Evaluation device and program for contamination effect

Abstract

A server device (40) is provided with: an acquisition means (412) for acquiring the degree of fouling in a plurality of regions on the hull surface of a ship; and a calculation means (415) for calculating the frictional resistance of the entire hull using frictional resistance coefficients corresponding to the degree of fouling of the plurality of regions.

Description

Technical Field

[0001] This invention relates to a technique for evaluating the impact of fouling on ship hulls. Background Technology

[0002] There are known techniques for evaluating the fouling of ship hulls (e.g., Patent Document 1).

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2018-27740 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] To assess the impact of hull fouling, performance analysis using ship speed and horsepower is considered. However, the performance degradation identified through this analysis includes not only hull fouling but also effects caused by other factors, thus this method cannot accurately assess the impact of hull fouling. As another method, Underwater Inspection (UWI) reports sometimes include images of the bow, midships, and stern of the hull, along with the fouling conditions determined using these images. Therefore, this information from UWI reports is also considered for assessing the impact of hull fouling. However, UWI reports only provide information on localized fouling conditions, thus this method cannot grasp the impact of fouling on the entire hull surface.

[0008] The purpose of this invention is to accurately assess the impact of fouling on the entire surface of a ship's hull.

[0009] Methods for solving problems

[0010] One aspect of the present invention provides an apparatus for evaluating the impact of fouling, comprising: an acquisition unit for acquiring the degree of fouling in multiple regions of the hull surface of a ship; and a calculation unit for calculating the overall frictional resistance of the hull using frictional resistance coefficients corresponding to the degree of fouling in the multiple regions.

[0011] Alternatively, the acquisition unit may also acquire position information representing the positions of the plurality of regions within the hull, and the calculation unit may calculate the frictional resistance of each of the plurality of regions using the flow velocity at the position represented by the position information of the region and the frictional resistance coefficient corresponding to the fouling degree of the region, and add the frictional resistances of the plurality of regions together to calculate the overall frictional resistance of the hull.

[0012] Alternatively, the fouling impact assessment device may further include: a receiving unit that receives images of the plurality of areas captured by an underwater moving body; a determination unit that uses the images to determine the degree of fouling of the plurality of areas; and a mapping unit that associates the plurality of areas with location information representing the location of the area and the degree of fouling of the area, respectively.

[0013] Alternatively, the underwater mobile body may take images along the welding lines of the hull, and the mapping unit may determine the positions of the plurality of regions within the hull based on the welding lines contained in the images.

[0014] Alternatively, the mapping unit may determine the positions of the plurality of regions within the hull based on the position of the underwater moving body determined using an acoustic lighthouse.

[0015] Alternatively, the mapping unit may determine the positions of the plurality of regions within the hull based on the position of the underwater moving body determined using an inertial navigation device.

[0016] Alternatively, the plurality of regions on the surface of the hull may be marked with markers indicating the positions of the plurality of regions within the hull, and the mapping unit may use the markers contained in the image to determine the positions of the plurality of regions within the hull.

[0017] Alternatively, the fouling impact assessment device may further include: a receiving unit that receives images of the plurality of regions captured by the camera in an underwater moving body having an arm and a camera, together with a fouled sample plate held by the arm along the surface of the hull; and a determination unit that determines the degree of fouling of the plurality of regions based on the similarity between the fouled sample of the fouled sample plate included in the images and each of the plurality of regions.

[0018] Alternatively, the device for evaluating the impact of fouling may further include: a storage unit that stores the history of the overall frictional resistance of the hull or fuel consumption calculated based on that frictional resistance, as well as the periods during which maintenance operations were performed to reduce the frictional resistance of the hull; and

[0019] The analysis unit performs a trend analysis to predict future fuel consumption changes based on the history and the period, assuming the maintenance work was performed at specified time intervals.

[0020] Alternatively, the fouling impact evaluation device may further include: a receiving unit that receives an image of an object region captured by a photographic unit together with a fouled sample plate, showing the area between a first draft in a first draft state of the hull and a second draft in a second draft state different from the first draft state; and a determination unit that determines the degree of fouling of the object region based on the similarity between the fouled sample of the fouled sample plate contained in the image and the object region, wherein the calculation unit further uses a frictional resistance coefficient corresponding to the degree of fouling of the object region to calculate the overall frictional resistance of the hull.

[0021] Alternatively, the calculation unit may calculate the increase in frictional resistance of the object area caused by fouling based on the necessary horsepower difference between the first draft and the second draft.

[0022] In another aspect, the present invention provides a program for causing a computer to perform the following steps: obtaining the degree of fouling of multiple regions on the hull surface of a ship; and calculating the overall frictional resistance of the hull using frictional resistance coefficients corresponding to the degree of fouling of the multiple regions.

[0023] Invention Effects

[0024] According to the present invention, the impact of fouling on the entire surface of the hull can be measured with high precision. Attached Figure Description

[0025] Figure 1 This is a diagram illustrating an example of an evaluation system for an implementation method.

[0026] Figure 2 This is an example of an image taken by an underwater drone.

[0027] Figure 3 This is a diagram illustrating an example of the structure of a server device.

[0028] Figure 4 This is a flowchart illustrating the process for quantitatively evaluating the impact of contamination.

[0029] Figure 5 This is a diagram illustrating the mapping data.

[0030] Figure 6 This is a graph illustrating the trend analysis results of the increase in fuel consumption caused by overall hull fouling.

[0031] Figure 7 This is a diagram showing an example of the water-submerged area of ​​the ship's hull.

[0032] Figure 8 This is a diagram illustrating an example of information related to the relationship between ship speed and engine horsepower.

[0033] Figure 9 This is another example of a graph showing the relationship between ship speed and engine horsepower. Detailed Implementation

[0034] 1. Structure

[0035] Figure 1 This diagram illustrates an example of an evaluation system 1 according to one embodiment. Evaluation system 1 uses images of the hull taken by an underwater drone 20 to evaluate the impact of fouling on the hull, providing information that helps determine the implementation of hull maintenance operations. Furthermore, the hull refers to the main body of the vessel 10 excluding cargo and appurtenances, and does not include the propeller.

[0036] The evaluation system 1 includes an underwater drone 20, a control device 30, and a server device 40. The underwater drone 20 and the control device 30 are communicatively connected via a communication cable 2. The control device 30 and the server device 40 are communicatively connected via a network 3, such as the Internet. Furthermore, the server device 40 is communicatively connected to a terminal device (not shown) mounted on the vessel 10 via the network 3 and a communication satellite 4. Thus, the server device 40 can acquire the outputs of various sensors mounted on the vessel 10.

[0037] The underwater drone 20 dives while the vessel 10 is moored and moves underwater along a prescribed path to capture images of multiple areas of the hull. More specifically, the underwater drone 20 captures images of multiple areas of the hull while moving along the weld lines of the hull. The underwater drone 20 is an example of an underwater mobile body of the present invention. The underwater drone 20 has an arm 21, a camera 22, and a communication IF (interface) 23.

[0038] Arm 21 holds a soiled sample plate, such as a Lambert measuring instrument, along the hull surface. More specifically, arm 21 uses a pressing unit, such as a spring, to press the soiled sample plate against the hull surface. This is because, when determining the degree of soiling of the hull using an image obtained by photographing the hull, the hull contained in that image is compared with the soiled sample plate. Therefore, making the distance from camera 22 to the hull as equal as possible to the distance from camera 22 to the soiled sample plate will increase the accuracy of the soiling determination.

[0039] Camera 22 captures images of multiple areas of the hull together with a fouled sample plate. The images captured by camera 22 are, for example, moving images. However, the images captured by camera 22 are not limited to moving images; they can also be still images captured at predetermined time intervals. To capture the hull as comprehensively as possible, the images are preferably horizontal panoramic images. Capturing the hull together with the fouled sample plate allows for comparison of the hull and the fouled sample plate within the image when determining the degree of fouling of the hull using the image obtained from capturing the hull. Therefore, the comparison can be made regardless of underwater environmental factors such as brightness, angle of light, water color, and turbidity.

[0040] Figure 2 This is an example of an image 220 captured by camera 22. Image 220 includes a region 221 of the hull surface and a contaminated sample plate 222. The contaminated sample plate 222 contains multiple contaminated samples 223 with varying degrees of contamination. Furthermore, as described above, since the underwater drone 20 captures images while moving along the weld line 224 of the hull, image 220 includes the weld line 224 formed on the hull surface.

[0041] Communication IF 23 transmits the image captured by camera 22 to control device 30 via communication cable 2. Additional information such as the date and time of capture can also be attached to the image. Furthermore, the image referred to here is a digital image.

[0042] The control device 30 is installed at the dock and controls the movement of the underwater drone 20 according to the operator's commands. The control device 30 transmits images received from the underwater drone 20 to the server device 40 via network 3.

[0043] Server device 40 is located on land and is managed and operated by the shipping company. Server device 40 evaluates the impact of fouling on the hull of vessel 10 based on images captured by underwater drone 20, and processes information to provide decisions for implementing maintenance operations on vessel 10. Server device 40 is an example of a fouling impact evaluation device of the present invention.

[0044] Figure 3 This diagram illustrates an example of the structure of a server device 40. The server device 40 includes a processor 41, a memory 42, a storage device 43, a communication IF 44, an input unit 45, and a display unit 46. The memory 42, storage device 43, communication IF 44, input unit 45, and display unit 46 are each connected to the processor 41 via a bus.

[0045] Processor 41 controls various parts of server device 40 and performs various calculations by executing programs. Examples of processor 41 include one or more CPUs (Central Processing Units). Memory 42 is a computer-readable storage medium used as a working area of ​​processor 41. Programs and data executed by processor 41 are stored in memory 42. Examples of memory 42 include ROM (Read Only Memory) and RAM (Random Access Memory). Storage device 43 is a computer-readable storage medium that stores various data used by processor 41. Examples of storage device 43 include HHD (Hard Disk Drive) and SSD (Solid State Drive). Memory 42 or storage device 43 is an example of the storage unit of the present invention. Communication IF 44 is connected to network 3 and communicates data with other devices via network 3 according to the prescribed communication standards. Input unit 45 inputs signals corresponding to user operations to processor 41. Examples of input unit 45 include a keyboard and a mouse. Display unit 46 displays various information under the control of processor 41. Examples of display units 46 include liquid crystal displays.

[0046] The processor 41 functions as a receiving unit 411, an acquiring unit 412, a determining unit 413, a mapping unit 414, a calculating unit 415, a processing unit 416, and an analyzing unit 417 by executing programs stored in the memory 42. The receiving unit 411, the acquiring unit 412, the determining unit 413, the mapping unit 414, the calculating unit 415, the processing unit 416, and the analyzing unit 417 are software modules implemented through the collaboration of software and hardware resources.

[0047] The receiving unit 411 receives images of multiple areas of the hull taken by the underwater drone 20. More specifically, when the underwater drone 20 transmits images of multiple areas of the hull, the receiving unit 411 receives the images via the control device 30.

[0048] The acquisition unit 412 uses the image received by the receiving unit 411 to acquire the degree of fouling of multiple areas on the hull surface and positional information indicating the location of these areas within the hull. The acquisition unit 412 includes a determination unit 413 and a mapping unit 414.

[0049] The determination unit 413 uses the image received by the receiving unit 411 to determine the degree of contamination of each of the multiple grids obtained by segmenting the hull surface. More specifically, the determination unit 413 divides the hull surface into multiple grids, treating the area of ​​the hull surface contained in an image as a grid. The number of grids also depends on the size of the hull, for example, from 100 to 1000. Additionally, if the image is a moving image, a frame constituting the moving image can be processed as a single image. The determination unit 413 determines the degree of contamination of each grid based on the similarity between the area of ​​the hull surface contained in the image and each contaminated sample on the contamination sample plate. The degree of contamination can be expressed in words such as "A" to "F" to indicate a grade, or in a qualitative evaluation such as "Good," or numerically.

[0050] The mapping unit 414 generates mapping data that maps the position information representing the grid's location within the hull and the degree of fouling of the grid determined by the determination unit 413 to each of the multiple grids on the hull. More specifically, the mapping unit 414 compares the weld lines contained in the image received by the receiving unit 411 with the steel plate layout diagram of the hull stored in the storage device 43, thereby determining the position of each grid within the hull. Next, the mapping unit 414 associates the position information representing the grid's location with the degree of fouling of the grid for each of the multiple grids on the hull. This generates mapping data. Then, the mapping unit 414 stores the generated mapping data in the storage device 43.

[0051] The calculation unit 415 calculates the overall frictional resistance of the hull based on the mapping data stored in the storage device 43. More specifically, firstly, for each grid within the multiple grids of the hull, the calculation unit 415 calculates the frictional resistance of the grid using the flow velocity at the location indicated by the grid's position information contained in the mapping data, the grid area, and the frictional resistance coefficient corresponding to the degree of fouling of the grid. The correspondence between the degree of fouling and the frictional resistance coefficient is obtained by measuring the frictional resistance coefficients of fouling samples with multiple degrees of fouling, and is stored in a correspondence table and pre-stored in the storage device 43. The higher the degree of fouling, the greater the frictional resistance coefficient. Furthermore, the correspondence table can be appropriately corrected based on the correspondence between the degree of fouling and the frictional resistance coefficient measured on an actual ship. Next, the calculation unit 415 calculates the overall frictional resistance of the hull by adding the frictional resistances of the multiple grids of the hull. Then, the calculation unit 415 stores the calculated overall frictional resistance of the hull in the ship database stored in the storage device 43. The overall frictional resistance of the hull represents the impact of fouling on the entire surface of the hull. If the overall frictional resistance of the hull increases, the amount of fuel required to travel at the same speed will increase. Therefore, it is preferable to carry out maintenance operations such as hull cleaning to reduce the frictional resistance of the hull and eliminate the effects of this fouling.

[0052] The production unit 416 generates accounting information based on the overall frictional resistance of the hull stored in the storage device 43. More specifically, the production unit 416 uses the increase in fuel consumption caused by fouling of the hull, calculated based on the overall frictional resistance of the hull, to calculate the payback period for maintenance operations and generates a report containing accounting information for that payback period. Furthermore, in this application, fuel consumption refers to fuel consumption rate, and more specifically, the distance that the vessel 10 can travel on a unit of fuel.

[0053] Analysis unit 417 performs trend analysis based on the overall frictional resistance of the hull stored in storage device 43 or the historical fuel consumption calculated based on the frictional resistance. More specifically, analysis unit 417 performs trend analysis to predict future fuel consumption changes when hull maintenance operations are performed at specified time intervals, based on the overall frictional resistance or historical fuel consumption of the hull and the history of hull maintenance operations.

[0054] 2. Actions

[0055] 2.1 Quantitative assessment of the impact of pollution

[0056] Figure 4 This is a flowchart illustrating the process for quantitatively assessing the impact of pollution. Whenever vessel 10 is moored at a dock and loading / unloading occurs, pollution monitoring is performed during that loading / unloading. However, pollution monitoring may not be performed every time the vessel is moored at a dock and loading / unloading occurs; for example, it may be performed only when moored at a dock equipped with pollution monitoring equipment, or at predetermined loading / unloading intervals, or even while anchored at sea or while drifting with the internal combustion engine stopped.

[0057] In pollution monitoring, the underwater drone 20, for example, moves underwater along the vertical weld line closest to the bow of a plurality of weld lines extending in the vertical direction (hereinafter referred to as "vertical weld lines"), proceeding sequentially along the starboard side, under the starboard side, bottom of the ship, under the port side, and then upward to the port side. It then moves to the next vertical weld line closest to the bow and moves in the opposite direction along that weld line. This process repeats along the vertical weld lines in order from bow to farthest point. Alternatively, the underwater drone 20, for example, moves underwater along the horizontal weld line closest to the starboard side of a plurality of weld lines extending in the horizontal direction (hereinafter referred to as "horizontal weld lines"), proceeding from bow to stern. It then moves to the next horizontal weld line closest to the starboard side and moves in the opposite direction along that weld line. This process repeats along the horizontal weld lines in order from starboard side, under the starboard side, bottom of the ship, under the port side, and then upward to the port side.

[0058] During this movement, the underwater drone 20 holds the contaminated sample plate 222 along the hull surface via its arm 21, while simultaneously capturing images of multiple areas of the hull along with the contaminated sample plate 222 using its camera 22. The underwater drone 20 transmits the images captured by the camera 22 to the control device 30 via communication IF 23. When the control device 30 transmits the image to the server device 40, the processing in step S11 begins.

[0059] In step S11, the receiving unit 411 receives the image transmitted from the underwater drone 20 via the control device 30 and stores the image in the storage device 43.

[0060] In step S12, the determination unit 413 determines the degree of fouling of each grid on the hull based on the image obtained in step S11. Figure 2 In the example shown, the determination unit 413 calculates the similarity between the region 221 of the hull surface contained in the image and each soiled sample 223 through image analysis. For example, if the soiled sample 223 with the highest similarity represents a soiling degree "E", the determination unit 413 determines that soiling degree "E" as the soiling degree of that grid.

[0061] In step S13, the mapping unit 414 maps positional information representing the location of each grid on the hull to the degree of contamination of that grid as determined in step S12. More specifically, the mapping unit 414 determines the position of each grid within the hull by comparing the weld lines contained in each image obtained in step S11 with the steel plate layout diagram of the hull stored in the storage device 43. For example, in Figure 2 In the image 220 shown, where the tenth vertical welding line from the stern on the starboard side of the hull intersects with the fiftieth horizontal welding line from the bottom of the hull, the location where these welding lines 224 intersect in the steel plate layout diagram is determined as the location of the grid captured in the image.

[0062] Furthermore, if the image acquired in step S11 contains markings painted on the hull, the mapping unit 414 can also consider these markings to determine the position of each grid within the hull. For example, if the image contains text such as "FPT" indicating a tank location, the mapping unit 414 can also determine the location of the grid within the hull where this text is painted. Additionally, on the hull, markings for determining the position of the corresponding grid can be pre-marked at all intersections of the weld lines. Once the positions of all grids are determined in this way, the mapping unit 414 generates mapping data that associates the position information of the grid and the degree of contamination of the grid with the multiple grids of the hull, and stores it in the storage device 43.

[0063] Figure 5This is an example of mapping data 500. Mapping data 500 can be a three-dimensional diagram or a two-dimensional diagram representing the starboard and port sides respectively. In mapping data 500, the position of the grid is represented by the arrangement of the grid on the hull surface. Each grid is represented by a color corresponding to the degree of fouling. Figure 5 In this diagram, different colors are represented by different shading lines. Furthermore, the mapping data 500 is not limited to... Figure 5 The example shown could be a hull unfolded diagram, or a table that associates the position information of each grid with the degree of fouling.

[0064] In cases where the image captured by the underwater drone 20 does not cover the entire hull, the grids used to determine the degree of fouling are discretely distributed. In such cases, the mapping element 414 can also interpolate between these grids using known methods such as spline interpolation.

[0065] Return to Figure 4 In step S14, the calculation unit 415 calculates the overall frictional resistance of the hull based on the mapping data created in step S13. First, the calculation unit 415 calculates the frictional resistance D of each grid of the hull using the following equation (1). f .

[0066] D f =1 / 2ρV 2 S×C f …(1)

[0067] Here, ρ is the specific gravity of water, V is the flow velocity of the grid, S is the area of ​​the grid, and C is the flow velocity of the grid. f This is the frictional resistance coefficient of the mesh. The specific gravity of water, ρ, is constant. The flow velocity V is inferred using CFD (Computational Fluid Dynamics). Alternatively, the flow velocity V can also be inferred from the wear rate of the coating on a real ship 10. The flow velocity V varies depending on the position of the hull. Therefore, the flow velocity V uses the flow velocity at the location represented by the position information of the object's mesh. For example, in the case where the mesh shape is a rectangle with dimensions of 1m x 5m, the area S is 1m x 5m = 5m². 2 For the frictional resistance coefficient C f For example, if the contamination level of the object's mesh is "E", the friction resistance coefficient associated with the contamination level "E" is used in the corresponding table stored in storage device 43.

[0068] Since the images captured by the underwater drone 20 do not cover the entire hull, the frictional resistance D is calculated. f When the grid is discretely distributed, the computational unit 415 can also use known methods such as spline interpolation to interpolate between these grids.

[0069] Next, the calculation unit 415 calculates the frictional resistance D of the entire mesh of the hull. f The frictional resistance of the hull is calculated by summing the values ​​of each grid. For example, if the hull is divided into 1000 grids, the calculation unit 415 calculates the frictional resistance D of these grids. f The frictional resistance of the hull is calculated by adding the values ​​together.

[0070] Furthermore, the calculation unit 415 can also calculate the effect of the increased frictional resistance of the propeller by subtracting the increase in horsepower required to maintain the same speed due to the increased frictional resistance of the entire ship 10 (including the hull and propeller) from the increase in horsepower required to maintain the same speed due to the increased frictional resistance of the entire ship 10. The overall frictional resistance of the ship 10 can also be calculated, for example, using known methods that utilize ship speed and horsepower.

[0071] In step S15, the calculation unit 415 uses the frictional resistance calculated in step S14 to calculate the increase in fuel consumption caused by the fouling of the hull using the following formula (2).

[0072] Increase in fuel consumption due to hull fouling = Increase in horsepower required to maintain the same speed due to hull fouling × Fuel consumption rate = Increase in frictional resistance due to hull fouling × Speed ​​× Combustion consumption rate … (2)

[0073] Here, the combustion consumption rate is the fuel consumption per unit horsepower, and its unit is, for example, g / kwh. The increase in frictional resistance caused by hull fouling is obtained by calculating the difference between the overall frictional resistance of the ship calculated in step S14 and the initial value or other reference values. The ship speed is the planned speed of the ship 10 or the actual speed of the ship 10. The ship speed can be input by the operator through the input unit 45, or it can be obtained from the sensors mounted on the ship 10.

[0074] Alternatively, the calculation unit 415 can use the increase in frictional resistance of the propeller in equation (2) above to replace the increase in frictional resistance caused by the fouling of the hull, thereby calculating the increase in fuel consumption caused by the fouling of the propeller.

[0075] In step S16, the calculation unit 415 stores the overall frictional resistance of the hull calculated in step S14 and the increase in fuel consumption caused by hull fouling calculated in step S15 in the ship database stored in the storage device 43. In the ship database, the overall frictional resistance of the hull and the increase in fuel consumption caused by hull fouling can be stored in association with the ship 10's identification information and the implementation date and time of fouling monitoring. The implementation date and time of fouling monitoring can also use the date and time of photography attached to the images obtained from photographing the hull.

[0076] Whenever loading or unloading occurs on vessel 10, the overall frictional resistance of the hull and the increase in fuel consumption caused by hull fouling are calculated and stored in the vessel database. This accumulates a historical record of the overall frictional resistance of the hull and the increase in fuel consumption caused by hull fouling over time. Additionally, the vessel database also stores the history of maintenance operations entered by the operator through input unit 45. This maintenance operation history includes the type of maintenance operation and the period in which the maintenance operation was performed.

[0077] Information stored in the ship's database can also be provided from the ship company to the management company that performs maintenance work on the ship 10. Examples of this provision method include sending to the management company's terminal device and mailing printed materials (not shown) to the ship's management company.

[0078] 2.2 Provision of accounting information for maintenance operations

[0079] To assist the management company's decision-making regarding the implementation of maintenance operations, the production unit 416 provides accounting information for maintenance operations based on the ship database stored in the storage device 43. More specifically, the production unit 416 uses the increase in fuel consumption caused by hull fouling stored in the ship database to calculate the investment payback period using the following formula (3).

[0080] Investment recovery period = maintenance operating costs / increase in fuel consumption due to hull fouling... (3)

[0081] Here, when the unit for the increase in fuel consumption due to hull fouling is ton / day, the unit for the investment recovery period is day; when the unit for the increase in fuel consumption due to hull fouling is ton / year, the unit for the investment recovery period is year. Maintenance operation costs are the costs required for maintenance operations and are predetermined for each management company implementing the maintenance operations. Maintenance operation costs may also include opportunity costs associated with the maintenance operations. The increase in fuel consumption due to hull fouling is eliminated through the implementation of maintenance operations; therefore, the period during which maintenance operation costs can be recovered is obtained through the above formula (3).

[0082] Production unit 416 generates a report including the investment payback period. Alternatively, production unit 416 can also determine whether maintenance work should be performed by comparing the investment payback period with a threshold, and include this determination in the report. This report is provided from the ship company to the management company performing maintenance work on vessel 10. Examples of this provision method include sending it to the management company's terminal device and mailing a printed copy (not shown). The head of the management company can determine whether maintenance work should be performed by comparing the investment payback period included in the report with a threshold set by each management company. For example, the head of the management company can also determine that hull cleaning should be performed if the investment payback period for recovering the cost of hull cleaning, which is less than 1.5 years, is sufficient to cover the increased fuel consumption due to hull fouling.

[0083] 2.3 Trend Analysis

[0084] Analysis unit 417 performs trend analysis based on the ship database stored in storage device 43. More specifically, analysis unit 417 predicts future changes in fuel consumption caused by hull fouling under conditions where hull maintenance is performed at specified time intervals, based on the annual changes in fuel consumption increases caused by past hull fouling and the periods during which maintenance operations were performed, stored in the ship database. Furthermore, while an example of predicting future fuel consumption increases caused by future hull fouling is given here, future fuel consumption itself can also be predicted.

[0085] Figure 6 This is a graph illustrating the trend analysis results of the increase in fuel consumption caused by the fouling effect of the hull, which represents the overall fouling effect of the hull. Figure 6 In the graph, the horizontal axis represents time (years), and the vertical axis represents the increase in fuel consumption (%) caused by hull fouling. Additionally, in... Figure 6 The example shown uses the percentage increase in fuel consumption due to hull fouling, but the percentage increase in frictional resistance due to hull fouling can be used instead.

[0086] exist Figure 6 (a) ~ Figure 6 In (c), the change in fuel consumption caused by past hull fouling is the same, but the future maintenance operation pattern is different. Figure 6 (a) shows the results of a trend analysis under the condition that hull cleaning is carried out at 1-year intervals in the future. Figure 6 (b) shows the results of a trend analysis under the scenario where hull cleaning is carried out at 1.5-year intervals in the future. Figure 6(c) shows the results of a trend analysis under the scenario where hull cleaning is carried out at 2-year intervals.

[0087] right Figure 6 The method for generating the trend analysis results is explained in detail below. Based on time-series data of fuel consumption increases (%) caused by past hull fouling, obtained from a ship database, a graph of the solid lines L1, L2, or L3 is generated. More specifically, by... Figure 6 Connecting the points (represented by black circles) that indicate the increase in fuel consumption (%) caused by hull fouling at multiple time points, we can create a graph with solid lines representing line segments L1, L2, or L3. In this example, hull cleaning was performed in past periods P1 and P2. If hull cleaning is performed, the increase in fuel consumption (%) caused by hull fouling decreases. Therefore, it is preferable to perform cleaning at least before and after these hull cleanings. Figure 4 The process shown is used to quantitatively evaluate the impact of fouling, calculating the increase in fuel consumption caused by the fouling of the hull. This yields points Q1 and Q2 representing the increase in fuel consumption (%) caused by the fouling of the hull before and after hull cleaning in period P1, and points Q3 and Q4 representing the increase in fuel consumption (%) caused by the fouling of the hull before and after hull cleaning in period P2.

[0088] In the solid lines of line segments L1, L2, or L3, points Q2 and Q4, representing the increase in fuel consumption (%) due to hull fouling after hull cleaning in periods P1 and P2, are connected to the origin using methods such as curve approximation, thus obtaining trend line L11. Because the hull's steel plates suffer irreversible deterioration during hull cleaning, the lower limit of the increase in fuel consumption due to hull fouling after cleaning gradually increases over time. Based on trend line L11, the trend of the increase in fuel consumption (%) caused by hull fouling due to factors other than hull fouling is determined. Furthermore, by joining the positive slope portions of the solid lines of line segments L1, L2, or L3, trend line L15 is obtained. Based on trend line L15, the trend of the increase in fuel consumption (%) caused by hull fouling is determined.

[0089] By using trend lines L11 and L15, it is possible to predict the trend of the increase in fuel consumption (%) caused by hull fouling when hull cleaning is performed at predetermined intervals, such as every 1 year, every 1.5 years, or every 2 years. For example, when hull cleaning is performed every 1 year, the trend can be predicted... Figure 6 The double-dotted section of line L1 in (a) shows the percentage increase in fuel consumption due to hull fouling. Assuming hull cleaning is performed every 1.5 years, the predicted increase is... Figure 6 The double-dotted section of line L2 in (b) shows the percentage increase in fuel consumption due to hull fouling. This is assuming hull cleaning is performed every two years. Figure 6 The double-dotted section of the broken line L3 in (c) shows the increase in fuel consumption (%) caused by hull fouling.

[0090] about Figure 6 (a) ~ Figure 6 Each of the trend analysis results shown in (c) can determine the frequency of hull cleaning by calculating (the amount of cost reduction due to increased fuel consumption - the amount of cost increase due to hull cleaning) over the entire remaining life of the vessel 10.

[0091] Figure 6 The dashed portion of line L1 shown in (a) represents the predicted increase in fuel consumption due to hull fouling, assuming hull cleaning is performed at 1-year intervals. Figure 6 In the example shown in (a), hull cleaning is scheduled to be carried out at one-year intervals from period P3 to period P5. Thus, the predicted increase in total fuel consumption due to hull fouling when hull cleaning is carried out at one-year intervals is represented by the area of ​​the graph enclosed by the double-dotted line portion of the broken line L1 and the horizontal axis.

[0092] Figure 6 The double-dotted section of the broken line L2 shown in (b) represents the predicted increase in fuel consumption due to hull fouling, assuming hull cleaning is implemented at 1.5-year intervals. Figure 6 In the example shown in (b), hull cleaning is scheduled to take place at 1.5-year intervals in periods P6 and P7. Thus, the predicted increase in total fuel consumption under the condition of hull cleaning at 1.5-year intervals is represented by the area of ​​the graph enclosed by the double-dotted line portion of the broken line L2 and the horizontal axis.

[0093] Figure 6 The double-dotted section of the broken line L3 shown in (c) represents the predicted increase in fuel consumption due to hull fouling, assuming hull cleaning is carried out at 2-year intervals. Figure 6 In the example shown in (c), hull cleaning is scheduled to take place at two-year intervals, period P8 and period P9. Thus, the predicted increase in total fuel consumption under the condition of hull cleaning at two-year intervals is represented by the area of ​​the graph enclosed by the double-dotted line portion of the broken line L3 and the horizontal axis.

[0094] according to Figure 6 (a) ~ Figure 6(c) shows the relationship between the frequency of maintenance operations during the life cycle of vessel 10 and the increase in total fuel consumption caused by hull fouling. A higher frequency of maintenance operations results in a smaller increase in total fuel consumption caused by hull fouling, thus reducing fuel costs. However, the increased number of maintenance operations leads to higher maintenance costs. Analysis unit 417 can also calculate the total cost reduction based on the maintenance costs and fuel cost reductions required when hull cleaning is performed at 1-year, 1.5-year, and 2-year intervals, respectively.

[0095] Figure 6 (a) ~ Figure 6 The trend analysis results shown in (c) are provided from the shipping company to the management company performing maintenance work on vessel 10. Alternatively, the total cost reductions that can be achieved can also be provided to the management company along with the trend analysis results. Examples of this provision method include sending to the management company's terminal device and mailing printed materials (not shown). The head of the management company, through... Figure 6 (a) ~ Figure 6 By comparing the results of the trend analysis shown in (c), the optimal maintenance work plan can be formulated. For example, the person in charge of the management company... Figure 6 In the case where the total cost reduction is maximized according to the trend analysis results shown in (b), a maintenance schedule with maintenance operations at 1.5-year intervals can also be developed.

[0096] Furthermore, if large-scale repairs such as sandblasting are implemented, deterioration that cannot be reversed during hull cleaning, such as unevenness in the hull plates and peeling of paint, is eliminated, thus reducing the baseline for increased fuel consumption due to hull fouling. For example, when large-scale repairs and hull cleaning are performed simultaneously, the lower limit of the increased fuel consumption caused by hull fouling after these procedures becomes lower. Therefore, trend analysis can also consider eliminating deterioration that cannot be reversed during hull cleaning based on large-scale repairs.

[0097] Furthermore, in Figure 6 (a) ~ Figure 6In the example shown in (c), only the result of the trend analysis of the increase in fuel consumption caused by the fouling effect of the hull representing the overall fouling effect of the hull is shown, but the result of the trend analysis of the increase in fuel consumption caused by the fouling effect of the propeller and the result of the trend analysis of the increase in fuel consumption caused by the fouling effect of the entire ship 10 calculated using the horsepower and ship speed can also be further shown. In addition, the mode of maintenance work is not limited to only the difference in the implementation interval of hull cleaning. It can also be the difference in the implementation interval of hull cleaning, propeller cleaning, major repairs, or at least two of them. It can also be the difference in the implementation time of the next maintenance work, such as immediately implementing the next maintenance work, implementing it after six months, or implementing it after one year.

[0098] According to the embodiment described above, the fouling degree of the hull is used to calculate the frictional resistance of the hull. Therefore, compared with the case of analyzing the performance of the ship 10 using the ship speed and horsepower, the fouling effect of the hull can be evaluated with high accuracy. In addition, mapping data mapping the position information and fouling degree of these areas is made based on the images obtained by photographing multiple areas of the hull, and the frictional resistance of the entire hull is calculated based on this mapping data. Therefore, the fouling effect on the entire surface of the hull can be grasped. By calculating the frictional resistance of the entire hull in this way, the fouling effect on the entire surface of the hull can be quantitatively evaluated. Therefore, the person in charge of the management company can make a logical judgment on whether to perform maintenance work. In addition, if the maintenance work is performed based on the frictional resistance of the entire hull calculated in this way, it is considered that the effect of the maintenance work is improved. If the effect of the maintenance work is improved, a sense of satisfaction regarding the implementation of the maintenance work can be obtained, and an increase in the implementation rate of the maintenance work can be expected.

[0099] Moreover, since accounting information including the investment recovery period is provided to the management company, the person in charge of the management company can judge whether to perform maintenance work based on profitability. And since the result of the trend analysis of the increase in fuel consumption caused by the fouling effect of the hull is provided to the management company, the person in charge of the management company can know the implementation frequency of the maintenance work that minimizes the total cost during the life cycle of the ship 10. Thus, the person in charge of the management company can formulate an optimal maintenance work plan.

[0100] Moreover, the frictional resistance of the entire hull and the frictional resistance of the propeller can be calculated separately. Therefore, the reasons for the performance degradation of the ship 10 can be distinguished between the fouling effect of the hull and the fouling effect of the propeller. Thus, the optimal maintenance work corresponding to the reason for the performance degradation of the ship 10 can be performed in such a way that the hull is cleaned when the reason for the performance degradation of the ship 10 is the fouling effect of the hull, and the propeller is cleaned when it is the fouling effect of the propeller.

[0101] 3. Variation

[0102] The above-described embodiment is one example of the present invention, and the present invention is not limited to this embodiment. The above-described embodiment can also be modified as follows: Furthermore, two or more of the following modifications can be combined to implement the invention.

[0103] 3.1 Variation Example 1

[0104] In the above-described embodiment, the mapping unit 414 can also determine the position of each grid within the hull using an acoustic beacon method. The acoustic beacons are located at at least three points, including the dock, the seabed, or the sea surface. The underwater drone 20 has a receiver that receives acoustic signals transmitted from the acoustic beacons. The underwater drone 20 determines its three-dimensional position by three-point positioning based on the acoustic signals received from the three acoustic beacons. Alternatively, the underwater drone 20 can also determine its three-dimensional position based on acoustic signals and depth gauge information received from two acoustic beacons, or acoustic signals received from one acoustic beacon and their receiving angle.

[0105] Additionally, the underwater drone 20 determines the shooting direction of the camera 22 and the shooting distance to the surface of the hull, which is the subject of the photography. The underwater drone 20 adds position information representing its three-dimensional position, shooting direction, and shooting distance as supplementary information to the image captured by the camera 22 and transmits it. The mapping unit 414 determines the position of each grid within the hull based on the position information, shooting direction, and shooting distance of the underwater drone 20 added to the image. For example, the mapping unit 414 determines the position of the corresponding grid within the hull as the position of the grid that is a distance away from the position of the underwater drone 20 along the shooting direction. In this modified method, the position of each grid within the hull can also be determined.

[0106] Furthermore, since the vessel 10 is moored, its three-dimensional position does not change significantly. However, due to variations in draft based on cargo load, water level, and bow-to-stern orientation, the three-dimensional position of the vessel 10 can still be determined. In this case, the position of the underwater drone 20 relative to the vessel 10 can be determined more accurately. Additionally, the method for determining the three-dimensional position of the vessel 10 can, for example, be implemented using the same method as that used for determining the three-dimensional position of the underwater drone 20.

[0107] In this variation, the underwater drone 20 can also determine its three-dimensional position by using a method that infers its known position, such as a method using an inertial navigation device, or by using an acoustic beacon as described above.

[0108] 3.2 Variation Example 2

[0109] In the above-described embodiments, markings for determining the three-dimensional positions within the hull can be applied to multiple areas of the hull surface, for example, through a textured coating. For instance, markings indicating the positions of areas can be placed along weld lines at predetermined intervals on the hull surface. The mapping unit 414 uses the markings contained in the image to determine the position of each grid within the hull. According to this variation, the position of each grid within the hull can be determined with high precision.

[0110] 3.3 Variation Example 3

[0111] In the above embodiment, the underwater drone 20 may also have wheels that travel on the surface of the hull. Furthermore, the underwater drone 20 can measure its travel distance and use the measured distance to determine its position relative to the vessel 10. The travel distance can be measured, for example, by calculating based on the wheel rotation speed or by using a laser rangefinder. The underwater drone 20 adds the measured travel distance as supplementary information to the image and transmits it. The mapping unit 414 determines the position of each grid within the hull based on the travel distance added to the image. For example, the mapping unit 414 determines the position of the grid corresponding to the hull as the position where the underwater drone 20 has traveled a distance away from its starting point along a predetermined travel path. In this modified method, the position of each grid within the hull can also be determined.

[0112] 3.4 Variation Example 4

[0113] In the above-described embodiment, the underwater drone 20 may not necessarily photograph the hull surface and the contaminated sample plate together. For example, the underwater drone 20 may only photograph the hull surface using camera 22. The storage device 43 stores images of contaminated samples representing the contaminated sample plate. The mapping unit 414 performs image analysis to calculate the similarity between each contaminated sample in the images stored in the storage device 43 and the area of ​​the hull surface in the images captured by the underwater drone 20, and determines the degree of contamination corresponding to the contaminated sample with the highest similarity. The contaminated sample image used for determining the degree of contamination preferably represents a contaminated sample plate used in an underwater environment similar to the hull's underwater environment. For example, a contaminated sample plate with a similar photographic environment may be selected and used based on information such as brightness during underwater photography. In this modified method, the degree of contamination of the hull's mesh can also be determined.

[0114] 3.5 Variation Example 5

[0115] In the above-described embodiment, the calculation unit 415 may also use the degree of propeller fouling to calculate the propeller's frictional resistance. For example, the underwater drone 20 uses camera 22 to capture images of the propeller before and after fouling removal. The determination unit 413 determines the degree of propeller fouling by analyzing these images. For example, if the difference between the image before and after fouling removal is large, it indicates a high degree of propeller fouling. The calculation unit 415 uses the degree of propeller fouling instead of the degree of hull fouling and calculates the propeller's frictional resistance using the above-described equation (1). However, the frictional resistance coefficient C of the mesh... f The frictional drag coefficient corresponding to the fouling degree of the propeller is used instead of the frictional drag coefficient corresponding to the fouling degree of the hull mesh. According to this variation, the frictional drag of the propeller with higher precision can be obtained.

[0116] 3.6 Variation Example 6

[0117] In the above-described embodiment, the underwater drone 20 does not need to capture images of the ship's surface. For example, a diver can use a camera to take pictures of the ship's surface while diving. The images captured by the camera are sent to the server device 40. In this modified method, it is also possible to capture images of the ship's surface.

[0118] 3.7 Variation Example 7

[0119] In the above-described embodiments, the structure of the evaluation system 1, the ship 10, the underwater drone 20, the control device 30, and the server device 40 is an example, and is not limited thereto. Multiple devices may have the functions of one device distributed across the entire system, or one device may have the functions of multiple devices integrated into a single system. Furthermore, the operation of the evaluation system 1, the ship 10, the underwater drone 20, the control device 30, and the server device 40 is an example, and is not limited thereto. As long as there are no contradictions, the order of the processing steps of the evaluation system 1, the ship 10, the underwater drone 20, the control device 30, and the server device 40 can be rearranged, or some processing steps can be omitted.

[0120] 3.8 Variation Example 8

[0121] Another aspect of the invention can provide a method having steps of processing performed in the evaluation system 1, the vessel 10, the underwater drone 20, the control device 30, and the server device 40. Furthermore, yet another aspect of the invention can provide a program executed in the underwater drone 20, the control device 30, or the server device 40. This program can be provided by storing it on a computer-readable recording medium or by downloading it via the Internet or the like.

[0122] 3.9 Variation Example 9

[0123] The fouling described in this disclosure includes not only biofouling but also deterioration of surface roughness such as unevenness of the hull's steel plates and peeling of paint. In this case, the degree of fouling described in this disclosure may include surface roughness. The server device 40 may also use images of the hull captured by the underwater drone 20 to determine the degree of fouling, which reflects both biofouling and deterioration of surface roughness such as unevenness of the hull's steel plates and peeling of paint, through methods such as machine learning, and thereby calculate the overall frictional resistance of the hull, taking into account the deterioration of surface roughness such as unevenness of the hull's steel plates and peeling of paint.

[0124] 3.10 Variation Example 10

[0125] In the above-described embodiment, the underwater drone 20 photographs the submerged portion of the hull, and the images are used to evaluate the impact of fouling on the hull. However, the draft of the vessel 10 differs depending on whether it is carrying cargo or not. Therefore, there are portions of the hull that are above water even when lightly loaded, but submerged when fully loaded. A fully loaded state refers to the state where the vessel 10 carries the largest amount of cargo or ballast and has the deepest draft. A lightly loaded state, also known as a ballast state, refers to the state where the vessel 10 carries almost or no cargo and has a shallower draft. The fully loaded state and the lightly loaded state are examples of the first and second draft states of this invention, respectively. Such portions of the hull can also be fouled due to biofouling, paint peeling, etc. Therefore, in this modified example, the impact of fouling is also evaluated on the portions of the hull that are underwater when fully loaded and above water when lightly loaded.

[0126] Figure 7 This diagram illustrates an example of the flooded area 100 of the hull. The flooded area 100 is the region between the full-water draft line 101 and the waterline 102 of the hull. The flooded area 100 is an example of the object area of ​​this invention. The full-water draft line 101 refers to the draft line submerged in water under a fully loaded state. The waterline 102 refers to the line where the submerged portion of the hull intersects the water surface under a light cargo state. The full-water draft line 101 and the waterline 102 are examples of the first and second waterlines of this invention, respectively. Figure 7 As shown, the immersion area 100 is submerged underwater when fully loaded and appears on the water surface when lightly loaded.

[0127] Evaluation system 1 has a photographic unit that captures images of the flooded area 100 together with a soiled sample plate. The photographic unit is, for example, a camera. There are several methods for capturing images of the flooded area 100 together with the soiled sample plate. In a first method, a person uses the photographic unit to capture images of the flooded area 100 from a dock. At this time, the soiled sample plate is held by the person's hand within the photographic range of the photographic unit. Thus, the photographic unit is able to capture images of the flooded area 100 together with the soiled sample plate.

[0128] In the second method, an aerial drone equipped with a camera unit flies around the ship 10 and captures images of the flooded area 100 from above using the camera unit. At this time, the contaminated sample plate can also be held within the camera unit's field of view by the arm of the aerial drone. Alternatively, the contaminated sample plate can be held by a wheeled drone that travels on the ship's surface, positioned within the camera range of the flooded area 100. Thus, the camera unit is able to capture images of the flooded area 100 together with the contaminated sample plate.

[0129] In the third method, a ship-shaped drone equipped with a photography device moves on the water surface around the vessel 10 and captures images of the flooded area 100 from the water surface using a photography unit. At this time, the contaminated sample plate can also be held within the photography range of the photography unit by the arm of the ship-shaped drone. Alternatively, the contaminated sample plate can also be held by a wheeled drone that travels on the surface of the hull and positioned within the photography range of the flooded area 100. Thus, the photography unit is able to capture images of the flooded area 100 together with the contaminated sample plate.

[0130] Furthermore, similar to Modification 4 described above, the imaging unit may not need to capture images of the immersion area 100 together with the soiled sample plate. For example, the imaging unit may only capture images of the immersion area 100. The storage device 43 stores images of the soiled sample plate. These images can be captured in advance in an environment unrelated to the immersion area 100, or they can be captured at the location where the immersion area 100 is photographed. In the latter case, the images of the immersion area 100 and the soiled sample are captured under substantially the same conditions, thus allowing for comparison without being affected by environmental factors such as sunlight.

[0131] Thus, the images captured by the camera unit are input to the server device 40 via human operation or through network 3. The receiving unit 411 accepts the input images. The receiving unit 411 is an example of the receiving unit of the present invention. The determination unit 413, similar to the above embodiment, determines the degree of contamination of the water-submerged area 100 of the hull based on the similarity between the water-submerged area 100 of the hull contained in the input image and each contaminated sample of the contaminated sample plate. The mapping unit 414 maps positional information representing the location of the water-submerged area 100 of the hull and the degree of contamination of the water-submerged area 100 determined by the determination unit 413 using the same method as in the above embodiment or variations. This mapping can also use photogrammetry (image stitching technology).

[0132] The calculation unit 415 can also use the friction resistance coefficient C corresponding to the degree of fouling of the immersion area 100. f The frictional resistance D of the immersion area 100 is calculated using the above equation (1). f The frictional resistance D of all the grids in the hull f Frictional resistance D with the immersion area 100 f The frictional resistance of the hull is calculated by summing these values. Based on this structure, the impact of fouling can be evaluated not only by including the underwater area in the light cargo state, but also by including the submerged area 100 on the water surface in the light cargo state.

[0133] Alternatively, in this modified example, a fouling impact correlation analysis can be performed based on the degree of fouling in the submerged area 100 and the difference in required horsepower between the fully loaded and light cargo states caused by fouling in the submerged area 100. Required horsepower refers to the horsepower required to maintain a certain speed. The calculation unit 415 calculates the increase in frictional resistance of the submerged area 100 caused by fouling based on the difference in required horsepower between the fully loaded and light cargo states. Furthermore, the required horsepower difference used for the fouling impact correlation analysis is not limited to the difference between the fully loaded and light cargo states. For example, the required horsepower difference between the fully loaded or light cargo states and other draft states, or the required horsepower difference between two draft states other than the fully loaded and light cargo states, can also be used.

[0134] Figure 8 This is a graph illustrating an example of information related to the relationship between ship speed and main engine horsepower. Figure 8In the diagram, the horizontal axis represents ship speed (kts), and the vertical axis represents engine horsepower (kw). This information is stored in the storage device 43 of the server device 40. This information includes speed-horsepower curves C1 to C4. Speed-horsepower curve C1 represents the relationship between ship speed and engine horsepower under a fully loaded state with contamination. Speed-horsepower curve C2 represents the relationship between ship speed and engine horsepower under a fully loaded state without contamination. Speed-horsepower curve C3 represents the relationship between ship speed and engine horsepower under a light cargo state with contamination. Speed-horsepower curve C4 represents the relationship between ship speed and engine horsepower under a light cargo state without contamination. The relationship between ship speed and engine horsepower can be determined, for example, from the measured values ​​of ship speed and engine horsepower in a tank test, or from the measured values ​​obtained from sensors mounted on the ship 10. Here, "contamination" refers to contamination of a degree determined by the determination unit 413.

[0135] If we focus on the speed-horsepower curves C1 and C3, then with the boat speed set at 15 kW, the necessary horsepower difference ΔBHP between the horsepower of speed-horsepower curve C1 and speed-horsepower curve C3 is... 污损吃水影响 In addition to the influence of draft changes, the fouling of the submerged area 100 is also included. The greater the fouling degree of the submerged area 100, the greater the required horsepower difference ΔBHP. 污损吃水影响 The more it increases.

[0136] The calculation unit 415 calculates the necessary horsepower difference ΔBHP between the fully loaded state and the light cargo state using the following equation (4). 污损吃水影响 Required horsepower difference ΔBHP 污损吃水影响 This represents the performance difference of the vessel 10 between its light cargo condition and its fully loaded condition, caused by fouling in the flooded area 100. The required horsepower difference ΔBHP 污损吃水影响 The effects of draft changes and fouling are included in the immersion area 100.

[0137] ΔBHP 污损吃水影响 =BHP C1 -BHP C3 …(4)

[0138] Here, BHP C1 It is the necessary horsepower for the speed-horsepower curve C1, BHP C3 It is the necessary horsepower for the speed-horsepower curve C3.

[0139] The horsepower (BHP) and frictional resistance (R) of the main engine f The relationship between the ship speed V and the ship speed V is expressed by the following equation (5).

[0140] BHP×η=EHP=R×V=(R f +R w )×V…(5)

[0141] Here, EHP is effective horsepower, η is the thrust coefficient, and R... w This is wave-making drag. Effective horsepower (EHP) represents the amount of axial work performed by the propeller. Wave-making drag (R) w It can be inferred from known inference formulas.

[0142] The propulsion coefficient η is obtained by the following equation (6).

[0143] η=η0×η hull ×η R …(6)

[0144] Here, η0 is the propeller efficiency, η hull It is the hull efficiency, η R This refers to the stern efficiency. Propeller efficiency η0, hull efficiency η hull , Ship rear efficiency η R All of them can be inferred using known inference formulas.

[0145] Calculation unit 415 uses the necessary horsepower difference ΔBHP by substituting the main engine's horsepower BHP in the above equation (5). 污损吃水影响 It can calculate the increase in frictional resistance ΔR in the submerged area 100 caused by changes in draft and fouling. f .

[0146] In addition, frictional resistance R f With frictional resistance coefficient C f The relationship is represented by the following equation (7).

[0147] R f =1 / 2ρC f SV 2 …(7)

[0148] Here, ρ is the specific gravity of water, S is the area of ​​the immersion region 100, and V is the flow velocity in the immersion region 100.

[0149] Calculation unit 415 uses the increase in frictional resistance ΔR in equation (7) above. f To replace frictional resistance R f It can calculate the increase in frictional resistance coefficient ΔC in the submerged area 100 caused by draft and fouling. f Additionally, the calculation unit 415 calculates the friction resistance coefficient by adding the increase in friction resistance coefficient ΔC to a predetermined, uncontaminated reference friction resistance coefficient. f And thus the frictional resistance coefficient C can be obtained. f Therefore, the more reliable coefficient of frictional resistance C corresponding to the degree of fouling in the immersion area 100 can be determined. f Based on this structure, the impact of fouling on the immersion area 100 can be evaluated more accurately.

[0150] Alternatively, the server device 40 may also have a correction unit that uses the frictional resistance coefficient C obtained in this modified example. f To correct the frictional resistance coefficient C used by the calculation unit 415 in the above embodiment. f The correction unit can also use the frictional resistance coefficient C obtained in this variant. f Not only correcting the frictional resistance coefficient C f It also corrects for the overall frictional resistance of the hull and the increase in frictional resistance caused by hull fouling. Based on this structure, the accuracy of evaluating the impact of hull fouling is improved.

[0151] As another example of pollution impact correlation analysis, calculation unit 415 can also use the necessary horsepower difference ΔBHP that does not include the effect of draft changes. 污损影响 To replace the necessary horsepower difference ΔBHP calculated by equation (4) above. 污损吃水影响 .

[0152] Figure 9 This is another example of a graph illustrating the relationship between ship speed and main engine horsepower. Figure 9 In the diagram, the horizontal axis represents the ship's speed (kts), and the vertical axis represents the engine's horsepower (kw). This information is stored in the storage device 43 of the server device 40. Within this information, [the text abruptly ends here, likely due to an incomplete sentence or missing information]. Figure 8 Similarly, it includes speed-horsepower curves C1 to C4.

[0153] If we focus on the speed-horsepower curves C1 and C2, then with the boat speed set at 15 kW, the necessary horsepower difference ΔBHP between the horsepower of speed-horsepower curve C1 and speed-horsepower curve C2 is... 满载状态 This includes the effects of fouling on the submerged area 100 and areas outside the submerged area 100 under full load conditions. On the other hand, considering the speed-horsepower curves C3 and C4, the necessary horsepower difference ΔBHP between the horsepower of speed-horsepower curve C3 and speed-horsepower curve C4 when the boat speed is set to 15 kts... 轻货状态 The effects of fouling are included in the area outside the submerged area 100 underwater in the light cargo state, but not in the effects of fouling in the submerged area 100 above water in the light cargo state. Therefore, by obtaining the necessary horsepower difference ΔBHP 满载状态 Difference in horsepower from required ΔBHP 轻货状态 The difference can be used to obtain the necessary horsepower difference ΔBHP caused by the fouling of the immersion area 100. 污损影响 The necessary horsepower difference ΔBHP 污损影响This includes the effects of fouling, but not the effects of draft. The greater the fouling degree of the immersion area 100, the greater the required horsepower difference ΔBHP. 污损影响 The more it increases.

[0154] The calculation unit 415 calculates the necessary horsepower difference ΔBHP using the following equations (8) to (10). 污损影响 .

[0155] ΔBHP 满载状态 =BHP C1 -BHP C2 …(8)

[0156] ΔBHP 轻货状态 =BHP C3 -BHP C4 …(9)

[0157] ΔBHP 污损影响 =ΔBHP 满载状态 -ΔBHP 轻货状态 …(10)

[0158] Here, ΔBHP 满载状态 It is the necessary horsepower difference between contaminated and uncontaminated conditions under full load, BHP C1 It is the necessary horsepower for the speed-horsepower curve C1, BHP C2 It is the necessary horsepower for the speed-horsepower curve C2, ΔBHP 轻货状态 It is the necessary horsepower difference between soiled and unsoiled conditions in light cargo mode, BHP C3 It is the necessary horsepower for the speed-horsepower curve C3, BHP C4 This is the required horsepower for speed-horsepower curve C4. The required horsepower difference ΔBHP 满载状态 This indicates the impact of fouling on the submerged area 100 and areas outside the submerged area 100 under full load conditions. On the other hand, the necessary horsepower difference ΔBHP... 轻货状态 This indicates the impact of fouling on areas outside the submerged water zone (100°) in a light cargo condition. Required horsepower difference ΔBHP 污损影响 This indicates the impact of contamination on the submerged area 100. The necessary horsepower difference ΔBHP 污损影响 This does not include the effect of draft.

[0159] The calculation unit 415 uses the necessary horsepower difference ΔBHP calculated in this way. 污损影响 The increase in frictional resistance ΔR caused by fouling in the immersion area 100 can be calculated using equations (5) to (7) above. f The increase in frictional resistance coefficient ΔC f Friction resistance coefficient C fAdditionally, as described above, the correction unit of server device 40 can also use the frictional resistance coefficient C obtained in this modified example. f To correct the frictional resistance coefficient C used by the calculation unit 415 in the above embodiment. f The overall frictional resistance of the hull and the increase in frictional resistance caused by fouling of the hull. Based on this structure, the impact of fouling on the submerged area 100 can be evaluated more accurately.

[0160] Label Explanation

[0161] 1: Evaluation system; 10: Ship; 20: Underwater drone; 21: Arm; 22: Camera; 23: Communication IF; 30: Control device; 40: Server device; 41: Processor; 42: Memory; 43: Storage device; 44: Communication IF; 45: Input unit; 46: Display unit; 411: Receiving unit; 412: Acquisition unit; 413: Judgment unit; 414: Mapping unit; 415: Calculation unit; 416: Production unit; 417: Analysis unit.

Claims

1. A device for evaluating the impact of contamination, comprising: The acquisition unit acquires the fouling level of multiple areas on the hull surface of the vessel; and The calculation unit uses a frictional resistance coefficient corresponding to the degree of fouling in the plurality of regions to calculate the overall frictional resistance of the hull.

2. The apparatus for evaluating the impact of contamination according to claim 1, wherein, The acquisition unit also acquires position information indicating the positions of the multiple regions within the hull. The calculation unit calculates the frictional resistance of each of the multiple regions using the flow velocity at the location indicated by the location information of that region and the frictional resistance coefficient corresponding to the fouling degree of that region, and adds the frictional resistance of the multiple regions together to calculate the overall frictional resistance of the hull.

3. The apparatus for evaluating the impact of contamination according to claim 1, wherein, The evaluation device also features: A receiving unit that receives images of the plurality of areas captured by an underwater moving body; A determination unit uses the image to determine the degree of soiling in the plurality of areas; as well as The mapping unit associates the plurality of regions with location information representing the location of the region and the degree of soiling of the region, respectively.

4. The apparatus for evaluating the impact of contamination according to claim 3, wherein, The underwater mobile object takes the images along the welding lines of the hull. The mapping unit determines the location of the plurality of regions in the hull based on the welding lines contained in the image.

5. The apparatus for evaluating the impact of contamination according to claim 3, wherein, The mapping unit determines the positions of the plurality of regions within the hull based on the position of the underwater moving body determined using an acoustic lighthouse.

6. The apparatus for evaluating the impact of contamination according to claim 3, wherein, The mapping unit determines the positions of the plurality of regions within the hull based on the position of the underwater moving body determined using an inertial navigation device.

7. The apparatus for evaluating the impact of contamination according to claim 3 or 4, wherein, The plurality of regions on the surface of the hull are marked with markings indicating the positions of the plurality of regions within the hull. The mapping unit uses the markers contained in the image to determine the location of the plurality of regions within the hull.

8. The apparatus for evaluating the impact of contamination according to claim 1, wherein, The evaluation device also features: A receiving unit that receives images of the plurality of areas captured by the camera in an underwater mobile body having an arm and a camera, together with a fouled sample plate held by the arm along the surface of the hull. as well as The determination unit determines the degree of soiling of the plurality of regions based on the similarity between the soiled sample of the soiled sample plate contained in the image and each of the plurality of regions.

9. The apparatus for evaluating the impact of contamination according to claim 1, wherein, The evaluation device also features: The storage unit stores the history of the frictional resistance of the hull as a whole or the fuel consumption calculated based on the frictional resistance, as well as the period during which maintenance operations were carried out to reduce the frictional resistance of the hull. as well as The analysis unit performs a trend analysis to predict future fuel consumption changes based on the history and the period, assuming the maintenance work was performed at specified time intervals.

10. The apparatus for evaluating the impact of contamination according to claim 1, wherein, The evaluation device also features: The receiving unit receives an input image of the object region between the first draft of the hull in the first draft state and the second draft in the second draft state, which is different from the first draft state, captured by the photographing unit together with the contaminated sample plate. as well as The determination unit determines the degree of soiling of the object region based on the similarity between the soiled sample in the image and the object region. The calculation unit also uses a frictional resistance coefficient corresponding to the degree of fouling in the object area to calculate the overall frictional resistance of the hull.

11. The apparatus for evaluating the impact of contamination according to claim 10, wherein, The calculation unit calculates the increase in frictional resistance of the object area caused by fouling based on the necessary horsepower difference between the first draft and the second draft.

12. A program, wherein, This program is used to make the computer perform the following steps: Obtain the fouling level of multiple areas on the hull surface of a ship; and The overall frictional resistance of the hull is calculated using a frictional resistance coefficient corresponding to the degree of fouling in the plurality of regions.

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