System and method for wave monitoring of construction area based on image information recognition

Abstract

To provide a wave monitoring system for a construction area based on image information recognition, which can optimize the route and adjust the work strategy based on accurate risk judgment results, reduce the probability of the ship blindly entering the risky sea area, ensure the smooth implementation of the navigation plan, and complete the construction work on time. [Solution] The system includes a monitoring area setting module, a wave image collection module, a wave parameter analysis module, a break condition monitoring module, a swell condition monitoring module, and a risk situation recognition module, and is configured to further determine whether a risk exists for the target dredging construction vessel based on the determination result of whether a wave risk situation will occur in each monitoring area.

Description

[Technical field]

[0001] The present invention relates to the technical field of wave monitoring for dredging ship operations, and more particularly to a system and method for monitoring waves in a construction area based on image information recognition. [Background technology]

[0002] Ship dredging refers to the process of excavating, transporting and disposing of sediments such as sand and rocks from the bottom of the water using specialized ship equipment. Its main purpose is to deepen or widen the water area of ​​a seaway or a port, improve the navigation conditions for ships and obtain materials such as sand for construction. Wave monitoring during ship dredging is an important prerequisite for ensuring the safety of ships and personnel, improving the efficiency of dredging work, effectively controlling the dispersion of suspended solids and protecting the marine ecosystem. Therefore, research into wave monitoring in construction areas based on image information recognition is of great significance.

[0003] In the prior art, waves are also monitored during ship dredging operations, but many problems still exist. In the prior art, wave monitoring only monitors basic wave parameters such as wave height and period, and does not monitor wave breaks and wave swells sufficiently. This analysis method reduces the comprehensiveness of security risk assessment, cannot adapt to the complex and changing marine environment, and significantly increases the risks of navigation. Meanwhile, in the prior art, only monitoring data is generally analyzed, and further processing of the analysis results, such as identifying risk monitoring areas and judging the risk status of ship dredging operations, is lacking. This analysis method reduces the effectiveness and timeliness of system analysis, increases the risks of ship dredging operations, and cannot efficiently optimize work routes, thereby reducing work efficiency.

[0004] Therefore, in order to solve the problems proposed in the above-mentioned background art, a system and method for wave monitoring of a construction area based on image information recognition is proposed. Summary of the Invention [Means for solving the problem]

[0005] The object of the present invention can be achieved by the following technical means: A wave monitoring system for a construction area based on image information recognition, A monitoring area setting step module for obtaining the position of a target dredging vessel, obtaining an influence area based on a preset setting area area, dividing a monitoring area for the influence area to obtain several monitoring areas, and setting the center point of each monitoring area as a monitoring point; a wave image collection module for collecting images at corresponding monitoring points in each monitoring area using a drone to obtain wave images in each monitoring area; a wave parameter analysis module for acquiring wave data for each monitoring area, including wave height and period, based on the wave image of each monitoring area, and further analyzing the wave risk assessment status of each monitoring area; a wave break status monitoring module for obtaining wave peak images for each monitoring area based on wave images for each monitoring area, analyzing the curl status of wave peaks for each monitoring area, determining whether waves are breaking in each monitoring area, and if so, recording the breaking position and breaking height, and analyzing the wave break risk assessment status for each monitoring area; a swell condition monitoring module for obtaining several collection points by uniformly arranging each monitoring area, obtaining the monitoring water level of each collection point corresponding to each monitoring area based on the wave image of each monitoring area, analyzing the similarity situation of the water level change in each monitoring area, determining whether wave swell occurs in each monitoring area, and if so, recording the water level and the duration of the swell, and analyzing the wave swell risk evaluation situation of each monitoring area; and a risk situation recognition module for judging whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and determining whether a risk exists for the target dredging construction vessel.

[0006] Furthermore, a method for monitoring waves in a construction area based on image information recognition is provided, Step 1: A monitoring area setting step of obtaining the position of the target dredging vessel, obtaining an influence area based on a preset setting area area, dividing the monitoring area into several monitoring areas based on the influence area, and setting the center point of each monitoring area as a monitoring point; Step 2: A wave image collection step of using a drone to collect images at corresponding monitoring points in each monitoring area to obtain wave images in each monitoring area; where step 2 is related to step 3, step 4, and step 5; Step 3 is a wave parameter analysis step to obtain wave data for each monitoring area, including wave height and period, based on the wave images of each monitoring area, and further analyze the wave risk assessment status of each monitoring area. Step 3 is related to Step 6, Step 4: A wave breaking status monitoring step, which obtains a wave peak image of each monitoring area based on the wave image of each monitoring area, analyzes the curl status of the wave peak of each monitoring area, judges whether waves are breaking in each monitoring area, and if so, records the breaking position and breaking height, and analyzes the wave breaking risk evaluation status of each monitoring area; where, step 4 is related to step 6, Step 5: a swell condition monitoring step of uniformly arranging each monitoring area to obtain several collection points, obtaining the monitoring water level of each collection point corresponding to each monitoring area according to the wave image of each monitoring area, analyzing the similarity situation of the water level change in each monitoring area, determining whether wave swell occurs in each monitoring area, and if so, recording the water level and the duration of the swell, and analyzing the wave swell risk evaluation situation of each monitoring area; where, step 5 is related to step 6, Step 6 includes a risk situation recognition step of judging whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and determining whether a risk exists for the target dredging construction vessel. Effect of the Invention

[0007] The beneficial effects of the present invention are as follows: (1) The present invention separately analyzes the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and then comprehensively judges whether a wave risk situation will appear in each monitoring area. Such an analysis method realizes all-round risk control for the dredger's ship operations, effectively reduces the risks of ship collision, capsizing and facility damage, supports accurate decision-making, provides a reliable basis for optimizing dredging work routes, etc., and improves work efficiency. (2) According to the judgment result of whether the wave risk situation occurs in each monitoring area, the present invention further judges whether the target dredging vessel has a risk, and such an analysis method can accurately judge the risk faced by the target dredging vessel, give early warning, effectively reduce the risk of damage caused by the wave impact of the vessel, ensure the life safety of the crew and the integrity of the vessel's equipment, and at the same time, it can support navigation decision-making, optimize the route and adjust the work strategy based on the accurate risk judgment result, reduce the probability of the vessel blindly entering the risk sea area, ensure the smooth implementation of the navigation plan, and complete the work on time. [Brief description of the drawings]

[0008] In order to more clearly describe the technical aspects of the embodiments of the present invention, the following briefly describes the drawings that need to be used for the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without paying creative labor. [Figure 1] FIG. 2 is a connection diagram of each module of the system of the present invention. [Diagram 2] FIG. 2 is a schematic diagram of a division of a monitoring area according to one embodiment provided by the present invention. [Diagram 3] FIG. 2 is a schematic diagram of a curl angle analysis of a wave peak according to one embodiment provided in the present invention. [Figure 4] 1 is a flow chart of the method of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in combination with the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative labor belong to the protection scope of the present invention.

[0010] As shown in Figure 1, the present invention proposes a wave monitoring system for construction areas based on image information recognition, which includes a monitoring area setting module, a wave image collection module, a wave parameter analysis module, a break condition monitoring module, a swell condition monitoring module, and a risk situation recognition module, where the monitoring area setting module is connected to the wave image collection module, the wave image collection module is respectively connected to the wave parameter analysis module, the break condition monitoring module, and the swell condition monitoring module, and the wave parameter analysis module, the break condition monitoring module, and the swell condition monitoring module are all connected to the risk situation recognition module.

[0011] The monitoring area setting module is used to obtain the position of the target dredging work vessel, and further obtain an influence area based on a preset setting area area, divide the monitoring area for the influence area to obtain several monitoring areas, and set the center point of each monitoring area as a monitoring point.

[0012] It should be noted that, referring to Figure 2, the specific method for dividing the monitoring area is as follows: obtain the position of the target dredging work vessel, and then obtain the affected area with the position of the target dredging work vessel as the center point. Then, divide the affected area based on the pre-set area to obtain several monitoring areas, and the area of ​​each monitoring area is consistent.

[0013] The wave image collecting module is used to collect images at corresponding monitoring points in each monitoring area using the unmanned aerial vehicle, and obtain wave images in each monitoring area.

[0014] The drone is equipped with a high-definition camera and collects several ocean wave images at each monitoring point.

[0015] The wave parameter analysis module is used to obtain wave data of each monitoring area, including wave height and period, based on the wave image of each monitoring area, and further analyze the wave risk assessment status of each monitoring area.

[0016] It should be noted that the method for obtaining the wave height is as follows: extract several wave images collected using an unmanned aerial vehicle, obtain the wave height of the monitoring point corresponding to each wave image, compare the wave heights in each wave image to obtain the maximum height and minimum height, calculate the difference between the maximum height and minimum height of the monitoring point in the wave image corresponding to each monitoring area, and then multiply by half to obtain the wave height of each monitoring area.

[0017] It should be noted that the method for obtaining the above-mentioned period is as follows: several wave images collected by an unmanned vehicle and the corresponding collection times are extracted, the collection time difference between each peak and the adjacent valley is obtained, and then an average value calculation is performed to obtain the wave period of each monitoring area.

[0018] In a preferred embodiment of the present invention, in order to analyze the wave risk assessment situation of each monitoring area, a wave risk assessment index for each monitoring area needs to be established, and the specific method is as follows: The wave height and period of each monitoring area are extracted and H i , T i Here, i is the number of the monitoring area, i=1, 2.....I, I is the number of monitoring areas, and the following formula is used for analysis:

[0019]

number

[0020] Wave risk assessment index for each monitoring area: Whei i Here, H 0 is the preset reference wave height, and T0 is a preset reference period.

[0021] The reason why wave height and period are selected as the influencing factors of the wave risk assessment index of each monitoring area is that wave height intuitively represents the energy of waves, the higher the value, the stronger the energy, and the greater the impact force, the higher the risk of destruction to the wind power base of offshore facilities such as drilling platforms and ships, and also has a great impact on the stability of ships. When small ships encounter waves that exceed the limit of wave height, they are prone to runaway and capsize, and it is closely related to wave breaks, and when they reach a certain height, they are prone to break under certain conditions, and the strong current caused by the break will cause great harm. Meanwhile, the period reflects the wave rhythm of the waves, and the long-period swell will cause ships to be subjected to uneven forces for a long time, making the structure easily fatigued and damaged, which will also affect the efficiency of marine work. Wave height and period work together to accurately measure the list level of waves, providing an important basis for early warning and protection.

[0022] The breaking condition monitoring module obtains wave peak images for each monitoring area based on wave images for each monitoring area, analyzes the curl condition of the wave peaks for each monitoring area, judges whether waves are breaking in each monitoring area, and if so, records the breaking position and breaking height, which are used to analyze the wave breaking risk assessment condition for each monitoring area.

[0023] In addition, the reasons for monitoring the wave breaking situation in each monitoring area are very important, and the reasons are mainly embodied in many aspects. From the viewpoint of safety, the huge impact force generated by wave breaking can bring huge lists to offshore structures such as breakwaters and offshore platforms, which can loosen stones and collapse structures, endangering the safety of personnel and facilities. The navigation of ships is affected by this, and when they encounter breaking waves, they will be violently shaken, making steering difficult, and prone to collisions and capsizing accidents. From the viewpoint of marine work, it is unfavorable to the development of construction works such as dredging and offshore wind power generation, reducing work efficiency and damaging equipment.

[0024] In a preferred embodiment of the present invention, referring to FIG. 3, in order to analyze the curl situation of the wave peak in each monitoring area, it is necessary to construct a curl index of the wave peak in each monitoring area, the specific method is as follows: a wave peak image in each monitoring area is extracted, and then an edge detection method is used to obtain the contour of the wave peak edge in each monitoring area, and an image processing software is used to obtain the tangential direction of the apex corresponding to the wave peak edge in each monitoring area, and the angle between the tangential direction of the wave peak apex in each monitoring area and the horizontal direction is represented as the curl angle of the wave peak in each monitoring area.

[0025] The curl angle of the wave peak in each monitoring area is compared with the curl angle of a preset reference wave peak to calculate the curl index of the wave peak in each monitoring area.

[0026] The reason for judging whether a wave break will occur in each monitoring area based on the wave peak curl index is that, firstly, the wave peak curl is the most intuitive representation feature before the wave breaks, and when the peak starts to curl, it means that the energy distribution in the wave changes, the water movement state becomes unbalanced, and it enters the breaking stage. Secondly, this index is easy to extract quantization from observation data such as images and videos, and through advanced image recognition algorithms, it can accurately capture the shape changes of the peak and quickly convert them into comparable data. In addition, compared with other complex and indirect judgment methods, judgment based on the peak curl index is more time-effective, and can issue an alarm at the moment when the wave breaks or just before it breaks, so that offshore workboats can evacuate in a timely manner and buy valuable time for response measures such as early reinforcement of coastal protection facilities.

[0027] In a preferred embodiment of the present invention, the specific method for determining whether waves are breaking in each monitoring area is as follows: extract the wave peak curl index of each monitoring area, and then compare it with a preset wave peak curl index threshold value. If the wave peak curl index of a monitoring area is greater than the preset wave peak curl index threshold value, it is determined that waves are breaking in the monitoring area, and conversely, it is determined that waves are not breaking in the monitoring area.

[0028] As an example, the threshold value for the curl exponent of the wave peak is 0.4.

[0029] In addition, when determining whether waves are breaking in each monitoring area, the basis for setting the threshold value of the wave peak curl index is, first, to originate from the deep drilling and statistical analysis of past wave data, to monitor a specific or similar sea area for a long time, to collect a large number of wave images and information, to accurately quantify the wave breaking peak curl index each time, to synthesize the statistical characteristics under different sea conditions, water depths, and topography, such as average values, standard differences, etc., and to take a reasonable value based on this, for example, a certain shallow sea work area will provisionally determine the threshold value based on many years of observation. Secondly, using the marine dynamics model simulation, inputting the local marine geography and meteorological data, simulating the change of wave generation and disappearance, focusing on the index change from the shape of the wave peak to the breaking criticality, and making the simulation fit the reality through repeated adjustments, to provide support for determining the threshold value, for example, setting restrictions based on this in the sea area of ​​the construction wind power field.

[0030] In a preferred embodiment of the present invention, in order to analyze the wave break risk assessment situation of each monitoring area, it is necessary to establish a wave break risk assessment index for each monitoring area, the specific method of which is as follows: The monitoring area where waves break is designated as the wave break monitoring area, and the break height of each wave break monitoring area is extracted and PH j Here, j indicates the number of the wave break monitoring area, j=1, 2....J, and J indicates the number of wave break monitoring areas.

[0031] The breaking height means the peak height when the waves break.

[0032] The break position of each wave break monitoring area and the current position of the target dredging work vessel are extracted, and the break position of each wave break monitoring area and the current position of the target dredging work vessel are connected to obtain the wave break influence path corresponding to each wave break monitoring area. Furthermore, the length of the wave break influence path corresponding to each wave break monitoring area is set as the break influence distance of each wave break monitoring area, and the PL j and analyzed using the following formula:

[0033]

number

[0034] Wave break risk assessment index Wbhei for each wave break monitoring area j Here, PH 0 Indicates the preset reference break height, PL 0 indicates a preset reference break influence distance, and e indicates the Napier's number.

[0035] In addition, the reason why breaking height and breaking impact distance are selected as the influencing factors of wave breaking risk assessment index is that breaking height is the scale that intuitively represents the energy release when waves break, and the impact force is strong when the energy is huge, which will cause structural destruction to berthing facilities such as breakwaters and wharves, bring the risk of capsizing to marine vessels such as dredging vessels, endanger the safety of crew and equipment, and also disrupt the physical and chemical properties and destroy the marine ecosystem. Break impact distance can accurately define the scope of damage, and its distance determines whether the dredging vessel is directly affected. When the distance is short, the water current and wave motion caused by breaking waves will interfere with the positioning of vessels and the operation of dredging equipment, hindering the work. In marine engineering planning, it is related to the location and protection layout of facilities such as offshore wind power plants, and the comprehensive two can accurately evaluate the list and ensure safety and stability in all aspects.

[0036] The wave break risk assessment index corresponding to the monitoring area where waves are not breaking is recorded as 0.

[0037] The swell condition monitoring module uniformly arranges each monitoring area to obtain several collection points, obtains the monitoring water level of each collection point corresponding to each monitoring area based on the wave image of each monitoring area, analyzes the similarity situation of the water level change in each monitoring area, judges whether wave swell occurs in each monitoring area, and if so, records the water level and duration of the swell, which is used to analyze the wave swell risk assessment situation of each monitoring area.

[0038] In addition, the reason for monitoring wave swell is that from the viewpoint of work safety, swell seriously threatens the stability of the ship, causing the ship to rock violently, which is likely to cause injury to crew members, and may damage the precision parts of the dredging equipment, greatly increasing the repair cost and the risk of work interruption; at the same time, under strong swell, the ship is likely to run out of control, and once it runs out of control in the work area or the surrounding complex water area, it may collide with auxiliary ships or passing ships, block the navigation route, and affect the operation of the port. From the viewpoint of work efficiency, swell interferes with the accurate operation of the dredging equipment, making it difficult for the grab bucket to accurately grab the sediment, causing the position of the suction pipe to shift, reducing the sludge suction efficiency, prolonging the work time, and bringing many obstacles to the smooth progress of the dredging work, so monitoring of swell cannot be delayed for a moment.

[0039] In a preferred embodiment of the present invention, in order to analyze the similarity of the water level changes in each monitoring area, it is necessary to construct a similarity index of the water level changes in each monitoring area, the specific method of which is as follows: Obtain the monitoring water levels of each collection point corresponding to each monitoring area, and then calculate the similarity index of the water level changes in each monitoring area. iz Here, z indicates the number of collection points, z=1, 2.....Z, z indicates the number of collection points, The analysis was carried out using the following formula:

[0040]

number

[0041] Similarity index of water level changes in each monitoring area (Wlcsi) i Here, SH 0 is the preset reference water level.

[0042] The reason why the similarity index of water level change is chosen as the basis for judging whether wave swell occurs is that, from the basic principles of physics, swell, as a wave motion of a water body, inevitably causes a rapid rise and fall of the water level, which is very different from the gradual water level changes such as normal tides, and this index can exactly capture this difference, and by comparing the actual measurement with the normal water level change mode, when swell occurs, the index can sensitively detect the deviation of the water level change from the normal state. It also has a remarkable effect in practical application, and based on long-term monitoring data, it can accurately define the normal range of water level change under different sea conditions, and can rapidly judge swell, is convenient to operate, and data is easily available, which can provide a timely and reliable decision basis for early warning of offshore work vessels and to assist the activation of coastal protection facilities.

[0043] In a preferred embodiment of the present invention, in order to determine whether a wave swell has occurred in each monitoring area, the specific method is as follows: extract the similarity index of water level changes in each monitoring area, and then compare it with a preset similarity index threshold of water level changes. If the similarity index of water level changes in a certain monitoring area is greater than the preset similarity index threshold of water level changes, it is determined that a wave swell has occurred in the monitoring area, and conversely, it is determined that a wave swell has not occurred in the monitoring area.

[0044] As an example, the threshold for the similarity index of water level change is 0.5.

[0045] The basis for setting the threshold value of the water level change similarity index comes from the system analysis and deep drilling of past water level data. Water level monitoring activities have been carried out in each monitoring area in a long-term, continuous and high-frequency manner, and large-scale, detailed and complete water level change data has been accumulated. Based on this, the data has been refined and classified and deeply explored based on multi-dimensional factors such as seasonal changes, weather conditions and time characteristics. Using scientific statistical methods, the important characteristic values ​​of water level changes under normal non-swell conditions, including average values, standard differences, wave sections, etc., are accurately extracted, and thus the "standard change mode" of water level is constructed. At the same time, the unique characteristics of the local sea area, such as the seabed topography and water flow direction, have been fully taken into consideration, and a more scientific and reasonable threshold value has been determined through comprehensive consideration and careful judgment.

[0046] In a preferred embodiment of the present invention, in order to analyze the wave swell risk evaluation situation of each monitoring area, it is necessary to construct a wave swell risk evaluation index for each monitoring area, and the specific method is as follows: The monitoring area where a wave swell occurs is set as the wave swell monitoring area, and the swell water level and the swell time length of each wave swell monitoring area are extracted, and the LH k , L.T. k Here, k indicates the number of the wave swell monitoring area, k=1, 2.....K, and K indicates the number of wave swell monitoring areas.

[0047] The monitoring point position of each wave swell monitoring area and the current position of the target dredging work vessel are extracted, and the monitoring point position of each wave swell monitoring area and the current position of the target dredging work vessel are connected to obtain several wave swell influence paths. The length of the wave swell influence path corresponding to each wave swell monitoring area is the swell influence distance of each wave swell monitoring area, which is denoted as LLk, and is analyzed using the following formula:

[0048]

number

[0049] Wave swell risk assessment index (Wshei) for each monitoring area kHere, LH 0 indicates the water level of the predefined reference wave swell, and LT 0 indicates the duration of the predefined reference wave swell, and LL 0 indicates the preset reference swell influence distance.

[0050] In addition, the reason for choosing the water level of the wave swell, the length of time of the wave swell and the influence distance of the wave swell as the influencing factors of the wave swell risk assessment index is that the water level of the wave swell intuitively reveals the strength of the energy of the wave swell. The higher the water level, the stronger the impact. It can not only cause structural destruction to breakwaters, wharves, etc., but also submerge coastal areas, expose lives and property to the list, and disrupt the marine ecosystem. The length of the wave swell determines the continuity of the harm. The long-term swell makes marine facilities unable to bear the heavy load, stagnates offshore operations, and inhibits the reproduction of marine organisms. The influence distance of the swell defines the scope of the damage, which hinders the work of dredging vessels close to the swell source, endangers safety, and has a profound impact on marine engineering planning and the balance of the ecosystem. By taking the three into consideration comprehensively, the list can be accurately evaluated and marine activities and ecological safety can be protected.

[0051] The wave swell risk assessment index corresponding to the monitoring area where no wave swell occurs is recorded as 0.

[0052] The risk situation recognition module is used to judge whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and to judge whether a risk exists for the target dredging work vessel.

[0053] In a preferred embodiment of the present invention, a specific method for determining whether there is a wave risk situation in each monitoring area is as follows: The wave risk assessment index, wave break risk assessment index, and wave swell risk assessment index of each monitoring area are extracted, and then added according to the weight to obtain the wave risk assessment index of each monitoring area; The wave risk assessment index of each monitoring area is compared with a predetermined wave risk assessment index threshold value, and if the wave risk assessment index of a certain monitoring area is greater than the predetermined wave risk assessment index threshold value, it is determined that a wave risk situation has occurred in that monitoring area, and conversely, it is determined that no wave risk situation exists in that monitoring area.

[0054] For example, the weights corresponding to the wave risk assessment index, the wave break risk assessment index and the wave swell risk assessment index are 0.4, 0.3 and 0.3, respectively.

[0055] The basis for setting the weights corresponding to the wave risk assessment index, wave break risk assessment index and wave swell risk assessment index is, firstly, to accurately consider the frequency and probability of disaster occurrence, and then use the long-term ocean monitoring information to statistically determine the occurrence frequency of various wave disasters in different sea areas, and then, in a certain area, wave breaks occur frequently, and waves occur accidentally, the former is a big daily threat, and the corresponding weight is high; in addition, according to the seasonal and periodic characteristics, the wave list increases greatly in the typhoon season, and the weight is subdivided according to the expression at the time of each disaster, and the weight is increased when there are many breaks. Next, based on the damage degree and loss scale, the damage situation of the wharf, platform and other marine facilities is evaluated, the wave breaker impacts the breakwater, and the wave swell evaluates the wharf equipment, and quantifies according to the repair cost and time consumption. At the same time, the impact on marine operations, the obstruction of ship navigation caused by swell, and the list of berthing operations caused by breaks are considered, and comprehensive consideration is given to ensure the scientific rationality of the weight and accurately reflect the list degree.

[0056] The wave risk assessment index of each monitoring area is compared with a predetermined wave risk assessment index threshold value, and if the wave risk assessment index of a certain monitoring area is greater than the predetermined wave risk assessment index threshold value, it is determined that a wave list situation has occurred in that monitoring area, and conversely, it is determined that no wave list situation exists in that monitoring area.

[0057] In addition, the present invention separately analyzes the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and then makes a comprehensive judgment on whether a wave risk situation will occur in each monitoring area. This analysis method realizes all-round risk control for the dredger's ship operations, effectively reduces the risks of ship collision, capsizing and facility damage, supports accurate decision-making, provides a reliable basis for optimizing dredging work routes, etc., and improves work efficiency.

[0058] In a preferred embodiment of the present invention, a specific method for determining whether a list exists in the target dredging vessel is as follows: The monitoring area that is judged to have a wave risk condition is designated as a risk area, the number of risk areas and the number of monitoring areas are statistically obtained, and the ratio of the number of risk areas and the number of monitoring areas is calculated to obtain the ratio of risk areas. The risk area ratio is compared with a preset risk area ratio threshold, and if the risk area ratio is greater than the preset risk area ratio threshold, it is determined that there is a risk to the target dredging work vessel, and conversely, it is determined that there is no risk to the target dredging work vessel.

[0059] In addition, the present invention further judges whether there is a risk to the target dredging vessel based on the judgment result of whether the wave risk situation occurs in each monitoring area, and such analysis method can accurately judge the risk faced by the target dredging vessel, give early warning, effectively reduce the risk of damage caused by the wave impact of the vessel, ensure the life safety of the crew and the integrity of the vessel's equipment, and at the same time, it can support navigation decision-making, optimize the route and adjust the work strategy based on the accurate risk judgment result, reduce the probability of the vessel blindly entering the risk sea area, ensure the smooth implementation of the navigation plan, and complete the work on time.

[0060] In addition, the present invention discloses a method for monitoring waves in a construction area based on image information recognition, as shown in FIG. Step 1: A monitoring area setting step of obtaining the position of the target dredging vessel, obtaining an influence area based on a preset setting area area, dividing the monitoring area into several monitoring areas based on the influence area, and setting the center point of each monitoring area as a monitoring point; Step 2: A wave image collection step of using a drone to collect images at corresponding monitoring points in each monitoring area to obtain wave images in each monitoring area; where step 2 is related to step 3, step 4, and step 5; Step 3 is a wave parameter analysis step to obtain wave data for each monitoring area, including wave height and period, based on the wave images of each monitoring area, and further analyze the wave risk assessment status of each monitoring area. Step 3 is related to Step 6, Step 4: A wave breaking status monitoring step, which obtains a wave peak image of each monitoring area based on the wave image of each monitoring area, analyzes the curl status of the wave peak of each monitoring area, judges whether waves are breaking in each monitoring area, and if so, records the breaking position and breaking height, and analyzes the wave breaking risk evaluation status of each monitoring area; where, step 4 is related to step 6, Step 5: a swell condition monitoring step of uniformly arranging each monitoring area to obtain several collection points, obtaining the monitoring water level of each collection point corresponding to each monitoring area according to the wave image of each monitoring area, analyzing the similarity situation of the water level change in each monitoring area, determining whether wave swell occurs in each monitoring area, and if so, recording the water level and the duration of the swell, and analyzing the wave swell risk evaluation situation of each monitoring area; where, step 5 is related to step 6, Step 6 includes a risk situation recognition step of judging whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status and wave swell risk assessment status of each monitoring area, and determining whether a risk exists for the target dredging construction vessel.

[0061] The above are merely examples and explanations of the concept of the present invention, and should fall within the protection scope of the present invention as long as they do not deviate from the concept of the present invention or go beyond the scope defined by the present invention. Those skilled in the art may make various modifications or supplements to the specific embodiments described or substitute them in similar ways. [Explanation of symbols]

[0062] 1, location of target dredging vessel; 2, impact area; 3, monitoring area; 4, monitoring point; 5, contour of wave peak edge; 6, vertex corresponding to wave peak edge; 7, tangential direction; 8, curl angle of wave peak; 9, horizontal direction.

Claims

1. A wave monitoring system for a construction area based on image information recognition, A monitoring area setting step module for obtaining the position of a target dredging vessel, obtaining an influence area based on a preset setting area area, dividing a monitoring area for the influence area to obtain several monitoring areas, and setting the center point of each monitoring area as a monitoring point; a wave image collection module for collecting images at corresponding monitoring points in each monitoring area using a drone to obtain wave images in each monitoring area; a wave parameter analysis module for acquiring wave data for each monitoring area, including wave height and period, based on the wave image of each monitoring area, and further analyzing the wave risk assessment status of each monitoring area; a wave break status monitoring module for obtaining wave peak images for each monitoring area based on wave images for each monitoring area, analyzing the curl status of wave peaks for each monitoring area, determining whether waves are breaking in each monitoring area, and if so, recording the breaking position and breaking height, and analyzing the wave break risk assessment status for each monitoring area; a swell condition monitoring module for obtaining several collection points by uniformly arranging each monitoring area, obtaining the monitoring water level of each collection point corresponding to each monitoring area based on the wave image of each monitoring area, analyzing the similarity situation of the water level change in each monitoring area, determining whether wave swell occurs in each monitoring area, and if so, recording the water level and the duration of the swell, and analyzing the wave swell risk evaluation situation of each monitoring area; A wave monitoring system for a construction area based on image information recognition, characterized in including a risk situation recognition module for determining whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status, and wave swell risk assessment status of each monitoring area, and for determining whether a risk exists for the target dredging construction vessel.

2. In order to analyze the wave risk assessment situation of each monitoring area, it is necessary to establish a wave risk assessment index for each monitoring area, the specific method of which is as follows: The wave height and period of each monitoring area are extracted, and H ｉ , T ｉ Here, i is the number of the monitoring area, i=1, 2...I, I is the number of the monitoring area, and the following formula is used for analysis: [0050] Wave risk assessment index for each monitoring area: ｉ Here, H ０ is a preset reference wave height, and T ０ The wave monitoring system for a construction area based on image information recognition according to claim 1, characterized in that:

3. In order to analyze the wave peak curl situation of each monitoring area, it is necessary to establish the wave peak curl index of each monitoring area, the specific method of which is as follows: The wave peak image of each monitoring area is extracted, and the contour of the wave peak edge of each monitoring area is obtained using an edge detection method. The tangent direction of the apex corresponding to the wave peak edge of each monitoring area is obtained using image processing software. The angle between the tangent direction and the horizontal direction of the wave peak apex of each monitoring area is represented as the wave peak curl angle of each monitoring area. A wave monitoring system for construction areas based on image information recognition as described in claim 1, characterized in that the curl index of the wave peak in each monitoring area is calculated by comparing the curl angle of the wave peak in each monitoring area with the curl angle of a predetermined reference wave peak.

4. The specific method for determining whether waves are breaking in each monitoring area is as follows: A wave monitoring system for construction areas based on image information recognition as described in claim 3, characterized in that the wave peak curl index of each monitoring area is extracted and further compared with a predetermined wave peak curl index threshold value, and if the wave peak curl index of a certain monitoring area is greater than the predetermined wave peak curl index threshold value, it is determined that waves are breaking in that monitoring area, and conversely, it is determined that waves are not breaking in that monitoring area.

5. In order to analyze the wave break risk assessment situation of each monitoring area, it is necessary to establish a wave break risk assessment index for each monitoring area, the specific method of which is as follows: The monitoring area where waves break is designated as the wave break monitoring area, and the break height of each wave break monitoring area is extracted, and PH ｊ where j is the number of the wave break monitoring area, j=1, 2...J, J is the number of the wave break monitoring area, The break position of each wave break monitoring area and the current position of the target dredging work vessel are extracted, and the break position of each wave break monitoring area and the current position of the target dredging work vessel are connected to obtain the wave break influence path corresponding to each wave break monitoring area. Furthermore, the length of the wave break influence path corresponding to each wave break monitoring area is set as the break influence distance of each wave break monitoring area, and the PL ｊ and analyzed using the following formula: [006] Wave break risk assessment index Wbhei for each wave break monitoring area ｊ Here, PH ０ Indicates the preset reference break height, PL ０ indicates a preset reference break influence distance, e indicates Napier's number, A wave monitoring system for a construction area based on image information recognition as described in claim 2, characterized in that a wave break risk evaluation index corresponding to a monitoring area where waves are not breaking is recorded as 0.

6. In order to analyze the similarity of water level changes in each monitoring area, it is necessary to construct a similarity index of water level changes in each monitoring area, the specific method of which is as follows: Obtain the monitored water level of each collection point corresponding to each monitoring area, and ｉｚ Here, z indicates the number of collection points, z=1, 2...Z, z indicates the number of collection points, The analysis was carried out using the following formula: [0070] Similarity index of water level changes in each monitoring area (Wlcsi) ｉ Here, SH ０ The wave monitoring system for a construction area based on image information recognition according to claim 5, characterized in that:

7. The specific method for determining whether wave swell occurs in each monitoring area is as follows: A wave monitoring system for construction areas based on image information recognition as described in claim 6, characterized in that the similarity index of water level changes for each monitoring area is extracted and further compared with a predetermined similarity index threshold of water level changes, and if the similarity index of water level changes for a certain monitoring area is greater than the predetermined similarity index threshold of water level changes, it is determined that a wave swell has occurred in the monitoring area, and conversely, it is determined that a wave swell has not occurred in the monitoring area.

8. In order to analyze the wave swell risk assessment situation of each monitoring area, it is necessary to establish a wave swell risk assessment index for each monitoring area, the specific method is as follows: The monitoring area where the wave swell occurred is designated as the wave swell monitoring area, and the swell water level and the length of the swell time in each wave swell monitoring area are extracted, and the LH ｋ , L.T. ｋ where k is the number of the wave swell monitoring area, k = 1, 2...K, K is the number of the wave swell monitoring areas, The monitoring point position of each wave swell monitoring area and the current position of the target dredging work vessel are extracted, and the monitoring point position of each wave swell monitoring area and the current position of the target dredging work vessel are connected to obtain several wave swell influence paths. The length of the wave swell influence path corresponding to each wave swell monitoring area is defined as the swell influence distance of each wave swell monitoring area. ｋ and analyzed using the following formula: [0080] Wave swell risk assessment index Wshei for each monitoring area ｋ Here, LH ０ indicates the water level of the reference wave swell that was set in advance, and LT ０ is the length of time of the predefined reference wave swell, L ０ indicates the preset reference swell influence distance, A wave monitoring system for a construction area based on image information recognition as described in claim 5, characterized in that a wave swell risk evaluation index corresponding to a monitoring area where no wave swell is occurring is recorded as 0.

9. The specific method for determining whether there is a wave risk situation in each monitoring area is as follows: The wave risk assessment index, wave break risk assessment index, and wave swell risk assessment index of each monitoring area are extracted, and then added according to the weight to obtain the wave risk assessment index of each monitoring area; A wave monitoring system for construction areas based on image information recognition as described in claim 8, characterized in that the wave risk assessment index of each monitoring area is respectively compared with a predetermined wave risk assessment index threshold value, and if the wave risk assessment index of a certain monitoring area is greater than the predetermined wave risk assessment index threshold value, it is determined that a wave risk situation has occurred in the monitoring area, and conversely, it is determined that no wave risk situation exists in the monitoring area.

10. A specific method for determining whether the target dredging vessel has a list is as follows: The monitoring area that is judged to have a wave risk condition is designated as a risk area, the number of risk areas and the number of monitoring areas are statistically obtained, and the ratio of the number of risk areas and the number of monitoring areas is calculated to obtain the ratio of risk areas. A wave monitoring system for a construction area based on image information recognition as described in claim 9, characterized in that the risk area ratio is compared with a predetermined risk area ratio threshold, and if the risk area ratio is greater than the predetermined risk area ratio threshold, it is determined that there is a risk to the target dredging work vessel, and conversely, it is determined that there is no risk to the target dredging work vessel.

11. A method for monitoring waves in a construction area based on image information recognition, comprising: Step 1: A monitoring area setting step of obtaining the position of the target dredging vessel, obtaining an influence area based on a preset area area, dividing the influence area into several monitoring areas, and setting the center point of each monitoring area as a monitoring point; Step 2: A wave image collection step of using a drone to collect images at corresponding monitoring points in each monitoring area to obtain wave images in each monitoring area; where step 2 is related to step 3, step 4, and step 5; Step 3: A wave parameter analysis step of obtaining wave data for each monitoring area, including wave height and period, based on the wave images of each monitoring area, and further analyzing the wave risk assessment status of each monitoring area; Step 3 is related to Step 6, Step 4: A wave breaking status monitoring step of obtaining a wave peak image of each monitoring area based on the wave image of each monitoring area, analyzing the curl status of the wave peak of each monitoring area, determining whether waves are breaking in each monitoring area, and if they are breaking, recording the breaking position and breaking height, and analyzing the wave breaking risk evaluation status of each monitoring area; where, step 4 is related to step 6, Step 5: a swell condition monitoring step of uniformly arranging each monitoring area to obtain several collection points, obtaining the monitoring water level of each collection point corresponding to each monitoring area according to the wave image of each monitoring area, analyzing the similarity situation of the water level change in each monitoring area, determining whether wave swell occurs in each monitoring area, and if so, recording the water level and the duration of the swell, and analyzing the wave swell risk evaluation situation of each monitoring area; where step 5 is related to step 6, Step 6: a risk situation recognition step of judging whether a wave risk situation has occurred in each monitoring area based on the wave risk assessment status, wave break risk assessment status, and wave swell risk assessment status of each monitoring area, and judging whether a risk exists for the target dredging construction vessel; A method for monitoring waves in a construction area based on image information recognition, comprising:

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