Hull management method for vessel and hull management device for vessel

Abstract

To provide a hull management method for a vessel and a hull management device for a vessel capable of carrying out appropriate measures by predicting soiled state of a hull.SOLUTION: A hull management method for a vessel and a hull management device for a vessel: has a contamination growth prediction model learnt and built from teaching data having the hull size, vessel speed, surface state of the hull, and rate of increase in friction resistance associated beforehand, and having a correlational relationship with the rate of increase in friction resistance and surface state of the hull; speculates the output in navigation in a specific sea route for the subject vessel, ideal fuel consumption at that time, actual fuel consumption trend, and resistance of the strait in the sea route, based on the output in a specific sea route in the past for a vessel of the same type as the subject vessel, ideal fuel consumption, actual fuel consumption, and resistance of the strait, and estimates the rate of increase in friction resistance; and generates contamination growth prediction data indicating relationship between the contamination rate and the number of days which is in a corresponding relationship with the surface state of the hull by inputting the hull size of the vessel and the speculated rate of increase in friction resistance rate to the constructed contamination growth prediction model.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method for managing a ship's hull and a ship's hull management device, and more particularly, to a method for managing a ship's hull and a ship's hull management device that can take appropriate measures during the navigation of the hull by predicting the fouling state of the hull in advance.

Background Art

[0002] The impact of the cross-border movement of organisms on ecosystems has become an international environmental issue, and the international legal system for the management of "ship's ballast water" and "hull fouling organisms", which are derived from ships, is being developed.

[0003] Regarding the management of "ship's ballast water", the "International Convention for the Control and Management of Ships' Ballast Water and Sediments, 2004" came into force on September 8, 2017. Regarding the management of "hull fouling organisms", in 2011, the "Hull Fouling Prevention Guidelines (Resolution MEPC.207(62))" were formulated. Since 2020, a review has been carried out based on the evaluation of the practicality and effectiveness of the guidelines, and in 2023, the IMO / International Maritime Organization adopted a revised version of the guidelines on hull fouling organisms (RESOLUTION MEPC.378(80)).

[0004] The newly revised guidelines in 2023 mention that a five-level fouling assessment is carried out based on the underwater inspection results, and a cleaning method is selected based on the fouling assessment.

[0005] When the fouling assessment is a low fouling assessment, it is stated that deposits are removed with a soft brush or water flow, while in the case of a high fouling assessment, removal and recovery of deposits are required, which will result in a huge increase in the labor involved. Additionally, in New Zealand and Australia, local regulations require proof that the hull has been cleaned within a certain period of time.

[0006] On the other hand, hull fouling caused by biological attachment to the hull can lead to problems such as reduced operational performance, increased hull resistance resulting in reduced fuel efficiency, increased operating costs, and increased greenhouse gas (GHG) emissions. Non-patent document 1 reports on the impact of long-term ship demurrage on ship hull fouling, and the summary reads as follows:

[0007] The authors write, "The effects of long periods of congestion at Australian coal and iron ore export ports over the past three years are now clearly evident in the biological fouling and fuel consumption of ships on their return voyages. Australia exports a large amount of coal to Japan, and many coal carriers bound for Japan are being forced to wait for long periods of time at Australian loading ports. This, along with rising fuel oil prices, is becoming a major problem for ship operators. Biofouling is also thought to be a cause of the transportation of aquatic organisms. The need for measures to combat biofouling is also being discussed at the IMO. The authors therefore investigated the arrival of ships bound for Japan over the past 10 years at the major coal export ports of Newcastle and Gladstone. They also investigated the operating history of coal carriers in service in Australia. They also analyzed the impact of biological fouling on ships, using the fuel consumption coefficient per unit time as an evaluation value." [Prior art documents] [Non-patent literature]

[0008] [Non-Patent Document 1] https: / / www.jstage.jst.go.jp / article / jin / 121 / 0 / 121_KJ00005822061 / _pdf / -char / ja [Patent documents]

[0009] [Patent Document 1] Special Table 2022-526652 (Monitoring Module) [Patent Document 2] Special Table 2022-526655 (Monitoring Module) [Patent Document 3] Special Table 2022-519354 (Method and System for Reducing Ship Fuel Consumption) [Summary of the Invention] [Problems to be Solved by the Invention]

[0010] Conventionally, Patent Documents 1 and 2 disclose technologies for controlling a robot configured to clean while the hull of a ship is moving. However, these technologies do not perform fouling evaluation and only disclose that cleaning can be performed by the robot, and do not present the timing when cleaning is possible during low fouling evaluation.

[0011] Patent Document 3 states that the proportion of navigation time that a ship spends in an optimal draft, trim, and speed state can be increased. However, on the other hand, it states that hull fouling reduces the accuracy of the process and only points out a decrease in fuel efficiency.

[0012] Therefore, an object of the present invention is to provide a method for managing the hull of a ship and a device for managing the hull of a ship that can take appropriate measures by predicting the fouling state of the hull.

[0013] Another object of the present invention will become apparent from the following description. [Means for Solving the Problems]

[0014] The above problems are solved by the following inventions.

[0015] 1. In advance, a fouling growth prediction model is learned and constructed using teacher data in which the hull size, ship speed, surface state of the hull, and increase rate of frictional resistance are associated with each other and which has a correlation between the increase rate of frictional resistance and the surface state of the hull. Based on the output of similar ships that have sailed on the same route as the route of the target ship's sailing plan in the past, the ideal fuel consumption and actual fuel consumption of the output, and the resistance of the strait in the route, the output of the target ship during navigation on the route of the target ship's sailing plan, the trend of the ideal fuel consumption of the output and the trend of the actual fuel consumption, and the resistance of the strait in the planned route are estimated, and the increase rate of the frictional resistance of the target ship is estimated. Input the hull size of the target ship and the estimated increase rate of the frictional resistance rate into the constructed fouling growth prediction model, and generate fouling growth prediction data indicating the relationship between the fouling rate and the number of days, which is in a corresponding relationship with the surface state of the hull. A ship hull management method characterized by this. When the estimated number of days to reach the destination country and the fouling rate that meets the standards of the destination country are input, Based on the fouling growth prediction data, calculate the cleaning timing that requires the minimum number of cleaning times to reach the specified fouling rate, which is the timing when cleaning can be performed by a predetermined cleaning method, so as to reach the fouling rate that meets the standards of the destination country. The ship hull management method according to claim 1, characterized by this. 3. Notify the calculated cleaning timing that requires the minimum number of cleaning times. The ship hull management method according to claim 2, characterized by this. 4. Preset the cleaning cost by a predetermined cleaning method in advance. Calculate the fuel cost when not cleaned by a predetermined cleaning method, calculate the total cost by adding the fuel cost when cleaning and the cleaning cost, and calculate the cost difference by comparing the total cost and the fuel cost when not cleaning. The notification unit notifies the total cost and the fuel cost when not cleaning, and notifies the cost difference. The ship hull management method according to claim 2, characterized by this. 5. The operation profile data that records at least the history of the track, sea area, ship speed, and water temperature during the movement of the ship from port to port, and the image data of the ship's hull are associated and stored. The ship hull management method according to any one of claims 1 to 4, characterized by this. 6. A data generation unit is provided that preliminarily correlates a hull size, a ship speed, a surface condition of the hull, and an increase rate of frictional resistance, and learns and constructs a fouling growth prediction model with teacher data having a correlation between the increase rate of frictional resistance and the surface condition of the hull. Based on the output of a ship similar to the target ship that has sailed on the same route as the route planned for navigation of the target ship in the past, the ideal fuel consumption and the actual fuel consumption of the output, and the resistance of the strait in the route, the output of the target ship during navigation on the route planned for navigation of the target ship, the trend of the ideal fuel consumption and the trend of the actual fuel consumption of the output, and the resistance of the strait in the planned navigation route are estimated, and an estimation unit that estimates the increase rate of the frictional resistance of the target ship is provided. The data generation unit inputs the hull size of the target ship estimated by the estimation unit and the increase rate of the frictional resistance ratio estimated by the estimation unit into the constructed fouling growth prediction model, and generates fouling growth prediction data indicating the relationship between the fouling rate of the hull surface and the number of days, and is characterized by a hull management device for a ship. 7. It further includes an acquisition unit that acquires the estimated number of days to reach the destination country and the fouling rate that meets the standards of the destination country. Based on the fouling growth prediction data, a calculation unit is provided that calculates the cleaning timing at which the minimum number of cleaning times is required to reach a specified fouling rate that can be cleaned by a predetermined cleaning method so as to achieve a fouling rate that meets the standards of the destination country in relation to the number of days to reach the specified fouling rate. The hull management device for a ship according to item 6 above is characterized by this. 8. The hull management device for a ship according to item 7 above includes a notification unit that notifies the predicted cleaning timing that requires the minimum number of cleaning times. 9. The calculation unit preliminarily sets the cleaning cost by a predetermined cleaning method. Calculates the fuel cost when not cleaned by a predetermined cleaning method, calculates the total cost by adding the fuel cost when cleaning and the cleaning cost, and also calculates the cost difference by comparing the total cost with the fuel cost when not cleaning. The notification unit notifies the total cost and the fuel cost when not cleaning, and also notifies the cost difference, and the hull management device for a ship according to item 7 described above is characterized in that. 10. When the acquisition unit acquires imaging data of the hull surface of the target ship, A ship data storage unit in which the operation profile data of the ship that records at least the history of the track, sea area, ship speed, and water temperature while moving from the port of call to the port of call, which is stored in advance in the target ship, is associated with and stored together with the imaging data. The hull management device for a ship according to any one of items 6 to 9 described above is characterized by comprising.

Effect of the Invention

[0016] According to the present invention, it is possible to provide a hull management method for a ship and a hull management device for a ship that can take appropriate measures during navigation of the hull by predicting the fouling state of the hull.

[0017] Further, according to the present invention, it is possible to provide a hull management method for a ship and a hull management device for a ship that can achieve the minimum necessary number of cleanings, and can present the time when cleaning is possible among the low fouling evaluations, and can obtain a fuel cost reduction effect.

Brief Description of the Drawings

[0018]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Mode for Carrying Out the Invention

[0019] Hereinafter, preferred embodiments of the present invention will be described.

[0020] An example of the hull management method of the present invention will be described with reference to FIG. 1. FIG. 1 is a flowchart showing an example of the hull management method of the present invention.

[0021] First, in advance, a fouling growth prediction model is learned and constructed using teacher data in which the hull size, ship speed, hull surface condition, and increase rate of frictional resistance are associated with each other and which has a correlation between the increase rate of frictional resistance and the hull surface condition (S1).

[0022] FIG. 2 is a diagram showing the correspondence relationship among the hull size, ship speed, hull surface condition, and increase rate of frictional resistance, and FIG. 3 is a diagram showing the relationship between the hull surface condition and the fouling rate.

[0023] As shown in FIG. 2, the hull size, ship speed, hull surface condition, and increase rate of frictional resistance are associated with each other. According to the illustrated example, the hull size shows an example of a 230 m container and an example of a 175 m bulk carrier, and their speeds are shown. Further, the relationship with the frictional resistance rate in these hull surface conditions is shown.

[0024] According to this table, it can be seen that the frictional resistance increases according to the adhesion rate of the biofilm. In addition, the frictional resistance rate of a ship with an AF coating (Anti-Fouling Coating) is shown, and the frictional resistance rate in the surface condition attached to the surface of this ship is shown. From these facts, there is a correlation between the hull surface condition and the increase rate of frictional resistance.

[0025] It is constructed by training a fouling growth prediction model for a hull using the data in the table shown in FIG. 2 as training data. In the present embodiment, for example, FIG. 2 shown as training data is an example, and there is data showing the relationship between various hull sizes, speeds, the state of the hull surface, and the rate of increase in frictional resistance that are not shown. By using these as training data, the fouling growth prediction model can generate fouling growth prediction data, which will be described later, corresponding to various ship types.

[0026] Also, FIG. 3 shows the correspondence between the state of the hull surface and the fouling rate. According to FIG. 3, since the surface state and its fouling rate are shown, by training using this as training data, the fouling growth prediction model can grasp the relationship between the surface state shown in FIG. 2 and the surface state shown in FIG. 3. As a result, it becomes possible to output the state of the hull surface as the fouling rate.

[0027] Next, the tendency of the rate of increase in the frictional resistance of the target hull is estimated (S2). The rate of increase in frictional resistance can be estimated, for example, before the ship sails.

[0028] For example, in a ship management system (not shown), the same route as the planned route of the target ship has accumulated the operation history of ships similar to the target ship that have operated on this route in the past. The operation history accumulated at that time includes at least data on the transition of ship speed and output. By grasping the transition of ship speed and the tendency of output at that time accumulated in the ship management system, and grasping the tendency of ideal fuel consumption and the tendency of actual fuel consumption in the tendency of that output, based on these, the tendency of the increase rate of frictional resistance can be estimated. In the present embodiment, similar ships that have operated on the same route may include both the target ship and a ship different from the target ship. Therefore, it is possible to use the operation history of the target ship when it sailed in the past, and it is also possible to use the operation history of a ship different from the target ship when it sailed in the past. Similar ships to the target ship may have the same or different manufacturers as the target ship, and ships with the same or similar loading capacity, hull size, etc. as the target ship are included in the similar ships.

[0029] In the present embodiment, in addition to the above, when estimating the tendency of the increase rate of frictional resistance, if there is necessary data for grasping the increase rate of frictional resistance, these data can also be obtained from the operation history, etc. of the ship management system (not shown). As a result, the tendency of the increase rate of frictional resistance of the target ship on the relevant route can be estimated from the past operation history, etc. of a similar ship different from the target ship. In the present embodiment, based on the operation history of the target ship itself when it operated on a specific route in the past, the tendency of the increase rate of frictional resistance on the relevant route can also be estimated.

[0030] In the present embodiment, the estimated increase rate of frictional resistance can be corrected at the stage when the target ship is actually sailing on the route. For example, when there is a difference between the data such as the output and actual fuel consumption actually obtained by the target ship and the output and actual fuel consumption in the operation history of past ships, the increase rate of frictional resistance may be corrected based on that difference.

[0031] In this way, when the route that is the sailing schedule of the target ship is determined, the tendency of the increase rate of the frictional resistance in that route can be estimated. Further, even during the sailing of the target ship on a specific route, if there are differences in the output tendency and the actual fuel consumption tendency of the ships with past operation histories compared to the actual fuel consumption of the target ship, the tendency of the increase rate of the frictional resistance in the target ship during sailing can also be corrected by taking these into account. As a result, the tendency of the more accurate increase rate of the frictional resistance can be estimated, and the effect of increasing the accuracy of the fouling growth prediction data described later is exerted.

[0032] Next, fouling growth prediction data showing the relationship between the fouling rate and the number of days of the fouling rate is generated (S3). An example of the fouling growth prediction data is shown in FIG. 4. The fouling growth prediction data shown in FIG. 4 shows an example created based on the estimated data before departure. In the present embodiment, as described above, the increase rate of the frictional resistance of the target ship that is the input data can be corrected during sailing. An example when the fouling growth prediction data is corrected is shown in FIG. 5. As shown in FIG. 5, when the increase rate of the fouling resistance changes at a certain point, as a result of the correction, for example, when the increase rate of the frictional resistance increases, since the frictional resistance has increased, the fouling rate will be higher than the estimation before sailing, and it will become a graph like the two-dot chain line shown in FIG. 5. On the other hand, when the increase rate of the frictional resistance decreases, since the frictional resistance has decreased, the fouling rate will be lower than the estimation before sailing, and it will become a graph like the one-dot chain line shown in FIG. 5. As described above, by acquiring operation data during sailing, correcting the input data, and inputting the corrected data into the fouling growth prediction model, fouling growth prediction data based on the operation data during sailing can be generated.

[0033] When the hull size of the target ship and the tendency of the increase rate of the frictional resistance ability are input into the fouling growth prediction model, based on these, the fouling growth prediction data showing the relationship between the number of days and the fouling rate is output. The increase rate of the frictional resistance is based on the past operation history before sailing.

[0034] This fouling growth prediction data indicates, for example, between 0 and 100 of the fouling rate shown in FIG. 3, how many days of navigation are required for this fouling rate to be reached. That is, it indicates the degree of fouling growth on the hull.

[0035] The inventors of the present invention studied the influence of fouling on the hull surface on fuel consumption, and in the output of the hull, in terms of the relationship between the actual fuel consumption and the ideal fuel consumption, the increase rate of the frictional resistance in a state where resistances such as the resistance in power and the resistance in the strait are excluded can be grasped, and it has been found that this increase rate of the frictional resistance is the fuel consumption caused by the resistance of the hull surface in the actual fuel consumption.

[0036] Therefore, by grasping the tendency of the increase rate of the frictional resistance, the tendency of the state of the hull surface can be grasped.

[0037] In the present embodiment, the operation history of the target ship can be added to the teacher data of the fouling growth prediction model. As a result, since the teacher data of the fouling growth prediction model increases, more accurate prediction becomes possible.

[0038] Next, a further embodiment of the present invention will be described with reference to FIG. 6. FIG. 6 is a flowchart showing the cleaning timing calculation process based on the fouling growth prediction data of the present invention.

[0039] When the fouling growth prediction data showing the relationship between the above fouling rate and the number of days of the fouling rate is generated, the scheduled number of days to reach the destination country of the target ship is input (S10). The input means is not particularly limited, and it may be captured by a ship management system (not shown).

[0040] Next, a fouling rate that meets the criteria of the destination country is input (S11). This input means is also not particularly limited, and it is sufficient to be able to obtain a fouling rate that meets the criteria of the destination country.

[0041] Next, based on the fouling growth prediction data, the cleaning timing that requires the minimum number of cleanings with a predetermined cleaning method to reach a specified fouling rate, which is the timing at which cleaning can be performed with the predetermined cleaning method, is calculated (S12) so as to achieve a fouling rate that meets the standards of the destination country.

[0042] Here, as the predetermined cleaning method, proactive cleaning and reactive cleaning can be selected.

[0043] Proactive cleaning is a cleaning method mainly performed for initial fouling (Soft Fouling) of the hull, and is a cleaning method that performs cleaning with a soft brush, water flow, etc. so as not to damage the antifouling paint applied to the hull as much as possible. This proactive cleaning is a recommended underwater hull cleaning method in the revision of the guidelines regarding hull fouling organisms, and has the merit that attachment recovery is not required.

[0044] Reactive cleaning is a cleaning method performed for late-stage fouling (Hard Fouling) of the hull, and is a cleaning method that scrapes off severe fouling such as barnacle attachment using tools such as a hard wire brush and a spatula. This reactive cleaning has the merit that it can be cleaned even for severe fouling, but has the demerit that attachment recovery is required and the antifouling paint of the hull is also scraped off.

[0045] In the present embodiment, considering cost and labor, it is preferable to perform proactive cleaning during the navigation of the ship. Hereinafter, the case where the predetermined cleaning method is proactive cleaning will be described.

[0046] FIG. 7 is a drawing showing an example of calculating the cleaning timing that requires the minimum number of cleanings with proactive cleaning until reaching the destination country A. FIG. 7 shows, for example, the soiling rate serving as a standard in destination country A and an example of the designated cleaning rate of proactive cleaning.

[0047] For the soiling rate serving as a standard in destination country A, when arriving in destination country A, the soiling rate needs to be below the standard.

[0048] In this case, when the designated soiling rate to be cleaned by proactive cleaning is known, in order to reach the soiling rate serving as a standard in destination country A by the scheduled number of days of arrival in destination country A, as shown in the figure, if not cleaned as it is after cleaning at the second cleaning timing, according to the soiling growth prediction data, it will exceed the standard in destination country A. In this case, in order to be able to enter destination country A, it is necessary to perform cleaning immediately before entry. As a result, it can be seen that 3 times of cleaning are required. And the cleaning timing (timing) for performing the 3 times of cleaning can also be calculated based on the soiling growth prediction data. Thereby, while minimizing the cleaning cost, it is possible to prevent the situation of not being able to enter the port of the destination country.

[0049] FIG. 8 is a drawing showing an example of calculating the cleaning timing at which the number of times of proactive cleaning until reaching destination country B is the minimum number of times of cleaning. In the case of destination country B, compared with the case of destination country A shown in FIG. 7, the standard rate is higher than the designated soiling rate in proactive cleaning.

[0050] In this case, as shown in FIG. 8, it is expected that the soiling rate will not exceed the standard on the arrival date in destination country B even if not cleaned after the second cleaning timing. In this case, in order to be able to enter destination country B, it is not necessary to perform cleaning immediately before entry. As a result, the number of times of cleaning is 2 times, and the cleaning timing (timing) for performing the 2 times of cleaning can also be calculated based on the soiling growth prediction data. Thereby, while minimizing the cleaning cost, it is possible to prevent the situation of not being able to enter the port of the destination country.

[0051] In this embodiment, when the first cleaning is performed, the fouling rate of the hull will decrease. It is also possible to newly generate fouling growth prediction data from the decreased fouling rate and the number of days.

[0052] In this case, by acquiring ship data at regular intervals on the trends of the current ideal fuel consumption and actual fuel consumption, calculating the increase rate of frictional resistance, and inputting it into the fouling growth prediction model, it becomes possible to predict again. Also, before the ship sails, it is possible to use the fouling growth prediction data created by the fouling growth prediction model based on the data obtained from the ship management system (not shown) described above.

[0053] Also, the specified fouling rate for cleaning by proactive cleaning may be any rate as long as it is a fouling rate in fouling that can be cleaned by proactive cleaning, that is, within the range where dirt can be removed. Therefore, it can be freely specified within the range where the specified rate can be tolerated.

[0054] Next, notify the cleaning timing that can be achieved with the calculated minimum number of cleaning times (S13).

[0055] Thereby, it is possible to arrange for a reservation with a cleaning contractor in the destination country. In this embodiment, a mechanism may be constructed to arrange a reservation with the cleaning contractor simultaneously with the notification in S13 based on the cleaning timing calculated in S12.

[0056] Next, a further embodiment of the present invention will be described with reference to FIG. 9. FIG. 9 is a flowchart showing still another embodiment of the present invention.

[0057] In advance, acquire a predetermined cleaning method and the corresponding cost (S20).

[0058] Next, calculate the cost when cleaning the minimum number of times calculated in S12 of the cleaning timing calculation process with a predetermined cleaning method, calculate the fuel cost when cleaning, and calculate the total cost (S21).

[0059] When calculating the fuel cost in the case of cleaning, since the increase rate of frictional resistance is reset by cleaning and the actual fuel consumption is also improved, the fuel cost in this case can be calculated by calculating the trend of the actual fuel consumption with reference to the timing until the first cleaning. Thereby, based on the prediction data, the cleaning cost and the fuel cost can be calculated, and the total cost obtained by combining these costs can also be calculated.

[0060] Next, calculate the fuel cost when not cleaning by a predetermined cleaning method (S22). The fuel cost when not cleaning can be calculated based on, for example, the trend of the actual fuel consumption used to calculate the increase rate of frictional resistance estimated before departure.

[0061] In the present embodiment, the case of not cleaning by the predetermined cleaning method in S22 does not mean the case of not cleaning at all, but the case where the cleaning timing is not calculated by adopting the predetermined cleaning method. In order to meet the standards of the destination country, since the ship cannot enter the country without removing the fouling of the hull, in this case, it is necessary to clean reliably. For example, at least reactive cleaning must be performed to meet the entry standards of the destination country. The cleaning cost in this case shall be included in the fuel cost when not cleaning.

[0062] Next, arrange and notify the total cost calculated in S21 and the fuel cost calculated in S22 (S23). For example, the notification can be visually displayed on a display unit (not shown) to facilitate the comparison of costs.

[0063] Next, calculate the differential cost between the total cost calculated in S21 and the fuel cost calculated in S22 (S24), and notify the calculated differential cost (S25).

[0064] The differential cost notified in S25 is displayed together with the total cost calculated in S21 notified in S23 and the fuel cost calculated in S22, making it easier to compare and consider measures for hull management from a cost perspective.

[0065] In the present embodiment, it is preferable to record at least the history of the track, sea area, ship speed, and water temperature while the ship moves from port to port. It is preferable to create operation profile data including these histories. In addition, it is preferable to acquire image data of the ship's hull and associate and store the operation history profile data and the image data. These are preferably stored together with the fouling growth prediction data created for the target ship. Thereby, since the operation management of the target ship is stored together with the state of the hull, the state of the hull can be appropriately managed.

[0066] The ship hull management device according to the present invention will be described with reference to FIG. 10. FIG. 10 is a block diagram showing an example of the ship hull management device according to the present invention.

[0067] As shown in FIG. 10, the ship hull management device includes a data generation unit 100, an estimation unit 101, an acquisition unit 102, a calculation unit 103, a notification unit 104, and a ship data storage unit 105.

[0068] The data generation unit 100 stores a fouling growth prediction model. In advance, the hull size, ship speed, surface state of the hull, and the increase rate of frictional resistance are associated with each other, and the fouling growth prediction model is learned and constructed by teacher data having a correlation between the increase rate of frictional resistance and the surface state of the hull. The data generation unit 100 generates fouling growth prediction data showing the relationship between the fouling rate and the number of days on the hull surface by using the fouling growth prediction model.

[0069] The estimation unit 101 receives, from a ship in navigation, the output during navigation of the ship in navigation, the ideal fuel consumption and the actual fuel consumption at that time, and the resistance of the strait during navigation, and estimates the increase rate of the frictional resistance. Further, the estimation unit 101 previously grasps the transition of the ship speed and the tendency of the output at that time from the operation history of the target ship and past ships of the same type and size that were operating on the same route, and from a hull management system (not shown) in which data regarding the tendency of the ideal fuel consumption and the tendency of the actual fuel consumption in the tendency of the output are accumulated, the acquisition unit acquires those data, and based on these data, can also estimate the tendency of the increase rate of the frictional resistance.

[0070] The acquisition unit 102 acquires the number of days until the scheduled arrival in the destination country and the fouling rate that satisfies the standard of the destination country. Further, the acquisition unit 102 acquires imaging data in which the hull surface of the target ship is imaged. The acquisition unit 102 can also send the data acquired from the outside to the data generation unit 100, the estimation unit 101, and the calculation unit 103.

[0071] Based on the fouling growth prediction data generated by the data generation unit 100, the calculation unit 103 can calculate the cleaning timing at which the number of cleaning times with a predetermined cleaning method is minimized so as to reach the specified fouling rate, which is the timing at which cleaning can be performed with a predetermined cleaning method, so as to reach the fouling rate that satisfies the standard of the destination country.

[0072] Further, the calculation unit 103 is provided with a storage unit (not shown), stores correspondence data between a predetermined cleaning method and its cost, calculates the fuel cost when cleaning is performed with a predetermined cleaning method, calculates the total cost obtained by adding the fuel cost when cleaning is performed and the cleaning cost, and can also calculate the cost difference by comparing the total cost and the fuel cost when not cleaning.

[0073] The notification unit 104 can be exemplified by a display unit having a display function, or may be a transmission unit having a transmission function. It is possible to display the cleaning timing at which the number of cleaning times for cleaning with a predetermined cleaning method calculated by the calculation unit 103 is minimized. As a result, the cleaning arrangements can be carried out smoothly.

[0074] The ship data storage unit 105 stores in association with each other the operation profile data of the ship that records at least the history of the track, sea area, ship speed, and water temperature during the movement of the ship from port of call to port of call, and the imaging data obtained by imaging the hull surface of the ship.

[0075] The operation profile data is preferably stored as data during the movement from port of call to port of call. This is preferable because the data on the movement from port of call to port of call can be used as reference data for another target ship.

[0076] The imaging data obtained by imaging the hull surface of the ship is stored in association with, for example, the mapping data of the entire target ship generated when the target ship is in dry dock, and the imaging data is stored in association with the operation profile data, so that the image data of the state of the hull surface between the docks of the hull is recorded. In addition, it can also be used as reference data when selecting the hull paint of the target ship at the time of dry docking.

[0077] Regarding the method of using the hull management device for ships according to the present invention, the description is omitted with reference to the above-described hull management method for ships.

Explanation of Reference Numerals

[0078] 100 Data generation unit 101 Estimation unit 102 Acquisition unit 103 Calculation unit 104 Notification unit 105 Ship data storage unit

Claims

1. Previously, a fouling growth prediction model is learned and constructed using teacher data in which the hull size, ship speed, hull surface condition, and increase rate of frictional resistance are associated with each other and which has a correlation between the increase rate of frictional resistance and the hull surface condition. Based on the output of a similar ship that has sailed on the same route as the route of the target ship's planned voyage in the past, the ideal fuel consumption and actual fuel consumption of the output, and the resistance of the strait in the route, the output of the target ship during navigation on the route of the target ship's planned voyage, the trend of the ideal fuel consumption and the trend of the actual fuel consumption of the output, and the resistance of the strait in the planned voyage route are estimated, and the increase rate of the frictional resistance of the target ship is estimated. A ship hull management method characterized by inputting the hull size of the target ship and the estimated increase rate of the frictional resistance rate into the constructed fouling growth prediction model to generate fouling growth prediction data indicating the relationship between the fouling rate and the number of days in correspondence with the hull surface condition.

2. When the estimated number of days to reach the destination country and the fouling rate meeting the standards of the destination country are input, Based on the fouling growth prediction data, the cleaning timing at which the number of cleaning times with a predetermined cleaning method to reach a specified fouling rate, which is the timing at which cleaning can be performed, is minimized so as to reach the fouling rate meeting the standards of the destination country is calculated. The ship hull management method according to claim 1, characterized by this.

3. The ship hull management method according to claim 2, characterized by notifying the calculated cleaning timing that requires the minimum number of cleaning times.

4. The cleaning cost by a predetermined cleaning method is set in advance. The fuel cost when not cleaning by a predetermined cleaning method is calculated, and the total cost obtained by adding the fuel cost when cleaning and the cleaning cost is calculated. In addition, the cost difference is calculated by comparing the total cost and the fuel cost when not cleaning. The notification unit notifies both the total cost and the fuel cost when not cleaning, and also notifies the cost difference. The ship hull management method according to claim 2, characterized by this.

5. The ship hull management method according to any one of claims 1 to 4, characterized in that operation profile data recording at least the history of the track, sea area, ship speed, and water temperature during the movement from the port of call to the port of call of the ship, and the image data of the photographed ship hull are stored in association with each other.

6. A data generation unit that is preliminarily associated with the hull size, ship speed, surface state of the hull, and the increase rate of frictional resistance, and learns and constructs a fouling growth prediction model with teacher data having a correlation between the increase rate of frictional resistance and the surface state of the hull. Based on the output of a ship similar to the target ship that has sailed on the same route as the planned route of the target ship in the past, the ideal fuel consumption and actual fuel consumption of the output, and the resistance of the strait in the route, the output of the target ship during navigation on the planned route of the target ship, the trend of the ideal fuel consumption and the trend of the actual fuel consumption of the output, and the resistance of the strait in the planned route of navigation are estimated, and an estimation unit for estimating the increase rate of the frictional resistance of the target ship is provided. The data generation unit generates fouling growth prediction data indicating the relationship between the fouling rate of the hull surface and the number of days by inputting the hull size of the target ship estimated by the estimation unit and the increase rate of the frictional resistance rate estimated by the estimation unit into the constructed fouling growth prediction model. A ship hull management device characterized by the above.

7. It further includes an acquisition unit that acquires the estimated number of days to reach the destination country and the fouling rate that meets the standards of the destination country. Based on the fouling growth prediction data, a calculation unit is provided that calculates the cleaning timing at which the minimum number of cleaning times is required to reach the specified fouling rate, which is the timing at which cleaning can be performed by a predetermined cleaning method, so as to achieve the fouling rate that meets the standards of the destination country. The ship hull management device according to claim 6, characterized in that it is provided.

8. The ship hull management device according to claim 7, further comprising a notification unit that notifies the predicted cleaning timing that requires the minimum number of cleaning times.

9. The calculation unit preliminarily sets the cleaning cost by a predetermined cleaning method. Calculate the fuel cost when not cleaning by a predetermined cleaning method, calculate the total cost by adding the fuel cost when cleaning and the cleaning cost, and calculate the cost difference by comparing the total cost with the fuel cost when not cleaning. The notification unit according to claim 7, wherein the notification unit notifies both the total cost and the fuel cost when not washed, and notifies the cost difference, for the hull management device of a ship.

10. When the acquisition unit acquires imaging data of the hull surface of the target ship, The ship data storage unit that stores the operation profile data of the ship that records at least the track, sea area, ship speed, and water temperature history during the movement from port to port, which is pre-stored in the target ship, and the imaging data are stored in association with each other. The hull management device for a ship according to any one of claims 6 to 9, characterized in that it comprises.

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