Ship surface rust removal process optimization method and system

Abstract

The invention provides a ship surface rust removal process optimization method and system, and relates to the technical field of digital processing, and the method comprises the steps: obtaining an image collection result; constructing coordinates of a rust removal area; environment influence data is generated based on the task data collection result and the rust removal area coordinates; obtaining a rust feature matching result; obtaining basic information, and generating basic influence data; inputting a rust evaluation analysis model to obtain an output result; and obtaining a rust removal process matching result, and carrying out rust removal treatment on the target ship. The technical problem that the precision of the control parameters of the rust removal process is low due to the fact that the adaptation degree of the control parameters of the ship surface rust removal process, the rust features and the rust area environment data is low is solved, and the purposes that based on the control parameters, the rust features and the rust area environment data, rust removal process matching is conducted, the precision of the control parameters of the rust removal process is accurately and rapidly generated, and the precision of the control parameters is improved are achieved. And the adaptation degree of the control parameters, the rust features and the rust area environment data of the ship surface rust removal process is improved.

Description

Technical Field

[0001] The invention relates to the technical field of digital processing, and in particular to a method and system for optimizing a ship surface rust removal process. Background Art

[0002] Ships sail in humid environments, and the metal components of ships are very prone to rust in the air and humid environment. Ship rust removal is particularly important in the ship repair industry and ship painting industry. Before ship painting and protection, rust must be removed first to make the surface rust-free so that the painting can achieve the expected effect; after ship painting and protection, the ship surface needs to be regularly rusted to make the surface rust-free to ensure the stability of the ship's metal components. At this stage, the rust removal effect and rust removal cost are unbalanced, and the control parameter accuracy of the ship surface rust removal process is limited.

[0003] In the prior art, there is a technical problem that the control parameters of the ship surface rust removal process have a low degree of compatibility with the rust characteristics and the environmental data of the rust area, resulting in low accuracy of the control parameters of the rust removal process. Summary of the invention

[0004] The present application provides a method and system for optimizing the rust removal process on the surface of a ship, thereby solving the technical problem that the control parameters of the rust removal process on the surface of a ship have a low degree of adaptability to the rust characteristics and environmental data of the rust area, resulting in low accuracy of the control parameters of the rust removal process. The application achieves the technical effect of matching the rust removal process based on the control parameters and the rust characteristics and environmental data of the rust area, accurately and quickly generating the accuracy of the rust removal process control parameters, and improving the adaptability of the control parameters of the rust removal process on the surface of a ship to the rust characteristics and environmental data of the rust area.

[0005] In view of the above problems, the present application provides a method and system for optimizing the rust removal process on the surface of a ship.

[0006] In a first aspect of the present application, a method for optimizing a rust removal process on a ship surface is provided, wherein the method is applied to an intelligent processing system, the intelligent processing system is communicatively connected with an image acquisition device and an information exchange device, and the method comprises: acquiring an image of a target ship through the image acquisition device to obtain an image acquisition result; identifying a rust removal area on the image acquisition result and constructing rust removal area coordinates; acquiring mission data of the target ship through the information exchange device, and generating environmental impact data based on the mission data acquisition result and the rust removal area coordinates; performing rust feature matching on the image acquisition result to obtain a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; obtaining basic information of the target ship, and generating basic impact data based on the basic information and the rust removal area coordinates; inputting the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation and analysis model to obtain an output result; performing rust removal process matching based on the output result to obtain a rust removal process matching result, and performing rust removal processing on the target ship based on the rust removal process matching result.

[0007] The second aspect of the present application provides a ship surface rust removal process optimization system, wherein the system includes: an image acquisition unit, the image acquisition unit is used to acquire an image of a target ship through an image acquisition device to obtain an image acquisition result; a region coordinate construction unit, the region coordinate construction unit is used to identify the rust removal region on the image acquisition result and construct the rust removal region coordinates; an impact data generation unit, the impact data generation unit is used to acquire task data of the target ship through an information interaction device, and generate environmental impact data based on the task data acquisition result and the rust removal region coordinates; a feature matching unit, the feature matching unit is used to identify the rust feature on the image acquisition result matching, obtaining a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; an impact data generating unit, the impact data generating unit is used to obtain basic information of the target ship, and generate basic impact data according to the basic information and the rust removal area coordinates; an output result obtaining unit, the output result obtaining unit is used to input the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation and analysis model to obtain an output result; a rust removal process matching unit, the rust removal process matching unit is used to perform rust removal process matching according to the output result, obtain a rust removal process matching result, and perform rust removal treatment on the target ship according to the rust removal process matching result.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: The method adopts the following steps: obtaining image acquisition results; identifying rust removal areas on image acquisition results and constructing rust removal area coordinates; generating environmental impact data based on task data acquisition results and rust removal area coordinates; matching rust features on image acquisition results to obtain rust feature matching results; obtaining basic information of the target ship and generating basic impact data based on the basic information and rust removal area coordinates; inputting a rust evaluation and analysis model to obtain output results; matching rust removal processes based on the output results to obtain rust removal process matching results, and performing rust removal on the target ship based on the rust removal process matching results. The present application achieves the technical effect of matching rust removal processes based on control parameters, rust features, and rust area environmental data, accurately and quickly generating the accuracy of rust removal process control parameters, and improving the adaptability of control parameters of ship surface rust removal processes to rust features and rust area environmental data. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of a process for optimizing a ship surface rust removal process according to the present application; Figure 2 A schematic diagram of a process of rust removal treatment of a target ship by optimizing the rust removal process in a method for optimizing the rust removal process of a ship surface according to the present application; Figure 3 A schematic diagram of the process of obtaining and correcting rust removal data for a method for optimizing a ship surface rust removal process according to the present application; Figure 4 This is a structural schematic diagram of a ship surface rust removal process optimization system for this application.

[0010] Explanation of the reference numerals: image acquisition unit 11 , area coordinate construction unit 12 , impact data generation unit 13 , feature matching unit 14 , impact data generation unit 15 , output result acquisition unit 16 , rust removal process matching unit 17 . DETAILED DESCRIPTION

[0011] The present application provides a method and system for optimizing the rust removal process on the surface of a ship, thereby solving the technical problem that the control parameters of the rust removal process on the surface of a ship have a low degree of adaptability to the rust characteristics and environmental data of the rust area, resulting in low accuracy of the control parameters of the rust removal process. The application achieves the technical effect of matching the rust removal process based on the control parameters and the rust characteristics and environmental data of the rust area, accurately and quickly generating the accuracy of the rust removal process control parameters, and improving the adaptability of the control parameters of the rust removal process on the surface of a ship to the rust characteristics and environmental data of the rust area. Embodiment 1

[0012] like Figure 1 As shown, the present application provides a method for optimizing the rust removal process on the surface of a ship, wherein the method is applied to an intelligent processing system, the intelligent processing system is communicatively connected with an image acquisition device and an information interaction device, and the method includes: Step S100: acquiring an image of a target ship through the image acquisition device to obtain an image acquisition result; Step S200: identifying the rust removal area based on the image acquisition result, and constructing the rust removal area coordinates; Step S300: collecting mission data of the target ship through the information interaction device, and generating environmental impact data based on the mission data collection result and the rust removal area coordinates; Specifically, ships sail in humid environments, and the metal components of ships are seriously corroded, so the surface needs to be painted for protection. Before painting the ship, rust must be removed to make the surface rust-free so that the painting can achieve the desired effect. In the ship repair industry, ship rust removal is equally important. The main methods of ship rust removal include manual rust removal, mechanical rust removal, chemical rust removal and ultra-high pressure water rust removal.

[0013] Specifically, the target ship is a ship that needs to undergo surface rust removal treatment. The target ship is captured at all angles by an image acquisition device to obtain an image acquisition result, which is the full-angle acquisition output of the image acquisition device. The image acquisition result is subjected to rust removal area recognition (the rust removal area recognition is to locate the rust on the image acquisition result and circle the rust position in the image acquisition result), and the rust removal area coordinates are constructed. The rust removal area coordinates are the boundary coordinates in the rust location coordinates; the information interaction device is an information interaction sending device (in simple terms, it is a plurality of information interaction channels, and one end of the information interaction device is connected to a data input device). The target The mission data of the ship is collected, and the mission data is the navigation mission data of the target ship. The mission data collection results include mission duration, mission distance, target ship draft distance, target ship displacement and other related data information. The mission data collection results and the rust removal area coordinates are associated and bound to generate environmental impact data. The environmental impact data is simply explained as follows: the first area (any area in the rust removal area coordinates) can always be in the sea; the first area can also be in the sea for a period of time and exposed for another period of time; the first area can also always be above the sea surface and occasionally get wet. The relative position information of the first area and the sea water needs to be determined through the mission data collection results to provide a data basis for subsequent data analysis.

[0014] Step S400: performing rust feature matching on the image acquisition result to obtain a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; Step S500: obtaining basic information of the target ship, and generating basic impact data according to the basic information and the rust removal area coordinates; Step S600: inputting the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation and analysis model to obtain an output result; Step S700: performing rust removal process matching according to the output result to obtain a rust removal process matching result, and performing rust removal processing on the target ship according to the rust removal process matching result.

[0015] Specifically, the image acquisition result is matched with rust features (the rust features include metal oxide color features, surface oxidation depth and other related feature parameter information) to obtain rust feature matching results, which include coordinate identification; basic information of the target ship is obtained, which includes relevant basic data such as length, breadth, depth, design draft, scale ratio, etc., and data association and binding are performed based on the basic information and the rust removal area coordinates to generate basic impact data; a rust evaluation and analysis model is trained and constructed based on empirical data, and the environmental impact data, the basic impact data and the rust feature matching results are input into the rust evaluation and analysis model to obtain output results; rust removal process matching is performed based on the output results (the rust removal process can be manual rust removal, mechanical rust removal, chemical rust removal and ultra-high pressure water rust removal, and manual rust removal is preferred for rust removal in small areas and individual locations; it is further determined in combination with the specific scenario), and a rust removal process matching result is obtained, and rust removal treatment of the target ship is performed based on the rust removal process matching result, so as to provide support for ensuring the compatibility of the rust removal process with the target ship and improving the rust removal treatment efficiency of the target ship.

[0016] Training and building a rust evaluation and analysis model based on empirical data specifically includes: using historical environmental impact data, historical basic impact data, historical rust feature matching results and historical output results as training data, using the BP network model as the model basis, inputting the training data into the input end of the BP network model, performing fitting training, and determining the rust evaluation and analysis model after the model output tends to be stable.

[0017] Further, such as Figure 2 As shown, the embodiment of the present application also includes: Step S810: constructing a weld feature set; Step S820: performing weld feature recognition on the image acquisition result based on the weld feature set, and obtaining weld coordinate data according to the rust removal area coordinates; Step S830: optimizing the process parameter control of the rust removal process matching result according to the weld coordinate data to obtain an optimized rust removal process; Step S840: performing rust removal treatment on the target ship by using the optimized rust removal process.

[0018] Specifically, if there is a weld at the rust removal location, the rust removal process parameters need to be optimized, including: the weld features include weld width information, weld length information, weld surface flatness and other related features, the weld features are sorted out to construct a weld feature set; based on the weld feature set, weld feature recognition is performed in the image acquisition result (the weld features of each weld in the image acquisition result are identified, and multiple groups of weld width data, weld length data, and weld surface flatness are determined), and weld coordinate data (the weld coordinate data) are obtained in the rust removal area coordinate limitation area. According to the weld coordinate data, the process parameter control of the rust removal process matching result is optimized (rust removal is performed at the weld position, such as mechanical rust removal. Excessive mechanical vibration is transmitted to the welding port position, which may cause the welding position to loosen. It is necessary to optimize the process parameter control in combination with the scene parameters) to obtain an optimized rust removal process (the optimized rust removal process is specifically used for the weld at the rust removal position); the target ship is rust-removed by the optimized rust removal process to provide support for ensuring the rationality of the rust removal process parameters.

[0019] Furthermore, the embodiment of the present application also includes: Step S850: when performing rust removal treatment on the target ship, obtaining regional rust removal data of each region according to the rust removal process matching result; Step S860: setting the rust removal correction control threshold; Step S870: when the regional rust removal data is executing a node that satisfies the rust removal correction control threshold, the image acquisition device is used to acquire an image of the rust removal region to obtain a corrected image acquisition result; Step S880: generating corrected rust removal data based on the corrected image acquisition result, and adjusting the rust removal data of subsequent areas of the rust removal area by using the corrected rust removal data.

[0020] Specifically, when the rust removal treatment of the target ship is carried out, the rust removal data of each area is extracted synchronously according to the rust removal process matching result, and the regional rust removal data of each area is obtained; the rust removal correction control threshold is set; the rust removal correction control threshold can be set to one value or multiple values. If multiple values ​​are set, the median of the multiple values ​​is taken to control the correction. When the regional rust removal data is executing a node that meets the rust removal correction control threshold, the image of the rust removal area is captured in real time through the image acquisition device to obtain the real-time image acquisition result, which is the corrected image acquisition result; based on the corrected image acquisition result, the corrected rust removal data is generated, and the subsequent regional rust removal data of the rust removal area is adjusted through the corrected rust removal data to avoid excessive rust removal caused by untimely updating of the rust removal data, and the rust removal data is updated in time to provide support for maintaining the rationality of the rust removal process.

[0021] Further, such as Figure 3 As shown, the embodiment of the present application also includes: Step S881: performing rust state matching on the corrected image acquisition result to obtain a rust state matching result; Step S882: performing a rust removal effect deviation analysis on the rust state matching result through the rust removal process matching result to obtain a deviation analysis result; Step S883: generating compensation rust removal control data according to the deviation analysis result, and obtaining the corrected rust removal data according to the compensation rust removal control data.

[0022] Specifically, based on the corrected image acquisition result, the corrected rust removal data is generated, which specifically includes: performing rust state matching on the corrected image acquisition result (the rust state includes relevant state indicators such as rust area, rust color, rust shape, etc.) to obtain a rust state matching result; when performing rust removal treatment on the target ship, performing rust removal effect deviation analysis on the rust state matching result through the rust removal process matching result (in the rust removal treatment, the material characteristics of the target ship components are related to the oxidation and rusting conditions of the materials, and the material characteristics of different target ship components may have certain differences. The deviation of the rust removal effect due to the difference in material characteristics is the rust removal effect deviation), and obtaining a deviation analysis result; based on the deviation analysis result, sequentially obtaining the regional deviation analysis results of each rust removal area, generating compensation rust removal control data through the regional deviation analysis results of each area, setting the corrected rust removal data according to the compensation rust removal control data, and correcting the rust removal control data in combination with the material characteristic differences, so as to provide support for ensuring the accuracy of the corrected rust removal data.

[0023] Furthermore, the embodiment of the present application also includes: Step S884: setting the rust removal stop control threshold; Step S885: when the regional rust removal data is executing a node that satisfies the rust removal stop control threshold, the image acquisition device is used to acquire an image of the rust removal region to obtain a stop image acquisition result; Step S886: performing a stop control deviation analysis based on the stop image acquisition result, and generating stop rust removal control data based on the stop control deviation analysis result; Step S887: performing rust removal processing on subsequent areas of the rust removal area according to the rust removal stop control data.

[0024] Specifically, the rust removal data of subsequent areas in the rust removal area are adjusted by the modified rust removal data to avoid excessive rust removal caused by untimely updating of rust removal data, which specifically includes: setting a rust removal stop control threshold, and the rust removal stop control threshold can be set as a conditional control threshold, and the conditional control threshold can be set when the diameter of the rust spot is not greater than 0.1 mm, and can also be set when 1 / 10 of the rust removal time period of the rust removal treatment is completed (that is, when the rust removal time period reaches 9 / 10, a detection is performed, and if it is consistent with expectations, the rust removal operation is directly terminated. The difference is that after the rust removal operation has been completed, a detection is performed, and there is inevitably a lag in the termination of the rust removal operation). When the regional rust removal data is executing a node that meets the rust removal stop control threshold, the image acquisition device is used to acquire an image of the rust removal area to obtain a stop image acquisition result; stop based on the stop image acquisition result Control deviation analysis (stop control deviation analysis, that is, directly end the rust removal operation, there may still be some rust spots no larger than 0.1 mm on the surface. If there are some rust spots no larger than 0.1 mm, stop control deviation analysis can be performed at 10%, such as setting the conditional control threshold to when the diameter of the rust spot is no larger than 0.1-10%×0.1=0.09 mm; if there are no rust spots, stop control deviation analysis can be performed at 10%, such as setting the conditional control threshold to when the diameter of the rust spot is no larger than 0.1+10%×0.1=0.11 mm, until the minimum resolution unit of the image acquisition device), generate stop rust removal control data based on the stop control deviation analysis result; perform rust removal treatment on subsequent areas of the rust removal area through the stop rust removal control data, so as to further improve the accuracy of the stop rust removal control data and provide support for ensuring the stability of the rust removal stop control instruction.

[0025] Furthermore, the embodiment of the present application also includes: Step S910: obtaining rust removal requirement data; Step S920: performing demand analysis on the rust removal demand data, and generating balance data of rust removal effect and rust removal cost based on the demand analysis result; Step S930: performing rust removal process matching through the output result and the balance data to obtain the rust removal process matching result.

[0026] Specifically, the rust removal demand data includes multi-dimensional demand information such as the user's rust removal cycle and the rust removal energy consumption limit demand, and the rust removal demand data is obtained; the rust removal demand data is analyzed in turn (the rust removal demand data is analyzed from the two perspectives of rust removal effect and rust removal cost), and based on the demand analysis result, the balance data of rust removal effect and rust removal cost are generated (the rust removal effect and rust removal cost functions are segment functions. Generally, in the first part of the segment function, the rust removal cost increases, and the rust removal effect is correspondingly improved; in the second part of the segment function, the rust removal cost increases, and the rust removal effect tends to be stable; the rust removal cost increases, and the rust removal effect tends to be stable; the rust removal cost increases, and the rust removal effect tends to be stable; the rust removal cost increases, and the rust removal effect tends to be stable. The rust removal process can be manual rust removal, mechanical rust removal, chemical rust removal and ultra-high pressure water rust removal. Different rust removal processes have different rust removal effect and rust removal cost functions. Rust removal process matching is performed through the output result and the balance data. The rust removal process matching is to screen the rust removal process whose rust removal effect meets the output result and has low rust removal cost in the balance data, and set the rust removal process whose rust removal effect meets the output result and has low rust removal cost in the balance data as the rust removal process matching result.

[0027] Furthermore, the embodiment of the present application also includes: Step S940: performing rust removal space limitation analysis based on the rust removal area coordinates to obtain rust removal space limitation analysis results; Step S950: optimizing the rust removal process matching result according to the rust removal space limitation analysis result to obtain a space optimized rust removal process; Step S960: performing rust removal treatment on the target ship through the space-optimized rust removal process.

[0028] Specifically, excessive rust removal at a certain position will cause depression on the ship's surface. Rust removal space limitation can avoid the problem of uneven ship surface caused by rust removal, which specifically includes: performing rust removal space limitation analysis (rust removal space limitation includes rust spot area limitation and rust removal depth limitation) through the rust removal area coordinates to obtain rust removal space limitation analysis results; performing process optimization of the rust removal process matching results through the rust removal space limitation analysis results (the process optimization can be performed by mechanical rust removal equipment to smooth the uneven position on the ship's surface) to obtain a space-optimized rust removal process; performing rust removal treatment on the target ship through the space-optimized rust removal process to provide support for sustainable rust removal treatment of the target ship.

[0029] In summary, the ship surface rust removal process optimization method and system provided by the present application have the following technical effects: The present application provides a method and system for optimizing the rust removal process on the surface of a ship, thereby achieving the technical effect of matching the rust removal process based on the control parameters, the rust characteristics, and the environmental data of the rust removal process, accurately and quickly generating the precision of the rust removal process control parameters, and improving the adaptability of the control parameters of the ship surface rust removal process to the rust characteristics and the environmental data of the rust removal area.

[0030] The rust removal stop control threshold is set; image acquisition is performed in the rust removal area to obtain the stop image acquisition result; stop control deviation analysis is performed, and stop rust removal control data is generated based on the stop control deviation analysis result; subsequent area rust removal processing is performed in the rust removal area, which provides support for improving the accuracy of the stop rust removal control data and ensuring the stability of the rust removal stop control instruction.

[0031] By using the rust removal area coordinates to perform rust removal space limitation analysis, the rust removal space limitation analysis results are obtained; the rust removal process matching results are optimized through the rust removal space limitation analysis results to obtain the space optimized rust removal process; the rust removal treatment of the target ship is carried out through the space optimized rust removal process, providing support for sustainable rust removal treatment of the target ship. Embodiment 2

[0032] Based on the same inventive concept as the method for optimizing the rust removal process on the surface of a ship in the aforementioned embodiment, Figure 4 As shown, the present application provides a ship surface rust removal process optimization system, wherein the system comprises: An image acquisition unit 11, wherein the image acquisition unit 11 is used to acquire an image of a target ship through an image acquisition device to obtain an image acquisition result; A region coordinate construction unit 12, the region coordinate construction unit 12 is used to identify the rust removal region based on the image acquisition result and construct the rust removal region coordinates; An impact data generating unit 13, the impact data generating unit 13 is used to collect mission data of the target ship through an information interaction device, and generate environmental impact data based on the mission data collection result and the rust removal area coordinates; A feature matching unit 14, the feature matching unit 14 is used to perform rust feature matching on the image acquisition result to obtain a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; An impact data generating unit 15, the impact data generating unit 15 is used to obtain basic information of the target ship, and generate basic impact data according to the basic information and the rust removal area coordinates; An output result obtaining unit 16, wherein the output result obtaining unit 16 is used to input the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation analysis model to obtain an output result; The rust removal process matching unit 17 is used to perform rust removal process matching according to the output result, obtain a rust removal process matching result, and perform rust removal processing on the target ship according to the rust removal process matching result.

[0033] Furthermore, the system comprises: A weld feature set construction unit, wherein the weld feature set construction unit is used to construct a weld feature set; A weld coordinate data acquisition unit, the weld coordinate data acquisition unit is used to perform weld feature recognition of the image acquisition result based on the weld feature set, and obtain weld coordinate data according to the rust removal area coordinates; An optimized rust removal process obtaining unit, the optimized rust removal process obtaining unit is used to control and optimize the process parameters of the rust removal process matching result according to the weld coordinate data to obtain an optimized rust removal process; A rust removal treatment unit for a target ship, wherein the rust removal treatment unit for a target ship is used to perform rust removal treatment on the target ship through the optimized rust removal process.

[0034] Furthermore, the system comprises: A regional rust removal data acquisition unit, wherein the regional rust removal data acquisition unit is used to obtain regional rust removal data of each region according to the rust removal process matching result when performing rust removal treatment on the target ship; A correction control threshold setting unit, wherein the correction control threshold setting unit is used to set a rust removal correction control threshold; A corrected image acquisition result obtaining unit, wherein the corrected image acquisition result obtaining unit is used to acquire an image of the rust removal area through the image acquisition device when the regional rust removal data is executing a node that satisfies the rust removal correction control threshold, and obtain a corrected image acquisition result; A regional rust removal data adjustment unit is used to generate corrected rust removal data based on the corrected image acquisition result, and to adjust subsequent regional rust removal data of the rust removal area through the corrected rust removal data.

[0035] Furthermore, the system comprises: A rust state matching unit, the rust state matching unit is used to perform rust state matching on the corrected image acquisition result to obtain a rust state matching result; A rust removal effect deviation analysis unit, wherein the rust removal effect deviation analysis unit is used to perform a rust removal effect deviation analysis on the rust state matching result through the rust removal process matching result to obtain a deviation analysis result; A modified rust removal data obtaining unit is used to generate compensated rust removal control data according to the deviation analysis result, and obtain the modified rust removal data according to the compensated rust removal control data.

[0036] Furthermore, the system comprises: A stop control threshold setting unit, wherein the stop control threshold setting unit is used to set a rust removal stop control threshold; A stop image acquisition result acquisition unit, wherein the stop image acquisition result acquisition unit is used to acquire an image of the rust removal area through the image acquisition device when the regional rust removal data is executing a node that meets the rust removal stop control threshold, and obtain a stop image acquisition result; A stop rust removal control data generating unit, the stop rust removal control data generating unit is used to perform a stop control deviation analysis based on the stop image acquisition result, and generate stop rust removal control data based on the stop control deviation analysis result; A regional rust removal processing unit is used to perform subsequent regional rust removal processing on the rust removal area according to the rust removal stop control data.

[0037] Furthermore, the system comprises: A rust removal requirement data obtaining unit, wherein the rust removal requirement data obtaining unit is used to obtain rust removal requirement data; A balance data generating unit, the balance data generating unit is used to perform demand analysis on the rust removal demand data, and generate balance data of rust removal effect and rust removal cost based on the demand analysis result; A rust removal process matching unit is used to perform rust removal process matching through the output result and the balance data to obtain the rust removal process matching result.

[0038] Furthermore, the system comprises: A rust removal space limitation unit, the rust removal space limitation unit is used to perform rust removal space limitation analysis through the rust removal area coordinates to obtain rust removal space limitation analysis results; A process optimization unit, wherein the process optimization unit is used to optimize the rust removal process matching result according to the rust removal space limitation analysis result, so as to obtain a space-optimized rust removal process; A rust removal control unit is used to perform rust removal on the target ship through the space-optimized rust removal process.

[0039] This specification and drawings are merely exemplary illustrations of the present application, and various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. These modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, and the present application intends to include these modifications and variations.

Claims

1. A method for optimizing the rust removal process on a ship surface, characterized in that: The method is applied to an intelligent processing system, the intelligent processing system is communicatively connected with an image acquisition device and an information interaction device, and the method comprises: The image acquisition device is used to acquire an image of the target ship to obtain an image acquisition result; Identify the rust removal area on the image acquisition result and construct the rust removal area coordinates; Collecting the mission data of the target ship through the information interaction device, and generating environmental impact data based on the mission data collection result and the rust removal area coordinates; Performing rust feature matching on the image acquisition result to obtain a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; Obtaining basic information of the target ship, and generating basic impact data according to the basic information and the coordinates of the rust removal area; Inputting the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation and analysis model to obtain an output result; A rust removal process is matched according to the output result to obtain a rust removal process matching result, and rust removal treatment is performed on the target ship according to the rust removal process matching result.

2. The method according to claim 1, characterized in that The method comprises: Build a weld feature set; Perform weld feature recognition on the image acquisition result based on the weld feature set, and obtain weld coordinate data according to the rust removal area coordinates; Control and optimize the process parameters of the rust removal process matching result according to the weld coordinate data to obtain an optimized rust removal process; The target ship is subjected to rust removal treatment by means of the optimized rust removal process.

3. The method according to claim 1, characterized in that The method comprises: When performing rust removal treatment on the target ship, obtaining regional rust removal data of each region according to the rust removal process matching result; Set the rust removal correction control threshold; When the regional rust removal data is executing a node that satisfies the rust removal correction control threshold, the image acquisition device is used to acquire an image of the rust removal region to obtain a corrected image acquisition result; Corrected rust removal data is generated based on the corrected image acquisition result, and the rust removal data of subsequent areas of the rust removal area are adjusted by using the corrected rust removal data.

4. The method according to claim 3, characterized in that The method comprises: Performing rust state matching on the corrected image acquisition result to obtain a rust state matching result; Performing a rust removal effect deviation analysis on the rust state matching result through the rust removal process matching result to obtain a deviation analysis result; The compensation rust removal control data is generated by the deviation analysis result, and the correction rust removal data is obtained according to the compensation rust removal control data.

5. The method according to claim 3, characterized in that The method comprises: Set the rust removal stop control threshold; When the regional rust removal data is executing a node that satisfies the rust removal stop control threshold, the image acquisition device is used to acquire an image of the rust removal region to obtain a stop image acquisition result; Performing a stop control deviation analysis based on the stop image acquisition result, and generating stop rust removal control data based on the stop control deviation analysis result; The rust removal stop control data is used to perform rust removal processing in subsequent areas of the rust removal area.

6. The method according to claim 1, characterized in that The method comprises: Obtain rust removal demand data; Performing demand analysis on the rust removal demand data, and generating balance data of rust removal effect and rust removal cost based on the demand analysis result; The rust removal process is matched by using the output result and the balance data to obtain the rust removal process matching result.

7. The method according to claim 1, characterized in that The method comprises: Performing rust removal space limitation analysis based on the rust removal area coordinates to obtain rust removal space limitation analysis results; Performing process optimization of the rust removal process matching result through the rust removal space limitation analysis result to obtain a space optimized rust removal process; The target ship is subjected to rust removal treatment by means of the space-optimized rust removal process.

8. A ship surface rust removal process optimization system, characterized in that: The system comprises: An image acquisition unit, wherein the image acquisition unit is used to acquire an image of a target ship through an image acquisition device to obtain an image acquisition result; A region coordinate construction unit, the region coordinate construction unit is used to identify the rust removal region based on the image acquisition result and construct the rust removal region coordinates; An impact data generating unit, the impact data generating unit is used to collect mission data of the target ship through an information interaction device, and generate environmental impact data based on the mission data collection result and the rust removal area coordinates; A feature matching unit, the feature matching unit is used to perform rust feature matching on the image acquisition result to obtain a rust feature matching result, wherein the rust feature matching result includes a coordinate identifier; An impact data generating unit, the impact data generating unit is used to obtain basic information of the target ship, and generate basic impact data according to the basic information and the rust removal area coordinates; An output result obtaining unit, the output result obtaining unit is used to input the environmental impact data, the basic impact data and the rust feature matching result into a rust evaluation analysis model to obtain an output result; A rust removal process matching unit is used to perform rust removal process matching according to the output result, obtain a rust removal process matching result, and perform rust removal processing on the target ship according to the rust removal process matching result.

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