CN113834523B - Marine pasture intelligent breeding system based on unmanned ship - Google Patents
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Abstract
The invention relates to an intelligent marine pasture cultivation system based on an unmanned ship, which solves the technical problem that how to apply the unmanned ship to detect and manage the marine pasture environment is a technical problem to be solved urgently by the skilled person, and the working process is as follows: (1) Setting operation targets such as an unmanned ship working area, a return position and the like through a ground station and control software, and releasing the unmanned ship to a target sea area; (2) After the unmanned ship reaches the target sea area, the unmanned ship automatically plans a path to operate through the autonomous controller of the unmanned ship, and starts the shipborne environment detection module to collect and detect the fishery water quality index. And simultaneously, the ship-borne communication module transmits all environmental indexes of the target sea area back to the ground station in real time. When the shipborne environment detection module detects that a certain fishery water quality index of the target sea area is abnormal, starting the shipborne water quality maintenance device to improve the water quality of the target sea area; (3) After the unmanned ship finishes the operation, the unmanned ship returns to and maintains at a preset return position, and the personnel can go to the preset position for recovery.
Description
Technical Field
The invention relates to the field of analysis and measurement control, in particular to an intelligent marine pasture cultivation system based on an unmanned ship.
Background
With the gradual increase of the fishing intensity, the marine pollution range is continuously enlarged, the decay phenomenon of marine fishery resources in China is increasingly serious, and the mariculture industry is rapidly developed in recent years as a supplement to the marine fishing. But the problems of environment, disease and quality safety brought by mariculture are increasingly remarkable, and the resources and environment in the development of fishery and a series of problems brought by the environment become one of the bottlenecks restricting the sustainable development of the mariculture industry and even the marine fishery in China. Research, development and application of the marine pasture become strategic choices of the main marine country, and are one of the main attack directions of fishery development in developed countries in the world, so that the research and development of the marine pasture are worthy of close attention and study in China.
In which intensive and continuous research on marine ecological monitoring and biological resource management is necessary for sustainable development of marine ranches. The construction of monitoring capability, including the monitoring of ecological environment quality and the monitoring of biological resources, strengthens the protection and treatment of the water quality environment of the marine pasture, and is an important guarantee for maintaining the sustainable development of the marine pasture industry. However, the fishery monitoring work is difficult to frequently monitor due to various factors such as large workload, wide working range and the like, so that the relevant monitoring data of the water quality condition of the fishery sea area cannot be updated in time. At present, domestic environment monitoring ships are still few, and similar products mainly represent the following two types: (1): "astronomical image number one" unmanned marine survey vessel. The weather detection system of the astronomical ship with the astronomical character number one can provide measured values of wind speed, wind direction, air temperature, humidity, water temperature and the like. The main operation object is a meteorological condition. The astronomical phenomenon No. one makes great contribution to weather guarantee service of Qingdao Sail of Beijing Olympic Games, which is also the first application of unmanned ships in the world for weather detection. (2) "Changjiang river water ring prison 2000". The monitoring ship can rapidly and accurately monitor the water environment of the Yangtze river, monitor and control the sewage discharge condition of the river along the river, and dynamically monitor the water body of province, key pollution river segments and water pollution accidents. The ship is put into use in 2000, and is specially provided with a plurality of sets of professional equipment before the 'Yangtze river action' is started.
The current research on the marine ranching environment detection technology mainly comprises the following steps: the system comprises a water quality automatic monitoring system, a smoke dust and SO2 online automatic monitoring system, an organic pollutant automatic continuous monitoring system, a heavy point pollution source monitoring system, online portable emergency monitoring equipment and the like.
Therefore, how to use unmanned ships to detect and manage the marine ranching environment is a technical problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The invention provides an intelligent marine pasture cultivation system based on an unmanned ship, which aims to solve the technical problem that how to detect and manage the marine pasture environment by using the unmanned ship is a technical problem to be solved urgently by a person skilled in the art.
The invention discloses an intelligent maritime pasture breeding system based on an unmanned ship, which comprises a ground station, the unmanned ship, an environment detection module, a sensor fusion sensing module, an adaptive intelligent decision module and a water quality maintenance device, wherein the unmanned ship is provided with an unmanned ship autonomous controller, a communication module and a Beidou navigation device; the environment detection module, the sensor fusion sensing module, the adaptive intelligent decision module and the water quality maintenance device are respectively arranged on the unmanned ship;
the environment detection module is configured to continuously track and monitor the marine pasture environment in real time and detect various water quality parameters of the fishery water;
the sensor fusion sensing module is configured to perform fusion processing analysis on the water quality parameter data detected by the environment detection module; the data after the fusion processing analysis is transmitted to the ground station through the communication module;
the ground station is configured to set a working area of the unmanned ship, a return position and release the unmanned ship to a target sea area; the sensor fusion sensing module is used for receiving the data after fusion processing analysis, judging and analyzing the real-time state of the marine pasture, and judging whether the water quality parameters are in a normal range or not;
the water quality maintenance device is configured to be started to improve water quality when the ground station judges that the water quality parameter is not in a normal range;
the unmanned ship autonomous controller is configured to control the unmanned ship to run in a data driving mode according to the data information and the multi-time and space scale information output by the sensor fusion sensing module after the unmanned ship reaches a target sea area; and automatically planning a path to enable the unmanned ship to perform autonomous operation.
Preferably, the unmanned ship-based intelligent marine pasture cultivation system further comprises an adaptive intelligent decision module;
the adaptive intelligent decision module is configured to predict the marine ranch status based on real-time marine ranch status data and multi-time space scale data.
The invention has the beneficial effects that through the application of the technologies of autonomous navigation, environment detection, water quality maintenance and the like, the real-time monitoring of the marine ranch environment can be realized, the strong marine habitat monitoring and analyzing capability is formed, the automatic and intelligent construction of the marine ranch is promoted, and the interlocking economic benefit can be brought.
Compared with a manual driving monitoring ship, the unmanned ship can reach the monitored water area more accurately, and human resources are saved.
Can monitor various fishery water quality parameters and can realize real-time continuous tracking and monitoring of the marine pasture environment.
And (3) water quality index autonomous detection: the ship-borne environment detection device can judge whether the water quality parameter is in a normal range. When the water quality parameter is not in the normal range, the shipborne water quality maintaining device is started, the water quality is improved autonomously, and the intelligence of the ship is improved.
Clean energy power system: the unmanned ship carries a solar power supply system, so that zero pollution discharge of the unmanned ship is realized.
Perfect safety system: the unmanned ship is provided with various sensors, (such as an infrared pyroelectric sensor and a water inlet sensor) which can give an alarm in time when encountering emergency such as invasion of outsiders, obstacles and collision, so that the unmanned ship sailing operation is safe and reliable.
The integration level is high: the environment monitoring system is organically integrated with mature technologies such as GPS, so that a plurality of problems of system integration are solved, and the advantages of a single technology are converted into the advantages of an application system. Compared with other monitoring ships, the monitoring ship has small volume and convenient operation.
Further features and aspects of the present invention will become apparent from the following description of specific embodiments with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic structural view of the unmanned ship of the present invention;
FIG. 2 is a schematic diagram of an unmanned ship provided with an environment detection module, an adaptive intelligent decision module, a sensor fusion sensing module and a water quality maintenance device;
fig. 3 is a system schematic.
The symbols in the drawings illustrate:
1. unmanned ship 1-2, unmanned ship autonomous controller 1-3, communication module, 1-4, big dipper navigation device, 2, environment detection module, 3, water quality maintenance device, 4, adaptive intelligent decision module, 5, sensor fusion perception module.
Detailed Description
The invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1 and 2, the present invention is based on an unmanned ship and various sensors, and the unmanned ship 1 has an unmanned ship autonomous controller 1-2, a communication module 1-3, and a Beidou navigation device 1-4. The environment detection module 2, the sensor fusion sensing module 5, the adaptive intelligent decision module 4 and the water quality maintenance device 3 are respectively arranged on the hull of the unmanned ship 1.
The invention discloses an intelligent marine pasture detection and cultivation method based on an unmanned ship, which is mainly carried out by the following steps: (1) Setting operation targets such as an unmanned ship working area, a return position and the like through a ground station and control software, and releasing the unmanned ship to a target sea area; (2) After the unmanned ship reaches the target sea area, the unmanned ship automatically plans a path to operate through the autonomous controller of the unmanned ship, and starts the shipborne environment detection module to collect and detect the fishery water quality index. And simultaneously, the ship-borne communication module transmits all environmental indexes of the target sea area back to the ground station in real time. When the shipborne environment detection module detects that a certain fishery water quality index of the target sea area is abnormal, starting the shipborne water quality maintenance device to improve the water quality of the target sea area; (3) After the unmanned ship finishes the operation, the unmanned ship returns to and maintains at a preset return position, and workers can go to the preset position for recovery, or the unmanned ship is remotely controlled to navigate to the preset position and recover through a ground station and control software.
The environment detection module 2 integrates a batch of environment monitoring sensors, can realize real-time continuous tracking and monitoring of the marine pasture environment, and can detect various fishery water quality parameters such as water temperature, pH value, dissolved oxygen, heavy metal content, ammonia nitrogen and the like.
The sensor fusion perception module 5 is mainly used for carrying out calculation processing on the water quality parameter data detected by the environment detection module 2, mining deep-level connection among different sensor data, carrying out fusion processing analysis on the basis, and wirelessly transmitting the data after the fusion processing analysis to a ground station through the communication module 1-3, wherein software of the ground station carries out judgment analysis on the real-time state of the ocean pasture to judge whether the water quality parameter is in a normal range. When the water quality parameter is not in the normal range, the water quality maintaining device 3 is started to improve the water quality so as to maintain the water quality in the normal range. (for example, when the oxygen content of the water body is detected to be insufficient, the unmanned ship starts the ship-mounted aerator so as to increase and maintain the oxygen content of the water body of the target sea area to be within a normal range.
The control software on the ground station sets working targets such as unmanned ship working areas, return positions and the like, and releases the unmanned ship to the target sea area. After the unmanned ship reaches the target sea area, the unmanned ship autonomous controller 1-2 can control the unmanned ship to run in a data driving mode according to the data information and the multi-time and space scale information output by the sensor fusion sensing module 5. The specific analysis process for controlling the unmanned ship motion in a data-driven manner is as follows: firstly, the time alignment is designed and realized by a time stamp in a mode of combining software and hardware triggering, and after a hardware synchronous triggering signal is sent on the basis of remote communication, the level periodicity is realized effectively by programming in the system so as to realize simultaneous triggering, and the data collected by sensors with different sampling frequencies are optimized by a mode of a least square method so as to realize the time cooperativity. The spatial coordination is mainly realized by spatial coordinate conversion, and the same coordinate system calibration among different sensor data is realized, for example, the real coordinates of the image data are obtained by solving the internal and external parameter matrixes imaged by the camera, so that the same spatial contrast analysis with the radar data is realized. Secondly, preprocessing of multi-source sensor data, mining deep internal relations among different sensors, for example, simple image processing can acquire information of categories of targets and the like, and combining prior knowledge of the categories of the targets can iterate out actual three-dimensional contour information of the targets and the like better on the basis of radar and image data through a Bayesian network. The last part is based on the fusion processing of the multi-source sensor data, the part takes the sensor acquisition data and the corresponding marine environment state for a plurality of times as a training basis, and the fusion model is trained and optimized through the deep learning neural network, so that the analysis and judgment can be carried out on the multi-source data, and the incremental learning network is added in the practical application, so that the continuous learning and optimization are carried out on the basis of analyzing the new acquisition data.
The unmanned ship autonomous controller 1-2 can automatically plan a path to enable the unmanned ship to perform autonomous operation, and the autonomous path planning is based on the communication module 1-3 and the Beidou navigation device 1-4, and the specific implementation process is as follows:
taking the ocean pasture as a communication node n, and for a multi-ocean pasture network, n 1 ,n 2 ,n 3 ……n m Corresponding to sea pasture 1, sea pasture 2, sea pasture 3, up to sea pasture m, further, assume n 0 Is a port node.
A path type communication network is constructed according to distance information of a plurality of marine ranch nodes and port nodes. With port node n 0 Is the initial node P of the communication path 0 The kth communication path node is found by:
P k ＝n min (d(n k ,n k+1 ),d(n k ,n k+2 ),d(n k ,n k+3 ),...d(n k ,n m ))
in the above, d (n k ,n k+1 ) Representing the distance between the kth node and the k +1 node. The shortest distance is selected by traversing the distance value between the following node and the node at each node position to form the next node of the communication path network, so as to construct the whole shortest communication path network structure.
After the communication path network is constructed, each node gathers and senses the state and environment information of the ocean pasture through the multi-source sensor, the acquired information is transmitted to the previous node through the communication network, and the information of all the ocean pastures is transmitted back to the port step by step through the communication path network for comprehensive analysis and judgment.
After the analysis and judgment are completed, the information of each node is analyzed by the big data described in the part above, and the state of each marine pasture is analyzed, for example, the oxygen content replenishment state of the water quality of the marine pasture is recorded as S o Suppose S o Is a real value between 0 and 1, and the larger the real value is, the more the corresponding marine pasture needs to supplement oxygen to the water quality, S o (P n ) And (3) representing the oxygen content replenishment status of the water quality of the marine pasture at the nth node of the communication path. The autonomous navigation path of the unmanned ship is completed by the following formula:
in the above, U a (t) represents the magnitude of the potential force at the t position in the automatic path planning, and the larger the potential force is, the closer the t position is to the end point of the path planning, eta is a potential force coefficient and S o,goal S represents the water quality oxygen content replenishment state of the target position o (P t ) The water quality oxygen content replenishment state of the communication path node closest to the t position is represented, ρ represents absolute value information of a distance difference value, and the absolute value of a difference value between a distance between the initial node and the target node and a distance between the initial node and a current closest node is represented.
By gravitation function U a And (t) taking the communication path network as a pre-planned path, calculating the relative potential field values in the path, forming potential force difference, enabling the potential force value of the target position to be maximum, enabling the unmanned ship to traverse the whole communication path by combining the potential force values, and enabling the unmanned ship to quickly and efficiently reach a destination to supply oxygen content of water.
Similarly, the state diagnosis and the supplement of other marine pastures are basically consistent with the unmanned ship path rule method of the water quality oxygen content, and the state function is replaced only in the process of solving the potential function. The representation range and meaning of the function aiming at different states may be different, so normalization treatment is needed before use.
The adaptive intelligent decision module 4 is based on the premise of the marine ranching state detection system, and predicts the marine ranching state according to real-time marine ranching state data and multi-time space scale data under the condition of detecting the marine ranching state in real time, and the specific implementation process is as follows:
(1) And (5) analyzing the state of the marine pasture. The environment detection module 2 and the sensor fusion perception module 5 are used for collecting and analyzing the environment information of the marine pasture, and the deep learning neural network is used for analyzing the three-dimensional environment and the state of the marine pasture, including the surrounding environment change of the marine pasture, the self water quality analysis and other information.
(2) And predicting the state trend of the marine pasture. The method comprises the steps of optimizing and predicting the state trend of the marine pasture based on a basic network framework of a convolution long-short-term memory network (ConvLSTM), analyzing trend items, adjacent inertia, periodicity and spatial correlation of a real-time space-time data sequence of the marine pasture, and introducing the periodic network, the trend network and a space-time attention module to capture short-term signals and long-term trend items in the real-time space-time data sequence of the marine pasture. The method comprises the steps of extracting short-term trend features by using a circulation network, merging historical data features transmitted by the circulation network, introducing a space-time attention mechanism into the network, cascading time attention and space attention, calculating the similarity of the circulation trend and the approaching trend, and further obtaining the prediction of the state trend of the marine pasture.
(3) Intelligent decisions based on predicted trends. By introducing an intelligent expert system, namely a corresponding processing method for gathering and arranging the problems of different states of the marine pasture in advance, training and optimizing the expert system through a neural network, introducing a prediction result into the intelligent expert system on the basis of analyzing and predicting the state of the marine pasture, and making an intelligent analysis decision aiming at the predicted state trend of the marine pasture.
By adopting the whole set of intelligent marine ranching detection method based on unmanned ship autonomous path planning, the whole process is highly intelligent, so that the cultivation efficiency of the marine ranching can be effectively improved; the mode of combining real-time data and multi-time space scale data analysis is adopted, so that prediction is also effectively made on the marine pasture state environment, and partial natural disasters can be effectively avoided.
The above description is only for the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the scope of the claims of the present invention should fall within the protection scope of the present invention.
Claims (2)
1. The intelligent marine pasture cultivation system based on the unmanned ship is characterized by comprising a ground station, the unmanned ship, an environment detection module, a sensor fusion sensing module, an adaptive intelligent decision-making module and a water quality maintenance device, wherein the unmanned ship is provided with an unmanned ship autonomous controller, a communication module and a Beidou navigation device; the environment detection module, the sensor fusion sensing module, the adaptive intelligent decision module and the water quality maintenance device are respectively arranged on the unmanned ship;
the environment detection module is configured to continuously track and monitor the marine pasture environment in real time and detect various fishery water quality parameters;
the sensor fusion sensing module is configured to perform fusion processing analysis on the water quality parameter data detected by the environment detection module; the data after the fusion processing analysis is transmitted to the ground station through the communication module;
the ground station is configured to set an unmanned ship working area, a return position and release the unmanned ship to a target sea area; the sensor fusion sensing module is used for receiving the data after fusion processing analysis, judging and analyzing the real-time state of the marine pasture, and judging whether the water quality parameters are in a normal range or not;
the water quality maintenance device is configured to be started to improve water quality when the ground station judges that the water quality parameter is not in a normal range;
the unmanned ship autonomous controller is configured to control the unmanned ship to run in a data driving mode according to the data information and the multi-time and space scale information output by the sensor fusion sensing module after the unmanned ship reaches a target sea area; and automatically planning a path to enable the unmanned ship to perform autonomous operation;
the process of automatically planning the path is as follows:
taking the ocean pasture as a communication node n, and for a multi-ocean pasture network, n 1 ,n 2 ,n 3 ……n m Corresponding to sea pasture 1, sea pasture 2, sea pasture 3, up to sea pasture m, further, assume n 0 Is a port node;
constructing a path communication network according to the distance information of a plurality of marine pasture nodes and port nodes, wherein the port nodes are n 0 Is the initial node P of the communication path 0 The kth communication path node is found by:
P k ＝n min (d(n k ,n k+1 ),d(n k ,n k+2 ),d(n k ,n k+3 ),...d(n k ,n m ))
in the above, d (n k ,n k+1 ) Representing the distance between the kth node and the (k+1) th node, and constructing the whole shortest communication path network structure by traversing the distance value between the subsequent node and the node at each node position to select the next node of the shortest distance to form the communication path network;
after the communication path network is constructed, each node gathers and senses the state and environment information of the ocean pasture through a multi-source sensor, the acquired information is transmitted to a front node through the communication network, and the information of all the ocean pastures is transmitted back to a port step by step through the communication path network for comprehensive analysis and judgment;
after the analysis and judgment are completed, the information of each node is analyzed by the big data described in the part, and then the state of each marine pasture is analyzed; the oxygen content replenishment state of the water quality of the marine pasture is recorded as S aiming at the oxygen content of the water quality of the marine pasture o Suppose S o Is a real value between 0 and 1, and the larger the real value is, the more the corresponding marine pasture needs to supplement oxygen to the water quality, S o (P n ) The autonomous navigation path of the unmanned ship is completed through the following formula when the oxygen content replenishment condition of the water quality of the marine pasture at the nth node of the communication path is represented:
in the above, U a (t) represents the magnitude of the potential force at the t position in the automatic path planning, and the larger the potential force is, the closer the t position is to the end point of the path planning, eta is a potential force coefficient and S o,goal S represents the water quality oxygen content replenishment state of the target position o (P t ) Representing the water quality oxygen content replenishment state of the communication path node closest to the t position, wherein ρ represents the absolute value information of the distance difference value, and represents the absolute value of the difference value between the distance between the initial node and the target node and the distance between the initial node and the current closest node;
by gravitation function U a And (t) taking the communication path network as a pre-planned path, calculating the relative potential field values in the path, forming potential force difference, enabling the potential force value of the target position to be maximum, enabling the unmanned ship to traverse the whole communication path by combining the potential force values, and enabling the unmanned ship to quickly and efficiently reach a destination to supply oxygen content of water.
2. The unmanned ship-based marine ranch intelligent farming system of claim 1, wherein the unmanned ship-based marine ranch intelligent farming system further comprises an adaptive intelligent decision module;
the adaptive intelligent decision module is configured to predict the marine ranching state according to real-time marine ranching state data and multi-time space scale data, and the process is as follows:
(1) The method comprises the steps of analyzing the state of the marine pasture, collecting and analyzing the environmental information of the marine pasture through an environment detection module and a sensor fusion sensing module, and analyzing the three-dimensional environment and the state of the marine pasture by means of a deep learning neural network;
(2) The method comprises the steps of predicting the state trend of the marine pasture, analyzing trend items, adjacent inertia, periodicity and spatial correlation of a real-time space-time data sequence of the marine pasture by optimizing and predicting the state trend of the marine pasture based on a basic network frame of a convolution type long-short-term memory network, and introducing a periodic network, a trend network and a space-time attention module to capture short-term signals and long-term trend items in the real-time space-time data sequence of the marine pasture; extracting short-term trend features by using a circulation network, merging historical data features transmitted by the circulation network, introducing a space-time attention mechanism into the network, cascading time attention and space attention, calculating the similarity of the circulation trend and the approaching trend, and further obtaining the state trend prediction of the marine pasture;
(3) Based on the intelligent decision of the prediction trend, the intelligent expert system is introduced, namely the corresponding processing method for gathering and arranging the problems of different states of the ocean pasture in advance, the expert system is trained and optimized through the neural network, the prediction result is introduced into the intelligent expert system on the basis of analyzing and predicting the state of the ocean pasture, and the intelligent analysis decision is made for the predicted state trend of the ocean pasture.
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