Evaluation system, evaluation method, and program

Abstract

This evaluation system is provided with: a removal means for removing contamination from the surface of a propeller of a ship; a determination means (412) for determining the degree of fouling on the surface of the propeller before fouling has been removed and the surface roughness of the propeller after fouling has been removed; and an output means (46) that outputs the degree of fouling and the surface roughness.

Description

Technical Field

[0001] The present invention relates to a technology for evaluating the surface condition of a propeller of a ship. Background Art

[0002] A technique for a diver to measure the surface roughness of a propeller underwater is known (for example, Patent Documents 1 and 2).

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2011-108216

[0006] Patent Document 2: Japanese Patent Application Publication No. 2011-145184 Summary of the invention

[0007] Problems to be solved by the invention

[0008] However, the surface condition of the propeller includes surface roughness and contamination. Surface roughness indicates the degree of concavity and convexity of the surface. Contamination indicates the degree of contamination caused by the attachment of marine organisms. Sometimes the maintenance method of the propeller is different in the case of large surface roughness and in the case of large contamination. In recent years, it has been pointed out that the biofilm, which is a fouling originating from organisms, becomes more solid as it grows and becomes organized. If the biofilm grows firmly, it is difficult to remove the biofilm during maintenance. Therefore, in order to implement appropriate maintenance before the biofilm grows firmly, for example, in the case of large contamination on the surface of the propeller, it is preferable to increase the frequency of maintenance compared to the case of large surface roughness of the propeller. In addition, in the case of large contamination on the surface of the propeller and in the case of large surface roughness of the propeller, the tools used for maintenance, the grinding method, and the time required for maintenance are different. However, in the prior art, it is impossible to distinguish and evaluate surface roughness and contamination, so it is impossible to perform appropriate maintenance corresponding to each state.

[0009] An object of the present invention is to assist in performing appropriate maintenance according to the respective states of the surface roughness and the degree of contamination of a propeller of a ship.

[0010] Means for solving problems

[0011] One embodiment of the present invention provides an evaluation system comprising: a removal unit that removes stains from the surface of a propeller of a ship; a determination unit that determines the degree of stain on the surface of the propeller before the stain is removed and the surface roughness of the propeller after the stain is removed; and an output unit that outputs the degree of stain and the surface roughness.

[0012] The evaluation system may further include a measuring unit that uses an interferometry method to measure index values ​​indicating a thickness and a refractive index of a deposit that has contaminated the surface of the propeller before the contamination is removed, and the degree of contamination may be determined based on the index values.

[0013] Alternatively, the evaluation system further comprises: a storage unit which stores a sample image of a reference surface roughness; and a photographing unit which photographs an image of the surface of the propeller after the stain is removed, wherein the surface roughness is determined based on a similarity between the photographed image and the sample image.

[0014] The evaluation system may further include a measuring unit that irradiates light onto the surface of the propeller after the stain is removed, receives light reflected from the surface, and measures the intensity of the received light, and the surface roughness is determined based on the intensity of the light.

[0015] The determination unit may determine a surface condition of the propeller before the stain is removed, and the degree of stain may be determined based on the surface condition and the surface roughness.

[0016] Alternatively, the evaluation system further comprises: a storage unit which stores a sample image of a reference surface state; and a photographing unit which photographs an image of the surface of the propeller before the stain is removed, wherein the surface state is determined based on a similarity between the photographed image and the sample image.

[0017] The evaluation system may further include a measuring unit that irradiates light onto the surface of the propeller before the stain is removed and receives light reflected from the surface, and measures the intensity of the received light, and the surface state is determined based on the intensity of the light.

[0018] Alternatively, the evaluation system further includes a photographing unit which photographs a first image of the surface of the propeller before the stain is removed and a second image of the surface of the propeller after the stain is removed, and the determination unit determines the degree of stain by comparing the first image and the second image before and after the stain is removed.

[0019] Alternatively, the evaluation system further includes a measuring unit, which irradiates the surface of the propeller with a first light before the stain is removed and receives the first light reflected from the surface, and measures the intensity of the received first light, and irradiates the surface of the propeller with a second light after the stain is removed and receives the second light reflected from the surface, and measures the intensity of the received second light, and the determination unit determines the degree of stain based on the difference in intensity between the reflected first light and the reflected second light before and after the stain is removed.

[0020] The evaluation system may further include an underwater moving body, and the underwater moving body may include the removing unit.

[0021] Alternatively, the evaluation system further comprises: a storage unit which stores a first correlation between a past first navigation condition of at least one ship and the degree of contamination of at least one propeller caused by navigation in accordance with the first navigation condition in the at least one ship, and a second correlation between the first navigation condition and the surface roughness of at least one propeller affected by navigation in accordance with the first navigation condition in the at least one ship; an acquisition unit which acquires a second navigation condition predetermined for the ship; and an estimation unit which estimates the degree of contamination of the surface of the propeller when the ship navigates in accordance with the second navigation condition based on the first correlation, and estimates the surface roughness of the propeller when the ship navigates in accordance with the second navigation condition based on the second correlation, and the output unit further outputs the estimated degree of contamination and the estimated surface roughness.

[0022] Another embodiment of the present invention provides an evaluation method, comprising the following steps: removing stains from the surface of a propeller of a ship; determining the degree of stain on the surface of the propeller before the stain is removed and the surface roughness of the propeller after the stain is removed; and outputting the degree of stain and the surface roughness.

[0023] Another aspect of the present invention provides a program for causing a computer to execute the following steps: determining the degree of contamination of the surface of a propeller of a ship before removing contamination from the surface of the propeller and the surface roughness of the propeller after the contamination is removed; and outputting the degree of contamination and the surface roughness.

[0024] Effects of the Invention

[0025] According to the present invention, it is possible to assist in performing appropriate maintenance according to the respective states of the surface roughness and the degree of contamination of a propeller of a ship. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1This is a diagram showing an example of an evaluation system according to an embodiment.

[0027] Figure 2 This is a cross-sectional view showing an example of the surface state of the propeller according to the embodiment.

[0028] Figure 3 This is a diagram showing an example of the configuration of a server device according to an embodiment.

[0029] Figure 4 This is a diagram showing an example of a sample plate showing the overall surface condition of the propeller according to the embodiment.

[0030] Figure 5 This is a timing chart showing an example of the operation of evaluating the surface condition of the propeller according to the embodiment.

[0031] Figure 6 This is a timing chart showing an example of an operation of analyzing the correlation between the navigation conditions and the surface state of the propeller according to the embodiment.

[0032] Figure 7 This is a flowchart showing an example of an operation of estimating the surface state of the propeller according to the embodiment. DETAILED DESCRIPTION

[0033] structure

[0034] Figure 1 1 is a diagram showing an example of an evaluation system 1 according to an embodiment. The evaluation system 1 uses the inspection results of the propeller 110 of the ship 11 to evaluate the surface condition of the propeller 110. The evaluation system 1 includes a terminal device 10, an underwater drone 20, a control device 30, and a server device 40. The terminal device 10 is mounted on the ship 11. The terminal device 10 is connected to a network 52 via a communication satellite 50. The server device 40 is connected to the control device 30 via the network 52. The network 52 is a communication line that connects a plurality of devices in a manner that enables communication, and includes, for example, the Internet. The underwater drone 20 is connected to the control device 30 via a control line 54. In addition, Figure 1 Only a single vessel 11 is shown, but a plurality of vessels 11 may also be included.

[0035] The ship 11 has a propeller 110, and is propelled by the rotation of the propeller 110. In addition to the terminal device 10 described above, various sensors (not shown) are also provided in the ship 11. The various sensors include a speedometer, a positioning sensor, and a thermometer (all not shown). The speedometer measures the speed of the ship 11. The positioning sensor measures the position of the ship 11 at prescribed time intervals. The positioning sensor is, for example, a GNSS (Global Navigation Satellite System) receiver. By connecting the position of the ship 11 measured by the positioning sensor along a time series, the route of the ship 11 can be obtained. The thermometer measures the seawater temperature. The terminal device 10 obtains the output of various sensors, and sends the actual navigation conditions obtained based on the obtained output to the server device 40 via the communication satellite 50 and the network 52.

[0036] Figure 2 1 is a cross-sectional view showing an example of the surface state of the propeller 110. The surface state of the propeller 110 deteriorates as the ship 11 sails, and becomes a state requiring maintenance. The surface state of the propeller 110 includes surface roughness and contamination. Surface roughness refers to the roughness of the surface of the propeller 110, that is, the degree of concavity. The surface roughness of the propeller 110 increases as the ship 11 sails. The contamination indicates the degree of fouling from organisms attached to the surface of the propeller 110. As the ship 11 sails, attachments 111 from organisms attach to the surface of the propeller 110. The attachments 111 include higher structures of microorganisms also called biofilms or barnacles. When the surface roughness or contamination increases, the frictional resistance increases and the performance of the propeller 110 decreases. Therefore, when the surface roughness or contamination increases, the propeller 110 is maintained. However, the optimal maintenance method is different when the surface roughness increases and when the contamination increases. For example, when the surface roughness increases or the contamination degree increases, different polishing units are used to perform maintenance with different polishing methods. In addition, when the surface roughness increases or the contamination degree increases, the maintenance frequency and the time required for maintenance are different.

[0037] return Figure 1, the underwater drone 20 dives and moves underwater to inspect the propeller 110. The underwater drone 20 has a function of hovering underwater. The underwater drone 20 is an example of the "underwater moving body" of the present invention. The underwater drone 20 has a brush 21, a camera 22, and an interferometer 23. The camera 22 and the interferometer 23 have a waterproof function so that they can be used underwater. The brush 21 removes the dirt on the surface of the propeller 110. For example, the brush 21 rotates and contacts the surface of the propeller 110 to remove the attachment 111 attached to the surface of the propeller 110. The brush 21 is an example of the "removal unit" of the present invention. The camera 22 captures an image of the surface of the propeller 110. The camera 22 is an example of the "photographing unit" of the present invention. The interferometer 23 uses the interference method to measure the index value of the dirt on the surface of the propeller 110. The index value represents the thickness and refractive index of the attachment 111 attached to the surface of the propeller 110. The interferometer 23 is an example of the “measuring unit” of the present invention.

[0038] The interferometer 23 includes, for example, a light emitting unit, a spectrometer, an imaging element, and a processing unit. The light emitting unit irradiates light such as laser light. The spectrometer divides the light irradiated by the light emitting unit into two or more lights. The light divided by the spectrometer is irradiated onto the surface of the propeller 110. Figure 2 As shown, when the attachment 111 is attached to the surface of the propeller 110, the light irradiated from the interferometer 23 becomes the light L1 reflected on the surface of the attachment 111 and the light L2 refracted in the attachment 111 and incident and reflected on the surface of the propeller 110. The optical path length of the light L2 reflected on the surface of the propeller 110 is greater than the optical path length of the light L1 reflected on the surface of the attachment 111, so interference fringes are formed on the surface of the attachment 111 by this optical path difference. The imaging element captures an image of the interference fringes formed on the surface of the attachment 111. The processing unit measures the interval between the interference fringes using the image captured by the imaging element, and calculates the index value (n×d) using the measured interval. Here, n represents the refractive index of the attachment 111, and d represents the thickness of the attachment 111. The larger the index value, the greater the thickness of the attachment 111 or the higher the concentration of the attachment 111. In addition, the structure of the interferometer 23 described here is an example, and other known structures may also be used.

[0039] In one example, the index value (n×d) is obtained based on the following mathematical formula (1) which represents the condition for mutually reinforcing light.

[0040] 2ndcosθ=(m+1 / 2)λ…(1)

[0041] In the mathematical formula (1), n ​​is the refractive index of the attachment 111, d is the thickness of the attachment 111, θ is the refraction angle, m is an integer (m=0, 1, 2, ...), and λ is the wavelength in air.

[0042] In other examples, a database representing the correspondence between the spacing of interference fringes and the index value (n×d) may be prepared based on past performance of at least one ship 11 or a tank test of a model ship, and the index value (n×d) may be calculated based on the database according to the spacing of interference fringes measured by the processing unit.

[0043] The control device 30 controls the underwater drone 20. The control device 30 is used by the operator to operate the underwater drone 20. The control device 30 receives the operation of the operator and sends a control signal corresponding to the operation to the underwater drone 20 via the control line 54. The underwater drone 20 operates according to the control signal received from the control device 30. In addition, the control device 30 obtains information obtained in the inspection of the propeller 110 from the underwater drone 20 via the control line 54, and sends it to the server device 40 via the network 52. In addition, the underwater drone 20 may have a storage medium for storing the information obtained in the inspection of the propeller 110, and the control device 30 obtains the information from the storage medium of the underwater drone 20.

[0044] Figure 3 1 is a diagram showing an example of the structure of the server device 40. The server device 40 is set on land. The server device 40 uses the information obtained in the inspection of the propeller 110 to determine the overall surface state, contamination degree and surface roughness of the propeller 110. The server device 40 has a processor 41, a memory 42, a storage 43, a communication interface (Interface) 44, an input unit 45 and a display unit 46. The various parts of the server device 40 are connected via a bus.

[0045] The processor 41 controls various parts of the server device 40 and performs various operations by executing programs. The processor 41 includes, for example, one or more CPUs (Central Processing Units). The memory 42 is used by the processor 41 to perform various processes. The memory 42 includes, for example, a ROM (Read Only Memory) and a RAM (Random Access Memory). The storage 43 stores various data used by the processor 41. The storage 43 includes, for example, an HHD (Hard Disk Drive) or an SSD (Solid State Drive). Programs for implementing the functions of the server device 40 are stored in the memory 42 or the storage 43. The memory 42 and the storage 43 are examples of the "storage unit" of the present invention. The communication interface 44 performs data communication with other devices according to a prescribed communication standard. The input unit 45 inputs a signal corresponding to the user's operation to the processor 41. The input unit 45 includes, for example, a keyboard and a mouse. The display unit 46 displays various information. The display unit 46 includes, for example, a liquid crystal display. The display unit 46 is an example of the "output unit" of the present invention.

[0046] The memory 43 stores a roughness sample image 431 and a whole sample image 432 in advance. The roughness sample image 431 is an image obtained by photographing a sample plate 61 of the reference surface roughness of the propeller 110. The roughness sample image 431 is an example of the "sample image of the reference surface roughness" of the present invention. The whole sample image 432 is an image obtained by photographing a sample plate 60 of the whole reference surface state combining the degree of contamination of the surface of the propeller 110 and the surface roughness. The whole sample image 432 is an example of the "sample image of the reference surface state" of the present invention.

[0047] The sample plate 61 of the reference surface roughness includes a plurality of samples of reference roughness. For example, the sample plate 61 of the reference surface roughness includes samples of four levels of reference roughness. The sample plate 61 of the reference surface roughness is, for example, a Rubert gauge. Alternatively, the sample plate 61 of the reference surface roughness may be made by molding the cavitation of the propeller 110 actually used.

[0048] Figure 41 is a diagram showing an example of a sample plate 60 for the overall surface condition of the propeller 110. The sample plate 60 has a double-layer structure, and a sample plate 62 for the baseline contamination degree of the propeller 110 is overlapped on a sample plate 61 for the baseline surface roughness of the propeller 110. The sample plate 62 for the baseline contamination degree includes a plurality of samples for the baseline contamination degree. For example, the sample plate 62 for the baseline contamination degree includes samples for three levels of baseline contamination degrees. Each sample for the baseline contamination degree preferably has the same index value (n×d) as the corresponding baseline contamination degree. Here, n represents the refractive index of the attachment, and d represents the thickness of the attachment. The sample plate 62 for the baseline contamination degree is artificially made to simulate the attachment 111. The sample plate 62 for the baseline contamination degree can also be formed of an artificial material. The sample plate 60 for the overall surface condition includes a plurality of samples for the baseline surface condition. For example, when the reference surface roughness sample plate 61 includes four levels of reference roughness samples and the reference contamination degree sample plate 62 includes three levels of reference contamination degree samples, the overall surface condition sample plate 60 includes 4×3=12 types of reference surface condition samples.

[0049] The server device 40 functions as a first acquisition unit 411 , a determination unit 412 , a display control unit 413 , a second acquisition unit 414 , an analysis unit 415 , and an estimation unit 416 . These functions are realized by the processor 41 executing a program stored in the memory 42 or the storage 43 .

[0050] The first acquisition unit 411 acquires information acquired by the underwater drone 20 during the inspection of the propeller 110 via the control device 30. The information includes an image obtained by photographing the surface of the propeller 110 before the stain is removed, an index value of the stain of the propeller 110 before the stain is removed, and an image obtained by photographing the surface of the propeller 110 after the stain is removed.

[0051] The determination unit 412 determines the overall surface state of the propeller 110 before stain removal, the degree of stain of the propeller 110 before stain removal, and the surface roughness of the propeller 110 after stain removal, using the information acquired by the first acquisition unit 411. The determination unit 412 determines the overall surface state of the propeller 110 before stain removal based on the similarity between the image obtained by photographing the surface of the propeller 110 before stain removal and the sample portion of the reference surface state included in the overall sample image 432 stored in the memory 43. In addition, the determination unit 412 determines the degree of stain of the propeller 110 before stain removal based on the index value of stain of the propeller 110 before stain removal. In addition, the determination unit 412 determines the surface roughness of the propeller 110 after stain removal based on the similarity between the image obtained by photographing the surface of the propeller 110 after stain removal and the sample portion of the reference surface roughness included in the roughness sample image 431 stored in the memory 43.

[0052] The display control unit 413 causes the display unit 46 to display the overall surface state, the degree of contamination, and the surface roughness of the propeller 110 determined by the determination unit 412 .

[0053] The second acquisition unit 414 acquires the actual navigation conditions of at least one ship 11 and the scheduled navigation conditions of the ship 11. The actual navigation conditions are navigation conditions when at least one ship 11 sailed in the past. The actual navigation conditions are an example of the "first navigation conditions" of the present invention. The scheduled navigation conditions are navigation conditions predetermined for the ship 11. The scheduled navigation conditions are an example of the "second navigation conditions" of the present invention.

[0054] The analysis unit 415 analyzes the correlation between the actual navigation conditions obtained by the second acquisition unit 414 and the degree of contamination of the propeller 110 determined by the determination unit 412. The correlation between the actual navigation conditions and the degree of contamination is an example of the "first correlation" of the present invention. In addition, the analysis unit 415 analyzes the correlation between the actual navigation conditions obtained by the second acquisition unit 414 and the surface roughness of the propeller 110 determined by the determination unit 412. The correlation between the actual navigation conditions and the surface roughness is an example of the "second correlation" of the present invention. The degree of contamination and the surface roughness of the propeller 110 determined by the determination unit 412 are respectively the actual degree of contamination and the surface roughness of the propeller 110 caused by or affected by past voyages in accordance with the actual navigation conditions in at least one ship 11. Each correlation can also be formulated. In addition, the analysis of the correlation can also be performed using AI (Artificial Intelligence).

[0055] The estimation unit 416 estimates the degree of contamination and the surface roughness of the propeller 110 when the ship 11 is sailing according to the predetermined sailing conditions acquired by the second acquisition unit 414, based on the correlation between the actual sailing conditions and the surface state of the propeller 110 obtained by the analysis of the analysis unit 415. The estimation unit 416 estimates the degree of contamination of the propeller 110 when the ship 11 is sailing according to the predetermined sailing conditions, based on the correlation between the actual sailing conditions and the degree of contamination of the propeller 110. In addition, the estimation unit 416 estimates the surface roughness of the propeller 110 when the ship 11 is sailing according to the predetermined sailing conditions, based on the correlation between the actual sailing conditions and the surface roughness of the propeller 110.

[0056] action

[0057] Figure 5 1 is a timing chart showing an example of the operation of evaluating the surface condition of the propeller 110. This operation starts when the propeller 110 of the ship 11 moored at the pier is inspected.

[0058] In step S101, after the operator drops the underwater drone 20 into the sea, the operator operates the control device 30 to move the underwater drone 20 to the inspection position of the propeller 110. The control device 30 sends a control signal corresponding to the operator's operation to the underwater drone 20. In step S102, the underwater drone 20 moves underwater according to the control signal received from the control device 30 and reaches the inspection position of the propeller 110. When reaching the inspection position, the underwater drone 20 hovers at the inspection position.

[0059] In step S103, the underwater drone 20 uses the camera 22 to take an image of the surface of the propeller 110 before the stain is removed. In step S104, the underwater drone 20 uses the interferometer 23 to measure the stain index value of the propeller 110 before the stain is removed. In step S105, the underwater drone 20 uses the brush 21 to remove the stain on the surface of the propeller 110. In step S106, the underwater drone 20 uses the camera 22 to take an image of the surface of the propeller 110 after the stain is removed. In step S107, the underwater drone 20 sends the information obtained in steps S103, S104, and S106 to the control device 30.

[0060] In step S108, the control device 30 sends the information received from the underwater drone 20 to the server device 40. In this example, the information acquired in steps S103, S104, and S106 is collectively sent, but it can also be sent separately each time the information is acquired. The first acquisition unit 411 of the server device 40 receives information from the control device 30.

[0061] In step S109, the determination unit 412 of the server device 40 determines the overall surface condition of the propeller 110 before the stain is removed, using the image captured in step S103. For example, the determination unit 412 compares the image acquired in step S103 with the sample portions of a plurality of reference surface conditions included in the overall sample image 432 stored in the storage 43, and determines the reference surface condition represented by the sample portion with the highest similarity among the 12 reference surface conditions as the overall surface condition of the propeller 110.

[0062] In step S110, the determination unit 412 of the server device 40 determines the degree of contamination of the propeller 110 based on the index value measured in step S104. For example, among the three levels of reference contamination, the determination unit 412 determines that the degree of contamination is higher as the index value is larger.

[0063] In step S111, the determination unit 412 of the server device 40 determines the surface roughness of the propeller 110 after the stain is removed based on the image captured in step S106. For example, the determination unit 412 compares the image captured in step S106 with the sample portions of a plurality of reference surface roughnesses included in the roughness sample image 431 stored in the storage 43, and determines the reference surface roughness represented by the sample portion with the highest similarity among the four levels of reference surface roughnesses as the surface roughness of the propeller 110.

[0064] In step S112, the determination unit 412 of the server device 40 stores the overall surface state, contamination degree, and surface roughness determined in steps S109 to S111 in the storage 43. In step S113, the display control unit 413 of the server device 40 causes the display unit 46 to display the overall surface state, contamination degree, and surface roughness determined in steps S109 to S111. The user can perform appropriate maintenance of the propeller 110 based on the overall surface state, contamination degree, and surface roughness displayed on the display unit 46.

[0065] Figure 5 The operation shown is repeated, for example, every time the propeller 110 of each ship 11 is inspected for a plurality of ships 11. The inspection of the propeller 110 is preferably performed each time the propeller 110 is moored at a pier, but sometimes it is not possible to inspect the propeller 110 before and after sailing. Therefore, the inspection of the propeller 110 may also be performed at a predetermined time such as when the propeller 110 is moored at a pier after a predetermined period of time, when the propeller 110 is moored at a specific pier where the underwater drone 20 is installed. Thus, a plurality of data sets consisting of the overall surface state, contamination degree, and surface roughness of the propeller 110 are accumulated in the storage 43 for a plurality of ships 11.

[0066] Figure 61 is a timing chart showing an example of an action of analyzing the correlation between the navigation conditions and the surface state of the propeller 110. The surface state of the propeller 110 of the ship 11 is affected by the navigation conditions of the ship 11. Therefore, by analyzing the overall surface state, degree of contamination, and surface roughness of the propeller 110 of at least one ship 11 obtained based on the action of evaluating the surface state of the propeller 110 described above and the actual navigation conditions of the ship 11, their correlation can be known. This action can be started each time the action of evaluating the surface state of the propeller 110 described above for one ship 11 is completed, can be started at a predetermined timing, and can be started when the user uses the input unit 45 to instruct the action of analyzing the correlation.

[0067] In step S201, the second acquisition unit 414 of the server device 40 acquires the actual navigation conditions from the terminal device 10 of the ship 11 that has been inspected in the operation of evaluating the surface condition of the propeller 110. The second acquisition unit 414 of the server device 40 sends a request for acquiring the actual navigation conditions to the terminal device 10. The terminal device 10 sends the actual navigation conditions to the server device 40 in accordance with the acquisition request. The actual navigation conditions include, for example, the ship speed, route, and seawater temperature of the ship 11. In step S202, the second acquisition unit 414 of the server device 40 receives the actual navigation conditions sent from the terminal device 10 and stores them in the storage 43.

[0068] In step S203, the analysis unit 415 of the server device 40 uses the actual navigation conditions and judgment results stored in the storage 43 to analyze the correlation between the actual navigation conditions of the ship 11 and the degree of contamination and surface roughness of the propeller 110 of the ship 11 when the ship 11 is sailing according to the actual navigation conditions.

[0069] In step S204 , the storage 43 of the server device 40 stores the analysis result of step S203 . Thus, the storage 43 stores the correlation between the actual navigation conditions and the degree of contamination of the propeller 110 , and the correlation between the actual navigation conditions and the surface roughness of the propeller 110 .

[0070] Figure 7 1 is a flowchart showing an example of an action of estimating the surface state of the propeller 110. The inspection of the propeller 110 cannot be performed every time the ship 11 is moored at the dock. For example, when the dock is not equipped with an underwater drone 20, the propeller 110 cannot be inspected using the underwater drone 20. Therefore, in such a case, an action of estimating the surface state of the propeller 110 is performed. This action is started, for example, when the user uses the input unit 45 to instruct the action of estimating the surface state of the propeller 110 before the ship 11 sails.

[0071] In step S301, the second acquisition unit 414 of the server device 40 acquires the planned navigation conditions of the ship 11. The planned navigation conditions may be acquired from the terminal device 10 of the ship 11, or may be inputted by a user's operation using the input unit 45.

[0072] In step S302, the estimation unit 416 of the server device 40 estimates the degree of contamination of the propeller 110 when the ship 11 is sailing under the predetermined sailing condition based on the correlation between the actual sailing condition and the degree of contamination stored in the storage 43. For example, in the correlation, the degree of contamination that is correlated with the actual sailing condition that is most similar to the predetermined sailing condition is estimated.

[0073] In step S303, the estimation unit 416 of the server device 40 estimates the surface roughness of the propeller 110 when the ship 11 is sailing under the predetermined navigation condition based on the correlation between the actual navigation condition and the surface roughness stored in the memory 43. For example, in the correlation, the surface roughness having a correlation with the actual navigation condition most similar to the predetermined navigation condition is estimated.

[0074] In step S304, the display control unit 413 of the server device 40 causes the display unit 46 to display the contamination degree and surface roughness estimated in steps S302 to S303. Thus, the user can recognize the estimated results of the contamination degree and surface roughness of the propeller 110 when the ship 11 sails according to the predetermined navigation conditions. Therefore, after the ship 11 sails according to the predetermined navigation conditions, the user can perform appropriate maintenance on the propeller 110 based on the estimated contamination degree and surface roughness.

[0075] According to the above-described embodiment, the degree of contamination and the surface roughness of the propeller 110 of the ship 11 are determined separately, so that they can be evaluated separately. Thus, it is possible to assist in the implementation of appropriate maintenance corresponding to the respective states of the degree of contamination and the surface roughness of the propeller 110. In addition, by determining the degree of contamination and the surface roughness of the propeller 110 of the ship 11 separately, the cause of the performance reduction of the ship 11 can be distinguished into the cause caused by the surface roughness and the cause caused by contamination for analysis. In addition, the underwater drone 20 performs the inspection of the propeller 110, so compared with the case where the inspection of the propeller 110 is performed by a person, time and cost can be reduced. In addition, in the case where the inspection of the propeller 110 cannot be performed, the degree of contamination and the surface roughness of the propeller 110 when the ship 11 is sailing according to the predetermined navigation conditions can be estimated separately, so that they can be evaluated separately. Thus, even in the case where the inspection of the propeller 110 cannot be performed, it is possible to perform appropriate maintenance corresponding to the degree of contamination and the surface roughness of the propeller 110. Furthermore, in the above-mentioned embodiment, the overall surface state of the propeller 110 of the ship 11 is determined and displayed, so that the user can recognize the overall surface state of the propeller 110. On the surface of the propeller 110, the surface roughness of the metal forming the propeller 110 serves as a base, on which the biological attachments 111 are superimposed. The overall surface state reflects the state of both the surface roughness and the contamination caused by the biological attachments 111. Since the overall surface state affects the propeller efficiency in fluid mechanics, it is important for the user to recognize the overall surface state. Furthermore, if the relationship between the change in the overall surface state of the propeller 110 before and after maintenance and the change in propeller efficiency can be identified, the user can determine the implementation of more appropriate maintenance.

[0076] Modifications

[0077] The above-mentioned embodiment is an example of the present invention, and the present invention is not limited to the embodiment. The above-mentioned embodiment can also be modified as in the following modified examples. In addition, two or more of the following modified examples can also be combined for implementation.

[0078] Modification 1

[0079] In the above-mentioned embodiment, the overall surface state of the propeller 110 may be determined based on the intensity of light reflected on the surface of the propeller 110 before the stain is removed, instead of or on the basis of the image of the surface of the propeller 110 taken before the stain is removed. In this modified example, the intensity of reflected light reflected by the sample when light is irradiated to each reference surface state sample of the sample plate 60 of the overall surface state is stored in the storage 43. The underwater drone 20 has a light sensor. The light sensor is an example of a "measuring unit" of the present invention. The light sensor has, for example, a light emitting unit, a light receiving unit, and a processing unit. The light emitting unit irradiates light to the surface of the propeller 110 before the stain is removed. The light receiving unit receives light reflected from the surface of the propeller 110. The processing unit measures the intensity of light received by the light receiving unit. In addition, the structure of the light sensor described here is an example, and other known structures may also be used. The determination unit 412 compares the intensity of light measured by the optical sensor with the intensity of reflected light of each sample of the reference surface state stored in the memory 43, and determines the reference surface state represented by the sample with the smallest intensity difference as the overall surface state of the propeller 110. Alternatively, the determination unit 412 may determine that the smaller the intensity of light measured by the optical sensor, the more deteriorated the overall surface state of the propeller 110. Even with the structure of this modified example, the overall surface state of the propeller 110 of the ship 11 can be determined.

[0080] In addition, the overall surface state of the propeller 110 is affected by both the influence of the stain caused by the biological attachments 111 of the upper layer and the influence of the surface roughness of the metal of the lower layer. However, for the overall surface state determined by the method using the image of the surface of the propeller 110 taken before the stain is removed, the influence of the stain caused by the biological attachments 111 is greater. On the other hand, for the overall surface state determined by the method using the reflection intensity of light on the surface of the propeller 110 before the stain is removed, it is estimated that not only the stain caused by the biological attachments 111 but also the surface roughness of the metal is greater. Therefore, by implementing these two methods while comparing with the sample and performing factor decomposition based on the removal of the biological attachments 111, the surface state of the propeller 110 determined by the complex factors can be determined with a certain degree of accuracy.

[0081] Modification 2

[0082] In the above-mentioned embodiment, the degree of contamination of the propeller 110 may be determined based on an image of the surface of the propeller 110 captured before the contamination is removed, instead of the index value of contamination of the propeller 110 before the contamination is removed or based on the index value. In this modified example, a contamination sample image obtained by capturing the sample plate 62 of the reference contamination degree as a single body is pre-stored in the storage 43. The contamination sample image is an example of the "reference contamination degree sample image" of the present invention. The determination unit 412 compares the image of the surface of the propeller 110 captured before the contamination is removed with a plurality of reference contamination degree sample portions included in the contamination sample image stored in the storage 43, and determines the reference contamination degree represented by the sample portion with the highest similarity as the contamination degree of the propeller 110. Even with the structure of this modified example, the degree of contamination of the propeller 110 of the ship 11 can be determined.

[0083] Modification 3

[0084] In the above-mentioned embodiment, the degree of contamination of the propeller 110 may be determined based on the intensity of light reflected on the surface of the propeller 110 before the contamination is removed, instead of or in addition to the index value of contamination of the propeller 110 measured before the contamination is removed. In this modification, the intensity of reflected light reflected by each sample of the reference contamination degree of the sample plate 62 of the reference contamination degree is stored in the storage 43. The underwater drone 20 has the optical sensor described in the above-mentioned modification. The optical sensor irradiates light to the surface of the propeller 110 before the contamination is removed, receives light reflected by the surface of the propeller 110, and measures the intensity of the received light. The determination unit 412 determines the degree of contamination of the propeller 110 based on the intensity of light measured by the optical sensor. For example, the determination unit 412 compares the intensity of light measured by the optical sensor with the intensity of reflected light of each sample of the reference contamination degree stored in the storage 43, and determines the reference contamination degree represented by the sample with the smallest intensity difference as the degree of contamination on the surface of the propeller 110. Alternatively, the determination unit 412 may also determine that the smaller the intensity of light measured by the optical sensor, the higher the degree of contamination of the propeller 110. In addition, the determination unit 412 may also determine the degree of contamination of the propeller 110 based on both the index value of contamination of the propeller 110 and the intensity of light measured by the optical sensor. Even with the structure of this modified example, the degree of contamination of the propeller 110 of the ship 11 can be determined. In addition, as described above, the index value of contamination is composed of the refractive index n of the attachment 111 and the thickness d of the attachment 111. Among them, the thickness d of the attachment 111 also affects the intensity of the reflected light. Therefore, the index value (n×d) can also be decomposed into elements according to the intensity of the reflected light.

[0085] Modification 4

[0086] In the above-mentioned embodiment, the surface roughness of the propeller 110 may be determined based on the intensity of light reflected on the surface of the propeller 110 after the stain is removed, instead of or based on the image of the surface of the propeller 110 photographed after the stain is removed. In this modification, the intensity of the reflected light reflected by the sample of each reference stain degree of the sample plate 61 of the reference surface roughness is stored in the storage 43. The underwater drone 20 has the optical sensor described in the above-mentioned modification. The optical sensor irradiates light to the surface of the propeller 110 after the stain is removed and receives the light reflected by the surface of the propeller 110, and measures the intensity of the received light. For example, the determination unit 412 compares the intensity of light measured by the optical sensor with the intensity of reflected light of each reference surface roughness sample stored in the storage 43, and determines the reference surface roughness represented by the sample with the smallest intensity difference as the surface roughness of the propeller 110. Alternatively, the determination unit 412 may determine that the smaller the intensity of light measured by the optical sensor, the lower the surface roughness of the propeller 110. Even with the configuration of this modified example, the surface roughness of the propeller 110 of the ship 11 can be determined.

[0087] Modification 5

[0088] In the above-mentioned embodiment, it is not necessary to determine all of the surface state, contamination degree, and surface roughness of the propeller 110 based on the information obtained through the inspection of the propeller 110. For example, it is also possible to determine only the overall surface state and surface roughness of the propeller 110 based on the information obtained through the inspection of the propeller 110, and determine the contamination degree based on the overall surface state and surface roughness of the propeller 110. For example, in a case where the overall surface state of the propeller 110 is a combination of the determined surface roughness and a certain contamination degree, the contamination degree is determined. As another method, it is also possible to determine that the contamination degree of the propeller 110 is high when the overall surface state of the propeller 110 is deteriorated and the surface roughness is small. It is also possible to determine that the contamination degree of the propeller 110 is low when the overall surface state of the propeller 110 is deteriorated and the surface roughness is large. In addition, it is also possible to determine only the contamination degree and surface roughness of the propeller 110 without determining the overall surface state of the propeller 110. Even with the configuration of this modified example, the degree of contamination and the surface roughness of the propeller 110 of the ship 11 can be evaluated separately.

[0089] Modification 6

[0090] In the above-mentioned embodiment, the display of the determination result of the determination unit 412 and the inference result of the inference unit 416 is an example of the output of the determination result and the inference result, and is not limited to this. For example, the server device 40 may have a speaker, and the sound representing the determination result and the inference result may be output from the speaker. In addition, the determination result and the inference result may also be sent to an external device from the communication interface 44. The speaker or the communication interface 44 is an example of the "output unit" of the present invention. Even with the structure of this modified example, the degree of contamination and the surface roughness of the propeller 110 of the ship 11 can be evaluated separately.

[0091] Modification 7

[0092] In the above-mentioned embodiment, the underwater drone 20 is an example of an underwater moving body, but the invention is not limited thereto. For example, the underwater moving body may be any device as long as it is a manned submarine, an underwater robot, or the like that moves underwater.

[0093] Modification 8

[0094] In the above-mentioned embodiment, the propeller 110 may be inspected by a person, i.e., a diver, instead of the underwater drone 20. In this modified example, for example, the diver carries a sample plate 60 for the overall surface condition, a sample plate 61 for the reference surface roughness, a sample plate 62 for the reference contamination degree, and a brush 21 to dive and move to the inspection position of the propeller 110. When arriving at the inspection position, the diver uses the sample plate 60 for the overall surface condition to determine the overall surface condition of the propeller 110 before removing the contamination. Then, the diver uses the sample plate 62 for the reference contamination degree to determine the contamination degree of the propeller 110 before removing the contamination. Then, the diver removes the contamination of the propeller 110 using the brush 21. Then, the diver uses the sample plate 61 for the reference surface roughness to determine the surface roughness of the propeller 110 after removing the contamination. When the inspection is completed, the diver surfaces and goes on land. Then, the diver records the determined overall surface condition, contamination degree, and surface roughness of the propeller 110 in an inspection report and hands it over to the person in charge. This record is an example of output of the overall surface condition, contamination degree, and surface roughness of the propeller 110. Even with the configuration of this modified example, the contamination degree and surface roughness of the propeller 110 of the ship 11 can be evaluated separately.

[0095] Modification 9

[0096] In the above-mentioned embodiment, the configurations of the evaluation system 1, the terminal device 10, the underwater drone 20, the control device 30, and the server device 40 are examples and are not limited thereto. A plurality of devices may have the functions of one device in a distributed manner, or a single device may have the functions of a plurality of devices in a centralized manner.

[0097] Modification 10

[0098] In the above-mentioned embodiment, the operations of the evaluation system 1, the terminal device 10, the underwater drone 20, the control device 30, and the server device 40 are examples and are not limited thereto. The processing procedures of the evaluation system 1, the terminal device 10, the underwater drone 20, the control device 30, and the server device 40 may be reversed in order or a part of the processing procedures may be omitted as long as there is no contradiction.

[0099] Modification 11

[0100] Another aspect of the present invention may provide a method having steps of processing performed in the evaluation system 1, the terminal device 10, the underwater drone 20, the control device 30, and the server device 40. In addition, another aspect of the present invention may provide a program executed in the terminal device 10, the underwater drone 20, the control device 30, or the server device 40. The program may be provided by being stored in a computer-readable recording medium or by downloading via the Internet or the like.

[0101] Modification 12

[0102] In the above-mentioned embodiment, the degree of contamination may be determined by comparing the image of the propeller 110 taken before the contamination is removed with the image of the propeller 110 taken after the contamination is removed. The greater the difference between the images before and after the contamination is removed, the greater the degree of contamination. Therefore, when the difference between these images is large, the determination unit 412 may determine that the degree of contamination is higher than when the difference between these images is small.

[0103] In one example, the determination unit 412 compares the image of the surface of the propeller 110 before the stain is removed, which is captured by the camera 22 of the underwater drone 20, with the sample portions of the plurality of reference surface conditions included in the overall sample image 432 stored in the storage 43, and determines the reference surface condition represented by the sample portion with the highest similarity as the overall surface condition of the propeller 110. In addition, the determination unit 412 compares the image of the surface roughness of the propeller 110 after the stain is removed, which is captured by the camera 22 of the underwater drone 20, with the sample portions of the plurality of reference surface roughnesses included in the roughness sample image 431 stored in the storage 43, and determines the reference surface roughness represented by the sample portion with the highest similarity as the surface roughness of the propeller 110.

[0104] Here, as described above, the plurality of reference surface states included in the sample plate 60 of the overall surface state are composed of a combination of a plurality of reference roughnesses and a plurality of reference contamination degrees. In this modified example, the sample plate 60 of the overall surface state includes a plurality of samples having the same reference surface state but different contamination degrees and surface roughness. Therefore, the determination unit 412 determines a combination including the determined surface roughness from among the plurality of combinations constituting the determined overall surface state, and determines the contamination degree constituting the determined combination as the contamination degree of the surface of the propeller 110. For example, assuming that the overall surface state of the propeller 110 is T1, and the plurality of samples of the reference surface state T1 include a combination of reference roughness R1 and reference contamination degree P1, a combination of reference roughness R2 and reference contamination degree P2, and a combination of reference roughness R3 and reference roughness P3. In this case, when the surface roughness of the propeller 110 is R2, a combination of reference roughness R2 and reference contamination degree P2 is determined, and P2 is determined as the contamination degree of the surface of the propeller 110. Even with the configuration of this modified example, the degree of contamination of the propeller 110 of the ship 11 can be determined.

[0105] Modification 13

[0106] In the above-mentioned embodiment, the degree of contamination may be determined by comparing the reflection intensity of light on the surface of the propeller 110 before the contamination is removed with the reflection intensity of light on the surface of the propeller 110 after the contamination is removed. The greater the difference in the reflection intensity of light before and after the contamination is removed, the greater the degree of contamination. Therefore, when the difference in the reflection intensity of light is large, the determination unit 412 may determine that the degree of contamination is higher than when the difference in the reflection intensity of light is small.

[0107] In one example, similar to the above-mentioned modification 1, the intensity of reflected light reflected by the sample of each reference surface state of the sample plate 60 of the overall surface state is stored in the storage 43. The determination unit 412 compares the intensity of reflected light reflected by the surface of the propeller 110 before decontamination is removed and measured by the optical sensor of the underwater drone 20 with the intensity of reflected light of the samples of each reference surface state stored in the storage 43, and determines that the reference surface state represented by the sample with the smallest intensity difference is the surface state of the propeller 110. In addition, the determination unit 412 compares the intensity of reflected light reflected by the surface of the propeller 110 after decontamination is removed and measured by the optical sensor of the underwater drone 20 with the intensity of reflected light of the samples of each reference surface state stored in the storage 43, and determines that the reference surface roughness represented by the sample portion with the smallest intensity difference is the surface roughness of the propeller 110.

[0108] Here, as described above, the plurality of reference surface conditions included in the sample plate 60 of the overall surface condition are composed of a combination of a plurality of reference roughnesses and a plurality of reference contamination degrees. Therefore, similarly to the above-mentioned modification 12, the determination unit 412 determines a combination including the determined surface roughness from a plurality of samples of the reference surface condition corresponding to the determined overall surface condition, and determines the contamination degree constituting the determined combination as the contamination degree of the surface of the propeller 110. Even with the structure of this modification, the contamination degree of the propeller 110 of the ship 11 can be determined.

[0109] Modification 14

[0110] Alternatively, the overall surface state, degree of contamination, and surface roughness of the propeller 110 determined in the above-mentioned embodiment may be stored in the storage 43, and these data may be analyzed as teaching data by AI, thereby using the analysis result to determine the degree of contamination and surface roughness based only on the overall surface state. As a method for determining the overall surface state, the method using an image of the propeller 110 taken before the contamination is removed as described in the above-mentioned embodiment may be used, or the method using the reflection intensity of light on the surface of the propeller 110 before the contamination is removed as described in the above-mentioned modification 1 may be used.

[0111] Modification 15

[0112] In the above-mentioned embodiment, the method for determining the degree of contamination on the surface of the propeller 110 is not limited to the method using interference fringes. For example, the degree of contamination on the surface of the propeller 110 may be determined by irradiating a plurality of lights of different wavelengths onto the surface of the propeller 110 and determining the degree of contamination on the surface of the propeller 110 based on the difference in the refractive index of these lights or the absorptivity of light of a specific wavelength.

[0113] Description of symbols

[0114] 1: evaluation system; 10: terminal device; 11: ship; 20: underwater drone; 21: brush; 22: camera; 23: interferometer; 30: control device; 40: server device; 41: processor; 42: memory; 43: storage; 44: communication interface; 45: input unit; 46: display unit; 110: propeller; 411: first acquisition unit; 412: determination unit; 413: display control unit; 414: second acquisition unit; 415: analysis unit; 416: inference unit.

Claims

1. An evaluation system comprising: a removal unit that removes fouling from the surface of a propeller of a vessel; a determination unit configured to determine a degree of contamination of the surface of the propeller before the contamination is removed and a surface roughness of the propeller after the contamination is removed; as well as An output unit outputs the contamination degree and the surface roughness.

2. The evaluation system according to claim 1, wherein: The evaluation system further includes a measuring unit for measuring, by using an interferometry method, an index value indicating a thickness and a refractive index of an attached substance that has contaminated the surface of the propeller before the contamination is removed. The degree of contamination is determined based on the index value.

3. The evaluation system according to claim 1, wherein: The evaluation system also has: a storage unit storing a sample image of a reference surface roughness; and a photographing unit that photographs an image of the surface of the propeller after the stain is removed, The surface roughness is determined based on the similarity between the captured image and the sample image.

4. The evaluation system according to claim 1, wherein: The evaluation system further includes a measuring unit that irradiates light onto the surface of the propeller after the stain is removed, receives light reflected from the surface, and measures the intensity of the received light. The surface roughness is determined based on the intensity of the light.

5. The evaluation system according to claim 1, wherein: The determination unit determines the surface condition of the propeller before the stain is removed. The contamination degree is determined based on the surface state and the surface roughness.

6. The evaluation system according to claim 5, wherein: The evaluation system also has: a storage unit that stores a sample image of a reference surface state; and a photographing unit that photographs an image of the surface of the propeller before the stain is removed, The surface state is determined based on the similarity between the captured image and the sample image.

7. The evaluation system according to claim 5, wherein: The evaluation system further includes a measuring unit that irradiates light onto the surface of the propeller before the stain is removed, receives light reflected from the surface, and measures the intensity of the received light. The surface state is determined based on the intensity of the light.

8. The evaluation system according to claim 1, wherein: The evaluation system further includes an imaging unit that captures a first image of the surface of the propeller before the stain is removed and a second image of the surface of the propeller after the stain is removed. The determination unit determines the degree of defacement by comparing the first image and the second image before and after removal of the defacement.

9. The evaluation system according to claim 1, wherein: The evaluation system further includes a measuring unit that irradiates the surface of the propeller before the stain is removed with a first light and receives the first light reflected from the surface, and measures the intensity of the received first light, and irradiates the surface of the propeller after the stain is removed with a second light and receives the second light reflected from the surface, and measures the intensity of the received second light. The determination unit determines the degree of stain based on a difference in intensity between the reflected first light and the reflected second light before and after removal of the stain.

10. The evaluation system according to claim 1, wherein: The evaluation system further includes an underwater moving body having the removal unit.

11. The evaluation system according to claim 1, wherein: The evaluation system also has: a storage unit storing a first correlation between a past first navigation condition of at least one ship and the degree of contamination of at least one propeller caused by navigation in the at least one ship according to the first navigation condition, and a second correlation between the first navigation condition and the surface roughness of at least one propeller affected by navigation in the at least one ship according to the first navigation condition; an acquisition unit configured to acquire a second navigation condition predetermined for the ship; as well as an estimating unit that estimates the degree of contamination of the surface of the propeller when the ship is sailing according to the second navigation condition based on the first correlation, and estimates the surface roughness of the propeller when the ship is sailing according to the second navigation condition based on the second correlation, The output unit further outputs the estimated contamination degree and the estimated surface roughness.

12. An evaluation method comprising the following steps: Removing fouling from the surface of a ship's propeller; determining a degree of contamination of the surface of the propeller before the contamination is removed and a surface roughness of the propeller after the contamination is removed; as well as The contamination degree and the surface roughness are output.

13. A program for causing a computer to execute the following steps: determining a degree of contamination of the surface of a propeller of a ship before removing contamination from the surface of the propeller and a surface roughness of the propeller after the contamination is removed; and The contamination degree and the surface roughness are output.

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