Ship speed dynamic determination method and device based on operation data

Abstract

The present application relates to the technical field of ship testing and state monitoring, and proposes a ship speed dynamic determination method and device based on operation data, which comprises the following steps: automatically collecting the data of six-way draft, high-precision position and ground speed, main engine speed and water depth of the ship in the operation process through the sensor cluster installed on the ship; selecting the water area meeting the preset still water condition in the daily route to set the electronic fence area, controlling the ship to sail at different stable main engine speed points and collecting data; using the three-step iterative regression analysis algorithm to clean and model the data after cleaning, and finally fitting the relationship model between the ship still water speed and the main engine speed. The present application changes the speed determination from the expensive special voyage test to the low-cost and normalized operation process data utilization, realizes the dynamic, accurate and convenient determination of the ship speed, and provides the key data basis for the ship energy efficiency management, technical evaluation and intelligent operation and maintenance.

Description

Technical Field

[0001] This invention belongs to the field of ship testing and condition monitoring technology, specifically relating to a method and device for dynamic measurement of ship speed based on operational data. Background Technology

[0002] Speed ​​is a core indicator of ship performance and a key parameter for ship energy efficiency assessment (such as EEDI and EEXI) and carbon emission accounting. Currently, the industry mainly relies on standards such as the "Test Method for Speed ​​Measurement of Seagoing Ships" (CB / T 3767-1996) to conduct specialized voyage tests after new ships have been delivered or after major repairs. This method requires: a clean hull and testing at a specific water depth (usually requiring the test area to meet certain depth requirements). ,in, The water depth in the test area is expressed in meters (m). The maximum speed expected to be achieved during the test, in kN; The test is conducted in a dedicated waterway with good sea conditions (wind force ≤ 4, waves ≤ 2, and stable current) and the length between vertical lines of the vessel (in meters). During the test, the vessel needs to sail back and forth on the same speed measurement line 2-3 times with different main engine power (e.g., 50%, 75%, 90%, 100%). A large amount of data is manually recorded. Finally, the displacement, wind, waves, yaw and other factors are complicatedly corrected by methods such as BSRA and ITTC to derive the full-load still water speed.

[0003] Existing methods have significant drawbacks:

[0004] (1) High cost: It requires organizing a professional team, occupying dedicated waterways, and arranging independent voyages, which consumes a lot of manpower, time and fuel, raising the cost of speed measurement, resulting in the vast majority of inland waterway vessels never having their speed measured.

[0005] (2) Harsh and inconvenient conditions: The test environment (water depth, wind and waves, water flow) is very demanding. It requires turning and accelerating in wide waters, which affects normal navigation. Ideal test windows are hard to find.

[0006] (3) Accuracy is difficult to verify: Tests are usually conducted under non-full load and non-ideal conditions, relying on manual correction, which makes the accuracy of the correction model and the verifiability of the results poor.

[0007] (4) Lack of dynamism: It is only a one-time "factory qualified" test, which cannot reflect the changes in speed performance of the ship during its life cycle due to hull fouling, propeller damage or replacement, and is difficult to provide real-time data support for energy efficiency management and operation and maintenance decisions.

[0008] As the shipping industry transforms towards green, intelligent, and low-carbon development, there is an urgent need for a method that can measure the speed of operating vessels in a low-cost, convenient, dynamic, and accurate manner. Summary of the Invention

[0009] To address the aforementioned technical issues, this invention proposes a dynamic method for measuring ship speed based on operational data analysis. By automatically collecting data during daily ship operations and analyzing it in suitable waters, this method achieves low-cost, high-precision, routine, and dynamic speed measurement, meeting the needs for real-time monitoring of ship energy efficiency and dynamic performance evaluation.

[0010] This invention provides a method for dynamically determining ship speed based on operational data, comprising:

[0011] Step 1: Continuously collect status data and waterway environment data during ship operation through a cluster of sensors installed on the ship;

[0012] Step two involves triggering the measurement and filtering the data, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the ship's daily route; when the ship enters the electronic fence area and is fully loaded, triggering the speed measurement process, controlling the ship to sail at multiple different stable main engine speed points, and collecting the status data and waterway environment data during the stable navigation period.

[0013] Step 3 involves data analysis and modeling, including: cleaning the filtered data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed using a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel currents and a second parameter characterizing the ship's still water speed performance from the model; using the second parameter to construct a relationship model between the ship's still water speed and main engine speed, which serves as the speed measurement result.

[0014] On the other hand, this invention protects a device for dynamically measuring ship speed based on operational data. The device utilizes the steps of the aforementioned method to achieve dynamic measurement of ship speed based on operational data. The device includes:

[0015] The first module is used to continuously collect status data and waterway environment data during the ship's operation through a cluster of sensors installed on the ship;

[0016] The second module is used for measurement triggering and data filtering, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the daily route of the ship; when the ship enters the electronic fence area and is fully loaded, the speed measurement process is triggered, the ship is controlled to sail at multiple different stable main engine speed points, and the state data and waterway environment data during stable navigation are collected.

[0017] The third module is used for data analysis and modeling, including: cleaning the screened data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed through a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel current and a second parameter characterizing the ship's still water speed performance from the model, and using the second parameter to construct a relationship model between the ship's still water speed and main engine speed as the speed measurement result.

[0018] Compared with the prior art, the present invention achieves the following beneficial effects:

[0019] 1. Providing low cost and high accessibility, the dynamic speed measurement method for ships provided by this invention eliminates the costs of dedicated test voyages, professional teams, and fuel consumption. It can be completed using existing operational voyages, making regular speed measurement of all in-service ships an economically feasible and routine practice.

[0020] 2. The method of the present invention is convenient to implement and does not interfere with operations. The test can be flexibly carried out at the most ideal time and place in the global route network, and can be fully integrated into the normal flight plan without additional detours or waiting for the window period, and has no impact on shipping efficiency.

[0021] 3. High accuracy and reliability of measurement: It can conduct tests in excellent waters around the world that are closest to the theoretical conditions of "still water" under the actual full-load operation of ships, which greatly reduces the interference of external factors such as wind, waves and currents, and reduces the errors caused by complex manual corrections, resulting in more direct and realistic results.

[0022] 4. Achieve true dynamic performance monitoring: It can be easily repeated monthly, quarterly or as needed to continuously track changes in ship speed performance caused by hull fouling, mechanical wear or maintenance, providing real-time and dynamic data support for ship energy efficiency management (CII rating), speed optimization and maintenance decisions. It is a key technology for realizing intelligent and green operation of ships. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the steps of a method for dynamically determining ship speed based on operational data in one embodiment of the present invention.

[0025] Figure 2This is a schematic diagram of the relationship between the left engine rotation speed and airspeed obtained through regression fitting in the experiment of this invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0027] In one embodiment, reference is made to Figure 1 As shown, a method for dynamically determining ship speed based on operational data is provided, including:

[0028] Step 1: Continuously collect status data and waterway environment data during ship operation through a cluster of sensors installed on the ship;

[0029] Step two involves triggering the measurement and filtering the data, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the ship's daily route; when the ship enters the electronic fence area and is fully loaded, triggering the speed measurement process, controlling the ship to sail at multiple different stable main engine speed points, and collecting the status data and waterway environment data during the stable navigation period.

[0030] Step 3 involves data analysis and modeling, including: cleaning the filtered data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed using a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel currents and a second parameter characterizing the ship's still water speed performance from the model; using the second parameter to construct a relationship model between the ship's still water speed and main engine speed, which serves as the speed measurement result.

[0031] Specifically, in step one, the sensor cluster includes at least: an electronic draft gauge for measuring the draft of a ship in six directions, a dual-frequency GPS speedometer for high-precision measurement of the ship's position and speed over land, a tachometer for measuring the engine speed, and a depth sounder for measuring the water depth of the waterway.

[0032] The continuous collection of ship operation status data and waterway environment data also includes:

[0033] Data is collected and temporarily stored at the highest frequency using shipboard data acquisition equipment;

[0034] Data is uploaded to the shore-based database via a data pass-through device at a second frequency lower than the first frequency.

[0035] In one embodiment, the first frequency is once every 2 seconds, the storage duration is greater than 1 month, and periodic rolling deletion is performed. The second frequency is once every 1 minute, and the data storage duration is greater than 5 years.

[0036] Furthermore, in step two, the water area that meets the preset still water conditions is a wide waterway area with gentle and stable water flow, including the lock reservoir area of ​​inland rivers, the lake area during the dry season, the calm navigation area of ​​seagoing vessels, or the calm ocean area in the open ocean.

[0037] In the course of ship operations, sections of the waterway whose depth, wind, and waves meet measurement standards are selected as measurement sections. Electronic fences are set up on the management platform to define the data for these areas, referencing a map. The selected areas should be wide waterways with gentle and stable currents, such as sections of inland rivers within lock reservoirs or lakes during the dry season; calm waters for ocean-going vessels; and calm ocean-going vessels in calm ocean areas (e.g., near the equator in the Pacific Ocean).

[0038] In one embodiment, the plurality of different stable host speed points include at least four speed points, which are speed points corresponding to 50%, 75%, 90%, and 100% of the host's rated power.

[0039] In one embodiment, the plurality of different stable main engine speed points are four or more speed points uniformly selected within the range of the lowest to the highest speed of the main engine; the stable sailing time of the ship at each speed point is not less than half an hour.

[0040] In step three, data analysis and modeling are performed, including:

[0041] Based on the ship's draft data when it was stationary, it was confirmed that the ship was fully loaded.

[0042] The data sets of main engine rotation speed and ground speed collected within the electronic fence area are cleaned according to water depth, and data exhibiting shallow water effects are removed; in accordance with the regulations of the International Shipping Association, the water depth-to-draft ratio is used. For critical values: It is deep water and does not produce a shallow water effect; To account for the shallow water effect, the water depth-to-draft ratio is excluded. The range of data; among which, Indicates water depth. It indicates the ship's draft, that is, the depth to which the ship's hull is submerged in water.

[0043] The first linear regression analysis was performed on the remaining data set after cleaning to obtain the first regression relationship. Since the collected data set was randomly collected at regular intervals during the continuous navigation of the ship, some of it was unstable operation data during the acceleration and deceleration process of the ship, and some was abnormal interference data during the steering process of the ship. The impact of the abnormal data set could bring more than 5% error to the speed measurement. The abnormal data set must be removed according to the first preset deviation threshold.

[0044] A second linear regression analysis is performed on the remaining data groups after removing outlier data groups to obtain a second regression relationship. Fluctuating data groups are further removed based on a second preset deviation threshold; the second preset deviation threshold is less than the first preset deviation threshold.

[0045] A third linear regression analysis was performed on the remaining data sets after removing the fluctuating data sets to obtain the final main engine speed. and ground speed Relational model:

[0046] ;

[0047] Where, constant The first parameter represents the average influence of channel current on navigation speed, and the coefficient is... The second parameter represents the speed coefficient;

[0048] Based on the aforementioned relational model, the ship's still water speed is obtained. With the main unit speed Relationship:

[0049] .

[0050] In one embodiment, the first preset deviation threshold can also be preset to a fixed percentage based on the ship's navigation experience. For example, the first preset deviation threshold can be set to 5%, and data groups with a residual relative value / error rate exceeding 5% can be identified as abnormal data groups and removed. This fixed threshold method is simple to calculate, easy to implement in engineering, and suitable for scenarios where the historical data distribution pattern is known and the navigation conditions are relatively stable.

[0051] In one embodiment, the first preset deviation threshold is determined using an adaptive outlier detection method: the residual sequence of the first regression relation is calculated, and the discrimination boundary is dynamically set based on the statistical characteristics of the residual distribution.

[0052] The adaptive outlier detection method specifically employs a strong outlier criterion based on box plots: calculating the first quartile of the residual sequence. With the third quartile Calculate the interquartile range The residual is less than or greater than The data set is identified as an anomaly and removed; when the residual sequence is non-normally distributed or has multimodal characteristics, the adaptive outlier detection method can more accurately identify real outliers than the fixed threshold method, avoiding misjudging normal fluctuations as anomalies.

[0053] In one embodiment, the second preset deviation threshold can also be a fixed percentage threshold. For example, the second preset deviation threshold is set to 5%, and data groups with a residual relative value / error rate exceeding 3% are identified as fluctuating data groups and removed. In this case, since the first data removal has removed large outliers, the fixed threshold of 3% is sufficient to identify the small fluctuations remaining in the second level, and it is convenient to implement uniformly across different ships and different routes.

[0054] In one embodiment, the second preset deviation threshold is dynamically set based on the standard deviation of the regression residuals: the standard deviation of the residuals of the second linear regression is calculated. The absolute value of the residual is greater than Data groups identified as fluctuating data groups are removed; if the number of remaining data groups after removal is less than 80% of the total number of original data groups, the threshold is automatically relaxed to [a higher threshold]. The process of eliminating samples is repeated until the quantity requirement is met; this adaptive adjustment mechanism can ensure data purity while preventing the regression model from becoming unstable due to insufficient sample size caused by excessive elimination.

[0055] Furthermore, this invention also verifies the effectiveness, convenience, and accuracy of the method through experiments, and compares it with the shortcomings of traditional methods. Specifically, a typical inland waterway operating vessel was selected for the verification experiment.

[0056] (1) Ship selection and experimental setup

[0057] Experimental vessel: A cargo ship operating between upstream and downstream ports on an inland waterway was selected. The ship is 86.48 meters long, 15.80 meters wide, 4.0 meters deep, has a full-load draft of 3.20 meters, and a full-load displacement of 3512 tons. It has two main engines with a rated speed of 1000 r / min and a daily operating speed range of 550-1000 r / min.

[0058] Experimental conditions: The ship was confirmed to be fully loaded, with a draft of 3.20 meters both forward and aft.

[0059] Measurement Area Selection: According to the method requirements of this invention, a water area meeting the preset still water conditions was selected as the measurement section. In the experiment, a deep-water section within an inland reservoir was chosen, where the water flow is gentle and stable. Confirmed by a shipborne depth sounder, the water depth in this section was greater than 60 meters, far exceeding the method requirements, making it an ideal measurement environment. An electronic fence was set so that the measurement process was automatically triggered when a vessel entered this area.

[0060] Traditional methods using existing technologies typically involve shipyards organizing specialized teams for speed measurements, incurring dedicated costs. Furthermore, shipyards are generally located near main shipping channels, making it difficult to find suitable measurement sites and time windows that meet standard requirements. If the density of vessels operating in the main channel is high, it's difficult to find a sufficiently long open area to perform small rudder angle turns and smooth acceleration maneuvers. Because channel divisions require separate lanes for upstream and downstream vessels, it's difficult to ensure that round-trip speed measurements are conducted on the same channel, and it's also difficult to guarantee that speed measurements at 50%, 75%, 90%, and 100% main engine power are performed on the same route, making data quality unreliable. This method is costly, inconvenient to implement, and involves complex data correction. It is generally only used for verifying design specifications on new ships or after major overhauls, conducted under no-load or ballast conditions, and used for life after a single measurement. Once a ship is put into operation, its speed is no longer measured, making it impossible to track changes in ship speed and reflect changes in the ship's technical condition.

[0061] The method of this invention is carried out entirely during the daily full-load operation of the vessel, without the need for special voyages, professional teams to board the ship, or occupying the main channel for testing. It automatically collects data using shipboard sensors, and only when the vessel passes through a preset electronic fence (deep-water section of the reservoir area) does it achieve stable operation of the vessel in different pre-selected power ranges for a period of time by changing the main engine speed, and then automatically analyzes and processes the data through an algorithm.

[0062] (2) Data acquisition and trigger measurement

[0063] Once a fully loaded vessel enters the electronic fence of the deep-water section of the aforementioned reservoir area, the speed measurement process is automatically triggered. The operator is instructed to control the vessel's main engine within its operating speed range, navigating at multiple stable RPM points (this experiment collected continuous data from approximately 550 r / min to 960 r / min). After navigating stably for a sufficient time at each RPM point, ground speed and main engine RPM data are simultaneously collected via a sensor cluster (dual-frequency GPS speedometer, main engine RPM meter, etc.). An example of a set of raw data is shown in Table 1.

[0064] Table 1. Example of a set of raw data on ground speed and main engine speed collected in the experiment.

[0065]

[0066] (3) Conduct data analysis and modeling based on the three-step regression analysis algorithm.

[0067] Step 1: Modeling and removing gross errors in the initial regression analysis, including: performing linear regression analysis on the left main engine speed and ground speed in all the original data.

[0068] By performing a linear regression on the relationship between the main engine speed and the ship's speed, the following formula was obtained: Decision coefficient The relationship between the engine speed and the ship's speed is as follows: Decision coefficient The difference between the left and right sides is minimal, so either one can be selected for analysis.

[0069] The following example, using the left host, yields the initial relational model: Decision coefficient ; Calculate the error rate between the theoretical speed and the measured speed at each point. Examples of the calculation results are shown in Table 2. Based on the first preset deviation threshold (e.g.) Remove data groups with an error rate exceeding this range (e.g., data with an error rate exceeding this range in the table). , , (equal points).

[0070] Table 2. Example of data showing the error rate between theoretical and measured speeds at various points.

[0071]

[0072] The second step involves performing quadratic regression analysis and modeling, as well as removing random fluctuations. This includes performing a second linear regression on the remaining data sets to obtain a new model (left host). , Using this model, the error rate between the theoretical and measured speeds of the remaining data for the left main engine was recalculated. Data examples are shown in Table 3, and a more stringent second preset deviation threshold (e.g.) was applied. Further, data groups with large fluctuations were removed, and examples of data groups after removing random fluctuations are shown in Table 4.

[0073] Table 3. Examples of error rates between theoretical and measured speeds for the remaining data.

[0074]

[0075] Table 4 Examples of data sets after removing random fluctuations

[0076]

[0077] The third step involves performing final (third) regression analysis modeling and static performance separation, including a third linear regression on the remaining high-quality data set to obtain the final relational model of the left host: Decision coefficient A value as high as 0.9872 indicates an excellent model fit. The specific model fitting curve for the relationship between the left (main) engine speed and airspeed is shown below. Figure 2 As shown.

[0078] According to the ship speed dynamic measurement method based on operational data provided by the present invention, the constant term in the final regression analysis model of the left engine... The first parameter, representing the average impact of water flow on ship speed within the measured section (approximately 1.19 km / h of boost or drag), is the linear coefficient. This is the second parameter, characterizing the ship's still-water speed performance. Therefore, the separated still-water speed of the ship ( ) and main engine speed ( The relationship model (speed measurement results) is as follows: .

[0079] Similarly, the constant term in the final regression analysis model of the right host can be obtained. linear coefficients Decision coefficient .

[0080] (4) Analysis of experimental results

[0081] This experiment successfully completed the dynamic measurement of ship speed during daily operations. The aforementioned experiment demonstrates that the ship speed dynamic measurement method based on operational data provided by this invention can automatically complete the measurement without interrupting operations or requiring a dedicated team, utilizing existing sensors and algorithms. It significantly lowers the measurement threshold by selecting natural still water areas such as reservoirs and triggering the measurement using electronic fences, avoiding the dependence on absolutely calm weather and dedicated test sites required by traditional methods. Based on real-world data from full-load operations, it intelligently eliminates abnormal and fluctuating data through a three-iteration regression algorithm, resulting in a high R² value for the final model. Furthermore, it eliminates the need for complex artificial environmental corrections, directly reflecting the ship's true performance under current conditions. The provided dynamic monitoring can be repeated at any time on suitable sections of the ship's daily route, continuously tracking changes in ship speed performance due to hull fouling and mechanical changes, providing real-time and accurate data support for ship energy efficiency management and low-carbon operations. Compared to traditional speed measurement methods, this invention overcomes their main drawbacks, such as high cost, inconvenient implementation, difficulty in accuracy verification, and inability to dynamically update, providing an efficient and feasible solution for large-scale, routine measurement of operational ship speed performance.

[0082] In another embodiment of the present invention, a device for dynamically measuring ship speed based on operational data is provided. The device utilizes the steps of the aforementioned method to dynamically measure ship speed based on operational data. The device includes:

[0083] The first module is used to continuously collect status data and waterway environment data during the ship's operation through a cluster of sensors installed on the ship;

[0084] The second module is used for measurement triggering and data filtering, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the daily route of the ship; when the ship enters the electronic fence area and is fully loaded, the speed measurement process is triggered, the ship is controlled to sail at multiple different stable main engine speed points, and the state data and waterway environment data during stable navigation are collected.

[0085] The third module is used for data analysis and modeling, including: cleaning the screened data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed through a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel current and a second parameter characterizing the ship's still water speed performance from the model, and using the second parameter to construct a relationship model between the ship's still water speed and main engine speed as the speed measurement result.

[0086] Furthermore, the third module includes:

[0087] Submodule 1 is used to confirm that the ship is fully loaded based on the ship's draft data when it is stationary.

[0088] Submodule two is used to clean the data sets of host rotation speed and ground speed collected within the electronic fence area according to water depth, removing data that exhibits a shallow water effect; the data exhibiting a shallow water effect refers to the water depth-to-draft ratio. Data;

[0089] Submodule 3 is used to perform the first linear regression analysis on the remaining data group after cleaning, obtain the first regression relationship, and remove abnormal data groups according to the first preset deviation threshold.

[0090] Submodule four is used to perform a second linear regression analysis on the remaining data groups after removing abnormal data groups to obtain a second regression relationship, and further remove fluctuating data groups based on a second preset deviation threshold; the second preset deviation threshold is less than the first preset deviation threshold.

[0091] Submodule five is used to perform a third linear regression analysis on the remaining data sets after removing the fluctuating data sets, to obtain the final host engine speed. and ground speed Relational model:

[0092] ;

[0093] Where, constant The first parameter represents the average influence of channel current on navigation speed, and the coefficient is... The second parameter represents the speed coefficient;

[0094] Submodule five is used to obtain the ship's still water speed based on the aforementioned relational model. With the main unit speed Relationship:

[0095] .

[0096] In summary, the beneficial effects achieved by this invention through the design of a method and apparatus for dynamic measurement of ship speed based on operational data are as follows:

[0097] 1. Providing low cost and high accessibility, the dynamic speed measurement method for ships provided by this invention eliminates the need for dedicated test voyages, professional teams, and occupation of main channels. It can be completed using existing operating voyages, making regular speed measurement of all in-service ships an economically feasible and routine practice.

[0098] 2. The method of the present invention is convenient to implement and does not interfere with operations. The test can be flexibly carried out at the most ideal time and place in the global route network, and can be fully integrated into the normal flight plan without additional detours or waiting for the window period, and has no impact on shipping efficiency.

[0099] 3. High accuracy and reliability of measurement: It can conduct tests in excellent waters around the world that are closest to the theoretical conditions of "still water" under the actual full-load operation of ships, which greatly reduces the interference of external factors such as wind, waves and currents, and reduces the errors caused by complex manual corrections, resulting in more direct and realistic results.

[0100] 4. Achieve true dynamic performance monitoring: It can be easily repeated monthly, quarterly or as needed to continuously track changes in ship speed performance caused by hull fouling, mechanical wear or maintenance, providing real-time and dynamic data support for ship energy efficiency management (CII rating), speed optimization and maintenance decisions. It is a key technology for realizing intelligent and green operation of ships.

[0101] In one embodiment, the present invention provides a computer device, which may be a server, comprising a processor, a memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores dynamic ship speed measurement data based on operational data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the dynamic ship speed measurement method based on operational data.

[0102] Those skilled in the art will understand that the description of the device technical features in the above embodiments does not constitute a limitation on all devices to which the present invention is applied. Specific devices may include more or fewer components, or combinations of certain components, or different component arrangements.

[0103] In another embodiment, a storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the aforementioned method for dynamically determining ship speed based on operational data.

[0104] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0105] Matters not covered in this invention are common knowledge.

[0106] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for dynamically determining ship speed based on operational data, characterized in that, include: Step 1: Continuously collect status data and waterway environment data during ship operation through a cluster of sensors installed on the ship; Step two involves triggering the measurement and filtering the data, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the ship's daily route; when the ship enters the electronic fence area and is fully loaded, triggering the speed measurement process, controlling the ship to sail at multiple different stable main engine speed points, and collecting the status data and waterway environment data during the stable navigation period. Step 3 involves data analysis and modeling, including: cleaning the filtered data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed using a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel currents and a second parameter characterizing the ship's still water speed performance from the model; using the second parameter to construct a relationship model between the ship's still water speed and main engine speed, which serves as the speed measurement result.

2. The method for dynamic determination of ship speed based on operational data according to claim 1, characterized in that, The sensor cluster includes at least: an electronic draft gauge for measuring the draft of a ship in six directions, a dual-frequency GPS speedometer for high-precision measurement of the ship's position and speed over land, a tachometer for measuring the engine speed, and a depth sounder for measuring the depth of the waterway.

3. The method for dynamic determination of ship speed based on operational data according to claim 2, characterized in that, Step one, the continuous collection of ship operation status data and waterway environment data, also includes: Data is collected and temporarily stored at the highest frequency using shipboard data acquisition equipment; Data is uploaded to the shore-based database via a data pass-through device at a second frequency lower than the first frequency.

4. The method for dynamic determination of ship speed based on operational data according to claim 3, characterized in that, The water area that meets the preset still water conditions is a wide waterway area with gentle and stable water flow, including the lock reservoir area of ​​inland rivers, the lake area during the dry season, the calm navigation area for seagoing ships, or the calm ocean area in the open ocean.

5. The method for dynamic determination of ship speed based on operational data according to claim 1, characterized in that, The plurality of different stable host speed points include at least four speed points, which are speed points corresponding to 50%, 75%, 90%, and 100% of the host's rated power.

6. The method for dynamic determination of ship speed based on operational data according to claim 1, characterized in that, The multiple different stable main engine speed points are four or more speed points evenly selected within the range of the lowest to the highest speed of the main engine; the stable sailing time of the ship at each speed point is not less than half an hour.

7. The method for dynamic determination of ship speed based on operational data according to claim 1, characterized in that, Step three includes: Based on the ship's draft data when it was stationary, it was confirmed that the ship was fully loaded. The data sets of host rotation speed and ground speed collected within the electronic fence area are cleaned according to water depth, and data exhibiting shallow water effect are removed; the data exhibiting shallow water effect refers to the water depth-to-draft ratio. Data within a range; The remaining data sets after cleaning are subjected to the first linear regression analysis to obtain the first regression relationship, and abnormal data sets are removed according to the first preset deviation threshold. A second linear regression analysis is performed on the remaining data groups after removing outlier data groups to obtain a second regression relationship. Fluctuating data groups are further removed based on a second preset deviation threshold; the second preset deviation threshold is less than the first preset deviation threshold. A third linear regression analysis was performed on the remaining data sets after removing the fluctuating data sets to obtain the final main engine speed. and ground speed Relational model: ； Where, constant The first parameter represents the average influence of channel current on navigation speed, and the coefficient is... The second parameter represents the speed coefficient; Based on the aforementioned relational model, the ship's still water speed is obtained. With the main unit speed Relationship: 。 8. The method for dynamic determination of ship speed based on operational data according to claim 7, characterized in that, The first preset deviation threshold is set as a fixed percentage or determined using an adaptive outlier detection method; the second preset deviation threshold is set as a fixed percentage threshold or dynamically based on the standard deviation of the regression residuals.

9. A device for dynamically measuring ship speed based on operational data, characterized in that, include: The first module is used to continuously collect status data and waterway environment data during the ship's operation through a cluster of sensors installed on the ship; The second module is used for measurement triggering and data filtering, including: selecting a water area that meets the preset still water conditions as the measurement segment and setting an electronic fence area in the daily route of the ship; when the ship enters the electronic fence area and is fully loaded, the speed measurement process is triggered, the ship is controlled to sail at multiple different stable main engine speed points, and the state data and waterway environment data during stable navigation are collected. The third module is used for data analysis and modeling, including: cleaning the screened data and removing data with shallow water effects; based on the cleaned data, establishing a linear relationship model between main engine speed and ground speed through a three-step iterative regression analysis algorithm, and separating a first parameter characterizing the influence of channel current and a second parameter characterizing the ship's still water speed performance from the model, and using the second parameter to construct a relationship model between the ship's still water speed and main engine speed as the speed measurement result.

10. The apparatus according to claim 9, characterized in that, The third module includes: Submodule 1 is used to confirm that the ship is fully loaded based on the ship's draft data when it is stationary. Submodule two is used to clean the data sets of host rotation speed and ground speed collected within the electronic fence area according to water depth, removing data that exhibits a shallow water effect; the data exhibiting a shallow water effect refers to the water depth-to-draft ratio. Data; Submodule 3 is used to perform the first linear regression analysis on the remaining data group after cleaning, obtain the first regression relationship, and remove abnormal data groups according to the first preset deviation threshold. Submodule four is used to perform a second linear regression analysis on the remaining data groups after removing abnormal data groups to obtain a second regression relationship, and further remove fluctuating data groups based on a second preset deviation threshold; the second preset deviation threshold is less than the first preset deviation threshold. Submodule five is used to perform a third linear regression analysis on the remaining data sets after removing the fluctuating data sets, to obtain the final host engine speed. and ground speed Relational model: ； Where, constant The first parameter represents the average influence of channel current on navigation speed, and the coefficient is... The second parameter represents the speed coefficient; Submodule six is ​​used to obtain the ship's still water speed based on the aforementioned relational model. With the main unit speed Relationship: 。

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