KR20220168910A - Method and system for ship engine management using 3d modeling image - Google Patents

Abstract

A ship engine management method and a system using a 3D modeling image are disclosed. The present invention may include steps of: preparing a 3D modeling image of a ship; receiving engine noise of the ship; performing a K-center clustering process based on the engine noise; generating two final clusters based on the K-center clustering process; extracting an average value of each of the two clusters; extracting a final distance value between each average value; obtaining engine state information based on the final distance value; and displaying the engine state information on the 3D modeling image. An objective of the present invention is to provide the ship engine management method and system capable of detecting an abnormal state of an engine based on engine noise through a clustering algorithm.

Description

Ship engine management method and system using 3D modeling image {METHOD AND SYSTEM FOR SHIP ENGINE MANAGEMENT USING 3D MODELING IMAGE}

The present invention relates to a method and system for managing a ship engine using a 3D modeling image. More specifically, it relates to a method for managing a ship engine by automatically detecting the engine state of a ship through artificial intelligence and displaying the engine state in a 3D modeling image, and a system using the same.

An artificial intelligence (AI) system is a computer system that implements human-level intelligence, and unlike existing rule-based smart systems, machines learn, judge, and become smarter on their own. The more AI systems are used, the higher the recognition rate and the more accurate understanding of user preferences, so existing rule-based smart systems are gradually being replaced by deep learning-based AI systems.

Artificial intelligence technology consists of machine learning (deep learning) and element technologies using machine learning. Machine learning is an algorithm technology that classifies/learns the characteristics of input data by itself, and element technology is a technology that utilizes machine learning algorithms such as deep learning, such as linguistic understanding, visual understanding, inference/prediction, knowledge expression, motion control, etc. consists of the technical fields of

A vessel is a structure that floats on water and can carry people, livestock, and goods and move on water. Broadly, it is a general term for transportation on water, and it is a means of transportation that moves on water by means of an engine. In the case of ships, there are many cases in which they operate for a long time, so the condition of the engine is periodically checked at sea.

In general, a ship's engine management system is configured to detect an immediate state through a sensor directly installed on an engine, such as checking an engine's output in real time. As a result, an engineer is dispatched to the site and repairs the engine only after an abnormality such as a significant reduction in engine output or excessive output occurs.

As such, in the prior art, it was confirmed that the engine was in a faulty state only after an abnormality occurred, which had a problem that greatly hindered the operation of the ship. Therefore, there is an increasing need for a technology capable of analyzing the state of the engine in real time by checking artificial intelligence algorithms, etc., and predicting the abnormal state of the engine through this.

Republic of Korea Patent Publication No. 10-2016-0134095 (Title of Invention: Automatic Detection System for Abnormal Situation of Ship, Automatic Notification System for Emergency State of Ship Engine and Their Transmission Method)

An object of the present invention is to provide a method and system for managing a ship engine using a 3D modeling image.

In addition, an object of the present invention is to provide a ship engine management method and system capable of detecting an abnormal state of an engine based on engine noise through a clustering algorithm.

Another object of the present invention is to provide a ship engine management method and system in which a manager can intuitively recognize the abnormal state of an engine by displaying the abnormal state of the engine in a 3D modeling image.

In addition, an object of the present invention is to provide a method and system capable of generating a more accurate predictive model by reflecting the power, speed, displacement, and the like of a marine engine in weights.

In order to solve the above problems, the present invention provides the steps of preparing a 3D modeling image of a ship, receiving engine noise of the ship, performing a K-center clustering process based on the engine noise, and the K -generating the final two clusters based on the centroid clustering process, extracting the average value of each of the two clusters, extracting the final distance value between the average values, and engine based on the final distance value The method may include acquiring state information and displaying the engine state information on the 3D modeling image.

In addition, the performing of the K-center clustering process may include extracting random K pieces of data for the engine noise, generating a plurality of clusters centered on the K pieces of data, and performing the center of gravity of each of the plurality of clusters. extracting a value, extracting a median distance value between the center values, allocating data to a cluster having the shortest distance based on the median distance value, and updating the center of the cluster including the allocated data steps may be included.

In addition, the vessel may include a plurality of engines, and the engine noise may be individually received from a plurality of sensors corresponding to each of the plurality of engines.

Also, the 3D modeling image may include a plurality of engine images corresponding to the plurality of engines, and the plurality of engine images may include engine state information on the plurality of engines.

In addition, in order to solve the above problems, the present invention is a non-transitory computer readable medium storing instructions, and when the instructions are executed by a processor, the processor can perform the above-described method.

In addition, in order to solve the above problems, the present invention generates a sensing unit for detecting engine noise from an engine included in a ship, generates engine state information for the engine based on the engine noise, and performs 3D modeling of the ship. A computing device for storing an image and a display device for displaying the engine state information together with the 3D modeling image, wherein the computing device performs a K-center clustering process for generating the engine state information based on the engine noise , and finally generate two clusters through the K-center clustering process, and generate the engine state information based on the two clusters.

The present invention has an effect of providing a method and system for managing a ship engine using a 3D modeling image.

In addition, the present invention can protect the sensing unit from corrosion through the coating composition, and at the same time has an effect of accurately detecting engine noise even after a long time.

In addition, the present invention has an effect that a manager can intuitively recognize the abnormal state of the engine by displaying the abnormal state of the engine on a 3D modeling image.

In addition, the present invention has an effect of generating a more accurate predictive model by reflecting the output, speed, displacement, and the like of the marine engine to weights.

Effects obtainable according to the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. will be.

1 illustrates a ship engine management method using a 3D modeling image according to the present invention.
2 shows steps of performing a K-center clustering process based on engine noise according to the present invention.
3 is a graph showing the final two clusters according to the present invention.
4 and 5 show a ship engine management system using a 3D modeling image according to the present invention.
6 is a simplified representation of a computing device in accordance with the present invention.
7 shows an example of a 3D modeling image according to the present invention.
The accompanying drawings, which are included as part of the detailed description to aid understanding of the present specification, provide examples of the present specification and describe technical features of the present specification together with the detailed description.

Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar elements are given the same reference numerals regardless of reference numerals, and redundant description thereof will be omitted.

In addition, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of a related known technology may obscure the gist of the embodiment disclosed in this specification, the detailed description thereof will be omitted.

In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, the technical idea disclosed in this specification is not limited by the accompanying drawings, and all changes included in the spirit and technical scope of the present invention , it should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

Hereinafter, a ship engine management method and system using a 3D modeling image according to a preferred embodiment of the present specification based on the above description will be described in detail as follows.

In addition, a subject of the method for managing a ship engine using a 3D modeling image according to the present invention may be a system for managing a ship engine, a computing device included in the system, or a processor included in the computing device.

1 illustrates a ship engine management method using a 3D modeling image according to the present invention.

According to FIG. 1, the ship engine management method according to the present invention includes preparing a 3D modeling image of the ship (S1100), receiving engine noise of the ship (S1200), and performing K-center clustering based on the engine noise. The step of performing the process (S1300), the step of generating the final two clusters based on the K-center clustering process (S1400), the step of extracting the average value of each of the two clusters (S1500), the final distance between each average value It may include extracting a value (S1600), obtaining engine state information based on the final distance value (S1700), and displaying the engine state information on a 3D modeling image (S1800).

Preparing a 3D modeling image of a ship (S1100) may be a step of loading a 3D modeling image stored in a memory. The 3D modeling image is a 3D modeling image of a corresponding ship, and may be, for example, a CAD image.

Receiving engine noise of the ship (S1200) may be a step of receiving engine noise from a sensor installed around the engine. When a plurality of engines are provided, sensors may be installed around each engine to separately receive engine noise.

The step of performing the K-center clustering process based on the engine noise (S1300) may be a step for classifying the engine noise through the K-center clustering algorithm, which is one of the algorithms for clustering.

2 shows steps of performing a K-center clustering process based on engine noise according to the present invention.

According to FIG. 2, the step of performing the K-center clustering process according to the present invention (S1300) includes the step of extracting random K pieces of data with respect to the engine noise (S1310), and a plurality of data centered on the K pieces of data. Generating a cluster (S1320), extracting the central value of each of the plurality of clusters (S1330), extracting an intermediate distance value between the central values (S1340), based on the intermediate distance value, It may include allocating data to the short cluster (S1350) and updating the center of the cluster including the allocated data (S1360).

In the present invention, the median distance value may mean a distance value between clusters in a clustering process for generating two final clusters.

In this case, since the engine noise is measured as a wavelength, information on the frequency (Hz) and the amplitude (dB) may be included. Information on the frequency (Hz) and amplitude (dB) of each engine noise is described in FIG. 3 below.

At this time, in the step of performing the K-center clustering process based on the engine noise (S1300), the clustering process may be performed according to Equation 1 representing the Euclidean distance below.

[Equation 1]

(However, d is a distance value, (x, y) is a coordinate value, x corresponds to frequency (Hz), and y corresponds to amplitude (dB))

3 is a graph showing the final two clusters according to the present invention.

According to FIG. 3 , the x-axis may correspond to frequency (Hz) as feature 1, and the y-axis may correspond to amplitude (dB) as feature 2. Cluster 1 is for a lower frequency (Hz) and amplitude (dB) and may mean a stable engine condition. Cluster 2 is for a higher frequency (Hz) and amplitude (dB) and may mean an unstable engine condition. Each dot represents the size of the frequency (Hz) and amplitude (dB) of each engine noise as coordinates, and may mean the size at a specific point in time. That is, the engine state can be analyzed according to the distance of the cluster formed from the engine noise.

The ship engine management method according to the present invention may extract final distance values of cluster 1 and cluster 2, and obtain/generate abnormal state information on the corresponding ship engine based on the final distance values.

At this time, the final distance value according to the present invention can be extracted in the following order.

(1) Extracting the first average value (x1, y1) of cluster 1 and the second average value (x2, y2) of cluster 2

(2) The first average value and the second average value are coordinate values, respectively, and the final distance value (L) between the first average value and the second average value is extracted based on Equation 2 below.

[Equation 2]

(However, (x1, y1) is a coordinate value generated based on the average value of cluster 1, and (x2, y2) is a coordinate value generated based on the average value of cluster 2)

In the present invention, when the extracted final distance value (L) is greater than a preset distance value, it is determined that an abnormality has occurred or an abnormal state is expected to occur in the corresponding engine, and the present invention obtains abnormal state information about the engine based on this. /can be created.

In addition, the ship engine management method according to the present invention may extract a different final distance value (L) according to the type of engine. In general, a ship engine may have an output considering the size, weight, capacity, and number of engines installed in the ship. Therefore, in the case of a marine engine, it is more efficient to multiply the final distance value (L) by a correction coefficient and compare it with a preset distance value based on this. This is referred to as the corrected final distance value (L') and can be extracted based on Equations 3 and 4 below.

[Equation 3]

(However, (x1, y1) is a coordinate value generated based on the average value of cluster 1, and (x2, y2) is a coordinate value generated based on the average value of cluster 2)

[Equation 4]

However, the unit of displacement may be cc, the unit of output may be kW, and the unit of engine speed may be rpm. In this case, α is a constant for correcting the final distance value according to the specifications of the marine engine so that information on the engine abnormal state is more accurately derived, and its unit can be ignored. In addition, the constant α may be used when the fuel used in the marine engine is diesel.

Also, Equation 4 may be calculated assuming that the marine engine is an engine using diesel fuel.

In this way, when the fire occurrence information is generated based on the corrected final distance value L' using Equations 3 and 4, there is an effect that abnormal state information on the marine engine can be more accurately derived.

[Experimental Example: Sedimentation test of underwater submersible]

In order to confirm whether the result of predicting the deposition state of the underwater submersible according to the present invention and the accumulation state of the underwater submersible in the same environment as the actual environment matched, the following test was performed.

At this time, the change in water pressure at the point where the underwater submersible is deposited is the same, the point density is also the same using the same underwater submersible, and the inclination change of the underwater submersible is also set to be the same.

Five experts in the field compared the predicted model with the actual deposited state and asked for a judgment on the consistency. Five experts in the field evaluated the concordance on a scale of 10 points.

expert 1 expert 2 expert 3 expert 4 expert 5 average score Weighted X 5.5 6 5 6 5 6.5 Weighting O 8 8 7.7 8.2 9 8.18

As can be seen from the results of Table 1, as a result of requesting evaluation by 5 experts, it was confirmed that the average score when learning with weights was 8.18 in the underwater submersible burial model generation system according to the present invention. . It was confirmed that the average score when learning without weighting was 6.5 points. That is, when learning proceeds by assigning weights according to the present invention, it is confirmed to have higher accuracy.

4 and 5 show a ship engine management system using a 3D modeling image according to the present invention.

According to FIGS. 4 and 5 , the ship engine management system according to the present invention may include a sensing unit 120 , a computing device 200 and a display device 300 .

The sensing unit 120 according to the present invention may detect engine noise from an engine included in the ship 10 (hereinafter referred to as ship engine 110). Engine noise may include all vibrations generated by marine engines. The sensing unit 120 may convert the detected engine noise into an electrical signal and transmit the converted electrical signal to the computing device 200 . The sensing unit 120 may be a noise sensor. In general, the noise detection sensor includes a plastic case, and a component for measurement may be provided inside the case.

The computing device 200 according to the present invention may generate engine state information for the engine 110 based on engine noise. In addition, the computing device 200 may store a 3D modeling image of a ship and load the stored 3D modeling image.

The display device 300 according to the present invention may output image information processed by the computing device 200 as visual information. Also, the display device 300 may refer to a device that receives screen data from a processor and displays it so that a user can check it through senses. The display device 300 may include a self-emissive display panel or a non-emissive display panel. For example, an OLED panel that does not require a backlight may be exemplified as a self-emissive display panel, and an LCD panel that requires a backlight may be exemplified as a non-emissive display panel, but is not limited thereto.

The display device 300 can be used as an input device in addition to an output device when a sensor (hereinafter referred to as a 'touch sensor') that detects a touch operation forms a mutually layered structure (hereinafter referred to as a 'touch screen'). can The touch sensor may have a form of, for example, a touch film, a touch sheet, or a touch pad.

The display device 300 according to the present invention may display the engine state information together with the 3D modeling image. The display device 300 may receive image information from the computing device 200 and display it.

The computing device 200 according to the present invention performs a K-center clustering process for generating the engine state information based on engine noise, finally generates two clusters through the K-center clustering process, and Engine state information may be generated based on clusters. In this case, the specific content of generating two clusters by the computing device 200 and generating the engine state information is the same as or overlaps with those of FIGS. 1 to 3 described above, and thus will be omitted.

According to FIG. 5, the ship 10 according to the present invention may include a plurality of ship engines 110, and the sensing unit 120 according to the present invention is provided with a number corresponding to the plurality of ship engines 110. It can be. There may be a plurality of sensing units 120 according to the present invention, and each sensing unit 120 may be installed around the corresponding marine engine 110 in order to receive engine noise of each marine engine. . For example, a plurality of marine engines 110 may be installed in separate engine rooms, and each sensing unit 120 may be separately installed in each engine room.

According to FIG. 5 , all of the plurality of sensing units 120 may be connected to the computing device 200 . The computing device 200 may receive engine noise data from the plurality of sensing units 120 and classify and record the data according to the marine engine.

The sensing unit 120 according to the present invention may be provided around the marine engine 110 or around the engine room in which the marine engine 110 is installed. In particular, when the sensing unit 120 is installed around the marine engine 110, the sensing unit 120 may be corroded by moisture including dust or salt generated from the engine 110. Since the computing device 200 according to the present invention must precisely detect the engine noise received from the sensing unit 120 and detect the abnormal state of the engine 110 based on this, it is necessary to prevent the sensing unit 120 from corrosion. can be very important.

The sensing unit 120 according to the present invention may be coated with a coating layer to be protected from moisture including engine dust and salt. The coating layer according to the present invention may mean one layer coated on the sensing unit 120 .

Preferably, the sensing unit 120 may include a fluorine-based polymer compound represented by Formula 1 below on its surface; It may be coated with a coating composition containing an organic solvent, inorganic particles and a dispersant.

[Formula 1]

here,

n and m are the same as or different from each other, and are each independently an integer of 1 to 100.

When coated with the coating composition, the inflow of moisture can be prevented, and in addition, static electricity generation can be blocked or corrosion can be prevented.

The inorganic particles may be selected from the group consisting of silica, alumina, and mixtures thereof. The average diameter of the inorganic particles is 70 to 100 μm, but is not limited to the above examples. After forming a coating layer on the surface of the sensing unit 120, the inorganic particles may improve physical strength and maintain viscosity within a certain range to increase moldability.

The organic solvent is selected from the group consisting of methyl ethyl ketone (MEK), toluene, and mixtures thereof, and preferably methyl ethyl ketone may be used, but is not limited to the above examples.

As the dispersing agent, a polyester-based dispersing agent may be used, and specifically, TEGO-Disperse 670 (manufacturer : EVONIK) can be used, but it is not limited to the above examples, and all dispersants obvious to those skilled in the art can be used without limitation.

For forming the coating layer, the coating composition is more specifically an acrylic compound represented by Formula 1; organic solvents, inorganic particles and dispersants.

The coating composition may include 40 to 60 parts by weight of the fluorine-based polymer compound represented by Chemical Formula 1, 20 to 40 parts by weight of inorganic particles, and 5 to 15 parts by weight of a dispersant, based on 100 parts by weight of the organic solvent. In the case of the above range, the effect of preventing static electricity generation and significantly lowering corrosion due to the interaction of each component is expressed, and when it is out of the above range, the synergistic effect is rapidly reduced or almost nonexistent.

More preferably, the viscosity of the coating composition is 1500 to 1800 cP, and when the viscosity is less than 1500 cP, there is a problem that it is not easy to form a coating layer because it flows down, and when it exceeds 1800 cP, it is not easy to form a uniform coating layer. there is a problem.

[Preparation Example 1: Preparation of coating layer]

1. Preparation of coating composition

A coating composition was prepared by mixing methyl ethyl ketone with a fluorine-based polymer compound represented by Formula 1, inorganic particles, and a dispersant:

[Formula 1]

here,

n and m are the same as or different from each other, and are each independently an integer of 1 to 100.

A more specific composition of the coating composition is shown in Table 2 below.

TX1 TX2 TX3 TX4 TX5 organic solvent 100 100 100 100 100 Fluorine-based high molecular compound 30 40 50 60 70 inorganic particles 10 20 30 40 50 dispersant One 5 10 15 20

(unit weight parts)

2. Preparation of coating layer

The coating composition of DX1 to DX5 was applied to the sensing unit 120 and then cured to form a coating layer.

[Experimental example]

1. Evaluation of surface appearance

Due to the difference in viscosity of the coating composition, after preparing the coating layer, a sensory evaluation was conducted on whether a uniform surface was formed. Evaluation was conducted on whether or not a uniform coating layer was formed, and the evaluation was conducted according to the following criteria.

○: uniform coating layer formation

×: Formation of non-uniform coating layer

TX1 TX2 TX3 TX4 TX5 sensory evaluation Х ○ ○ ○ Х

When forming the coating layer, when the viscosity is less than a certain amount, flow occurs on the surface of the sensing unit 120, and it is difficult to form a uniform coating layer after the curing process in many cases. Accordingly, a problem of lowering the production yield may occur. In addition, even when the viscosity is too high, it is difficult to uniformly apply the composition and it is impossible to form a uniform coating layer.

2. Evaluation of anti-corrosion ability

The sensing unit 120 having the coating layer according to the above embodiment was fixed within 30 cm from the marine engine installed on the ship, and the sensing unit 120 was exposed to the surrounding environment of the marine engine installed on the ship for 350 days. As a comparative example (Con), the same sensing unit 120 without a coating layer was used.

After that, the subjects before and after the experiment were surveyed to visually evaluate the degree of corrosion, and for objective comparison, the results were compared with the comparative example in which the coating layer was not formed, and the results were evaluated on a scale of 1 to 10, and are shown in Table 3 below. . The lower the index, the lower the change compared to the reference value, and the better the corrosion prevention ability.

- Visual and microscopic observation Degree of surface corrosion when coating layer is formed Degree of surface corrosion when no coating layer is formed TX1 4 8 TX2 One TX3 One TX4 One TX5 3

As shown in Table 4, after forming the coating layer using the coating compositions of TX1 to TX5, the degree of corrosion was observed with the naked eye and under a microscope. Referring to Table 4, in the case of forming a coating layer on the sensing unit 120, it was found that the anti-corrosion ability was significantly improved compared to the case where it was not. In particular, in the case of TX2 to TX4, it can be seen that the coating layer has a very excellent ability to prevent corrosion. FIG. 6 schematically shows a computing device according to the present invention.

According to FIG. 6 , a computing device 200 according to the present invention may include a processor 210, a memory 220, and a communication device. The processor 210 may perform the function of the command by executing the command stored in the memory 220 .

The processor 210 may execute commands stored in the memory 220 to control other components. The processor 210 may execute instructions stored in the memory 220 .

The processor 210 is a component capable of performing calculations and controlling other devices. Mainly, it may mean a central processing unit (CPU), an application processor (AP), a graphics processing unit (GPU), and the like. Also, the CPU, AP, or GPU may include one or more cores therein, and the CPU, AP, or GPU may operate using an operating voltage and a clock signal. However, while a CPU or AP consists of a few cores optimized for serial processing, a GPU may consist of thousands of smaller and more efficient cores designed for parallel processing.

The processor 210 may provide or process appropriate information or functions to a user by processing signals, data, information, etc. input or output through the components described above or by running an application program stored in the memory 220.

The memory 220 stores data supporting various functions of the controller. The memory 220 may store a plurality of application programs (or applications) driven by the control unit, data for operation of the control unit, and commands. At least some of these application programs may be downloaded from an external controller through wireless communication. In addition, the application program may be stored in the memory 220, installed in the control unit, and driven by the processor 210 to perform the operation (or function) of the control unit.

The memory 220 may be a flash memory type, a hard disk type, a solid state disk type, a silicon disk drive type, or a multimedia card micro type. ), card-type memory (eg SD or XD memory, etc.), RAM (random access memory; RAM), SRAM (static random access memory), ROM (read-only memory; ROM), EEPROM (electrically erasable programmable read -only memory), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk. Also, the memory 220 may include a web storage performing a storage function on the Internet.

In the case of the communication device 230, it transmits and receives information with a base station or a satellite including a communication function through an antenna. The communication device 230 may include a modulation unit, a demodulation unit, a signal processing unit, and the like. Communication may refer to communication using a communication facility previously installed by telecommunication companies and a wireless communication network using a frequency of the communication facility. Also, communication may refer to satellite communication using a satellite.

7 shows an example of a 3D modeling image according to the present invention.

According to FIG. 7 , a 3D modeling image displaying a plurality of marine engines according to the present invention may include engine state information. For example, it may be assumed that the plurality of marine engines are Engine 1 and Engine 2. The display device 300 according to the present invention may display engine 1 and engine 2 differently. When it is determined that the ship engine is in an abnormal state, the computing device 200 according to the present invention may indicate this on a 3D modeling image through a predetermined display.

For example, when it is determined that engine 1 is in a normal state and engine 2 is in an abnormal state, the computing device 200 displays the image of engine 1 included in the 3D modeling image in blue and displays the image of engine 2 in red. can be displayed in color.

The above-described present invention can be modeled as a computer readable code on a medium on which a program is recorded. The computer-readable medium includes all types of recording devices in which data readable by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. , and also includes those modeled in the form of carrier waves (eg, transmission over the Internet). Accordingly, the above detailed description should not be construed as limiting in all respects and should be considered illustrative. The scope of this specification should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of this specification are included in the scope of this specification.

Any or other embodiments of the present invention described above are not mutually exclusive or distinct. Certain or other embodiments of the present invention described above may be used in combination or combination of respective configurations or functions.

The above detailed description should not be construed as limiting in all respects and should be considered illustrative. The scope of the present invention should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of the present invention are included in the scope of the present invention.

10: ship
110: marine engine
120: sensing unit
200: computing device
300: display device

Claims (6)

Preparing a 3D modeling image of a ship;
Receiving engine noise of the vessel;
performing a K-center clustering process based on the engine noise;
generating final two clusters based on the K-center clustering process;
extracting an average value of each of the two clusters;
extracting a final distance value between the respective average values;
obtaining engine state information based on the final distance value; and
Displaying the engine state information on the 3D modeling image; including,
A ship engine management method using 3D modeling image.
According to claim 1,
The step of performing the K-center clustering process,
extracting random K pieces of data for the engine noise;
generating a plurality of clusters around the K pieces of data;
extracting a central value of each of the plurality of clusters;
extracting an intermediate distance value between the center values;
allocating data to a cluster having the shortest distance based on the intermediate distance value; and
Updating the center of the cluster by including the allocated data;
A ship engine management method using 3D modeling image.
According to claim 1,
The ship includes a plurality of engines,
The engine noise is individually received from a plurality of sensors corresponding to each of the plurality of engines,
A ship engine management method using 3D modeling image.
According to claim 3,
The 3D modeling image includes a plurality of engine images corresponding to the plurality of engines,
The plurality of engine images,
Including engine state information for the plurality of engines,
A ship engine management method using 3D modeling image.
A non-transitory computer readable medium storing instructions,
The instructions, when executed by a processor, cause the processor to perform the method of any one of claims 1-4.
A sensing unit for detecting engine noise from an engine included in the ship;
a computing device generating engine state information for the engine based on the engine noise and storing a 3D modeling image of the ship; and
A display device for displaying the engine state information together with the 3D modeling image;
The computing device,
A K-center clustering process for generating the engine state information is performed based on the engine noise, two clusters are finally generated through the K-center clustering process, and the engine state information is based on the two clusters. to generate information,
A ship engine management system using 3D modeling images.

Images