Ship bearing pre-judging system based on image recognition

Abstract

The invention discloses a ship bearing pre-judgment system based on image recognition, belongs to the technical field of image recognition, and solves the problem that a result obtained when the distance between a water surface and a waterline is recognized by an image is inaccurate due to the fact that the water surface has wave fluctuation and a ship also fluctuates. Comprising a plurality of wave-following image acquisition modules, an empty ship signal acquisition module and a data processing module which are arranged on a ship body, the plurality of wave-following image acquisition modules are uniformly arranged at intervals, and the wave-following image acquisition modules continuously acquire contact pictures of the ship body and the water surface and feed back the contact pictures to the data processing module; the empty ship signal acquisition module comprises ship ends and an empty end which are in communication connection, the number of the ship ends is the same as that of the wave-associated image acquisition modules, and the empty end can be horizontally arranged in a suspended mode. The method provides reference for stable load of the ship in waves, evaluates inclination, ensures reasonable distribution of cargoes, and avoids inaccurate image recognition caused by a water environment.

Description

Technical Field

[0001] The present invention relates to the technical field of image recognition, and in particular to a ship load prediction system based on image recognition. Background Art

[0002] Ships, as a form of water transportation, have played a vital role in the development of human civilization since ancient times. They are primarily used for the transport of goods and people, but they also serve a variety of purposes, including military, scientific research, and recreation. Modern ships come in a wide variety of types, including cargo ships, passenger ships, oil tankers, container ships, and warships. They vary in size, shape, and function, but all share the fundamental ability to navigate the water. With technological advancements, ship designs are becoming increasingly sophisticated, enabling faster speeds, greater payloads, and a lower environmental impact.

[0003] For ships, overload detection is a crucial component in ensuring maritime safety. It utilizes advanced technologies to monitor and assess whether a vessel has exceeded its approved load line. This detection typically incorporates technologies such as laser scanning, video analysis, and image recognition to accurately measure the vessel's actual load. These technologies automatically monitor a vessel's freeboard height and draft, intelligently determining whether it is overloaded or exceeding its draft, thereby effectively preventing safety incidents caused by overloading. Furthermore, a ship overload detection method based on video analysis uses a pan-tilt camera at the dockside to capture video and image information of the vessel. This information is then analyzed and processed by a video analysis server and compared against safety management regulations to determine whether the vessel is overloaded. This detection method not only improves efficiency but also reduces human interference, ensuring accuracy and reliability.

[0004] The current ship overload detection technology, such as the ship overload determination method and device based on image recognition with application number CN202410636646.2, has the following technical points: input the visible light image of the target ship to be identified into the first ship prediction model, obtain the first recognition result output by the first ship prediction model, input the infrared image of the target ship to be identified into the second ship prediction model, obtain the second recognition result output by the second ship prediction model; determine the ship model of the target ship according to the first recognition result and the second recognition result; input the visible light image to be identified into the preset segmentation model, obtain the segmented image output by the preset segmentation model, and determine the actual waterline from the segmented area of ​​the ship and the water surface in the segmented image; and determine the actual waterline from the preset ship model and the preset overload The target overload waterline of the ship model is determined in the corresponding relationship of the waterline. When the actual waterline is higher than the target overload waterline, the target ship is determined to be overloaded; the first ship prediction model is determined after training based on all visible light image samples and the probability of the ship model corresponding to each visible light image sample, and the second ship prediction model is determined after training based on all infrared image samples and the probability of the ship model corresponding to each infrared image sample. The preset segmentation model is determined after training based on all infrared image samples and the segmented surface part of the ship and the segmented underwater part of the ship corresponding to each infrared image sample. The segmented surface part of the ship and the segmented underwater part of the ship are distinguished according to the different temperatures of the surface part of the ship and the underwater part of the ship.

[0005] The above scheme can combine the image recognition model to recognize visible light images and infrared images, and combine the image segmentation model to recognize infrared images, thereby improving the applicability and accuracy of ship overload judgment, mainly to eliminate the influence of ambient light on image recognition. However, when a ship is parked in the water, the water surface does not always remain stable. Under the influence of weather, large waves may appear on the water surface, causing the ship to fluctuate up and down when parked in the water. In this way, not only the water surface has waves, but the ship itself also fluctuates, which causes the image to identify the distance between the water surface and the waterline. The result is not accurate.

[0006] Therefore, a ship load prediction system based on image recognition is proposed to solve or alleviate the above problems. Summary of the Invention

[0007] The purpose of the present invention is to solve the shortcomings of the existing technology and propose a ship load prediction system based on image recognition.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A ship load prediction system based on image recognition includes a wave-following image acquisition module, an empty ship signal acquisition module, and a data processing module, which are arranged on the hull. The number of the wave-following image acquisition modules is several and the plurality of the wave-following image acquisition modules are evenly spaced. The wave-following image acquisition module continuously acquires contact images between the hull and the water surface and feeds them back to the data processing module. The empty ship signal acquisition module includes a ship end and an empty end in communication connection. The number of the ship ends is the same as the number of the wave-following image acquisition modules, and the empty ends can be suspended horizontally. The empty end receives the ship end signal and outputs the vertical displacement of each ship end to the data processing module. The data processing module identifies the hull's waterline, inclination, and load based on the contact images and the vertical displacement of each ship end.

[0010] Preferably, the wave-based image acquisition module includes a camera.

[0011] Preferably, the wave-following image acquisition module continuously acquires the contact image between the hull and the water surface and feeds it back to the data processing module, including the following steps:

[0012] A number of evenly spaced points are set on the hull according to the number of wave-following image acquisition modules;

[0013] Install a single wave-following image acquisition module at the point;

[0014] The wave-following image acquisition module continuously collects the contact images between the hull and the water surface on the time axis and feeds them back to the data processing module.

[0015] Preferably, the ship end includes an infrared transmitter, the air end includes a drone, the number of the drones is at least three, the drone includes a microprocessor, an infrared receiver coupled to the microprocessor, and a wireless communication module coupled to the microprocessor, the drone is communicatively connected to the data processing module via the wireless communication module, and the drones are also communicatively connected to each other via the wireless communication module.

[0016] Preferably, the air end receives the ship end signal and outputs each ship end vertical displacement to the data processing module, including the following steps:

[0017] The drones fly above the ship and keep all drones at the same level;

[0018] Each drone D j (j=1,2,…,m) receives the ship end P i (i=1,2,…,n) distance information to the horizontal plane, and each drone D j The distance information between them is calculated by the Pythagorean theorem to obtain the vertical displacement z of each ship end on the time axis. i (t) is the vertical displacement of each point on the time axis.

[0019] Preferably, the data processing module includes a processor.

[0020] Preferably, the data processing module identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, including the following steps:

[0021] The contact images on the time axis are pre-processed by Gaussian filtering;

[0022] The edge detection algorithm is used to identify the boundary between the water surface and the hull on the contact image on the time axis;

[0023] The boundary between the water surface and the hull in the contact image on the time axis is normalized and the spectrum analysis is completed through Fourier transform to determine the amplitude and frequency of the water surface waves at each point;

[0024] Set the water surface wave to be a sine wave, h i (t) = A i sin(ω i t+φ i ), where h i (t) is the water surface height at the i-th point at time t, A i is the amplitude of the water surface fluctuation at the i-th point, ω i is the angular frequency of the water surface wave, ω i =2πf i , where fi is the surface wave frequency at the i-th point, φ i is the phase of the water surface wave;

[0025] The output result is the change of water surface height at each point on the time axis {h1(t), h2(t), ..., h n (t)}.

[0026] Preferably, the output result is the change of water surface height {h1(t), h2(t), ..., h n (t)}, including the following steps,

[0027] Calculating spatial wave synchronization and phase difference Where λ is the wavelength and Δx is the distance between two bits;

[0028] The water surface height change h at different positions is obtained through the spatial phase difference i (t) = A i sin(2πf i t+φ i +Δφ i ), where Δφ i is the phase change caused by the difference in spatial position;

[0029] The output result is the change of water surface height at each point on the time axis {h1(t), h2(t), ..., h n (t)}.

[0030] Preferably, the data processing module identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, and further includes the following steps:

[0031] Enter the water surface height change h at different positions on the time axis i (t) and the vertical displacement z of each point on the time axis i (t), calculate the waterline depth D at each point on the time axis by the difference between the two i (t).

[0032] Preferably, the data processing module identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, and further includes the following steps:

[0033] Enter the waterline depth D at each point on the time axis i (t), and calculate the average waterline depth at each point

[0034] Establish spatial coordinates, place the ship in the spatial coordinates, confirm the coordinates of each point in the spatial coordinates, and mark the average waterline of each point in the spatial coordinates based on the coordinates of each point and the average waterline depth of each point, and then connect them;

[0035] Calculate the volume of the ship below the average waterline at each point after the line is connected as the displacement;

[0036] The water weight is calculated from the displacement according to the density formula, and the deadweight is obtained from the difference between the water weight and the deadweight of the ship;

[0037] Calculate the average height of the waterline at all points

[0038] Calculate the standard deviation of the waterline

[0039] A standard threshold is set and the standard deviation of the waterline is compared with the standard threshold. If the standard deviation of the waterline is greater than the standard threshold, it is considered that the ship is tilted, otherwise it is considered that the ship is not tilted.

[0040] The present invention has the following beneficial effects:

[0041] The present invention can provide a certain reference for when a ship encounters wave fluctuations in the water, or when the ship sinks and floats in the water due to wave fluctuations, resulting in image recognition being unable to accurately obtain parameters such as the hull waterline to calculate the ship's load. The present invention can also assess whether the ship is tilted, and serve as an effective reference for the reasonable distribution of cargo weight on the ship, thereby avoiding the situation where the result obtained when the image recognizes the distance between the water surface and the waterline is inaccurate due to the water environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 It is a structural block diagram of the present invention.

[0044] 1. Wave-based image acquisition module; 2. Empty ship signal acquisition module; 3. Data processing module. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0046] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0047] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0048] In the description of the present invention, it should be understood that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, or are the orientation or position relationship in which the product of the invention is usually placed when in use, or are the orientation or position relationship commonly understood by those skilled in the art. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0049] Furthermore, the terms “first,” “second,” “third,” etc., are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0050] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0051] A ship load prediction system based on image recognition, such as Figure 1 As shown, it includes a wave-following image acquisition module 1, an empty ship signal acquisition module 2, and a data processing module 3 arranged on the hull. The number of the wave-following image acquisition modules 1 is several, and the several wave-following image acquisition modules 1 are evenly spaced. The wave-following image acquisition modules 1 continuously acquire the contact image between the hull and the water surface and feed it back to the data processing module 3. The empty ship signal acquisition module 2 includes a ship end and an air end that are communicatively connected. The number of the ship ends is the same as the number of the wave-following image acquisition modules 1, and the air end can be suspended horizontally. The air end receives the ship end signal and outputs the vertical displacement of each ship end to the data processing module 3. The data processing module 3 identifies the hull waterline, tilt, and load based on the contact image and the vertical displacement of each ship end. Among them, the wave-following image acquisition module 1 includes a camera, the ship end includes an infrared transmitter, and the air end includes a drone. The number of drones is at least three. The drone includes a microprocessor, an infrared receiver coupled to the microprocessor, and a wireless communication module coupled to the microprocessor. The drone is communicatively connected to the data processing module 3 via the wireless communication module, and the drones are also communicatively connected to each other via the wireless communication module. The wireless communication module includes WI FI module, data processing module 3 includes a processor.

[0052] The present invention aims to solve the problem that when a ship encounters waves while parked in the water, the ups and downs caused by the waves make it difficult for image recognition technology to accurately capture the waterline of the ship, thereby affecting the calculation of the ship's load. The present invention provides a new solution. By using a drone to establish a plane to measure the vertical displacement of the ship, it helps to confirm the changes in the interface between the ship and the water surface waves, thereby evaluating the waterline of the ship, and on this basis, judging whether tilting occurs and evaluating the load of the ship at this time, which is crucial for the reasonable distribution of the weight of the cargo on board. Through the application of the present invention, image recognition errors caused by water environment factors can be effectively avoided, ensuring the accuracy of the ship's load calculation.

[0053] Preferably, the wave image acquisition module 1 continuously acquires the contact image between the hull and the water surface and feeds it back to the data processing module 3, including the following steps:

[0054] A number of evenly spaced points are set on the hull according to the number of wave-following image acquisition modules 1;

[0055] A single wave-following image acquisition module 1 is installed at the point;

[0056] The wave-following image acquisition module 1 continuously acquires the contact images between the hull and the water surface on the time axis and feeds them back to the data processing module 3 .

[0057] Through the above method steps, multiple points can be set on the hull to provide data, so that the points can be split into multiple points when the vertical displacement of the ship is subsequently calculated. If the vertical displacement of the entire ship is required, it can be estimated based on the data of multiple points to ensure the accuracy of the final data. If it is necessary to evaluate whether the hull is tilted, it can also be compared by splitting multiple points to determine the direction of the hull tilt. In the case of load calculation, the hull can be divided according to the waterline of multiple points to obtain the volume of the hull under the water surface, so as to calculate a more accurate displacement. Even if the hull has tilted, more accurate data results can still be obtained.

[0058] Preferably, the air end receives the ship end signal and outputs each ship end vertical displacement to the data processing module 3, including the following steps:

[0059] The drones fly above the ship and keep all drones at the same level;

[0060] Each drone D j (j=1, 2, ..., m) receives the ship end P i (i=1,2,…,n) distance information to the horizontal plane, and each drone D j The distance information between them is calculated by the Pythagorean theorem to obtain the vertical displacement z of each ship end on the time axis. i(t) is the vertical displacement of each point on the time axis.

[0061] By maintaining the same horizontal plane with multiple drones, the horizontal plane formed by them can provide a plane reference for the ship to obtain the vertical displacement of the ship, ensuring that the ship can obtain its vertical displacement data even when there is no land or other reference around it.

[0062] Preferably, the data processing module 3 identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, including the following steps:

[0063] The contact images on the time axis are pre-processed by Gaussian filtering;

[0064] The edge detection algorithm is used to identify the boundary between the water surface and the hull on the contact image on the time axis;

[0065] The boundary between the water surface and the hull in the contact image on the time axis is normalized and the spectrum analysis is completed through Fourier transform to determine the amplitude and frequency of the water surface waves at each point;

[0066] Set the water surface wave to be a sine wave, h i (t) = A i sin(ω i t+φ i ), where h i (t) is the water surface height at the i-th point at time t, A i is the amplitude of the water surface fluctuation at the i-th point, ω i is the angular frequency of the water surface wave, ω i =2πf i , where f i is the surface wave frequency at the i-th point, φ i is the phase of the water surface wave;

[0067] The output result is the change of water surface height at each point on the time axis {h1(t), h2(t), ..., h n (t)}.

[0068] The output result is the change of water surface height at each point on the time axis {h1(t), h2(t), ..., h n (t)}, including the following steps,

[0069] Calculating spatial wave synchronization and phase difference Where λ is the wavelength and Δx is the distance between two positions. Assuming that different points on the hull have the same surface wave frequency, the surface waves are synchronized but have different initial phases φi. The phase difference Δφ between different points is related to the spatial distance Δx between them.

[0070] The synchronization of water surface waves at different points is calculated by the spatial phase difference to obtain the water surface height change h at different positions. i (t) = A i sin(2πf i t+φ i +Δφ i ), where Δφ i is the phase change caused by the difference in spatial position;

[0071] The output result is the change of water surface height at each point on the time axis {h1(t), h2(t), ..., h n (t)}.

[0072] Through the above steps and methods, the system can obtain more accurate changes in water surface height, taking into account the impact of surface waves, and then ensure the accuracy of the final data.

[0073] Preferably, the data processing module 3 identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, and further includes the following steps:

[0074] Enter the water surface height change h at different positions on the time axis i (t) and the vertical displacement z of each point on the time axis i (t), calculate the waterline depth D at each point on the time axis by the difference between the two i (t).

[0075] The data processing module 3 identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, and also includes the following steps:

[0076] Enter the waterline depth D at each point on the time axis i (t), and calculate the average waterline depth at each point

[0077] Establish spatial coordinates, place the ship in the spatial coordinates, confirm the coordinates of each point in the spatial coordinates, and mark the average waterline of each point in the spatial coordinates based on the coordinates of each point and the average waterline depth of each point, and then connect them;

[0078] Calculate the volume of the ship below the average waterline at each point after the line is connected as the displacement;

[0079] The water weight is calculated from the displacement according to the density formula, and the deadweight is obtained from the difference between the water weight and the deadweight of the ship;

[0080] Calculate the average height of the waterline at all points

[0081] Calculate the standard deviation of the waterline

[0082] A standard threshold is set and the standard deviation of the waterline is compared with the standard threshold. If the standard deviation of the waterline is greater than the standard threshold, it is considered that the ship is tilted, otherwise it is considered that the ship is not tilted.

[0083] Through the above steps and methods, the system can identify the waterline of the ship, assist in calculating the ship's load, and evaluate the ship's tilt condition, guiding the reasonable distribution of cargo and ensuring navigation safety.

[0084] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A ship load prediction system based on image recognition, characterized in that: The invention comprises a wave-following image acquisition module (1), an empty ship signal acquisition module (2), and a data processing module (3) arranged on the hull. The number of the wave-following image acquisition modules (1) is several, and the several wave-following image acquisition modules (1) are evenly spaced. The wave-following image acquisition module (1) continuously acquires the contact picture between the hull and the water surface and feeds back to the data processing module (3). The empty ship signal acquisition module (2) comprises a ship end and an empty end connected in communication. The number of the ship ends is the same as the number of the wave-following image acquisition modules (1), and the empty end can be suspended and horizontally arranged. The empty end receives the ship end signal and outputs the vertical displacement of each ship end to the data processing module (3). The data processing module (3) identifies the hull waterline, tilt, and load according to the contact picture and the vertical displacement of each ship end.

2. A ship load prediction system based on image recognition according to claim 1, characterized in that: The wave-based image acquisition module (1) comprises a camera.

3. The ship load prediction system based on image recognition according to claim 1 is characterized in that: The wave-following image acquisition module (1) continuously acquires the contact image between the hull and the water surface and feeds it back to the data processing module (3), comprising the following steps: A plurality of evenly spaced points are set on the hull according to the number of wave-following image acquisition modules (1); Installing a single wave-based image acquisition module (1) at a point; The wave-following image acquisition module (1) continuously acquires the contact images between the ship body and the water surface on the time axis and feeds back the images to the data processing module (3).

4. A ship load prediction system based on image recognition according to claim 3, characterized in that: The ship end includes an infrared transmitter, and the air end includes a drone, the number of which is at least three. The drone includes a microprocessor, an infrared receiver coupled to the microprocessor, and a wireless communication module coupled to the microprocessor. The drone is connected to the data processing module (3) through the wireless communication module, and the drones are also connected to each other through the wireless communication module.

5. A ship load prediction system based on image recognition according to claim 4, characterized in that: The air end receives the ship end signal and outputs the vertical displacement of each ship end to the data processing module (3), including the following steps: The drones fly above the hull and keep all drones at the same level; Each drone D j (j=1,2,…,m) receives the ship end P i (i=1,2,…,n) distance information to the horizontal plane, and the distance information of each drone D j The distance information between them is calculated by the Pythagorean theorem to obtain the vertical displacement z of each ship end on the time axis. i (t) is the vertical displacement of each point on the time axis.

6. The ship load prediction system based on image recognition according to claim 1, characterized in that: The data processing module (3) comprises a processor.

7. The ship load prediction system based on image recognition according to claim 5, characterized in that: The data processing module (3) identifies the waterline, tilt, and load of the ship according to the contact image and the vertical displacement of each ship end, including the following steps: The contact images on the time axis are preprocessed by Gaussian filtering; The edge detection algorithm is used to identify the boundary between the water surface and the hull on the contact screen on the time axis; The boundary line between the water surface and the hull in the contact image on the time axis is normalized and the spectrum analysis is completed through Fourier transform to determine the amplitude and frequency of the water surface waves at each point; Set the water surface wave to a sine wave, h i (t) = A i sin(ω i t+φ i ), where h i (t) is the water surface height at the i-th point at time t, A i is the amplitude of the water surface fluctuation at the i-th point, ω i is the angular frequency of the water surface wave, ω i =2πf i , where f i is the surface wave frequency at the i-th point, φ i is the phase of the water surface wave; The output result is the change of water surface height at each point on the time axis {h1(t),h2(t),…,h n (t)}.

8. The ship load prediction system based on image recognition according to claim 7 is characterized in that: The output result is the change of water surface height at each point on the time axis {h1(t),h2(t),…,h n (t)}, comprising the following steps, Calculating spatial wave synchronization and phase difference Among them, λ is the wavelength, Δx is the distance between two bits; Through the spatial phase difference, the water surface height change h at different positions is obtained i (t) = A i sin(2πf i t+φ i +Δφ i ), where Δφ i is the phase change caused by the difference in spatial position; The output result is the change of water surface height at each point on the time axis {h1(t),h2(t),…,h n (t)}.

9. A ship load prediction system based on image recognition according to claim 7 or 8, characterized in that: The data processing module (3) identifies the waterline, tilt and load of the ship according to the contact image and the vertical displacement of each ship end, and also includes the following steps: Enter the change in water surface height h at different positions on the time axis i (t) and the vertical displacement z of each point on the time axis i (t), and the waterline depth D at each point on the time axis is calculated by the difference between the two. i (t).

10. A ship load prediction system based on image recognition according to claim 9, characterized in that: The data processing module (3) identifies the waterline, tilt and load of the ship according to the contact image and the vertical displacement of each ship end, and also includes the following steps: Enter the waterline depth D at each point on the time axis i (t), and calculate the average waterline depth at each point Establish spatial coordinates, place the ship in the spatial coordinates, confirm the coordinates of each point in the spatial coordinates, and mark the average waterline of each point in the spatial coordinates based on the coordinates of each point and the average waterline depth of each point, and then connect them; Calculate the volume of the ship below the average waterline at each point after the line is connected as the displacement; The water weight is calculated from the displacement according to the density formula, and the load is obtained from the difference between the water weight and the ship's deadweight; Calculate the average height of the waterline at all points Calculate the standard deviation of the waterline A standard threshold is set, and the standard deviation of the waterline is compared with the standard threshold. If the standard deviation of the waterline is greater than the standard threshold, it is considered that the ship is tilted, otherwise it is considered that the ship is not tilted.

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