KR20220142340A - Prediction apparatus for predicting operating time of device provided on ship, prediction method, and recording medium having prediction program recorded thereon - Google Patents

Abstract

The present invention is to accurately predict the operation time of equipment installed on a ship. According to the present invention, a prediction apparatus (3) for predicting the operating time of equipment installed on a ship (S) comprises: a navigation plan acquisition unit (32) which acquires a navigation plan of the ship (S); a meteorological information acquisition unit (34) which acquires meteorological information of the route in the navigation plan; and an operating time prediction unit (35) for predicting the operating time of the equipment based on the meteorological information.

Description

Prediction device for estimating the operating time of equipment installed on a ship, a prediction method, and a recording medium recording the prediction program

The present invention relates to a prediction device for estimating the operating time of a device installed on a ship, a prediction method, and a recording medium in which a prediction program is recorded.

It is necessary to perform maintenance (checking or replacing parts of the equipment) for equipment such as a tide device or oil-water separator installed on a ship operating in the sea according to the total operation time. It is disclosed in patent document 1 to create a maintenance plan based on the daily operation time information of the marine engine, the maintenance period for each unit component which comprises the marine engine, maintenance history information, and the annual planned operating time of the marine engine.

Patent Document 1: Japanese Patent No. 4909175

Since maintenance cannot be performed during voyage, it is necessary to perform maintenance prior to departure of the vessel to prevent the occurrence of parts that are due to maintenance during voyage. However, since the operating conditions of the ship's equipment change according to the weather, the operating time of the equipment from the departure of the ship to the arrival at the destination is affected by the weather of the route. Therefore, it is difficult to determine whether maintenance is necessary from the accumulated operating time of the equipment at the time of departure. In addition, replacement parts for the device cannot be obtained due to forgetting to purchase or the like, so that when a replacement product of poor quality is used, there is a risk of shortening the life of the device on the contrary.

The present invention has been made to solve the above problem, and an object of the present invention is to accurately predict the operating time of a device installed on a ship.

The above object of the present invention is a prediction device for estimating the operating time of equipment installed on a ship, a navigation plan acquisition unit for acquiring a navigation plan of the ship, and weather information acquisition for acquiring weather information of a route in the navigation plan and a prediction device having an operating time prediction unit for predicting the operating time of the device based on the weather information.

The above object of the present invention is a prediction method for estimating the operating time of an apparatus installed in a ship, a navigation plan acquisition step of acquiring a navigation plan of the ship, and weather information acquisition of acquiring weather information of a route in the navigation plan It is solved by the prediction method provided with a process and the operation time prediction process of predicting the operation time of the said apparatus based on the said meteorological information.

In a preferred embodiment of the present invention, the meteorological information includes at least one of weather, wind speed, wind direction, wave height, sea surface temperature, sea current velocity, and sea current direction.

In a preferred embodiment of the present invention, the prediction device further includes a description information acquisition unit configured to acquire description information regarding the ship and equipment, and the operation time prediction unit is based on the weather information and the description information. It is characterized in that the operating time of the device is predicted. In addition, the prediction method further includes a description information acquisition step of acquiring description information about the ship and the equipment, wherein the operation time prediction step predicts the operation time of the device based on the weather information and the description information is characterized by

In a preferred embodiment of the present invention, the operating time prediction unit predicts the operating time of the device using a machine-learned operating time prediction model. In addition, the operating time prediction process is characterized in that the operating time of the device is predicted using a machine-learned operating time prediction model.

In a preferred embodiment of the present invention, the prediction device further includes a maintenance prediction unit that predicts whether the device needs maintenance based on the predicted operating time. In addition, the prediction method is characterized in that it further comprises a maintenance prediction step of predicting whether maintenance of the equipment is required based on the predicted operating time.

In the above embodiment, the device may be a fresh water generator for producing fresh water from seawater.

In the said embodiment, the said apparatus may be an oil-water separator which separates an oil component from a waste liquid.

The above object of the present invention is a computer readable recording medium recording a prediction program for causing a computer to function as a prediction device for estimating the operating time of an apparatus installed on a ship, wherein the prediction program is a navigation plan for acquiring the navigation plan of the ship It is solved by the recording medium which makes a computer function as an acquisition part, a meteorological information acquisition part which acquires the weather information of the route in the said navigation plan, and the operation time prediction part which predicts the operating time of the said apparatus based on the said weather information.

According to the present invention, it is possible to accurately predict the operating time of a device installed on a ship.

1 is a block diagram of a management system according to an embodiment of the present invention.
2 is an example of a route.
3 is an example of an area for acquiring route and weather information.
4 is an example of a meteorological map showing wind speed and wind direction.
5 is an example of a weather map showing a wave height and a wave direction.
6 is an example of a meteorological map showing sea level water temperature.
7 is an example of a weather map showing an ocean current velocity and an ocean current direction.
8 is an example of device management information.
9 is a flowchart showing the operation of the prediction apparatus.

EMBODIMENT OF THE INVENTION Hereinafter, embodiment of this invention is described with reference to an accompanying drawing. In addition, this invention is not limited to the following embodiment.

[System Configuration]

1 is a block diagram of a management system 1 according to an embodiment of the present invention. The management system 1 is a system which manages the ship S, and is provided with the control terminal 2 and the prediction device 3 .

The control terminal 2 is a terminal operated by the crew of the ship S, etc., and is equipped with input devices (not shown), such as a touch panel, and display devices (not shown), such as a liquid crystal display. The control terminal 2 may be comprised by a general-purpose computer, and may be comprised by a dedicated computer, such as a control panel. Alternatively, the control terminal 2 may be integrally configured with the fresh water generator 4 or the oil-water separator 5 . The control terminal 2 monitors the operating states of the fresh water generator 4 and the oil-water separator 5, and also controls the fresh water generator 4 and the oil-water separator 5 according to the operation with the input device.

[Configuration of Prediction Device]

The prediction device 3 is a device for estimating the operating hours of the fresh water generator 4 and the oil-water separator 5 which are devices installed in the ship S. The prediction device 3 is installed outside the ship, and is connected to the control terminal 2 so as to be able to communicate via a network N such as the Internet. The prediction device 3 can be configured by a general-purpose computer, and is managed, for example, by a management company that manages the ship S, or a company that manufactures the freshwater device 4 and the oil-water separator 5 .

The prediction device 3 includes, as a hardware configuration, a processor such as a CPU or GPU, a main storage device (not shown) such as DRAM or SRAM, and an auxiliary storage device 31 such as an HDD or SSD. The auxiliary storage device 31 stores various data such as a prediction program D1, an operating time prediction model D2, and equipment management information D3.

Moreover, the prediction apparatus 3 is a function block, The navigation plan acquisition part 32, the description information acquisition part 33, the weather information acquisition part 34, the operation time prediction part 35, and maintenance prediction A unit 36 and an external communication unit 37 are provided. Each of these units may be realized in hardware by a logic circuit or the like, or may be realized in software by a processor of the prediction device 3 . In the latter case, each of the above units can be realized by the processor reading and executing the prediction program D1 stored in the auxiliary storage device 31 into the main storage device. The prediction program D1 may be downloaded to the prediction device 3 via the network N, and is installed in the prediction device 3 via a computer-readable non-transitory recording medium such as a CD-ROM in which the prediction program D1 is recorded. good to do

The navigation plan acquisition part 32 acquires the navigation plan of the ship S. The navigation plan includes the departure point, destination, scheduled departure date, arrival date, etc. of the ship S, and in this embodiment, the crew of the ship S inputs the navigation plan through the control terminal 2 . The input data of the navigation plan is transmitted to the prediction device 3, and the navigation plan acquisition unit 32 acquires it.

The description information acquisition unit 33 acquires description information regarding the ship S, the fresh water generator 4 and the oil-water separator 5 . Specifically, the description information includes the ship type, size and age of the ship S, the production number and production water tank number of the freshwater generator 4, and the production number and waste liquid treatment tank number of the oil-water separator 5, and the like. In this embodiment, the serial number of the fresh water generator 4 or the oil-water separator 5 is transmitted from the control terminal 2 together with the navigation plan data, and the description information acquisition unit 33 transmits the serial number to the outside of the manufacturer. By collating with the server, other description information, such as the type of ship S, is acquired.

The weather information acquisition part 34 acquires the weather information of the route in the navigation plan of the ship S. For example, as shown in FIG. 2 , it is assumed that the navigation plan departs the port (A) on March 1 and arrives at the port (B) on March 3rd. In that case, the weather information acquisition unit 34 acquires the weather information (forecast) for March 1 to March 3 in the area R shown by the hatched line including the route P shown in FIG. 3 . do.

In addition, the standard route which navigates from the port A to the port B may be sufficient as the route P, and the crew of the ship S etc. may decide. In addition, the width|variety of the area|region R can be set suitably in consideration of the error of the route P and the actual route of the ship S.

The meteorological information may be acquired from a weather information provider such as the Korea Meteorological Administration through the network N. The type of weather is not particularly limited as long as it affects the operation status of the device, and examples thereof include weather, wind speed, wind direction, wave height, sea level water temperature, sea current speed and sea current direction.

Weather, wind speed, wind direction, wave height, sea current speed and current direction affect the load (ship speed) of the main engine (engine) of the vessel S. For example, when the headwind is strong, the load on the cycle tends to increase, and when the wave height is large, the load on the cycle tends to decrease for low-speed operation. In addition, when the ship S is a cargo ship, after implementing low-speed navigation, in order to recover the delay of a schedule, it may switch to high-speed navigation. The water temperature at sea level affects the amount of fresh water in the tidal device 4 .

Examples of weather information are shown in FIGS. 4 to 7 . 4 is an example of a weather map showing wind speed and direction, FIG. 5 is an example of a weather map showing wave height and wave direction, FIG. 6 is an example of a weather map showing sea surface water temperature, and FIG. This is an example of the illustrated weather map. 4 to 7 are schematic weather maps, and more detailed information is provided in reality.

The operating time prediction unit 35 predicts the operating hours of the fresh water generator 4 and the oil-water separator 5 based on the weather information and the description information. In the present embodiment, the operating time prediction unit 35 predicts the operating hours of the fresh water generator 4 and the oil-water separator 5 using the machine-learned operating time prediction model D2. That is, the operation time prediction unit 35 inputs the weather information acquired by the weather information acquisition unit 34 and the description information acquired by the description information acquisition unit 33 to the operation time prediction model D2, and predicts the operation time accordingly. The operating hours of the fresh water generator 4 and the oil-water separator 5 output from the model D2 are acquired as prediction results.

The operating time prediction model D2 is generated as follows, for example. First, with respect to a plurality of ships that have navigated the route in the navigation plan of the ship S in the past, information on the description and the actual weather information on the route are correlated with the actual operating hours of the tide device and the oil/water separator. Create data (training data set). Then, an uptime prediction model D2 is generated by machine learning an artificial intelligence model such as a neural network using the teacher data. The weather information in the teacher data may be information obtained by extracting an area of a predetermined range including the route from the weather map. For example, when the route is the route P shown in FIG. 3, weather information in the area R it's good In addition, when generating the operating time prediction model D2 specialized for a specific description, you may abbreviate|omit description information from teacher data.

The maintenance prediction unit 36 determines whether maintenance of the fresh water generator 4 and the oil-water separator 5 is necessary based on the operating time predicted by the operating time prediction unit 35 (hereinafter referred to as “predicted operating time”). predict In the present embodiment, the maintenance prediction unit 36 predicts whether inspection or replacement of each component of the fresh water generator 4 and the oil-water separator 5 is necessary with reference to the equipment management information D3.

8 is an example of the device management information D3. The device management information D3 includes the construction number, model number, consumable name, replacement standard time, and integrated operation time of the device. The replacement standard time is the time (maintenance cycle) from when the part is replaced until replacement is required again. The integration operation time is the integration time that an apparatus operated after replacing the said parts, and the prediction apparatus 3 is acquiring it regularly from the control terminal 2 of the ship S.

For example, when the predicted operating time is 15 hours, the integrated operating time of the component A exceeds the replacement reference time during the voyage of the ship S. Therefore, the maintenance prediction part 36 predicts that replacement|exchange of the component A is necessary.

The prediction result is transmitted from the prediction device to the control terminal 2 and displayed on the display device of the control terminal 2 . Accordingly, the crew of the ship (S) can grasp the parts requiring maintenance.

In addition, the prediction by the operation time prediction part 35 and the maintenance prediction part 36 may be implemented before navigation of the ship S, and may be implemented during navigation of the ship S. In addition, even when the above prediction is made before the navigation of the ship S, when the weather forecast is changed or the route is changed during the navigation of the ship S, the navigation plan acquisition unit 32, the equipment information acquisition part during the navigation It is preferable to acquire information by (33) and the meteorological information acquisition part 34, and to predict by the operation time prediction part 35 and the maintenance prediction part 36.

The external communication unit 37 may communicate with the external contact T through the network N or another network. For example, when it is predicted by the maintenance prediction unit 36 that replacement of the component A is necessary as described above, the external communication unit 37 communicates with the external contact T, and the component ( You can take measures such as delivering A) to the nearest port of call. In the present embodiment, the external contact T is, for example, a ship management company, a replacement parts distributor, a product manufacturing company, or the like.

[Processing order]

9 is a flowchart showing the operation of the prediction device 3 . In the prediction apparatus 3, the navigation plan acquisition part 32 acquires the navigation plan of the ship S from the control terminal 2 of the ship S (navigation plan acquisition process S1). At the same time, the equipment information acquisition unit 33 acquires equipment information about the ship S, the fresh water generator 4, and the oil-water separator 5 from the control terminal 2 (the equipment information acquisition step S2). Next, the weather information acquisition part 34 acquires the weather information of the route in the navigation plan of the ship S (weather information acquisition process S3). Next, the operating time prediction unit 35 predicts the operating hours of the fresh water generator 4 and the oil-water separator 5 based on the weather information and the description information (operation time prediction step S4). Moreover, the maintenance prediction part 36 predicts whether maintenance of the fresh water generator 4 and the oil-water separator 5 is necessary based on the predicted operating time (maintenance prediction process S5).

In addition, the order of process S1 - S3 is not specifically limited. In addition, as long as each process is executed by a computer, the operating subject of each process is not limited to the above. For example, at least a part of steps S1 to S5 may be performed by the control terminal 2 .

[Brief Summary]

As described above, in the present embodiment, the operating time of each device of the fresh water generator 4 and the oil-water separator 5 is calculated using the operating time prediction model D2 machine-learned based on the weather information of the route in the navigation plan. is predicting Therefore, it is possible to accurately predict the operating time of the device affected by the weather. In addition, it is possible to predict whether the equipment needs maintenance based on the predicted uptime.

[Variation]

As mentioned above, although embodiment of this invention was described, this invention is not limited to the said embodiment, Unless it deviates from the meaning, various changes are possible.

Although a fresh water generator and an oil-water separator are exemplified as equipment installed on a ship in the above embodiment, the present invention is not limited thereto. The device may be a main engine or the like, but in the present invention, the main object is a bogie.

In the above embodiment, the operating time prediction unit 35 predicts the operating time of the device based on the weather information and the device information. However, when the operating time prediction model D2 is a model specialized for a specific device, the operating time is predicted. The unit 35 may predict the operating time of the device based only on the weather information. In this case, the description information acquisition unit 33 can be omitted.

In addition, in the above embodiment, the operating time prediction unit 35 predicts the operating time of the device using the machine-learned operating time prediction model D2, that is, using artificial intelligence, but without using artificial intelligence. You can also predict the uptime of your device. In this case, for example, the operating time of the fresh water generator can be calculated by the following formula.

Operation time = Required quantity / Estimated amount of tide

Here, the required quantity is calculated as average consumption x number of sailing days x α. α is a safety factor, and is set in consideration of the period immediately before departure and immediately before entry into port (the number of spare days) in which the tide device cannot be used. In addition, the predicted tide quantity can be predicted from the engine load and the sea water surface temperature, and the engine load depends on the weather (especially wave height and wind speed).

In addition, in the said embodiment, although the maintenance prediction part 36 of the prediction apparatus 3 predicted automatically whether maintenance of an apparatus was necessary, in the prediction apparatus 3, the operating time of the apparatus by the operation time prediction part 35 may be predicted, and based on the predicted operating time, a user (crew of the ship S, etc.) may determine whether maintenance of the equipment is necessary.

1: Management system
2: control terminal
3: Prediction device
31: auxiliary storage device
32: navigation plan acquisition unit
33: description information acquisition unit
34: Weather information acquisition unit
35: Uptime Prediction Unit
36: maintenance prediction unit
4: tide device
5: Oil-water separator
D1: Prediction Program
D2: Uptime Prediction Model
D3: Device Management Information
N: network
P: Passage
R: area
S: ship

Claims (15)

As a prediction device for estimating the operating time of equipment installed on a ship,
a navigation plan acquisition unit for acquiring the navigation plan of the vessel;
a weather information acquisition unit for acquiring weather information of the route in the navigation plan;
An operating time prediction unit for predicting the operating time of the device based on the weather information
prediction device.
According to claim 1,
The weather information includes at least one of weather, wind speed, wind direction, wave height, sea level water temperature, sea current speed, and sea current direction
prediction device.
3. The method of claim 1 or 2,
Further comprising a description information acquisition unit for acquiring the description information about the vessel and equipment,
The operating time prediction unit predicts the operating time of the device based on the weather information and the described information
prediction device.
3. The method of claim 1 or 2,
The operating time prediction unit predicts the operating time of the device using a machine-learned operating time prediction model.
prediction device.
3. The method of claim 1 or 2,
Further comprising a maintenance prediction unit for predicting whether maintenance of the device is necessary based on the predicted operating time
prediction device.
3. The method of claim 1 or 2,
The device is a tidal device for producing fresh water from seawater
prediction device.
3. The method of claim 1 or 2,
The device is an oil-water separator that separates oil from waste liquid
prediction device.
As a prediction method for estimating the operating time of equipment installed on a ship,
a navigation plan acquisition step of acquiring the navigation plan of the vessel;
a meteorological information acquisition step of acquiring weather information of the route in the navigation plan;
an operation time prediction process of estimating the operation time of the device based on the weather information;
Prediction method.
9. The method of claim 8,
The weather information includes at least one of weather, wind speed, wind direction, wave height, sea level water temperature, sea current speed, and sea current direction
Prediction method.
10. The method according to claim 8 or 9,
Further comprising a description information acquisition step of acquiring the description information about the ship and equipment,
In the operation time prediction process, the operation time of the device is predicted based on the weather information and the described information.
Prediction method.
10. The method according to claim 8 or 9,
In the operation time prediction process, the operation time of the device is predicted using a machine-learned operation time prediction model.
Prediction method.
10. The method of claim 9,
Further comprising a maintenance prediction process of predicting whether maintenance of the device is required based on the predicted operating time
Prediction method.
10. The method according to claim 8 or 9,
The device is a tidal device for producing fresh water from seawater
Prediction method.
10. The method according to claim 8 or 9,
The device is an oil-water separator that separates oil from waste liquid
Prediction method.
A computer-readable recording medium in which a prediction program for making a computer function as a prediction device for estimating the operating time of a device installed on a ship is recorded,
The prediction program is
A navigation plan acquisition unit for acquiring the navigation plan of the vessel;
a weather information acquisition unit for acquiring weather information of the route in the navigation plan;
To function a computer as an operating time prediction unit that predicts the operating time of the device based on the weather information
recording medium.

Images