CN111637874A - Multi-AUV layered detection system and detection method for red tide sea area - Google Patents
Multi-AUV layered detection system and detection method for red tide sea area Download PDFInfo
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Abstract
The invention provides a multi-AUV layered detection system and a detection method for a red tide sea area. The AUV carries detection, navigation and positioning equipment. The AUV carries out original data acquisition in a detection area, the data comprises seawater temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll, a data model is established through periodic detection operation, and data analysis based on edge detection and deep learning is carried out to judge the coverage rate of the red tide area, the main cause and various different development stages, so that a basis is provided for selecting a targeted method to treat the red tide.
Description
Technical Field
The invention relates to a multi-AUV layered detection system and a multi-AUV layered detection method for a red tide sea area, and belongs to the field of marine environment detection.
Background
The red tide is caused by that a large amount of industrial wastewater and domestic sewage are discharged into the sea to cause the enrichment of nutrient substances in the sea water, so that the contents of nutrient salts such as nitrogen and phosphorus, organic substances and the like in the sea water are increased greatly, and plankton in the sea is propagated rapidly to cause the abnormal color of the sea water.
Red tide poses considerable harm to the marine ecological environment, fishery aquatic resources and human health. The red tide destroys the original normal ecological structure of the sea, which is interdependent and mutually restricted between organisms and environment, and causes that some marine organisms can not grow, develop and reproduce normally, thereby threatening the survival of the marine organisms. The abnormal explosive reproduction of red tide organisms can first cause the economic organisms such as fish, shrimp, shellfish to suffocate. Secondly, the bait in the fishery is damaged, so that the fishery production is reduced. Then, after the fish and shellfish in the toxic red tide area ingest the toxic red tide organisms, a large amount of toxins are accumulated in the human body eating the organisms, and the fish and shellfish can die when the toxic red tide organisms are serious.
In recent years, the frequency of red tide occurrence in our country is higher and higher, and the region is wider and wider. Red tides must be detected in order to minimize damage during red tide disaster control. In order to fully understand the occurrence process of red tide, the marine environment and the ecological environment should be fully detected. The current common detection means for the red tide adopts a remote sensing technology, has the advantages of low cost, wide detection area and long-term detection, but has poor detection data precision, more information loss caused by noise points, easy atmospheric influence and can not well solve the details of phenomena and processes occurring in the detection of the red tide. Therefore, the invention adopts AUV as the red tide detector, has the advantages of autonomy and flexibility, and can carry out short-distance detection on the red tide to obtain detailed information.
Disclosure of Invention
The invention aims to provide a multi-AUV layered detection system and a detection method for red tide sea areas. The near water surface detection system, the water body detection system and the seabed detection system are combined to construct a near water surface, water body and seabed integrated red tide detection network system so as to obtain marine ecological environment data with different spatial scales, provide accurate detection data for the follow-up research of red tide conditions, solve the defect of poor detection precision in the prior art and meet the requirement of red tide detection in coastal sea areas.
The purpose of the invention is realized as follows: the system comprises a near-water surface AUV detection system, a water body detection AUV system and a seabed detection AUV system, wherein the near-water surface AUV detection system is composed of a plurality of AUVs, and is used for finely detecting red tide algae on the water surface; the water body AUV detection system detects in the middle of the ocean water body; the seabed AUV detection system is used for detecting by arranging a plurality of AUVs on the seabed, and each AUV is provided with detection, navigation and positioning equipment.
The invention also includes such structural features:
1. the detection, navigation and positioning equipment carried by the AUV comprises underwater lighting equipment, an underwater high-definition network camera, a depth meter, an altimeter, an image acquisition card, a data processing module, a thermohaline depth gauge, a multi-parameter water quality measuring instrument, an acoustic Doppler flow velocity profiler, an attitude sensor, a compass, an inertial navigation system, a GPS and a main control module, the system comprises an image acquisition card, a GPS (global positioning system), a thermohaline depth gauge, a multi-parameter water quality measuring instrument, an acoustic Doppler flow velocity profiler, an attitude sensor, a compass and an inertial navigation, wherein the image acquisition card sends image data to a data processing module through a TCP/IP (transmission control protocol/Internet protocol) protocol, the GPS sends the acquired data to the data processing module through a serial port, a main control module is connected with a depth meter, an altimeter and the data processing module, the GPS is used for positioning the water surface of the AUV and providing the position of the AUV before diving, and the AUV is positioned by using the compass and the inertial navigation; the multi-parameter water quality measuring instrument is used for measuring various ecological environment factors including the pH value of seawater, the conductivity, dissolved oxygen and chlorophyll; the thermohaline depth gauge is used for measuring the electrical conductivity, temperature and depth of the water body; an acoustic doppler flow profiler is used to measure the seawater flow velocity.
2. The number of AUVs participating in detection in each part of detection system is not less than 3.
3. A detection method of a detection system, characterized by: the method comprises the following steps:
the method comprises the following steps: setting the number of AUVs to be distributed according to the area of an actual operation area, and dividing all AUVs participating in detection into a near-water AUV detection system, a water body AUV detection system and a seabed AUV detection system;
step two: throwing the AUV into the target detection sea area, and submerging a part of AUV to the position below the near water surface according to the task instruction to form a near water surface AUV detection system; a part of AUV submerges to the middle part of the sea water body to form a water body AUV detection system; the residual AUV submerges to the seabed to form a seabed AUV detection system;
step three: AUVs in the near-water AUV detection system work underwater near-water surface, and each AUV sails in the same depth along the direction parallel to the longitude line or the latitude line; each AUV utilizes an underwater camera to shoot the algae on the water surface upwards, simultaneously collects the temperature, salinity, PH value, dissolved oxygen, conductivity, chlorophyll and other data of the seawater close to the water surface, and records the collected data and the corresponding AUV position in a hard disk; uploading internal recorded data after AUVs of all near-water surface detection systems are recovered, performing data fusion by using redundant data information recorded in an overlapping mode in a plurality of AUV detection areas to obtain the distribution situation of water surface seaweed in the detection areas, calculating the proportion of the seaweed of various main target categories in the red tide, and obtaining the distribution situation of main components of the near-water surface red tide;
step four: the method comprises the following steps that a plurality of AUVs in a water body detection AUV system adopt a layered simultaneous detection operation method, the longitudinal distance between each AUV and an adjacent AUV is kept above 10 meters, data of seawater temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll in different water depths are collected, and the collected data and corresponding position information are sent to a data processing module through a serial port and recorded in a hard disk; uploading the internal recorded data after AUVs of all water body detection systems are recovered to obtain data information of a plurality of water depth planes, and providing a research basis for hydrological and biological research;
step five: the method comprises the following steps that an AUV in an AUV system for seabed detection autonomously selects proper seabed nodes according to area information of a target detection sea area and depth information measured by a depth meter, the AUV cruises near the seabed nodes to perform point winding detection, collects temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data of seawater near the seabed, sends the collected data and position information thereof to a data processing module through a serial port, and records the data and the position information in a hard disk; uploading the internal recording data after AUVs of all the seabed detection systems are recovered, and providing a research basis for hydrological and biological research;
step six: in the same red tide generation area, the AUV detection system is distributed and recovered for multiple times according to a certain period, the development stage of the red tide is comprehensively judged by comparing the temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data changes of different periods acquired by the near-water AUV detection system, the water body detection AUV system and the seabed detection AUV system, the comprehensive analysis is carried out by combining the distribution condition data of main components of the red tide, and a targeted method is selected to treat the red tide.
4. The distribution of main components of the red tide near the water surface comprises the calculation of the area coverage rate of the red tide and the main inducing factors of the red tide.
5. The red tide area coverage rate calculation method comprises the following steps:
(1) exporting all AUV images in the near-water surface detection system, and carrying out denoising enhancement pretreatment;
(2) compressing the sizes of all the images and converting the images into gray images;
(3) splicing detection sequence images on each measuring line along a longitude line or a latitude line according to the AUV position and the characteristic point corresponding to the image to obtain a strip-shaped high-resolution image;
(4) performing edge detection on the spliced high-resolution image by adopting an edge detection algorithm to obtain a binary image, and processing the binary image by utilizing a morphological opening and closing operation method;
(5) regarding the detected closed edge contour as red tide alga, filling the inside of the detected contour, counting the pixel number of a filling area in the image and the pixel number of the whole image, calculating the ratio of the pixel number of the filling area to the pixel number of the whole image, and regarding the ratio as the coverage rate of the red tide area on the measuring line;
(6) and averaging the red tide area coverage rate on each measuring line of all the near-water AUV detection systems, and taking the average value as the red tide area coverage rate of the detection task stage.
6. The calculation of the main inducing factors of red tide includes the following steps:
(1) establishing a red tide data set, wherein the data set is divided into 4 types, namely dinoflagellate, diatom, blue algae and chrysophyceae, and performing deep learning off-line training on the data set to generate a deep training model;
(2) exporting an image collected on a measuring line of an AUV in the near-water surface detection system, carrying out denoising enhancement pretreatment and carrying out size compression;
(3) splicing the video images on the measuring line according to the AUV position and the characteristic point corresponding to the images to obtain high-resolution strip images;
(4) equally dividing the spliced image into a plurality of sub-images with the resolution of M multiplied by N;
(5) performing target classification and identification on each subimage by using a deep learning neural network, and counting the number of each alga in each subimage to obtain the total number of each alga in all subimages on the measuring line;
(6) counting the number of each alga identified on each measuring line of all the AUVs near the water surface; the largest number of algae was counted and considered as the main inducing factor of the red tide.
7. The sixth step specifically comprises: by counting survey results of red tides occurring in various places historically, seawater environment condition data with different scales of 4 stages of initiation, development, maintenance and extinction in the red tide generating process are summarized to construct a historical model; matching various ecological environment factors such as the pH value, the conductivity, the dissolved oxygen, the chlorophyll and the like of the seawater collected by the red tide detection system with a historical model to obtain a red tide development stage closest to the current data; the distribution of main components of the red tide is combined, and the red tide is treated by selecting a targeted measure from engineering physical, chemical and biological methods.
Compared with the prior art, the invention has the beneficial effects that: 1. the invention combines the near-water surface detection system, the water body detection system and the seabed detection system to construct a near-water surface, water body and seabed integrated red tide detection network system to obtain marine ecological environment data with different spatial scales, provide accurate detection data for the subsequent research of red tide conditions, and provide corresponding research data for hydrological and biological research by the water body and seabed detection data. 2. The invention takes AUV as a detector, has autonomy and flexibility, and can carry out short-distance detection on red tide to obtain detailed information. 3. The invention can detect the red tide underwater, and the influence of severe weather on the detection is small.
In conclusion, the multi-AUV layered detection system is used for periodically detecting the red tide occurrence region, the coverage rate of the red tide area and main influence factors are analyzed by an image analysis means through the water surface red tide image and the hydrological information on the underwater multilayer depth, and the periodic hydrological detection data can provide important reference data for further analysis and effective treatment.
Drawings
FIG. 1 is a schematic diagram of AUV distribution of the AUV-based red tide detection system in coastal sea areas.
Fig. 2 is a flow chart of the system for detecting red tide in coastal waters based on AUV.
Fig. 3 is a block diagram of the detection, navigation and localization apparatus carried by the AUV.
Fig. 4 is a flow chart of red tide area coverage calculation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, the system for detecting red tide AUV in coastal sea area provided by the present invention is divided into a near water surface detection system, a water body detection system and a seabed detection system, wherein the near water surface detection system is composed of a plurality of AUVs, and the plurality of AUVs are distributed near water surface under water to perform fine detection on red tide algae on water surface; the water body detection system detects the middle part of the ocean water body through a plurality of AUVs; the seabed detection system is used for carrying out fixed-point detection by arranging a plurality of AUVs on the seabed.
As shown in fig. 2, the AUV performs raw data acquisition in the detection area, where the data includes seawater temperature, salinity, PH, dissolved oxygen, conductivity, and chlorophyll, establishes a data model through periodic detection, and performs data analysis based on edge detection and deep learning to determine the coverage of red tide area, main cause, and various different development stages, thereby providing a basis for selecting a targeted method to treat red tide.
The detection method of the system comprises the following steps:
step 1): setting the number of the distributed AUVs according to the actual operation area, dividing the AUVs into a near water surface detection system, a water body detection system and a seabed detection system, and issuing corresponding task instructions to each AUV.
Step 2): and (4) throwing the AUV to the target detection sea area, and submerging a part of AUV to the position below the sea surface according to the task instruction to form a near-water surface detection system. And a part of AUV submerges to the middle part of the sea water body to form a water body detection system. And the rest AUV submerges to the seabed to form a seabed detection system. Wherein, the number of AUVs participating in detection in each part of detection system is not less than 3.
Step 3): the AUV in the near-water surface detection system works at the underwater near-water surface, an underwater camera is used for shooting the seaweed on the water surface upwards, the temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data of the near-water surface seawater are collected at the same time, and the collected data and the corresponding AUV position are recorded in a hard disk. And uploading the internal recorded data after the AUVs of all near-water surface detection systems are recovered, performing data fusion by using redundant data information recorded in an overlapping mode in a plurality of AUV detection areas, calculating the proportion of the seaweeds of various main target classes in the red tide, and further obtaining the distribution condition of main components of the red tide.
Step 4): a plurality of AUVs in the water body detection system adopt a layered simultaneous detection operation method, the longitudinal distance between each AUV and an adjacent AUV is kept above 10 meters, data such as seawater temperature, salinity, PH value, dissolved oxygen, conductivity, chlorophyll and the like in different water depths are collected according to the sensor module, and the collected data and corresponding position information are sent to the data processing module through a serial port and recorded in a hard disk. And uploading the internal recording data after the AUVs of all the water body detection systems are recovered, and acquiring and analyzing data information of a plurality of water depth planes.
Step 5): and the AUV in the submarine detection system autonomously selects proper submarine nodes according to the area information of the target detection sea area and the depth information measured by the depth meter, and the AUV carries out fixed-point detection on the submarine nodes. The sensor module collects temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data of seawater near the seabed, and sends the collected data and position information thereof to the data processing module through the serial port and records the data in the hard disk. And uploading the internal recording data after the AUVs of all the seabed detection systems are recovered and analyzing the internal recording data.
Step 6): and in the same red tide generation area, an AUV detection system is distributed and recovered for multiple times according to a certain period, and the development stage of the red tide is comprehensively judged by comparing the data changes of temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll in different periods. And meanwhile, the comprehensive analysis is carried out by combining the distribution condition data of the main components of the red tide, and a targeted method is selected to treat the red tide.
As shown in fig. 3, the AUV-equipped detecting, navigating and positioning device includes an underwater lighting device (LED lighting lamp), an underwater high-definition network camera, a depth meter, an altimeter, an attitude sensor, an image acquisition card, a data processing module, a thermohaline depth meter (CTD), a multi-parameter water quality measuring instrument, an acoustic doppler flow velocity profiler (ADCP), a compass, an inertial navigation system, a GPS and a main control module. The GPS is used for positioning the AUV on the water surface and providing the position of the AUV before diving, and the AUV is positioned by utilizing compass and inertial navigation through push navigation under water. The multi-parameter water quality measuring instrument is used for measuring various ecological environment factors such as the pH value, the conductivity, dissolved oxygen, chlorophyll and the like of seawater, the thermohaline depth gauge (CTD) is used for measuring the conductivity, the temperature and the depth of a water body, and the Acoustic Doppler Current Profiler (ADCP) is used for measuring the flow velocity of the seawater. The image acquisition card sends the image data to the data processing module through a TCP/IP protocol. The sensor module is divided into a control sensor and a detection sensor, the control sensor comprises a GPS, a compass, an attitude sensor, a sound velocity profiler, an inertial navigation system and the like, and the detection sensor comprises a multi-parameter water quality measuring instrument, a temperature and salinity depth instrument (CTD), an Acoustic Doppler Current Profiler (ADCP) and the like. The sensor module collects the temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data of seawater near the seabed, and sends the collected data to the data processing module through the serial port.
The AUV in the seabed detection system acquires environmental elements and seabed organism images in the near sea water of the seabed. The influence of harmful algae in the red tide on the benthos is judged by analyzing and researching the red tide organisms collected by the near-water surface detection system, and then whether the red tide organisms can be removed by using a clay method is determined.
As shown in fig. 4, the step of calculating the red tide area coverage of the target area in the coastal sea area red tide AUV detection system is as follows:
step 1): and (4) exporting all the images acquired by the AUV in the near-water surface detection system, and carrying out denoising enhancement pretreatment.
Step 2): to increase the computation speed, all images are size-compressed and converted into grayscale images.
Step 3): and splicing the images in the detection area according to the AUV positions and the characteristic points corresponding to the images to obtain the high-resolution images.
Step 4): and performing edge detection on the spliced high-resolution image by adopting an edge detection algorithm to obtain a binary image, and processing the binary image by utilizing a morphological open-close operation method.
Step 5): and regarding the detected closed edge contour as red tide alga, filling the inside of the detected contour, counting the pixel number of a filling area in the image and the pixel number of the whole image, calculating the ratio of the pixel number of the filling area to the pixel number of the whole image, and regarding the ratio as the coverage rate of the red tide area in the detection area.
The steps of calculating the main induction factors of the red tide in the coastal sea area red tide AUV detection system are as follows:
step 1): establishing a red tide data set, wherein the data set is divided into 4 types, namely dinoflagellate, diatom, blue algae and chrysophyceae. And carrying out deep learning off-line training on the data set to generate the detector.
Step 2): and (4) exporting the image acquired by the AUV in the near-water surface detection system, carrying out denoising enhancement pretreatment and carrying out size compression.
Step 3): and splicing the images in the detection area according to the AUV positions and the characteristic points corresponding to the images to obtain the high-resolution images.
Step 4): the stitched image is equally divided into several sub-images with resolution M × N.
Step 5): and (3) performing target classification and identification on each sub-image by using a deep learning neural network, and counting the number of each alga in each sub-image to obtain the total number of each alga in all sub-images.
Step 6): the largest number of algae was counted and considered as the main inducing factor of the red tide.
The red tide detection system sums up the survey results of red tides occurring in various places in history, sums up the seawater environment condition data of different scales of 4 stages of initiation, development, maintenance and extinction in the red tide generation process, and constructs a history model. And matching various ecological environment factors such as the pH value, the conductivity, the dissolved oxygen, the chlorophyll and the like of the seawater collected by the red tide detection system with the historical model to obtain the red tide development stage closest to the current data. The distribution condition of main components of the red tide is combined, and a targeted measure is selected from engineering physical, chemical and biological methods to treat the red tide.
In summary, the invention relates to the field of marine environment detection, and discloses a coastal sea area red tide detection system based on An Underwater Vehicle (AUV) detection technology. Coastal waters red tide AUV detecting system divide into nearly surface of water AUV detecting system, water AUV detecting system and seabed AUV detecting system, nearly surface of water detecting system comprises a plurality of AUV, has the autonomy, carries out meticulous detection to surface of water red tide alga through laying a plurality of AUV near the surface of water under water, water AUV detecting system carries out the layering through several AUV in marine water middle part and surveys, seabed AUV detecting system arranges a plurality of AUV at the seabed and surveys. The AUV carrying detection, navigation and positioning device comprises an underwater lighting device (LED lighting lamp), an underwater high-definition network camera, a depth meter, an altimeter, an image acquisition card, a communication module, a data processing module, a task module, a thermohaline depth meter (CTD), a multi-parameter water quality measuring instrument, an acoustic Doppler flow velocity profiler (ADCP), a compass, an inertial navigation system, a GPS and a main control module. The AUV carries out original data acquisition in a detection area, the data comprises seawater temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll, a data model is established through periodic detection operation, and data analysis based on edge detection and deep learning is carried out to judge the coverage rate of the red tide area, the main cause and various different development stages, so that a basis is provided for selecting a targeted method to treat the red tide.
Claims (8)
1. The utility model provides a many AUV layering detecting system in red tide sea area which characterized in that: the system comprises a near-water surface AUV detection system, a water body detection AUV system and a seabed detection AUV system, wherein the near-water surface AUV detection system is composed of a plurality of AUVs, and is used for finely detecting red tide algae on the water surface; the water body AUV detection system detects in the middle of the ocean water body; the seabed AUV detection system is used for detecting by arranging a plurality of AUVs on the seabed, and each AUV is provided with detection, navigation and positioning equipment.
2. The system of claim 1, wherein the system comprises: the detection, navigation and positioning equipment carried by the AUV comprises underwater lighting equipment, an underwater high-definition network camera, a depth meter, an altimeter, an image acquisition card, a data processing module, a thermohaline depth gauge, a multi-parameter water quality measuring instrument, an acoustic Doppler flow velocity profiler, an attitude sensor, a compass, an inertial navigation system, a GPS and a main control module, the system comprises an image acquisition card, a GPS (global positioning system), a thermohaline depth gauge, a multi-parameter water quality measuring instrument, an acoustic Doppler flow velocity profiler, an attitude sensor, a compass and an inertial navigation, wherein the image acquisition card sends image data to a data processing module through a TCP/IP (transmission control protocol/Internet protocol) protocol, the GPS sends the acquired data to the data processing module through a serial port, a main control module is connected with a depth meter, an altimeter and the data processing module, the GPS is used for positioning the water surface of the AUV and providing the position of the AUV before diving, and the AUV is positioned by using the compass and the inertial navigation; the multi-parameter water quality measuring instrument is used for measuring various ecological environment factors including the pH value of seawater, the conductivity, dissolved oxygen and chlorophyll; the thermohaline depth gauge is used for measuring the conductivity, temperature and depth of the water body; an acoustic doppler flow profiler is used to measure the seawater flow velocity.
3. The system of claim 1 or 2, wherein the system comprises: the number of AUVs participating in detection in each part of detection system is not less than 3.
4. A detection method using the detection system according to claim 3, characterized in that: the method comprises the following steps:
the method comprises the following steps: setting the number of AUVs to be distributed according to the area of an actual operation area, and dividing all AUVs participating in detection into a near-water AUV detection system, a water body AUV detection system and a seabed AUV detection system;
step two: throwing the AUV into the target detection sea area, and submerging a part of AUV to the position below the near water surface according to the task instruction to form a near water surface AUV detection system; a part of AUV submerges to the middle part of the sea water body to form a water body AUV detection system; the residual AUV submerges to the seabed to form a seabed AUV detection system;
step three: AUVs in the near-water AUV detection system work underwater near-water surface, and each AUV sails in the same depth along the direction parallel to the longitude line or the latitude line; each AUV utilizes an underwater camera to shoot the algae on the water surface upwards, simultaneously collects the temperature, salinity, PH value, dissolved oxygen, conductivity, chlorophyll and other data of the seawater close to the water surface, and records the collected data and the corresponding AUV position in a hard disk; uploading internal recorded data after AUVs of all near-water surface detection systems are recovered, performing data fusion by using redundant data information recorded in an overlapping mode in a plurality of AUV detection areas to obtain the distribution situation of water surface seaweed in the detection areas, calculating the proportion of the seaweed of various main target categories in the red tide, and obtaining the distribution situation of main components of the near-water surface red tide;
step four: the method comprises the following steps that a plurality of AUVs in a water body detection AUV system adopt a layered simultaneous detection operation method, the longitudinal distance between each AUV and an adjacent AUV is kept above 10 meters, data of seawater temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll in different water depths are collected, and the collected data and corresponding position information are sent to a data processing module through a serial port and recorded in a hard disk; uploading the internal memory data after AUVs of all water body detection systems are recovered to obtain data information of a plurality of water depth planes, and providing a research basis for hydrological and biological research;
step five: the method comprises the following steps that an AUV in an AUV system for seabed detection autonomously selects proper seabed nodes according to area information of a target detection sea area and depth information measured by a depth meter, the AUV cruises near the seabed nodes to perform point winding detection, collects temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data of seawater near the seabed, sends the collected data and position information thereof to a data processing module through a serial port, and records the data in a hard disk; uploading the internal recording data after AUVs of all the seabed detection systems are recovered, and providing a research basis for hydrological and biological research;
step six: in the same red tide generation area, the AUV detection system is distributed and recovered for multiple times according to a certain period, the development stage of the red tide is comprehensively judged by comparing the temperature, salinity, PH value, dissolved oxygen, conductivity and chlorophyll data changes of different periods acquired by the near-water AUV detection system, the water body detection AUV system and the seabed detection AUV system, the comprehensive analysis is carried out by combining the distribution condition data of main components of the red tide, and a targeted method is selected to treat the red tide.
5. The method for detecting red tide AUV in coastal sea area according to claim 4, characterized in that: the distribution of main components of the red tide near the water surface comprises the calculation of the area coverage rate of the red tide and the main inducing factors of the red tide.
6. The method for detecting red tide AUV in coastal sea area according to claim 5, characterized in that: the red tide coverage rate calculation method comprises the following steps:
(1) exporting all AUV images in the near-water surface detection system, and carrying out denoising enhancement pretreatment;
(2) compressing the sizes of all the images and converting the images into gray images;
(3) splicing detection sequence images on each measuring line along a longitude line or a latitude line according to the AUV position and the characteristic point corresponding to the image to obtain a strip-shaped high-resolution image;
(4) performing edge detection on the spliced high-resolution image by adopting an edge detection algorithm to obtain a binary image, and processing the binary image by utilizing a morphological open-close operation method;
(5) the detected closed edge contour is regarded as red tide alga, the detected contour is filled internally, the number of pixels of a filling area in the image and the number of pixels of the whole image are counted, the ratio of the number of pixels of the filling area to the number of pixels of the whole image is calculated, and the red tide area coverage rate on the measuring line is regarded;
(6) and averaging the red tide coverage rate on each measuring line of all the near-water AUV detection systems, and taking the average value as the red tide area coverage rate of the detection task stage.
7. The method for detecting red tide AUV in coastal sea area according to claim 5 or 6, characterized in that: the calculation of the main inducing factors of red tide includes the following steps:
(1) establishing a red tide data set which is divided into 4 types, namely dinoflagellate, diatom, blue algae and chrysophyte, and performing deep learning off-line training on the data set to generate a training model of a deep learning recognition algorithm;
(2) exporting an image collected on a measuring line of an AUV in the near-water surface detection system, carrying out denoising enhancement pretreatment and carrying out size compression;
(3) splicing the video images on the measuring line according to the AUV position and the characteristic point corresponding to the images to obtain high-resolution strip images;
(4) equally dividing the spliced image into a plurality of sub-images with the resolution of M multiplied by N;
(5) performing target classification and identification on each sub-image by using a deep learning neural network, and counting the number of each alga in each sub-image to obtain the total number of each alga in all sub-images on the measuring line;
(6) counting the number of each alga identified on each measuring line of all the AUVs near the water surface; the algae with the highest number of occurrence in the statistical result are regarded as the main inducing factors of the red tide.
8. The method for detecting red tide AUV in coastal sea area according to claim 4 or 5, characterized in that: the sixth step specifically comprises: by counting survey results of red tides occurring in various places historically, seawater environment condition data with different scales of 4 stages of initiation, development, maintenance and extinction in the red tide generating process are summarized to construct a historical model; matching various ecological environment factors such as the pH value, the conductivity, the dissolved oxygen, the chlorophyll and the like of the seawater collected by the red tide detection system with a historical model to obtain a red tide development stage closest to the current data; the distribution of main components of the red tide is combined, and the red tide is treated by selecting a targeted measure from engineering physical, chemical and biological methods.
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