Method for judging suspected muck transportation of inland river dry cargo ship

Abstract

The invention relates to the technical field of muck ship discrimination, and discloses a method for discriminating the suspected muck transportation of an inland river dry cargo ship, and the method comprises the following steps: S1, equipment installation: installing a three-dimensional laser scanning device, an AIS signal receiving device and a visual AI recognition device at a monitoring bayonet, and carrying out the debugging; s2, AIS identification judgment: receiving an AIS signal sent by the ship through an AIS signal receiving device, if the AIS signal sent by the ship is received, not marking the ship, and if the AIS signal is not received, marking the ship; and S3, visual AI judgment: identifying the marked ship through visual AI identification equipment. According to the method, multiple times of identification and marking are carried out on the inland ship, layer-by-layer marking detection is carried out according to multiple characteristics of the muck ship, time and labor can be saved during intelligent detection, meanwhile, the judgment accuracy of the muck ship can be improved, monitoring loopholes are made up, and the inland river transportation route is better purified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of slag ship identification, in particular to a method for identifying a river dry cargo ship suspected of transporting slag. BACKGROUND

[0002] During the process of sailing in the river, the ship will pass through the monitoring passageway. Various identification and monitoring equipment are generally installed at the monitoring passageway to monitor the ship, especially the monitoring of the river dry cargo ship suspected of transporting slag. Most of the river dry cargo ships are modified into slag transport ships, and they dump the slag in the river in violation of the rules, which seriously affects the normal operation of river transportation.

[0003] Generally, the slag ship is transported at night, and manual monitoring is time-consuming and laborious. In addition, the visibility at night is not good, and the slag ship is well disguised. The existing automatic monitoring method of equipment and devices is not accurate enough, and there are some monitoring loopholes, so that some slag ships escape monitoring. Therefore, a method for identifying a river dry cargo ship suspected of transporting slag is proposed. SUMMARY

[0004] (I) Technical problems to be solved

[0005] In view of the deficiencies in the prior art, the present application provides a method for identifying a river dry cargo ship suspected of transporting slag, which solves the problem that the existing slag ship is transported at night, manual monitoring is time-consuming and laborious, and the visibility at night is not good. In addition, the slag ship is well disguised, the existing automatic monitoring method of equipment and devices is not accurate enough, and there are some monitoring loopholes, so that some slag ships escape monitoring.

[0006] (II) Technical solutions

[0007] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0008] A method for identifying a river dry cargo ship suspected of transporting slag, comprising the following steps:

[0009] S1: Equipment installation, install three-dimensional laser scanning equipment, AIS signal receiving equipment and visual AI recognition equipment at the monitoring passageway, and debug;

[0010] S2: AIS identification and judgment, receiving the AIS signal emitted by the ship through the AIS signal receiving equipment, if the AIS signal emitted by the ship is received, the ship is not marked, if the AIS signal is not received, the ship is marked;

[0011] S3: visual AI judgment, identifying the marked ship through the visual AI recognition equipment, if the AI identifies whether the ship name and number are clear, if clear, eliminate the mark, if not clear, mark again;

[0012] S4: overload judgment, the device identifies the ship with secondary mark through visual AI recognition, cooperates with three-dimensional laser ship recognizer to track and identify the height H6 of the deck of the ship and the height H5 of the water surface, then finds the corresponding standard line height H4 by identifying the ship, then calculates the height difference H1 of the deck to the water surface, wherein H1=H6-H5, then calculates the height difference of the deck to the standard line, that is, the water height value ΔH, wherein ΔH=H1-H4, because the ship is constantly moving on the water surface, and the three-dimensional laser ship recognizer is constantly detecting, there will be multiple sets of H6 and H5 values, so there will be multiple sets of ΔH values, for the obtained multiple sets of ΔH values, the values of the head 0-1 / 3 and the tail 0-1 / 3 are removed, and then the average value of ΔH is calculated, according to the calculated average value of ΔH, compared with the overload threshold of the configuration table of the water height empirical value corresponding to the ship size in the database, if it is lower than the water height empirical value corresponding to the ship size, it is judged as overload, at this time, three times of marking are carried out, otherwise, it is not overloaded;

[0013] S5: tonnage judgment, the length, width and height of the ship marked three times are scanned by the three-dimensional laser scanning device, and the tonnage is calculated, if the tonnage of the ship is greater than 500 tons, the mark is eliminated, if it is less than 500 tons, the ship is marked four times;

[0014] S6: height judgment, the height of the ship marked four times is scanned by the three-dimensional laser scanning device, the ship with water height greater than 3 meters is eliminated, and the ship with water height less than 3 meters is marked five times, and the ship marked five times is judged as a suspected transport of muck ship.

[0015] As a further scheme of the application, the S4 accumulates when marking, and cancels the detection of the ship whose mark is eliminated.

[0016] Further, the S2 includes an AIS signal receiving module responsible for receiving the AIS signal sent by the ship and an AI recognition module for recognizing the ship name and number.

[0017] On the basis of the foregoing scheme, the S3 includes a marking module, the marking module accumulates the marked ship, and the marking module is connected with an elimination module, the elimination module eliminates the mark of the ship that does not meet the condition.

[0018] Further, the S4 includes a verification module, after the identity of the ship is determined, the verification module checks the database to see the water height empirical value corresponding to the ship size, then compares the measured water height of the ship with the water height threshold value corresponding to the size according to the length interval range in which the ship size falls, if the threshold value is lower, it means overload, if it is higher, it means normal, and the overload verification result is saved into the database.

[0019] On the basis of the foregoing scheme, the S3 is provided with a judgment module, a marking module and a data access module, and the data access module comprises a data communication interface connected with a database.

[0020] (III) Beneficial Effects

[0021] Compared with the prior art, the application provides a method for discriminating whether an inland dry cargo ship is suspected of transporting muck, and has the following beneficial effects:

[0022] 1. In the application, the inland ship is identified and marked multiple times, the various characteristics of the muck ship are marked and detected layer by layer, the accuracy of muck ship discrimination is improved while saving time and labor in intelligent detection, monitoring loopholes are made up, and the inland transportation route is better purified.

[0023] 2. In the application, the deck height and water surface height are identified by the AI recognition device and the three-dimensional laser ship recognition device, and then the water height value is calculated by cooperating with the standard line height corresponding to each ship, so as to judge whether the ship is overloaded. Through accurate calculation and judgment, whether the ship is overloaded can be more accurately judged, which is more rational, and different types of ships can be judged, which is more intelligent. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A flow structure schematic diagram of the method for discriminating whether an inland dry cargo ship is suspected of transporting muck is provided. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0026] Embodiment 1

[0027] Reference Figure 1 A method for discriminating whether an inland dry cargo ship is suspected of transporting muck comprises the following steps:

[0028] S1: Equipment installation, install three-dimensional laser scanning equipment, AIS signal receiving equipment and visual AI recognition equipment at a monitoring port, and debug;

[0029] S2: AIS identification and judgment, receive the AIS signal emitted by the ship through the AIS signal receiving equipment, if the AIS signal emitted by the ship is received, the ship is not marked, and if the AIS signal is not received, the ship is marked;

[0030] S3: visual AI judgment, the marked ship is identified by the visual AI recognition device, if the AI identifies the ship name and number clearly, the mark is removed, if not, secondary marking is performed;

[0031] S4: overload judgment, the secondary marked ship is identified by the visual AI recognition device, and the three-dimensional laser ship identifier is used to track and identify the height H6 of the ship deck and the height H5 of the water surface, then the ship is identified to find its corresponding standard line height H4, then the height difference H1 of the deck to the water surface is calculated, where H1 = H6-H5, then the height difference of the deck to the standard line, that is, the water height value AH, where AH = H1-H4, since the ship is constantly moving on the water surface, and the three-dimensional laser ship identifier is constantly detecting, there will be multiple sets of H6 and H5 values, so there will be multiple sets of AH values, for the obtained multiple sets of AH values, the values of the head 0-1 / 3 and the tail 0-1 / 3 are removed, and then the average value of AH is calculated, according to the calculated average value of AH, compared with the overload threshold of the configuration table of the water height empirical value corresponding to the ship size in the database, if it is lower than the water height empirical value corresponding to the ship size, it is determined to be overloaded, at this time, three times of marking are performed, otherwise, it is not overloaded, the deck height and the water surface height are identified by the recognition AI recognition device and the three-dimensional laser ship identifier, and then the water height value is calculated according to the standard line height corresponding to each ship, so as to judge whether the ship is overloaded, through accurate calculation, the ship can be more accurately judged whether it is overloaded, more rationally, and different types of ships can be judged, more intelligently;

[0032] S5: tonnage determination, the length, width and height of the three times marked ship are scanned by the three-dimensional laser scanning device, and its tonnage is calculated, if the tonnage of the ship is greater than 500 tons, the mark is removed, if less than 500 tons, the ship is marked for the fourth time;

[0033] S6: height determination, the height of the four times marked ship is scanned by the three-dimensional laser scanning device, the ship with water height greater than 3 meters is marked, and the ship with water height less than 3 meters is marked for the fifth time, the five times marked ship is determined to be suspected of transporting soil ship, through multiple identification and marking of inland ships, and according to the characteristics of the soil ship, the soil ship can be detected layer by layer, which can improve the accuracy of soil ship identification, fill the monitoring gap, and better purify the inland transportation route.

[0034] In the application, accumulation is performed when marking in S4, and the marked ship is canceled for detection, S2 includes an AIS signal receiving module responsible for receiving the AIS signal emitted by the ship and an AI identification module for identifying the ship name and number, S3 includes a marking module, the marking module accumulates the marked ship, and the marking module is connected with an elimination module, which eliminates the marking of the ship not meeting the conditions.

[0035] Embodiment 2

[0036] Reference Figure 1 A method for identifying a river dry cargo ship suspected of transporting muck, comprising the following steps:

[0037] S1: equipment installation, install three-dimensional laser scanning equipment, AIS signal receiving equipment and visual AI recognition equipment at the monitoring aperture, and debug;

[0038] S2: AIS identification and judgment, receiving the AIS signal emitted by the ship through the AIS signal receiving equipment, if the AIS signal emitted by the ship is received, the ship is not marked, and if the AIS signal cannot be received, the ship is marked;

[0039] S3: visual AI judgment, identifying the marked ship through the visual AI recognition equipment, if the ship name and number are clear, the marking is eliminated, and if the ship name and number are not clear, the ship is marked again;

[0040] S4: overload judgment, identifying the marked ship again through the visual AI recognition equipment, cooperating with the three-dimensional laser ship identifier to track and identify the height H6 of the ship deck and the height H5 of the water surface, then identifying the ship to find the corresponding standard line height H4, then calculating the height difference H1 of the deck to the water surface, wherein H1 = H6-H5, then calculating the height difference of the deck to the standard line, that is, the water height value ΔH, wherein ΔH = H1-H4, since the ship is continuously moving on the water surface, and the three-dimensional laser ship identifier is continuously detecting, there will be multiple sets of H6 and H5 values, so there will be multiple sets of ΔH values, for the obtained multiple sets of ΔH values, the values of the head 0-1 / 3 and the tail 0-1 / 3 are removed, then the average value of ΔH is calculated, according to the calculated average value of ΔH, compared with the overload threshold of the configuration table of the water height empirical value corresponding to the ship size in the database, if it is lower than the water height empirical value corresponding to the ship size, it is determined as overload, at this time, marking three times, otherwise, it is not overloaded, the deck height and the water surface height are identified through the identification AI recognition equipment and the three-dimensional laser ship identifier, then the water height value is calculated by cooperating with the standard line height corresponding to each ship, so as to judge whether the ship is overloaded, through the accurate calculation judgment, the ship can be more accurately judged, it is more reasonable, and different types of ships can be judged, it is more intelligent;

[0041] S5: tonnage determination, scanning the length, width and height of the marked ship three times by the three-dimensional laser scanning device, and calculating the tonnage thereof, if the tonnage of the ship is greater than 500 tons, eliminating the marking, and if less than 500 tons, marking it four times;

[0042] S6: height determination, scanning the height of the marked ship four times by the three-dimensional laser scanning device, eliminating the marking for the ship with the water height greater than 3 meters, marking it five times for the ship with the water height less than 3 meters, and determining the five times marked ship as a suspected transport of muck ship, through multiple identification marking of the inland ship, and multiple characteristic marking detection of the muck ship, the accuracy of the muck ship discrimination can be improved while saving time and labor in intelligent detection, the monitoring loopholes are made up, and the inland transportation route is better purified.

[0043] In the present application, the marking in S4 is accumulated, and the marked ship is cancelled for detection, S2 includes an AIS signal receiving module responsible for receiving the AIS signal sent by the ship and an AI identification module for identifying the ship name and number, S3 includes a marking module, the marking module accumulates the marked ship, and the marking module is connected with an elimination module, the elimination module eliminates the marking of the ship not meeting the conditions, S4 includes a verification module, after the ship identity is determined, the verification module checks the database to see the water height experience value corresponding to the ship size, then according to the ship size falling in the ship length interval range, the size of the ship measured water height and the corresponding water height threshold of the size are compared, if lower than the threshold, it means overloading, if higher than the threshold, it means normal, and the overloading verification result is saved into the database, S3 includes a judgment module, a marking module and a data access module, and the data access module includes a data communication interface connected with the database.

[0044] In the description in the present document, it should be noted that the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or sequence between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0045] Although the embodiments of the present application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method of discriminating a river cargo ship suspected of transporting dredged soil, characterized by, The method comprises the following steps: S1: equipment installation, install three-dimensional laser scanning equipment, AIS signal receiving equipment, visual AI recognition equipment at the monitoring aperture, and debug; S2: AIS recognition and judgment, receive the AIS signal emitted by the ship through the AIS signal receiving equipment, if the AIS signal emitted by the ship is received, the ship is not marked, if the AIS signal cannot be received, the ship is marked; S3: visual AI judgment, identify the marked ship through the visual AI recognition equipment, if the AI identifies whether the ship name and number are clear, if clear, eliminate the mark, if not clear, mark twice; S4: overload judgment, identify the twice-marked ship through the visual AI recognition equipment, cooperate with the three-dimensional laser ship recognizer to track and identify the height H6 of the ship deck and the height H5 of the water surface, then identify the ship, find the corresponding standard line height H4, then calculate the height difference H1 of the deck to the water surface, wherein: H1=H6-H5, then calculate the height difference of the deck to the standard line, that is, the water height value ΔH, wherein ΔH=H1-H4, since the ship is constantly moving on the water surface, and the three-dimensional laser ship recognizer is constantly detecting, there will be multiple sets of H6 and H5 values, so there will be multiple sets of ΔH values, for the obtained multiple sets of ΔH values, remove the values of the head 0-1 / 3 and the tail 0-1 / 3, then calculate the average value of ΔH, compare the calculated average value of ΔH with the overload threshold value of the configuration table of the water height empirical value corresponding to the ship size in the database, if lower than the water height empirical value corresponding to the ship size, it is determined that the ship is overloaded, at this time, mark three times, otherwise, the ship is not overloaded; S5: tonnage judgment, scan the length, width and height of the thrice-marked ship through the three-dimensional laser scanning equipment, and calculate the tonnage, if the tonnage of the ship is greater than 500 tons, eliminate the mark, if less than 500 tons, mark the ship four times; S6: height judgment, scan the height of the quadruple-marked ship through the three-dimensional laser scanning equipment, eliminate the mark for the ship with water height greater than 3 meters, mark the ship with water height less than 3 meters for the fifth time, and determine the ship marked for the fifth time as a suspected transport of muck ship.

2. The method according to claim 1, wherein In S4, the marking is accumulated, and the marked ship is canceled.

3. The method of claim 1, wherein the method is characterized by: In S2, the AIS signal receiving module is responsible for receiving the AIS signal emitted by the ship, and the AI recognition module is responsible for identifying the ship name and number.

4. The method according to claim 2, wherein In S3, the marking module accumulates the marked ship, and the elimination module is connected to the marking module to eliminate the mark of the ship that does not meet the conditions.

5. The method of claim 1, wherein the method is characterized by: In S4, the verification module checks the database to find the water height empirical value corresponding to the ship size, then compares the measured water height of the ship with the threshold value of the corresponding water height of the size according to the length interval range of the measured size of the ship, if lower than the threshold value, it means overload, if higher than the threshold value, it means normal, and the overload verification result is saved into the database.

6. The method according to claim 5, wherein The S3 includes a judgment module, a marking module and a data access module, and the data access module includes a data communication interface connected with the database.

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