residue on the concrete surface of the bridge pier column, the surface of the bridge pier column to be coated is cleaned using the appropriate removal method.

[0082] S203. The moisture content of the cleaned bridge pier column surface to be sprayed is tested. Based on the moisture content test results, surface drying treatment or anti-corrosion coating spraying is carried out.

[0083] S204, microwave near-field scanning and laser-induced fluorescence were used to detect the coverage of the sprayed bridge pier surface.

[0084] First, microwave near-field scanning is used to inspect the surface of the sprayed bridge pier column. The change in microwave reflection coefficient, caused by the difference in dielectric constant between the silane layer and the concrete, is used to check for areas not covered by the silane anti-corrosion coating. During microwave near-field scanning, a flexible probe can be used to improve detection accuracy and surface adaptability. Next, laser-induced fluorescence is used to inspect the sprayed bridge pier column surface again. By irradiating fluorescent markers in the silane coating (which can be added later, such as pyridine derivatives), the principle of excited emission of specific wavelengths of fluorescence is used to distinguish areas without fluorescence signals (concrete surfaces without silane coverage). This allows for the identification of tiny "starry sky" leaks with high resolution, and exhibits strong anti-interference and surface adaptability, improving the detection accuracy of small leaks. Rapid, large-area scanning of the bridge pier column surface using microwave near-field scanning, combined with laser-induced fluorescence detection of tiny, invisible "starry sky" leaks, indicates the need for repair of the silane anti-corrosion coating, effectively preventing accelerated localized corrosion and improving the performance and durability of the anti-corrosion coating.

[0085] S205 uses a multispectral imager, an infrared thermal imager, and a laser displacement meter to detect the uniformity of the sprayed bridge pier surface and identify areas where the thickness of the silane anti-corrosion coating exceeds the design upper and lower limits.

[0086] The prefabrication and construction sites of cross-sea bridges are often located close to the sea, frequently affected by complex and harsh marine climates (wind, waves, salt spray, temperature and humidity variations, etc.), resulting in harsh construction environments and risks in construction process control. For example, insufficient nozzle pressure leads to inadequate atomization and dripping; nozzles that are too far or too close, or those that are clogged, can easily cause uneven coverage, resulting in tiny, invisible leaks resembling a "starry sky." Excessive or insufficient nozzle movement speed, or pausing in certain areas due to design flaws, can all lead to coatings that are too thin, too thick, or have bumps. Furthermore, the movement of the spraying robot may leave uncovered areas. Additionally, there are often areas on the concrete surface that have not been properly repaired, such as rebar ends, construction joints, and bolt holes. Rebar ends require metal rust prevention first, and construction joints and bolt holes require widening and sealing. Improper handling can affect the subsequent application of the silane anti-corrosion coating. By collecting multispectral, thermal, and laser point cloud data of the sprayed bridge pier surface, and utilizing reflectivity images in multiple bands of multispectral data, temperature matrix images of thermal images, and dense point clouds of laser point cloud data, the uniformity of the silane anti-corrosion coating on the sprayed bridge pier surface is detected. This is achieved by analyzing the reflectivity of multispectral data in specific bands, capturing the temperature field distribution generated by the concrete water splash reaction in the temperature matrix image, and combining this with the high-precision absolute three-dimensional surface morphology information of the dense point cloud. The method identifies areas with excessively thin coatings (below the design lower limit), excessively thick coatings (exceeding the design upper limit), as well as uncovered areas or minor leaks, facilitating timely repairs and ensuring project quality, safety, and durability.

[0087] Specifically, a multispectral imager, an infrared thermal imager, and a laser displacement meter were used to scan the surface of the bridge pier after spraying to obtain multispectral data, thermal image data, and laser morphology data after spraying.

[0088] The surface of the coated bridge pier was scanned using a multispectral imager, an infrared thermal imager, and a laser displacement meter, respectively, to collect post-coating multispectral data, post-coating thermal image data, and post-coating laser morphology data. Multispectral data utilizes the different reflectivities of different materials at different wavelengths to reflect information such as material composition, moisture content, and surface roughness of the coated concrete surface. Thermal image data reflects the temperature field distribution generated by the concrete hydration reaction. Concrete hydration heat is a relatively long-term process; although the heat release is large in the early stages of concrete hardening, hydration heat is generated over a long period due to the slow progress of the hydration reaction, which can be used to identify the coating coverage on the concrete surface. Laser morphology data mainly consists of dense point clouds and can reflect the three-dimensional morphology of the coated concrete surface with high accuracy. The collected data also requires appropriate preprocessing, such as radiometric correction, geometric correction, temperature calibration, and noise reduction.

[0089] Water absorption and scattering characteristics are extracted from the multispectral data after spraying; temperature rise rate and steady-state temperature difference characteristics are extracted from the thermal imaging data after spraying; and roughness and local curvature characteristics are extracted from the laser morphology data after spraying.

[0090] Water absorption characteristics are extracted using reflectance data in the 970mm band of multispectral data. Based on the reflectance of this band, representing the water absorption capacity after spraying, it is determined whether the anti-corrosion coating is too thin. Scattering characteristics are extracted using reflectance data in the 1410mm band of multispectral data. Based on the light scattering of the coating after spraying, it is determined whether the anti-corrosion coating is too thick. The temperature rise rate characteristics of thermal imaging data are used to analyze the heat storage capacity of the surface after spraying by assessing the rate of temperature increase. Combined with steady-state temperature difference characteristics, it is determined whether the coating is too thin or too thick. The roughness characteristics of laser topography data are used to identify the reference surface of the sprayed surface. Combined with local curvature characteristics, it is determined whether there are excessively thick areas such as runs or protrusions.

[0091] The water absorption characteristics, scattering characteristics, temperature rise rate characteristics, steady-state temperature difference characteristics, roughness characteristics, and local curvature characteristics are fused to obtain the post-spraying fused characteristics.

[0092] Water absorption characteristics , The reflectance is at the 970nm wavelength (water absorption peak). Reflectivity at 850nm band (reference baseline); An increase indicates weak water absorption capacity, reflecting that the anti-corrosion coating is too thin;

[0093] Scattering characteristics , An increase indicates enhanced light scattering ability, reflecting localized excessive thickness of the anti-corrosion coating. Wavelength (nm) For wavelength differentiation, wavelength Reflectance at that location;

[0094] Temperature rise rate characteristics , Temperature (°C) after 3 seconds. The initial temperature (°C) is given. For temperature difference, For the time difference, An increase indicates a rapid rate of temperature rise, suggesting a small heat capacity and indicating that the anti-corrosion coating is too thin.

[0095] Steady-state temperature difference characteristics , The smaller the value, the greater the heat storage capacity, indicating that the anti-corrosion coating is too thick;

[0096] Roughness characteristics , The deviation between the surface point cloud and the reference plane, i Number the sampling points. n The total number of sampling points. Indicates the reference plane;

[0097] Local curvature features , x The horizontal axis represents the laser scanning direction (unit: mm). y The vertical axis is perpendicular to the scanning direction (unit: mm). z To fit the height function ( z=z(x,y) (unit: )), It can indicate the presence of drips, bumps, etc. on the surface.

[0098] It should be noted that all the above features need to be normalized. A weighted splicing method is used to fuse these features, resulting in the fused features after spraying. The formula is:

[0099]

[0100] in, These are the weighting coefficients. As a feature, and , Characteristics of water absorption , Scattering characteristics , Characteristic of temperature rise rate , Steady-state temperature difference characteristics , Roughness features , Local curvature features CMA is a cross-modal attention feature, and its formula is:

[0101]

[0102] in, For learnable weight matrix, The weight coefficients for the features (normalized by softmax). As a feature, i, j This is the feature number.

[0103] Shared features are extracted from the post-coating fusion characteristics, and thinness and thickness detection heads are used to identify areas where the thickness of the silane anti-corrosion coating exceeds the design upper and lower limits.

[0104] MobileNetV3 is used to extract features from the fused features after spraying. Shared features are formed by increasing the dimensionality. The shared features are then input into the thinness detection head and the thickness detection head to identify areas that are too thin or too thick.

[0105] Thinness detection head:

[0106]

[0107]

[0108] in, For overly thin feature vectors, This is the first layer weight matrix of the thinness detection head. F This is a feature of post-spray fusion. This indicates that the thin eigenvector is a 128-dimensional eigenvector. This is the second layer weight vector of the thinness detection head. This is the bias term for the thinness detection head. It is a linear activation function. It is the Sigmoid activation function. The output of the thinness detection head is used to determine whether there is an excessively thin area based on the lower limit of the design requirements.

[0109] Thickness detection head:

[0110]

[0111]

[0112] in, For excessively thick feature vectors, This is the first layer weight matrix of the thickness detection head. F This is a feature of post-spray fusion. This indicates that the excessively thick feature vector is a 128-dimensional feature vector. This is the second layer weight vector of the thickness detection head. This is the bias term for the thickness detection head. It is a linear activation function. It is the Sigmoid activation function. The output of the thickness detection head is used to determine whether there are excessively thick areas based on the upper limit of design requirements. By using dual detection heads to identify excessively thin and excessively thick areas separately, with independent weights, each learning different feature patterns, the identification of excessively thin and excessively thick areas can be more accurate.

[0113] This embodiment utilizes microwave near-field scanning to rapidly identify uncovered areas, combined with laser-induced fluorescence to identify minute leaks, enabling efficient and accurate coverage identification of silane anti-corrosion coatings. Furthermore, by acquiring post-spraying multispectral data, post-spraying thermal imaging data, and post-spraying laser morphology data, water absorption features, scattering features, temperature rise rate features, steady-state temperature difference features, roughness features, and local curvature features are extracted. These features are then fused, and the fused post-spraying features are used to identify excessively thin and excessively thick areas using both thin and thick detection heads. By leveraging the different characteristics of each feature response and employing multiple feature fusion methods to detect excessively thin and excessively thick areas, and utilizing a dual-detection head structure to independently learn different feature patterns, the accuracy of identifying excessively thin and excessively thick areas is improved, reducing the false positive rate. This method can also be used to indicate efficient and accurate repairs to silane anti-corrosion coatings, ensuring the performance of the anti-corrosion coating.

[0114] Example 3

[0115] Figure 3 This is a flowchart of a detection method for anti-corrosion spraying of bridge pier columns according to Embodiment 3 of the present invention. This embodiment is based on the above embodiment and optimized. In this embodiment, S103 is specifically optimized as follows:

[0116] The moisture content of the bridge pier surface to be sprayed was detected by using a multispectral imager and an infrared thermal imager.

[0117] If the surface moisture content of the bridge pier exceeds the requirements for anti-corrosion coating application, the surface of the bridge pier shall be dried, and the moisture content shall be tested again after the drying process is completed.

[0118] If the moisture content of the bridge pier surface meets the requirements for anti-corrosion coating spraying, then the anti-corrosion coating spraying construction shall be carried out.

[0119] Accordingly, the detection method for anti-corrosion spraying of bridge pier columns provided in this embodiment specifically includes:

[0120] S301, Pre-spraying test is performed on the surface of the bridge pier column to be sprayed to analyze the residual condition of the concrete surface of the bridge pier column.

[0121] S302. Based on the results of the pre-coating test and the type of residue on the concrete surface of the bridge pier column, the surface of the bridge pier column to be coated shall be cleaned using the appropriate cleaning method.

[0122] S303, the moisture content of the bridge pier surface to be sprayed is detected by using a multispectral imager and an infrared thermal imager.

[0123] Multispectral imagers and infrared thermal imagers were used to scan the surface of the bridge pier column to be sprayed, acquiring multispectral and thermal data. Thermal image data was used to compensate for the multispectral data, reducing the influence of temperature on the spectrum and improving the accuracy of the multispectral data. A convolutional neural network was then used to extract spectral and temperature features from the multispectral and thermal image data, and these features were fused to calculate the moisture content of the bridge pier column surface.

[0124] Specifically, multispectral imagers and infrared thermal imagers are used to scan the surface of the bridge piers, collect multispectral and thermal data of the bridge pier surface, and perform corresponding data preprocessing.

[0125] After scanning the surface of the bridge pier column with a multispectral imager and an infrared thermal imager to generate multispectral and thermal image data, the multispectral and thermal image data need to be preprocessed to ensure data quality for subsequent accurate calculations. This can be done by performing radiometric correction on the multispectral data to eliminate light source fluctuations and by performing spatial differential calculations on the thermal image data.

[0126] The thermal imaging data is used to compensate the multispectral data to form compensated spectral data.

[0127] Because concrete undergoes a prolonged hydration heat release process during hardening and solidification, it is necessary to compensate for multispectral data using temperature gradients. This eliminates local microenvironmental differences caused by the hydration heat of large-volume concrete. When the internal water content is high and heat conduction is enhanced, the calculated reflectance value of that area is reduced. Conversely, when surface evaporation is rapid and the local temperature decreases, the reflectance weight of that area is increased, thereby reducing detection errors in hydration heat regions. (Compensation spectral data) The calculation formula is as follows:

[0128]

[0129] in, The original spectral reflectance was measured using a multispectral imager. The temperature linearity compensation coefficient is determined through laboratory isothermal calibration. This is the temperature gradient compensation coefficient. The difference between the current temperature and the reference temperature, assuming the reference temperature is 25℃, is obtained by subtracting 25℃ from the current temperature measured by the thermal imager. The temperature gradient modulus is calculated using spatial differentiation of thermal imaging data. Specifically, the temperature linear compensation coefficient is calculated by placing a concrete specimen in a temperature-controlled chamber and measuring the spectral reflectance under different temperature gradients. This is based on the difference in spectral reflectance between the actual temperature and the reference temperature, and the ratio of this difference to the spectral reflectance at the reference temperature is calculated. This ratio is then compared to the temperature difference between the actual and reference temperatures. The temperature gradient compensation coefficient is obtained by heating a precast concrete slab on one side to create a temperature gradient, measuring the reflectance deviation under different temperature gradients, and calculating the absolute value of the ratio of the reflectance deviation to the temperature gradient modulus.

[0130] Feature extraction is performed on the compensated spectral data and thermal imaging data to obtain spectral features and temperature features.

[0131] Convolutional neural networks (CNNs) are used to extract features from compensated spectral data to obtain spectral features. Convolutional neural networks (CNNs) are used to extract features from thermal imaging data to obtain temperature characteristics. Both spectral and temperature characteristics are represented in the form of multidimensional vectors.

[0132] The spectral and temperature features are used to perform feature fusion, and the surface moisture content of the bridge pier column is regressed and output.

[0133] Feature fusion is performed on spectral and temperature features. During feature fusion, temperature is used to calculate weighting coefficients, forming a temperature-weighted attention feature fusion. Higher fusion weights are assigned to high-temperature regions (regions with active heat of hydration / regions with active water migration), resulting in fused features. The formula is as follows:

[0134]

[0135] in, These are the weighting coefficients. , ( k =0.1), Spectral characteristics, , Temperature characteristics, The fused features are input into a fully connected layer for nonlinear mapping to obtain the surface moisture content of the bridge pier column. :

[0136]

[0137] in, For the weights of the fully connected layer, Indicates the first i The fusion features are obtained through backpropagation optimization during the training phase. This is the bias term, and represents the baseline of the average moisture content of concrete.

[0138] S304. Based on the surface moisture content of the bridge pier column, if the surface moisture content of the bridge pier column exceeds the requirements for anti-corrosion coating spraying, the surface of the bridge pier column shall be dried, and the moisture content shall be tested again after the drying process is completed.

[0139] To ensure the anti-corrosion performance of the silane anti-corrosion coating, the moisture content of the concrete surface to be sprayed must be strictly controlled before spraying. Excessive moisture content can lead to cracks, peeling, and flaking of the coating after spraying, ultimately resulting in localized loss of anti-corrosion capability and threatening the durability of the bridge piers and even the safety of the cross-sea bridge. If the moisture content of the bridge pier surface exceeds the requirements for anti-corrosion coating spraying, drying treatment is necessary to reduce the moisture content. Hot air drying (gradient hot air drying) can be used to dry the concrete surface of the bridge piers. For example, when drying the shallow layer (0-5mm), a stepped cooling from 60℃ to 40℃ with a wind speed of 8-10m / s can achieve good results within 12-24 hours. When drying the deeper layer (5-30mm), a constant temperature of 45℃ with a wind speed of 3-5m / s can achieve good results within 48-72 hours. However, this method requires attention to avoid thermal damage to the concrete surface. Another method is to use vacuum capillary pumping, which involves drilling holes in the concrete surface and embedding water-permeable needles, then connecting a vacuum pump for 48 hours of suction. This method can avoid thermal damage to the concrete surface, but it will cause corresponding drilling damage, which needs to be repaired during subsequent construction.

[0140] S305. If the moisture content of the bridge pier column surface meets the requirements for anti-corrosion coating spraying, then anti-corrosion coating spraying shall be carried out.

[0141] When the moisture content of the bridge pier column surface is found to meet the requirements for anti-corrosion coating spraying, the subsequent anti-corrosion coating spraying work can be carried out. If the moisture content test is still unqualified, drying treatment is still required to ensure the performance of the sprayed anti-corrosion coating.

[0142] S306. After the bridge pier column surface has been sprayed, an inspection is carried out, and corresponding repairs are made according to the inspection results.

[0143] This embodiment collects multispectral and thermal imaging data of the bridge pier column surface, compensates the multispectral data using the thermal imaging data, and calculates the surface moisture content of the bridge pier column by fusing the compensated spectral data with the spectral and temperature features extracted from the thermal imaging data. Utilizing the water absorption sensitive bands of the multispectral data, combined with the temperature gradient changes due to the difference in thermal absorption between moisture and concrete during thermal imaging processing, the moisture content of the concrete surface is accurately detected, providing reliable data support for subsequent silane anti-corrosion coating spraying and the resulting anti-corrosion effect. Simultaneously, the use of multispectral imagers and infrared thermal imagers, also employed in the post-spraying inspection stage, allows for different identification methods, improving equipment utilization and reducing inspection costs, making it suitable for various operational needs.

[0144] Example 4

[0145] Figure 4 This is a schematic diagram of the structure of a detection device for anti-corrosion spraying of bridge pier columns according to Embodiment 4 of the present invention. In this embodiment, the detection device for anti-corrosion spraying of bridge pier columns includes:

[0146] The pre-coating detection module 810 is used to perform pre-coating detection on the surface of the bridge pier column to be coated, and to analyze the residual condition of the concrete surface of the bridge pier column.

[0147] The surface cleaning module 820 is used to clean the surface of the bridge pier column to be sprayed based on the results of the pre-spraying test and the type of residue on the concrete surface of the bridge pier column.

[0148] The moisture content detection module 830 is used to detect the moisture content of the cleaned bridge pier column surface to be sprayed, and to perform surface drying treatment or anti-corrosion coating spraying based on the moisture content detection results.

[0149] The post-coating inspection module 840 is used to inspect the surface of the bridge pier after coating and to carry out corresponding repairs based on the inspection results.

[0150] This embodiment uses a pre-spraying detection module to detect residues on the surface of the bridge pier column to be sprayed. A surface cleaning module then cleans the surface based on the pre-spraying detection results. A moisture content detection module measures the moisture content of the cleaned bridge pier column surface and, based on the moisture content, performs drying treatment or applies the anti-corrosion coating. A post-spraying detection module measures the coverage and uniformity of the anti-corrosion coating on the finished bridge pier column surface. By performing pre-spraying detection on the surface of the bridge pier column to be sprayed before applying the silane anti-corrosion coating, residues such as oil, release agent, and laitance on the concrete surface are identified and cleaned accordingly. Following this, surface moisture content testing ensures the effectiveness of the subsequent silane anti-corrosion coating application. By inspecting the sprayed surfaces of the bridge piers after coating, uncovered areas, minor leaks, and sections with excessively thin or thick coatings are identified and repaired accordingly. This ensures the silane anti-corrosion coating covers the surface completely and is of uniform thickness, allowing for good penetration into the concrete surface and ultimately guaranteeing the coating's performance to meet the durability and safety requirements of the cross-sea bridge. Modern methods are used for high-precision acceptance testing of the anti-corrosion spraying operation on the bridge piers, ensuring construction quality and subsequent support requirements.

[0151] The detection device for anti-corrosion spraying of bridge piers provided in this embodiment of the invention can execute the detection method for anti-corrosion spraying of bridge piers provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0152] Example 5

[0153] Figure 5 This is a structural diagram of an electronic device according to Embodiment 5 of the present invention. Figure 5 A block diagram of an exemplary device 12 suitable for implementing embodiments of the present invention is shown. Figure 5 The device 12 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0154] like Figure 5 As shown, device 12 is represented as a general-purpose computing device. Components of device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and a bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0155] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0156] Device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by device 12, including volatile and non-volatile media, removable and non-removable media.

[0157] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 5 Not shown; usually referred to as a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0158] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0159] Device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with device 12 / server / computer, and / or with any device that enables device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0160] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the detection method for anti-corrosion spraying operations of bridge pier columns provided in the embodiments of the present invention.

[0161] Example 6

[0162] Embodiment 6 of the present invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the detection method for anti-corrosion spraying of bridge pier columns as provided in the above embodiments.

[0163] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0164] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0165] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0166] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and Python, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0167] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A detection method for anticorrosive spraying work of a pier column of a sea-crossing bridge, characterized by, The method comprises the following steps: S101, pre-spraying detection is performed on the surface of the bridge pier column to be sprayed to analyze the residual state of the surface of the bridge pier column; S102, according to the pre-spraying detection result, the surface of the bridge pier column to be sprayed is cleaned according to the residual type of the surface of the bridge pier column; S103, the surface of the bridge pier column to be sprayed is detected for moisture content, and surface drying treatment or anticorrosive coating spraying is performed according to the detection result; S104, post-spraying detection is performed on the surface of the bridge pier column after spraying, and corresponding repair is performed according to the detection result; The S104 comprises: Microwave near-field scanning and laser-induced fluorescence are used to detect the coverage of the surface of the bridge pier column after spraying; A multispectral imager, an infrared thermal imager and a laser displacement meter are used to scan the surface of the bridge pier column after spraying to obtain multispectral data, thermal image data and laser topography data after spraying; Water absorption characteristics and scattering characteristics are extracted from the multispectral data after spraying, temperature rise rate characteristics and steady-state temperature difference characteristics are extracted from the thermal image data after spraying, roughness characteristics and local curvature characteristics are extracted from the laser topography data after spraying, and the extracted characteristics are normalized, then the extracted characteristics are weighted and spliced to obtain fused features after spraying; A trained MobileNetV3 lightweight neural network is used to form shared features by dimensionality increasing according to the fused features after spraying, then a thinness detection head and a thickness detection head are used to identify over-thin areas and over-thick areas of the silane anticorrosive coating whose thickness exceeds the lower limit and upper limit of the design respectively.

2. The method of claim 1, wherein, The S103 comprises: A multispectral imager and an infrared thermal imager are used to detect the moisture content of the surface of the bridge pier column to be sprayed to obtain the moisture content of the surface of the bridge pier column; According to the moisture content of the surface of the bridge pier column, if the moisture content of the surface of the bridge pier column exceeds the anticorrosive coating spraying construction requirement, surface drying treatment is performed, and moisture content detection is performed again after the drying treatment is completed; If the moisture content of the surface of the bridge pier column meets the anticorrosive coating spraying construction requirement, anticorrosive coating spraying construction is performed.

3. The method of claim 2, wherein, The multispectral imager and the infrared thermal imager are used to detect the moisture content of the surface of the bridge pier column to be sprayed to obtain the moisture content of the surface of the bridge pier column, which comprises: A multispectral imager and an infrared thermal imager are used to scan the surface of the bridge pier column to collect multispectral data and thermal image data of the surface of the bridge pier column, and corresponding data preprocessing is performed; The thermal image data is used to compensate the multispectral data to form compensated spectral data; Spectrum characteristics and temperature characteristics are extracted from the compensated spectral data and thermal image data; The spectrum characteristics and the temperature characteristics are fused, and the moisture content of the surface of the bridge pier column is output by regression.

4. The method of claim 1, wherein, The S101 comprises: Oil residue detection is performed on the surface of the bridge pier column to be sprayed; Release agent residue detection is performed on the surface of the bridge pier column to be sprayed; Float residue detection is performed on the surface of the bridge pier column to be sprayed.

5. The method of claim 1, wherein, The S102 comprises: According to the pre-spraying detection result, the corresponding residual on the surface of the bridge pier column to be sprayed is cleaned; After cleaning, pre-spraying detection is performed again, and according to the detection result, it is determined whether to continue cleaning until the anticorrosive coating spraying construction requirement is met.

6. A detection device for implementing the detection method for the anticorrosive spraying work of a pier column of a sea-crossing bridge according to any one of claims 1 to 5, characterized by The method comprises the steps of: a pre-spraying detection module is configured to perform pre-spraying detection on the surface of the bridge pier column to be sprayed, and analyze the residual condition of the concrete surface of the bridge pier column; a surface cleaning module is configured to clean the surface of the bridge pier column to be sprayed according to the result of the pre-spraying detection and the residual type of the concrete surface of the bridge pier column; a moisture content detection module is configured to detect the moisture content of the cleaned surface of the bridge pier column to be sprayed, and perform surface drying treatment or anticorrosive coating spraying according to the moisture content detection result; a post-spraying detection module is configured to perform post-spraying detection on the surface of the bridge pier column after spraying, and perform corresponding repair according to the detection result.

7. An electronic device, comprising: The device comprises: one or more processors; a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the detection method for anticorrosive spraying operation of the bridge pier column of the sea-crossing bridge as claimed in any one of claims 1-5.

8. A storage medium containing computer executable instructions for performing the detection method for anticorrosive spraying operation of the bridge pier column of the sea-crossing bridge as claimed in any one of claims 1-5 when executed by a computer processor.

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