CN110778398A - Marine diesel engine fuel management control system - Google Patents
Marine diesel engine fuel management control system Download PDFInfo
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- CN110778398A CN110778398A CN201911064284.XA CN201911064284A CN110778398A CN 110778398 A CN110778398 A CN 110778398A CN 201911064284 A CN201911064284 A CN 201911064284A CN 110778398 A CN110778398 A CN 110778398A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02B—INTERNAL-COMBUSTION PISTON ENGINES; COMBUSTION ENGINES IN GENERAL
- F02B77/00—Component parts, details or accessories, not otherwise provided for
- F02B77/08—Safety, indicating or supervising devices
- F02B77/084—Safety, indicating or supervising devices indicating economy
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63H—MARINE PROPULSION OR STEERING
- B63H21/00—Use of propulsion power plant or units on vessels
- B63H21/38—Apparatus or methods specially adapted for use on marine vessels, for handling power plant or unit liquids, e.g. lubricants, coolants, fuels or the like
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
- F02M65/00—Testing fuel-injection apparatus, e.g. testing injection timing ; Cleaning of fuel-injection apparatus
Abstract
The invention relates to a fuel management control system of a marine diesel engine, which comprises a data storage unit, a data processing unit, an input unit, an output unit, a man-machine unit, a communication unit, an anemorumbometer and a flow direction and velocity meter, wherein a large amount of historical data of the ship, including hull appearance data, cargo carrying weight, course, navigational speed, wind direction, ocean current flow velocity, engine condition and position, is processed by utilizing an intelligent algorithm to obtain a navigational speed-fuel consumption rate model, and the real-time forecasted course, wind speed, wind direction, navigational speed and course data obtained on the spot and obtained on the network are input into the navigational speed-fuel consumption rate model to obtain the navigational speed-fuel consumption rate curves of the current position and each position on the front course, and obtaining the recommended navigational speed of each position, thereby achieving the effects of reducing fuel consumption, reducing pollution emission and reducing operation cost.
Description
Technical Field
The invention relates to the field of ship power device control, in particular to a fuel management control system of a diesel engine for a ship.
Background
With the increasing development of globalization and international trade, goods are transported more and more in various countries and regions around the world, and the demand for goods transportation is also increased. The ship transportation has become the most important transportation mode in international trade transportation by virtue of the advantages of large transportation volume, long transportation distance and low cost, and plays a very important role in the goods transportation of international trade.
At present, the marine engine mainly includes a gas turbine, a steam turbine, and a diesel engine. The diesel engine has the advantages of high thermal efficiency, good economy, easy starting, strong adaptability to various ships and the like, so that the diesel engine is mainly selected as the engine in the current commercial ships. In international logistics transportation, a commercial ship mainly uses a diesel engine as a power source, and due to the large carrying capacity and long sailing distance of the ship, a large amount of fuel oil needs to be consumed in the transportation process, and according to statistics, the consumption of the bunker fuel oil accounts for more than 35% of the total consumption of global fuel oil. The cost of fuel accounts for a considerable proportion of the total cost of operating a ship, and as the price of crude oil continues to rise, the cost of fuel is increasingly stressed. More seriously, when a ship enters an emission control area, the more expensive low-sulfur oil needs to be replaced to meet strict emission requirements, which undoubtedly increases the cost of fuel.
The use of fuel in the transportation process is reasonably managed and planned, the fuel efficiency is improved, the fuel consumption is reduced, and the method has great significance for reducing the operation cost of ships and reducing the emission of pollution. At present, a scientific, perfect and effective diesel engine fuel management system for ships does not exist, so that fuel used by a diesel engine in the transportation process is effectively planned and managed.
Disclosure of Invention
In order to solve the technical problems, the invention provides a fuel management control system of a marine diesel engine, which is used for establishing a model between fuel consumption rate and other variables by adopting a big data analysis and processing method based on a large amount of historical data of a ship in the previous use process, acquiring data and physical quantities in operation and giving a navigation suggestion of the optimal fuel consumption rate through the model, thereby solving the problems in the prior art.
A marine diesel fuel management control system comprising:
the data storage unit is used for storing historical data of the ship in previous sailing, and comprises hull appearance data, cargo carrying weight, course, speed, wind direction, ocean current flow speed, engine condition and position data; the model takes hull shape data, cargo carrying weight, course, ship speed, wind direction, ocean current flow rate and engine condition as input quantities, and obtains the corresponding relation between the ship speed and the diesel engine fuel consumption rate under the influence of the hull shape data, the cargo carrying weight, the course, the wind speed, the wind direction, the ocean current flow rate and the engine condition based on big data analysis;
a data processing unit for performing operations and processing on the received data;
the input unit receives the related data and transmits the data to the data processing unit;
the output unit is used for receiving the data output by the data processing unit and transmitting the output data;
the human-computer unit is used for human-computer interaction and comprises an input part and a display part; the input part is used for inputting data of a target route, a voyage, a fuel amount, a voyage and the like by an operator, and the display part is used for displaying output results, such as a current fuel consumption rate, a suggested fuel consumption rate, a residual fuel amount, a residual voyage and the like, and the man-machine unit is connected with the input unit.
The marine diesel engine fuel management control system further comprises an anemoscope and a flow velocity and flow direction instrument for ocean currents, wherein the anemoscope and the flow velocity and flow direction instrument are installed on the ship body and used for monitoring the wind direction and the wind speed of the ship at the position and the flow direction and the flow velocity of the ocean currents in real time.
The marine diesel engine fuel management control system also comprises a communication unit, wherein the communication unit is connected with a network to acquire relevant weather forecast information on a forward route. The communication unit is connected with the data processing unit and transmits the acquired related data to the data processing unit.
The ship speed-fuel consumption rate model is based on historical data of a ship, a support vector machine algorithm, a Bayesian optimization algorithm, an artificial neural network algorithm and the like based on big data are adopted to analyze a large amount of data which are stored by the ship and are related to ship shape data, cargo carrying weight, course, ship speed, wind direction, ocean current flow rate, engine condition and position, and the ship speed-fuel consumption rate model related to the relation between the ship speed and the fuel consumption rate under the influence of the factors is established. And inputting the data of the variables acquired in real time into the navigational speed-fuel consumption rate model so as to obtain a curve between the navigational speed and the fuel consumption rate under the current condition.
Further, the ship measures the wind speed and the wind direction at the position through a wind direction anemoscope carried by the ship, measures the flow speed and the flow direction of ocean current at the position through a flow speed and flow direction instrument carried by the ship, inputs the data obtained in real time into the navigational speed-fuel consumption rate model, obtains the relation between the navigational speed and the fuel consumption rate in real time, and can calculate and obtain the current optimal navigational speed in real time.
Meanwhile, the communication unit is connected with a network, acquires future meteorological information corresponding to a position on a route, transmits the meteorological information to the data processing unit, and inputs the meteorological information into the speed-fuel consumption rate model as a real-time variable to obtain a curve of estimated speed and fuel consumption rate at the corresponding position. Therefore, the speed-fuel consumption curve at each position under the remaining route can be obtained.
Furthermore, the data of wind direction, wind speed, ocean current flow direction and ocean current flow speed acquired in real time at the position is used as the correction data of the estimated navigational speed-fuel consumption rate curve, and the navigational speed-fuel consumption rate curve at the position is corrected.
After the speed-fuel consumption rate curve of each position under the remaining route is obtained, under the condition that the curve reaches a target port in a required voyage period, an intelligent algorithm is adopted to calculate and optimize the speed of each position under the remaining route, and the corresponding optimal speed is adopted at each position, so that the optimal and minimum fuel consumption total amount is achieved, and the purpose of reducing fuel consumption is achieved.
The implementation of the invention has the following beneficial effects: based on historical ship body shape data, cargo carrying weight, course, navigation speed, wind direction, ocean current flow rate, engine condition and position big data of a ship, a relation curve between the navigation speed and the fuel consumption rate under the influence of the factors is obtained by adopting a support vector machine algorithm; and then, acquiring data such as wind direction, wind speed, ocean current flow direction, ocean current flow speed, course and the like at the position in real time, acquiring weather forecast data of each position in the remaining flight path at corresponding time in the future from the network, and comprehensively acquiring a flight speed-fuel consumption rate curve at each position on the remaining flight path. Based on the speed-fuel consumption rate curve of each position on the remaining route, the optimal speed of each position is obtained on the premise of meeting the voyage period requirement, and the optimal and minimum total fuel consumption is further achieved, so that the effects of reducing fuel consumption, reducing cost, reducing emission and improving efficiency are achieved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a structural framework diagram of a fuel management control system of a marine diesel engine according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
As shown in fig. 1, the fuel management control system of the marine diesel engine of the present invention is specifically configured as a high-performance computer system with a data storage unit, a data processing unit, an input unit, an output unit, a man-machine unit, a communication unit, an anemoscope, and an ocean current flow velocity meter. Wherein: the data storage unit is a memory in a computer and stores historical data of the ship in previous sailing, including hull shape data, cargo carrying weight, course, speed, wind direction, ocean current flow speed, engine condition and position data. The historical data takes time as a reference parameter, and each time point comprises a group of data of the parameter, so that a huge database is formed. The data storage unit not only stores past historical data, but also groups the current related data according to time as a reference parameter and stores the grouped related data into the database.
The data storage unit also stores a speed-fuel consumption model, which is a relational model of the speed and the fuel consumption under the influence of the factors and is used for obtaining a relational curve of the speed and the fuel consumption.
The inputs to the cruise-fuel consumption model include hull form data, cargo carrying weight, heading, cruise, wind speed, wind direction, ocean current flow velocity, engine condition, and location.
The hull form data includes the form construction, shape, parameters of the ship, and form parameters under different cargo stacking modes. The draft of the ship is also taken into consideration, because under the condition of different loading weights, the weight of the cargo inevitably affects the draft of the ship, influences the appearance of the ship body and simultaneously influences the water flow resistance of the ship in navigation; the cargo is placed on the ship body, so that the appearance of the ship is influenced, and further the wind resistance condition of the ship is influenced.
When the ship sails on the air route, the influence of wind and ocean current on the ship must be referred to the heading of the ship, and the wind and the ocean current can be a positive power condition or a negative resistance condition, which depends on the vector relation between the wind or the ocean current and the air route. When the included angle between the course and the wind direction or the ocean current flow direction is an acute angle, the wind or the ocean current can generate positive power influence on the ship at the moment, and at least partial boosting force can be generated on the operation of the ship, so that the power of the ship can be saved, and the fuel consumption of the ship can be reduced. When the included angle between the course and the wind direction or the ocean current flow direction is an obtuse angle, the wind or the ocean current can generate negative resistance influence on the ship, the ship needs to overcome the resistance of the wind or the ocean current to operate, and the ship needs to output larger power to advance, so that the power consumption of the ship is increased, and the fuel consumption of the ship is also increased. When the included angle between the course and the wind direction or the ocean current flow direction is a right angle, the ship needs to output power to overcome the force of vertical wind or ocean current, namely the power output of the ship still needs to be increased, and the fuel consumption is increased. Therefore, when wind or ocean current forms an acute angle with the air line, the ship is assisted by the wind or the ocean current, and the fuel consumption of the ship can be reduced; when the wind or ocean current forms a direct or obtuse angle with the air route, the ship is subjected to the resistance action of the wind or ocean current, and the ship needs to output larger power, so that the fuel consumption of the ship is increased.
In addition, the condition of the diesel engine as an engine also affects the output of power and fuel consumption. After the diesel engine is operated, the operation conditions of the diesel engine are various and are also influenced by various factors such as internal components and related systems, for example, a cooling system is out of order to limit the power and power output of the diesel engine, the maximum output power of the diesel engine is reduced due to the wear and the aging of internal cylinders, and the like.
It is known that, although weather changes can be predicted, which tend to differ more or less from the actual weather conditions, marine weather and ocean current changes have a certain periodicity and predictability, which forms a substantially established circulation, and thus, at different locations, they are affected by such circulation also with a certain relevance and predictability.
The navigational speed-fuel consumption rate model adopts an intelligent algorithm based on big data, and the intelligent algorithm comprises but is not limited to a support vector machine algorithm, a Bayesian optimization algorithm or an artificial neural network algorithm. By classifying, optimizing and analyzing the input parameters, a relation curve of the navigational speed and the fuel consumption rate under the influence of the variables is obtained, namely the output quantity of the navigational speed-fuel consumption rate model is the navigational speed-fuel consumption rate curve.
The human-computer unit, that is, a human-computer interaction component, specifically includes a keyboard, a mouse, a touch screen, etc., and functions to provide a means for a user to input parameters and data, so that the user can input relevant data and parameters into the marine diesel engine fuel management control system. The operator inputs the data of the target route, the voyage, the fuel quantity, the voyage period and the like of the voyage through the man-machine unit; meanwhile, the man-machine unit also comprises a display device for displaying relevant output results, such as current navigational speed, current fuel consumption rate, suggested navigational speed, suggested fuel consumption rate, residual fuel quantity, residual navigational time, residual navigational range and the like.
The input unit is used as a data input interface of the data processing unit, the input unit is connected with the man-machine unit and the data processing unit, and the input unit receives data input by the man-machine unit and transmits the data to the data processing unit.
And the output unit is used as a data output interface of the data processing unit, is connected with the man-machine unit and the data processing unit, and transmits the data output by the data processing unit to the man-machine unit through the output unit so as to display related information.
The system also comprises a communication unit, wherein the communication unit is connected with the data processing unit and is also connected with a network to acquire weather forecast information at each position on the air route. When the ship sails offshore, the communication unit can receive mobile data signals on the land, and then the communication unit is connected to the network through the mobile data network to acquire weather forecast information at various positions on the air route. When the ship sails at ocean and far away from land, the ship can not obtain the mobile data signals near the shore, and the communication unit is connected to the network through satellite communication to obtain the weather forecast information at each position on the air route. After the communication unit acquires the weather forecast information, the weather forecast information is transmitted to the data processing unit.
The system also comprises a wind anemoscope and an ocean current velocity and direction instrument which are both connected to the data processing unit. The anemorumbometer and the flow velocity and direction instrument for measuring ocean currents are both arranged on the ship body and used for monitoring the wind direction and the wind velocity of the ship at the position of the ship in real time, the flow direction and the flow velocity of the ocean currents and transmitting acquired related data to the data processing unit.
The marine diesel engine fuel management control system establishes a navigational speed-fuel consumption rate model, adopts an intelligent algorithm including but not limited to a support vector machine algorithm, a Bayesian optimization algorithm or an artificial neural network algorithm based on huge historical data of a ship, and obtains a relationship curve of the navigational speed and the fuel consumption rate under the influence of various variables by classifying, optimizing and analyzing a large amount of data of hull shape data, cargo carrying weight, course, navigational speed, wind direction, ocean current flow rate, engine condition and position of the input model, namely the output quantity of the navigational speed-fuel consumption rate model is a navigational speed-fuel consumption rate curve.
The navigation speed-fuel consumption rate model is obtained by the following method:
1. preprocessing historical data of ship body shape data, cargo carrying weight, course, navigational speed, wind direction, ocean current flow speed, engine condition and position, wherein the preprocessing is performed according to a formula:
wherein A represents the history data after processing, A' represents the history data before processing,
representing the mean value of the historical data, A
maxRepresents the maximum value of the historical data, A
minRepresenting the minimum value of the historical data.
2. And constructing a navigational speed-fuel consumption rate model.
Constructing a neural network model, wherein the loss function adopts the following formula:
where u represents the number of iterations, v represents the output vector dimension, b
i,jRepresenting real training data, b
i,j' represents an estimated value of training data;
then dividing the training data into a plurality of groups, and updating parameters in the navigational speed-fuel consumption rate by adopting a random gradient descent algorithm, wherein the parameter updating formula is as follows:
n
i＝n
i-1-pz
wherein n is
i-1Representing the target parameter n after the training of the last group of data is completed
iRepresenting target parameters after the completion of the set of training data, p representing a learning ratio, and z representing a descent gradient;
and continuously updating different groups of training data until the error value is lower than the preset error value, finishing the training, and storing the final parameters to obtain the trained navigational speed-fuel consumption rate model.
3. And testing the obtained navigational speed-fuel consumption rate model, finishing training if the obtained error is within an allowable range, and returning to the step 1.2 for retraining until a stopping condition is reached if the obtained error is not within the allowable range.
And then acquiring data of the course, the wind speed, the wind direction, the flow speed and the flow direction of the ship in real time, acquiring meteorological information of future passing at each position on the remaining route from the network, inputting the data into a navigation speed-fuel consumption rate model, and acquiring a navigation speed-fuel consumption rate curve at each position on the remaining route. Because the ship needs to meet the requirement of reaching a target port in a specified voyage period, under the condition of meeting the voyage period, the voyage speed at each position of the remaining airline is calculated and optimized based on the obtained curve of the voyage speed-fuel consumption rate at each position on the remaining airline, and the corresponding optimal voyage speed is adopted at each position, so that the optimal and minimum total fuel consumption is achieved, and the aim of reducing the fuel consumption is fulfilled.
Furthermore, the data of wind direction, wind speed, ocean current flow direction and ocean current flow velocity acquired in real time at the position is used as the correction data of the cruise-fuel consumption rate curve estimated based on the weather forecast information, and the cruise-fuel consumption rate curve at the position is corrected.
The fuel management control system of the marine diesel engine can obtain the optimal navigational speed at each position on the premise of meeting the requirement of the navigational time, thereby achieving the optimal and least total fuel consumption, and further achieving the effects of reducing fuel consumption, reducing cost, reducing emission and improving efficiency.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. A marine diesel fuel management control system comprising: the data storage unit is used for storing historical data of the ship in previous sailing, and comprises hull appearance data, cargo carrying weight, course, speed, wind direction, ocean current flow speed, engine condition and position data; the model takes hull shape data, cargo carrying weight, course, ship speed, wind direction, ocean current flow rate and engine condition as input quantities, takes the relation between the ship speed and the fuel consumption rate as output quantities, and obtains a ship speed-fuel consumption rate curve under the influence of the hull shape data, the cargo carrying weight, the course, the wind speed, the wind direction, the ocean current flow rate and the engine condition on the basis of big data analysis;
the data processing unit is used for calculating and processing the received data and is connected with the data storage unit;
the input unit receives data and transmits the data to the data processing unit;
the output unit is connected with the data processing unit, receives the data output by the data processing unit and transmits the output data;
a human-machine unit connected to the input unit for human-machine interaction, the human-machine unit including an input part and a display part;
the marine diesel engine fuel management control system is characterized by further comprising an anemoscope and a flow velocity and direction instrument, wherein the anemoscope and the flow velocity and direction instrument are connected to the data processing unit and are installed on a ship body and used for monitoring the wind direction and the wind speed of wind at the position of a ship and the flow direction and the flow velocity of ocean current in real time;
the marine diesel engine fuel management control system also comprises a communication unit, wherein the communication unit is connected with the network and the data processing unit, acquires relevant weather forecast information of future passing on a front route from the network and transmits the weather forecast information to the data processing unit;
the navigational speed-fuel consumption rate model is obtained by the following method:
1.1, preprocessing historical data of ship body shape data, cargo carrying weight, course, navigation speed, wind direction, ocean current flow speed, engine condition and position, wherein the preprocessing is performed according to a formula:
wherein A isIndicating the history data after processing, a' indicating the history data before processing,
representing the mean value of the historical data, A
maxRepresents the maximum value of the historical data, A
minRepresenting a historical data minimum;
1.2 construct the model of speed-specific fuel consumption.
Constructing a neural network model, and setting an input layer, a hidden layer and an output layer, wherein sigmoid functions are adopted as activation functions between the input layer and the hidden layer, between the hidden layers and between the output layers; wherein the loss function employs the following formula:
where u represents the number of iterations, v represents the output vector dimension, b
i,jRepresenting real training data, b
i,j' represents an estimated value of training data;
then dividing the training data into a plurality of groups, and updating parameters in the navigational speed-fuel consumption rate by adopting a random gradient descent algorithm, wherein the parameter updating formula is as follows:
n
i＝n
i-1-pz
wherein n is
i-1Representing the target parameter n after the training of the last group of data is completed
iRepresenting target parameters after the completion of the set of training data, p representing a learning ratio, and z representing a descent gradient;
continuously updating different groups of training data until the error value is lower than a preset error value, finishing training, and storing final parameters to obtain a trained navigational speed-fuel consumption rate model;
1.3, testing the obtained navigational speed-fuel consumption rate model, finishing training if the obtained error is within an allowable range, and returning to the step 1.2 to retrain if the obtained error is not within the allowable range until a stop condition is reached;
the data and course data of the positions where the anemoscope and the current meter are obtained are transmitted to a data processing unit, the data processing unit inputs the course, wind direction, wind speed, flow direction and current speed which are obtained in real time on site into a navigational speed-fuel consumption rate model, and a navigational speed-fuel consumption rate curve of the position is obtained; simultaneously, weather forecast information at each position of a future ship passing on a front route acquired on the network is input into a navigational speed-fuel consumption rate model to acquire a navigational speed-fuel consumption rate curve at each position on the front route;
and under the condition that the destination is reached in a specified voyage period, analyzing and optimizing the voyage speed at each position on the front airline to obtain the recommended voyage speed at each position, so that the total fuel consumption is minimum.
2. The marine diesel fuel management and control system of claim 1, wherein the marine diesel fuel management and control system is a computer system, the data storage unit is a memory in the computer system, and the data processing unit is a processor in the computer system.
3. The marine diesel fuel management control system of claim 1, wherein the cruise-specific fuel consumption model is established using big data based algorithms; the algorithm includes but is not limited to a support vector machine algorithm, a Bayesian optimization algorithm and an artificial neural network algorithm.
4. The marine diesel fuel management control system according to claim 1 or 2, wherein the data processing unit is capable of reading data from the data storage unit and writing data into the data storage unit.
5. The marine diesel fuel management control system according to claim 1, wherein the initialization of the cruise-fuel consumption rate model is completed by inputting hull shape data, cargo carrying weight, and engine condition for the current voyage into the cruise-fuel consumption rate model before the voyage starts.
6. The marine diesel fuel management control system of claim 1, wherein the communication unit is capable of connecting a mobile data network and a satellite communication network.
7. The marine diesel fuel management control system of any one of claims 1 to 3, wherein the input part of the human machine unit comprises at least one of a keyboard, a mouse, and a touch screen, and the output part of the human machine unit comprises a display screen.
8. The marine diesel fuel management control system according to claim 1, wherein when the weather forecast information at a position on the forward route is not available from the network, the weather forecast information at a position adjacent thereto is used.
9. The marine diesel fuel management control system of claim 6, wherein the communication unit is connected to a mobile data network when the vessel is underway offshore; when the vessel is sailing in open sea, such as without a mobile data network, the communication unit is connected to a satellite communication network.
10. The marine diesel fuel management control system according to claim 1, wherein the data of the wind direction, the wind speed, the ocean current flow direction, and the ocean current flow velocity acquired in real time at the passing position are used as correction data of a previously estimated cruise-fuel consumption curve, and the cruise-fuel consumption curve at the passing position is corrected.
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| CN112977754A (en) * | 2021-04-07 | 2021-06-18 | 梧州欣欣科技发展有限公司 | Oil consumption analysis method suitable for running of inland ship |
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| CN109855878A (en) * | 2018-12-29 | 2019-06-07 | 青岛海洋科学与技术国家实验室发展中心 | Computer-readable medium, engine failure detection device and ship |
| CN110276479A (en) * | 2019-05-31 | 2019-09-24 | 南京航空航天大学 | The cruising phase fuel consumption prediction technique of Aircraft Quality variation |
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| CN111964678A (en) * | 2020-07-16 | 2020-11-20 | 武汉长江船舶设计院有限公司 | River channel navigation decision-making method, device and system |
| CN111964678B (en) * | 2020-07-16 | 2023-04-18 | 武汉长江船舶设计院有限公司 | River channel navigation decision-making method, device and system |
| CN112977754A (en) * | 2021-04-07 | 2021-06-18 | 梧州欣欣科技发展有限公司 | Oil consumption analysis method suitable for running of inland ship |
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