CN117557928A - Unmanned aerial vehicle-based ship water gauge intelligent measurement system and method - Google Patents
Unmanned aerial vehicle-based ship water gauge intelligent measurement system and method Download PDFInfo
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Abstract
Unmanned aerial vehicle-based ship water gauge intelligent measurement system and method, wherein the method comprises the following steps: 1. the unmanned aerial vehicle carries out autonomous cruising on the ship; 2. shooting a water gauge of a ship in the cruising process by the unmanned aerial vehicle; 3. transmitting the water gauge video from the unmanned aerial vehicle to the handheld terminal; 4. uploading the water gauge video to a mobile workstation by a user on a man-machine interaction platform; 5. identifying the water gauge video by using a ship water gauge identification algorithm to obtain a ship water gauge identification result; 6. transmitting the water gauge identification result to a man-machine interaction platform; 7. the man-machine interaction platform calculates the cargo load of the ship according to the ship water gauge identification result and other calculation parameters; 8. and after the ship cargo load calculation is completed, a ship load calculation report and a water gauge identification result are derived. Compared with the existing water gauge public estimation method, the method is more scientific and intelligent, has traceability, can effectively avoid various safety risks caused by a manual observation mode, and greatly reduces time and economic cost.
Description
Technical Field
The invention relates to the technical field of water gauge weighing, in particular to an intelligent measurement system and method for a ship water gauge based on an unmanned aerial vehicle.
Background
In the measurement of the weight of a freight ship, the water gauge weighing method is the most widely used at present. The principle is that the water displacement change of the ship is calculated by measuring parameters such as water gauge scales before and after loading and unloading the ship, liquid level heights before and after fresh water and fuel oil, sea water density and the like, so that the weight of the ship for carrying the ship is calculated.
The current common water gauge observation method comprises the following steps: the manual observation method, the liquid level sensor method, the ultrasonic water gauge method and the laser ranging method are the most commonly used method, namely, a professional water gauge weighing staff rides on a small ship to approach the water gauge scale of the ship, and the draft value of the ship is obtained by observing the water gauge reading of the ship through human eyes.
Therefore, in order to improve the safety and convenience of the ship load metering operation, ensure the efficient proceeding of cargo transactions, overcome the interference influence of the marine complex environment, and need more scientific and intelligent ship load metering means.
Disclosure of Invention
The invention provides an intelligent measurement system and method for a ship water gauge based on an unmanned aerial vehicle, which are used for solving the technical problems that the existing water gauge observation method needs manual participation, is unsafe and has low efficiency.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
the invention provides an intelligent measurement method of a ship water gauge based on an unmanned aerial vehicle, which comprises the following steps:
s1, the unmanned aerial vehicle carries out autonomous cruising on a ship according to a set waypoint route;
s2, the unmanned aerial vehicle automatically shoots a ship water gauge in the cruising process, and a shot water gauge video is obtained;
s3, transmitting the water gauge video from the unmanned aerial vehicle to the handheld terminal through a picture transmission technology;
s4, uploading the water gauge video to a mobile workstation by a user on a man-machine interaction platform of the handheld terminal;
s5, automatically identifying the water gauge video of the ship by using a ship water gauge identification algorithm deployed by the mobile workstation to obtain a ship water gauge identification result;
s6, transmitting the ship water gauge identification result in the mobile workstation to a man-machine interaction platform;
s7, calculating the cargo load of the ship by the man-machine interaction platform according to the ship water gauge identification result and other calculation parameters;
and S8, after the calculation of the ship cargo load is completed, a ship load calculation report and a water gauge identification result are derived.
Further, the step S1 specifically includes the following steps:
s11, presetting corresponding waypoint routes according to different port berths and different ship-type arrival ships, and uploading the preset waypoint routes to the unmanned plane;
s12, the unmanned aerial vehicle uses an RTK information positioning technology to realize the fly-away of each waypoint in the route;
s13, in the process that the unmanned aerial vehicle carries out autonomous cruising on the ship according to the set waypoint route, when a vision/radar obstacle avoidance system carried by the unmanned aerial vehicle detects that an obstacle exists in the waypoint route, the unmanned aerial vehicle automatically hovers and pauses the route, and an operator waits for selecting to continue flying from a breakpoint or continue flying from the next waypoint;
and enabling an automatic return program to automatically return to the departure point after the unmanned aerial vehicle flies through each preset waypoint according to the uploaded waypoint route.
Further, the implementation manner of S2 is as follows:
the unmanned aerial vehicle automatically cruises the ship according to the waypoint route, when the ship water gauge shooting waypoint is reached, the unmanned aerial vehicle can automatically hover and call a built-in cradle head camera of the unmanned aerial vehicle, the ship water gauge is automatically focused and balanced in white according to the camera zoom multiple and cradle head pitching angle preset by the waypoint, and a ship water gauge video with fixed time is shot.
Further, the step S3 specifically includes:
s31, wirelessly connecting a water gauge video shot by the unmanned aerial vehicle with a handheld terminal;
s32, selecting a corresponding water gauge video stored by the unmanned aerial vehicle on a man-machine interaction platform of the handheld terminal to download through a high-speed image transmission technology, and downloading the water gauge video to the handheld terminal after a certain time.
Further, the step S4 specifically includes the following steps:
s41, starting hot spot sharing of a mobile workstation, and selecting an unmanned aerial vehicle water gauge identification local area network for connection in network setting of a handheld terminal;
s42, opening a man-machine interaction platform on the handheld terminal, after the man-machine interaction platform is successfully connected with the mobile workstation through a preset fixed IP, clicking a newly built voyage, inputting voyage and berth of a ship to be identified currently, clicking an initial value uploading/final value uploading page on a voyage management page of the ship to enter a corresponding water gauge data uploading page, clicking an uploading video, and uploading a latest shot water gauge video to the mobile workstation.
Further, the step S5 specifically includes the following steps:
s51, firstly, performing frame extraction processing on a water gauge video, and reasoning pictures by using a deep learning segmentation model to obtain a water body segmentation binary image;
s52, carrying out edge detection on the water body segmentation binarization graph by adopting a Canny operator to obtain water line coordinates, and drawing the line on the original graph to obtain a new original graph;
s53, reasoning the new original image by using a deep learning detection model to obtain a detection result image with a plurality of character boundary boxes;
s54, calculating according to coordinates of the character boundary box to obtain a graduated scale; calculating according to the scale and the water line coordinates to obtain the water scale value of the single graph;
s55, circulating S51 to S54 to obtain water gauge values of different frames of images of the water gauge video, sampling the water gauge values of the multiple images by adopting a comprehensive sampling method, and judging the comprehensive water gauge values of the whole section of ship water gauge video according to the wave spray condition in the water gauge video and by utilizing the sampling result to obtain a ship water gauge recognition result.
Further, the implementation manner of S6 is as follows:
after the mobile workstation completes identification of the uploaded ship water gauge video, the final identification result is transmitted to a man-machine interaction platform of the handheld terminal through wireless transmission, and is reminded on a message notification page, and the man-machine interaction platform can display an identification result graph and an identification result of the corresponding ship water gauge page.
Further, the implementation manner of S7 is as follows:
after the water gauge values before and after the ship is unloaded are all identified, a user fills in ballast water readings, fuel oil readings, sea water density and ship constants before and after the ship is unloaded on a water gauge calculation page of the man-machine interaction platform, and after the filling is completed, "ship cargo load calculation" can be clicked, and the man-machine interaction platform can calculate the final load of the ship according to preset logic.
Further, the implementation manner of S8 is as follows:
after the water gauge calculation page finishes the ship cargo load calculation, the man-machine interaction platform can automatically derive the load settlement report of the navigation ship and store the report under a fixed folder path, and meanwhile, the water gauge video of the navigation ship can automatically rename according to the corresponding water gauge position and store the water gauge identification result diagram under the same directory.
The invention further provides an intelligent measurement system of the ship water gauge based on the unmanned aerial vehicle, which comprises the following components:
the unmanned aerial vehicle is internally provided with a tripod head camera, and the tripod head camera is used for shooting a water gauge video of the ship; the unmanned aerial vehicle is provided with a vision/radar obstacle avoidance system and is used for the unmanned aerial vehicle to avoid the obstacle;
the handheld terminal is in wireless connection with the unmanned aerial vehicle, a DJIPilot2 and a man-machine interaction platform are arranged in the handheld terminal, and the DJIPilot2 is used for controlling the unmanned aerial vehicle and displaying real-time flight pictures; the man-machine interaction platform is used for calculating the cargo load of the ship;
the mobile workstation is connected with the man-machine interaction platform of the handheld terminal, a water gauge identification algorithm is arranged in the mobile workstation and used for automatically identifying the water gauge video of the ship so as to obtain a ship water gauge identification result.
The invention has the beneficial effects that:
1. the invention provides an intelligent measurement method of a ship water gauge based on an unmanned aerial vehicle, which utilizes navigation point cruising of the unmanned aerial vehicle to realize automatic shooting of a water gauge video, wherein the unmanned aerial vehicle can be a Xingjiang unmanned aerial vehicle; in the second aspect, the method can realize the whole process from the ship water gauge image to the final ship cargo capacity, and in the process, excessive participation of users is not needed, and the manual strength is low.
2. According to the invention, the remote acquisition of the water gauge video is performed based on the unmanned aerial vehicle technology, so that the water gauge can be observed instead of manually entering a water surface area, and the safety of water gauge acceptance personnel is ensured; the quality of the collected video is guaranteed through a follow-up tracking technology, various sensors are integrated to collect related metering data and wirelessly transmit, and the collected data are automatically analyzed and processed to obtain the ship load, so that the disclosure, fairness and fairness of water gauge acceptance are guaranteed, and the efficiency of water gauge acceptance is improved.
Drawings
FIG. 1 is a flow chart of an intelligent measurement method of a ship water gauge in the invention;
fig. 2 is a schematic diagram of a character detection result according to an embodiment of the present invention.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many other different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Referring to fig. 1, an intelligent measurement method for a ship water gauge based on an unmanned aerial vehicle specifically comprises the following steps:
s1, the unmanned aerial vehicle carries out autonomous cruising on a ship according to a set waypoint route;
in some embodiments, the step S1 specifically includes the following steps:
s11, presetting corresponding waypoint routes according to different port berths and different ship-type arrival ships, and uploading the preset waypoint routes to the unmanned plane;
s12, the unmanned aerial vehicle realizes accurate flying of each waypoint in the route by using an RTK information positioning technology;
s13, in the process that the unmanned aerial vehicle carries out autonomous cruising on the ship according to the set waypoint route, when a vision/radar obstacle avoidance system carried by the unmanned aerial vehicle detects that an obstacle exists in the waypoint route, the unmanned aerial vehicle automatically hovers and pauses the route, and an operator waits for selecting to continue flying from a breakpoint or continue flying from the next waypoint;
and enabling an automatic return program to automatically return to the departure point after the unmanned aerial vehicle flies through each preset waypoint according to the uploaded waypoint route.
S2, the unmanned aerial vehicle automatically shoots a ship water gauge in the cruising process, and a shot water gauge video is obtained;
in some embodiments, the implementation of S2 is:
the unmanned aerial vehicle automatically cruises the ship according to the waypoint route, when the ship water gauge shooting waypoint is reached, the unmanned aerial vehicle can automatically hover and call a built-in cradle head camera of the unmanned aerial vehicle, the ship water gauge is automatically focused and balanced in white according to the camera zoom multiple and cradle head pitching angle preset by the waypoint, and a ship water gauge video with fixed time is shot.
S3, transmitting the water gauge video from the unmanned aerial vehicle to the handheld terminal through a picture transmission technology;
in some embodiments, the S3 specifically includes:
s31, wirelessly connecting a water gauge video shot by the unmanned aerial vehicle with a handheld terminal;
s32, selecting corresponding water gauge video stored by the unmanned aerial vehicle on a man-machine interaction platform of the handheld terminal to download through a high-speed image transmission technology, and downloading the 6-section 10S water gauge video to the handheld terminal within 1 minute after downloading the selected water gauge video.
S4, uploading the water gauge video to a portable mobile workstation by a user on a man-machine interaction platform of the handheld terminal;
in some embodiments, the step S4 specifically includes the following steps:
s41, starting hot spot sharing of a mobile workstation, and selecting an unmanned aerial vehicle water gauge identification local area network for connection in network setting of a handheld terminal;
s42, opening a man-machine interaction platform on the handheld terminal, after the man-machine interaction platform is successfully connected with the mobile workstation through a preset fixed IP, clicking a newly built voyage, inputting voyage and berth of a ship to be identified currently, clicking an initial value uploading/final value uploading page on a voyage management page of the ship to enter a corresponding water gauge data uploading page, clicking an uploading video, and uploading a latest shot water gauge video to the portable mobile workstation.
S5, automatically identifying the water gauge video of the ship by using a ship water gauge identification algorithm deployed by the mobile workstation to obtain a ship water gauge identification result;
in some embodiments, the step S5 specifically includes the following steps:
s51, firstly, performing frame extraction processing on a water gauge video, and reasoning pictures by using a deep learning segmentation model to obtain a water body segmentation binary image;
s52, carrying out edge detection on the water body segmentation binarization graph by adopting a Canny operator to obtain water line coordinates, and drawing the line on the original graph to obtain a new original graph;
specifically, the Canny operator is a common edge detection algorithm, a proper edge line is obtained by adjusting a threshold value, coordinates of the edge line are obtained, corresponding water line coordinates are drawn on an original image according to the coordinates, and the water line coordinates are stored as a new original image for the next character detection reasoning.
S53, reasoning the new original image by using a deep learning detection model to obtain a detection result image with a plurality of character boundary boxes;
s54, calculating according to coordinates of the character boundary box to obtain a graduated scale; calculating according to the scale and the water line coordinates to obtain the water scale value of the single graph;
in some embodiments, the step S54 specifically includes the following steps:
s541, removing a plurality of incomplete character boundary boxes in the detection result diagram in a sequencing mode;
specifically, the coordinates of the multiple character bounding boxes obtained in the previous step determine the scale, and incomplete character bounding boxes are removed through sorting because the situation that characters are incomplete but detected may occur.
S542, as the heights of the character boundary boxes are different, taking the central point of the residual character boundary box as a scale point, sequentially subtracting the y coordinates to obtain the number of pixels occupied by the distance between two adjacent characters in the figure, and taking the average value as the number of pixels between the two adjacent characters in the figure; the y coordinate is the pixel coordinate where the vertical direction is located, that is, the pixel coordinate where the upper left point in fig. 2 is the origin point downward;
s542 is expressed by a formula, specifically as follows:
where i and j are the sequence numbers of the character bounding boxes,a y-coordinate value for the center point of the jth character bounding box; />For the y coordinate value of the center point of the ith character boundary frame, N is the total number of the character boundary frames, and N is the number of pixels of the interval between two vertically adjacent characters.
S543, solving the real height h represented by a pixel value according to the character spacing in the actual scene;
specifically, in an actual scene, the height of the distance between two adjacent characters is 0.2 meters, so the actual height h represented by a pixel value in the graph can be obtained by the following formula:
h＝0.2/n。
s544, saving the Y coordinate Y of the center point of the whole meter character frame, and determining the real height H of the point. For example, the whole meter value is 15 meters, and the real height H of the point is 15.05 meters;
s545, finding the frame coordinates of the rest character frames at the lowest position, and determining the x coordinates x of the left lower point and the right lower point of the frame 1 And x 2 And find the position x 1 And x 2 All the coordinate points of the water level line in the middle are taken as the average value of the y coordinates of all the points to be taken as the height W of the water level line in the graph y The method comprises the steps of carrying out a first treatment on the surface of the The x coordinate is a pixel coordinate which is arranged horizontally and is perpendicular to the y axis, namely, the upper left point in fig. 2 is a pixel coordinate of which the origin is horizontal to the right;
the step S545 is expressed by a formula, and is specifically as follows:
wherein M is at x 1 And x 2 The number of coordinate points of the water line between the two coordinates, k is the serial number of the coordinate points, y k Y-coordinate value of kth coordinate point, W y Is the water line height in the figure.
S546, subtracting the height W of the water line in the figure from the Y coordinate Y of the central point y And further obtaining the difference of the height pixel values between the water level line and the center point of the whole meter character frame, multiplying the difference by the real height H represented by one pixel value to obtain the real height distance, and finally subtracting the real height distance from the real height H of the point to obtain the final real height of the water level line, namely the water gauge value v.
The step S546 is represented by a formula, which is specifically as follows:
v＝H-h×(Y-W y )。
s55, circulating S51 to S54 to obtain water gauge values of different frames of images of the water gauge video, sampling the water gauge values of the multiple images by adopting a comprehensive sampling method, and judging the comprehensive water gauge values of the whole section of ship water gauge video according to the wave spray condition in the water gauge video and by utilizing the sampling result to obtain a ship water gauge recognition result.
S6, transmitting the ship water gauge identification result in the mobile workstation to a man-machine interaction platform;
in some embodiments, the implementation manner of S6 is:
after the mobile workstation completes identification of the uploaded ship water gauge video, a final identification result is transmitted to a man-machine interaction platform of the handheld terminal in a wireless mode, the man-machine interaction platform reminds the user on a message notification page, and the man-machine interaction platform displays an identification result diagram and an identification result of the user on a corresponding ship water gauge page, for example, an internal bow page displays the identification result diagram and a final water gauge reading before unloading.
After all the water gauges at the ship 6 are identified, the man-machine interaction platform can automatically synchronize the identification results of all the water gauges to a water gauge calculation page for calculating the cargo carrying capacity of the ship.
S7, calculating the cargo load of the ship by the man-machine interaction platform according to the ship water gauge identification result and other calculation parameters;
in some embodiments, the implementation of S7 is:
after the 12 water gauge values before and after the ship is unloaded are all identified, a user fills in the ballast water readings, the fuel oil readings, the seawater density and the ship constants before and after the ship is unloaded on a water gauge calculation page of the man-machine interaction platform, and after the filling is completed, "ship cargo load calculation" can be clicked, and the man-machine interaction platform can calculate the final load of the ship according to preset logic.
And S8, after the calculation of the ship cargo load is completed, a ship load calculation report and a water gauge identification result are derived.
In some embodiments, the implementation manner of S8 is:
after the water gauge calculation page finishes the ship cargo load calculation, the man-machine interaction platform can automatically derive the load settlement report of the navigation ship and store the report under a fixed folder path, and meanwhile, the water gauge video of the navigation ship can automatically rename according to the corresponding water gauge position and store the water gauge identification result diagram under the same directory.
The invention further provides an intelligent measurement system of the ship water gauge based on the unmanned aerial vehicle, which comprises the following components:
the unmanned aerial vehicle is internally provided with a tripod head camera, and the tripod head camera is used for shooting a water gauge video of the ship; the unmanned aerial vehicle is provided with a vision/radar obstacle avoidance system and is used for the unmanned aerial vehicle to avoid the obstacle;
the handheld terminal is in wireless connection with the unmanned aerial vehicle, a DJIPilot2 and a man-machine interaction platform are arranged in the handheld terminal, and the DJIPilot2 is used for controlling the unmanned aerial vehicle and displaying real-time flight pictures; the man-machine interaction platform is used for calculating the cargo load of the ship;
the mobile workstation is connected with the man-machine interaction platform of the handheld terminal, a water gauge identification algorithm is arranged in the mobile workstation and used for automatically identifying the water gauge video of the ship so as to obtain a ship water gauge identification result.
According to the intelligent measurement system for the ship water gauge, the unmanned aerial vehicle can automatically cruise the ship according to a preset waypoint route, and can automatically shoot videos of the ship water gauge in the cruising process; the water gauge image data can be transmitted from the unmanned aerial vehicle to the handheld terminal through the image transmission technology, so that a user can upload the water gauge image data to the workstation through wireless transmission on the man-machine interaction platform; the ship water gauge scale recognition algorithm is deployed in the workstation, so that the ship water gauge scale recognition can be automatically performed; and meanwhile, the ship water gauge recognition result can be transmitted to a man-machine interaction platform, the man-machine interaction platform can calculate the ship cargo load according to the ship water gauge recognition result and other calculation parameters, and a ship load calculation report and a water gauge recognition result can be derived after calculation is completed.
The system can realize automatic measurement of the scale of the ship water gauge, has high measurement efficiency, can effectively reduce the cost of economy and manpower, and solves the problem of unsafe existing manual measurement methods.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Moreover, the technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can implement the embodiments, and when the technical solutions are contradictory or cannot be implemented, it should be considered that the combination of the technical solutions does not exist, and is not within the scope of protection claimed by the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The intelligent measurement method for the ship water gauge based on the unmanned aerial vehicle is characterized by comprising the following steps of:
s1, the unmanned aerial vehicle carries out autonomous cruising on a ship according to a set waypoint route;
s2, the unmanned aerial vehicle automatically shoots a ship water gauge in the cruising process, and a shot water gauge video is obtained;
s3, transmitting the water gauge video from the unmanned aerial vehicle to the handheld terminal through a picture transmission technology;
s4, uploading the water gauge video to a mobile workstation by a user on a man-machine interaction platform of the handheld terminal;
s5, automatically identifying the water gauge video of the ship by using a ship water gauge identification algorithm deployed by the mobile workstation to obtain a ship water gauge identification result;
s6, transmitting the ship water gauge identification result in the mobile workstation to a man-machine interaction platform;
s7, calculating the cargo load of the ship by the man-machine interaction platform according to the ship water gauge identification result and other calculation parameters;
and S8, after the calculation of the ship cargo load is completed, a ship load calculation report and a water gauge identification result are derived.
2. The intelligent measurement method of the ship water gauge according to claim 1, wherein the step S1 specifically comprises the following steps:
s11, presetting corresponding waypoint routes according to different port berths and different ship-type arrival ships, and uploading the preset waypoint routes to the unmanned plane;
s12, the unmanned aerial vehicle uses an RTK information positioning technology to realize the fly-away of each waypoint in the route;
s13, in the process that the unmanned aerial vehicle carries out autonomous cruising on the ship according to the set waypoint route, when a vision/radar obstacle avoidance system carried by the unmanned aerial vehicle detects that an obstacle exists in the waypoint route, the unmanned aerial vehicle automatically hovers and pauses the route, and an operator waits for selecting to continue flying from a breakpoint or continue flying from the next waypoint;
and enabling an automatic return program to automatically return to the departure point after the unmanned aerial vehicle flies through each preset waypoint according to the uploaded waypoint route.
3. The intelligent measurement method of the ship water gauge according to claim 1, wherein the implementation manner of S2 is as follows:
the unmanned aerial vehicle automatically cruises the ship according to the waypoint route, when the ship water gauge shooting waypoint is reached, the unmanned aerial vehicle can automatically hover and call a built-in cradle head camera of the unmanned aerial vehicle, the ship water gauge is automatically focused and balanced in white according to the camera zoom multiple and cradle head pitching angle preset by the waypoint, and a ship water gauge video with fixed time is shot.
4. The intelligent measurement method of the ship water gauge according to claim 1, wherein the step S3 specifically comprises:
s31, wirelessly connecting a water gauge video shot by the unmanned aerial vehicle with a handheld terminal;
s32, selecting a corresponding water gauge video stored by the unmanned aerial vehicle on a man-machine interaction platform of the handheld terminal to download through a high-speed image transmission technology, and downloading the water gauge video to the handheld terminal after a certain time.
5. The intelligent measurement method of the ship water gauge according to claim 1, wherein the step S4 specifically comprises the following steps:
s41, starting hot spot sharing of a mobile workstation, and selecting an unmanned aerial vehicle water gauge identification local area network for connection in network setting of a handheld terminal;
s42, opening a man-machine interaction platform on the handheld terminal, after the man-machine interaction platform is successfully connected with the mobile workstation through a preset fixed IP, clicking a newly built voyage, inputting voyage and berth of a ship to be identified currently, clicking an initial value uploading/final value uploading page on a voyage management page of the ship to enter a corresponding water gauge data uploading page, clicking an uploading video, and uploading a latest shot water gauge video to the mobile workstation.
6. The intelligent measurement method of the ship water gauge according to claim 1, wherein the step S5 specifically comprises the following steps:
s51, firstly, performing frame extraction processing on a water gauge video, and reasoning pictures by using a deep learning segmentation model to obtain a water body segmentation binary image;
s52, carrying out edge detection on the water body segmentation binarization graph by adopting a Canny operator to obtain water line coordinates, and drawing the line on the original graph to obtain a new original graph;
s53, reasoning the new original image by using a deep learning detection model to obtain a detection result image with a plurality of character boundary boxes;
s54, calculating according to coordinates of the character boundary box to obtain a graduated scale; calculating according to the scale and the water line coordinates to obtain the water scale value of the single graph;
s55, circulating S51 to S54 to obtain water gauge values of different frames of images of the water gauge video, sampling the water gauge values of the multiple images by adopting a comprehensive sampling method, and judging the comprehensive water gauge values of the whole section of ship water gauge video according to the wave spray condition in the water gauge video and by utilizing the sampling result to obtain a ship water gauge recognition result.
7. The intelligent measurement method of the ship water gauge according to claim 1, wherein the implementation manner of S6 is as follows:
after the mobile workstation completes identification of the uploaded ship water gauge video, the final identification result is transmitted to a man-machine interaction platform of the handheld terminal through wireless transmission, and is reminded on a message notification page, and the man-machine interaction platform can display an identification result graph and an identification result of the corresponding ship water gauge page.
8. The intelligent measurement method of the ship water gauge according to claim 1, wherein the implementation manner of S7 is as follows:
after the water gauge values before and after the ship is unloaded are all identified, a user fills in ballast water readings, fuel oil readings, sea water density and ship constants before and after the ship is unloaded on a water gauge calculation page of the man-machine interaction platform, and after the filling is completed, "ship cargo load calculation" can be clicked, and the man-machine interaction platform can calculate the final load of the ship according to preset logic.
9. The intelligent measurement method of a ship water gauge according to any one of claims 1 to 8, wherein the implementation manner of S8 is as follows:
after the water gauge calculation page finishes the ship cargo load calculation, the man-machine interaction platform can automatically derive the load settlement report of the navigation ship and store the report under a fixed folder path, and meanwhile, the water gauge video of the navigation ship can automatically rename according to the corresponding water gauge position and store the water gauge identification result diagram under the same directory.
10. Intelligent measurement system of boats and ships water gauge based on unmanned aerial vehicle, its characterized in that includes:
the unmanned aerial vehicle is internally provided with a tripod head camera, and the tripod head camera is used for shooting a water gauge video of the ship; the unmanned aerial vehicle is provided with a vision/radar obstacle avoidance system and is used for the unmanned aerial vehicle to avoid the obstacle;
the handheld terminal is in wireless connection with the unmanned aerial vehicle, a DJIPilot2 and a man-machine interaction platform are arranged in the handheld terminal, and the DJIPilot2 is used for controlling the unmanned aerial vehicle and displaying real-time flight pictures; the man-machine interaction platform is used for calculating the cargo load of the ship;
the mobile workstation is connected with the man-machine interaction platform of the handheld terminal, a water gauge identification algorithm is arranged in the mobile workstation and used for automatically identifying the water gauge video of the ship so as to obtain a ship water gauge identification result.
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