CN113865645A - Offshore sea area ecological environment monitoring system and method - Google Patents

Offshore sea area ecological environment monitoring system and method Download PDF

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CN113865645A
CN113865645A CN202111132476.7A CN202111132476A CN113865645A CN 113865645 A CN113865645 A CN 113865645A CN 202111132476 A CN202111132476 A CN 202111132476A CN 113865645 A CN113865645 A CN 113865645A
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ecological environment
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CN113865645B (en
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孙雨玘
叶海芬
宁景苑
黄科涛
梅正昊
熊思怡
张苏婕
蒋晨豪
李昱权
吴鹏
惠国华
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Zhejiang A&F University ZAFU
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    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
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    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
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    • B63B2022/006—Buoys specially adapted for measuring or watch purposes
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Abstract

The invention discloses an offshore sea area ecological environment monitoring system and method. The system comprises a monitoring terminal and a plurality of monitoring buoys arranged in different regions of an offshore sea area, wherein each monitoring buoy comprises a buoy body, a microprocessor, a power supply module, a GPS module, a wireless communication module, a data acquisition module and a solar charging module are arranged on each buoy body, the microprocessor is respectively electrically connected with the power supply module, the GPS module, the wireless communication module and the data acquisition module, the solar charging module is electrically connected with the power supply module, and the wireless communication module is wirelessly connected with the monitoring terminal through a wireless network. The method can monitor the ecological environment data of different regions of the offshore sea area in real time on line and judge the ecological environment health state of different regions of the offshore sea area.

Description

Offshore sea area ecological environment monitoring system and method
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to an offshore sea area ecological environment monitoring system and method.
Background
China has a long coastline from north to south, and offshore sea area resources are rich, but in recent years, as human activities have increasingly serious influence on the offshore sea area environment, the real-time monitoring of the ecological environment of the offshore sea area and the health assessment are of great significance. At present, the evaluation of the health of the offshore sea area ecosystem is usually only to study and judge the ecological condition of the offshore sea area according to certain measured key indexes, and the detection of the key indexes is generally carried out through manual measurement and analysis, so that the efficiency is low, the cost is high, and the whole situation in the detected area is difficult to be effectively monitored in real time according to a theoretical optimal model.
Disclosure of Invention
In order to solve the technical problems, the invention provides an offshore sea area ecological environment monitoring system and method, which can monitor ecological environment data of different regions of an offshore sea area on line in real time and judge the ecological environment health states of the different regions of the offshore sea area.
In order to solve the problems, the invention adopts the following technical scheme:
the invention discloses an offshore sea area ecological environment monitoring system which comprises a monitoring terminal and a plurality of monitoring buoys arranged in different areas of an offshore sea area, wherein each monitoring buoy comprises a buoy body, a microprocessor, a power supply module, a GPS (global positioning system) module, a wireless communication module, a data acquisition module and a solar charging module are arranged on each buoy body, the microprocessor is respectively electrically connected with the power supply module, the GPS module, the wireless communication module and the data acquisition module, the solar charging module is electrically connected with the power supply module, the wireless communication module is wirelessly connected with the monitoring terminal through a wireless network, and the data acquisition module comprises a negative oxygen ion sensor S1 for detecting the concentration of negative oxygen ions in sea area air, a light particulate matter sensor S2 for detecting the concentration of light particulate matters in sea area water, a water temperature sensor S3 for detecting the water temperature in sea area and a heavy particulate matter sensor S4 for detecting the concentration of heavy particulate matters in sea area water, The device comprises a pH sensor S5 for detecting the pH value of the sea area water body, a dissolved oxygen sensor S6 for detecting the dissolved oxygen amount of the sea area water body, a water conductivity sensor S7 for detecting the conductivity of the sea area water body, an ammonia nitrogen sensor S8 for detecting the ammonia nitrogen content of the sea area water body, a sound sensor S9 for detecting the noise of the sea area and an ultraviolet radiation sensor S10 for detecting the ultraviolet radiation amount of the sea area.
In the scheme, the monitoring buoys are uniformly distributed in different areas of an offshore sea area, each monitoring buoy collects detection data of the area and sends the detection data to the monitoring terminal, and the monitoring terminal analyzes and processes the detection data sent by each monitoring buoy respectively and judges the ecological environment state of the area where the monitoring buoy is located. The solar charging module can charge the power module by utilizing solar energy, so that the monitoring buoy can perform monitoring work for a long time, and the GPS module is used for positioning the position of the monitoring buoy, so that the monitoring terminal can conveniently master the current position of each monitoring buoy.
The invention discloses an offshore sea area ecological environment monitoring method, which is used for the offshore sea area ecological environment monitoring system and comprises the following steps:
the negative oxygen ion sensor S1 outputs detection data Ds1(t) to the microprocessor, the light particulate matter sensor S2 outputs detection data Ds2(t) to the microprocessor, the water temperature sensor S3 outputs detection data Ds3(t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data Ds4(t) to the microprocessor, the PH sensor S5 outputs detection data Ds5(t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data Ds6(t) to the microprocessor, the water conductivity sensor S7 outputs detection data Ds7(t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data Ds8(t) to the microprocessor, the sound sensor S9 outputs detection data Ds9(t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data Ds10(t) the microprocessor sends the detection data to the monitoring terminal through the wireless communication module, wherein t is time;
the monitoring terminal respectively analyzes and processes the detection data sent by each monitoring buoy and judges the ecological environment state of the area where the monitoring buoy is located, and the method comprises the following steps:
s1: the monitoring terminal will detect data Ds1(t)、Ds2(t)、Ds3(t)、Ds4(t)、Ds5(t)、Ds6(t)、Ds7(t)、Ds8(t)、Ds9(t)、Ds10(t) normalization to [1, 10 ] respectively]Within the interval, corresponding normalized data L is obtaineds1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t)；
S2: the monitoring terminal is based on the normalized data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) calculating the corresponding characteristic value ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10And calculating an ecological environment evaluation parameter SENK;
s3: the monitoring terminal calculates the average value SENKA and EN of the ecological environment evaluation parameter SENK every N secondss5Average value of ENAs5、ENs8Average value of ENAs8；
When SENKA is more than or equal to W1 and ENAs5、ENAs8When the monitoring buoy is located in the set range, judging that the current ecological environment of the area where the monitoring buoy is located is superior;
when W2 < SENKA < W1 and ENAs5、ENAs8When the monitoring buoy is located in the set range, judging that the current ecological environment of the area where the monitoring buoy is located is medium;
when SENKA is less than or equal to W2 or ENAs5、ENAs8When any one of the monitoring buoys exceeds the set range, the current ecological environment of the area where the monitoring buoys are located is judged to be poor, and the like.
In the scheme, ten kinds of data of the regional ecological environment where the monitoring buoy is located are detected by a negative oxygen ion sensor S1, a light particulate matter sensor S2, a water temperature sensor S3, a heavy particulate matter sensor S4, a pH sensor S5, a dissolved oxygen sensor S6, a water conductivity sensor S7, an ammonia nitrogen sensor S8, an acoustic sensor S9 and an ultraviolet radiation sensor S10, the ten kinds of data are conveyed to a monitoring terminal, the monitoring terminal processes and analyzes the data to calculate a parameter SENKA for comprehensively evaluating the ecological environment health state, and the comprehensive judgment on the ecological environment health state of the region where the monitoring buoy is located is carried out by combining the PH value and the ammonia nitrogen content which have large influences on the offshore sea environment.
Preferably, the step S2 includes the steps of:
s21: normalizing the data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) substituting the signals into the ecological discrimination model as input signals X (t) respectively to calculate corresponding characteristic values ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10；
Normalized data Lsi(t) substituting the signal into the ecological discrimination model to calculate the corresponding characteristic value ENsiThe method of (1) is as follows:
mixing L withsi(t) substituting as input signal X (t) into the ecological discriminant model:
Figure BDA0003277178250000041
Figure BDA0003277178250000042
wherein, P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of the lake ecological discrimination model, c, a, b and g are parameters, t is time, cos (2 pi ft) is a frequency component of an input signal, f is frequency, and M is the signal intensity of the excitation signal B (t);
adjusting the value of g from small to large, approaching the formula (1) and the formula (2) to a transition condition, stopping adjusting g when any one of the formula (1) and the formula (2) reaches the transition state, and recording the current value of g as gsiObtaining the characteristic curve FEDP of the lake ecology discrimination modelsi：
Figure BDA0003277178250000051
Taking characteristic curve FEDPsiMaximum value F1 and minimum value F2, characteristic value ENsi＝F1-F2：
S22: to ENs1As the response characteristic signal value of the negative oxygen ion sensor S1, the signal value is
Figure BDA0003277178250000052
EN is the value of the response characteristic signal of the light particulate matter sensor S2s3As the response characteristic signal value of the water temperature sensor S3, the response characteristic signal value is
Figure BDA0003277178250000053
EN is used as the response characteristic signal value of the heavy particulate matter sensor S4s5EN is used as the response characteristic signal value of the PH sensor S5s6EN is used as the response characteristic signal value of the dissolved oxygen sensor S6s7As a response characteristic signal value of the water conductivity sensor S7, ENs8As ammonia nitrogen transferThe response characteristic signal value of the sensor S8 is ENs9EN is the response characteristic signal value of the sound sensor S9s10As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multi-axis vector diagram with 10 sensor response axes on a plane by taking the response characteristic signal of each sensor as the response axis of the sensor, wherein the original points of all the sensor response axes are the same point, the included angle between the sensor Sn response axis and the sensor S (n +1) response axis is 36 degrees, and n is 1, 2 … … 9;
responding characteristic signal value EN corresponding to the sensor S1, the sensor S2, the sensor S4, the sensor S6 and the sensor S7s1、
Figure BDA0003277178250000054
ENs6、ENs7Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking the corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space A1, and calculating the sum of the areas of the enclosed closed spaces SA 1;
the response characteristic signal value EN corresponding to the sensor S3, the sensor S9 and the sensor S10s3、ENs9、ENs10Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking the corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space, and calculating the sum SA2 of the areas of the enclosed closed space A2;
and calculating an ecological environment evaluation parameter SENK-SA 1-SA 2.
Preferably, the negative oxygen ion sensor S1 is an HSTL-FYLZ sensor, the light particulate matter sensor S2 is an SIN-PTU110 sensor, the water temperature sensor S3 is a ZS02 sensor, the heavy particulate matter sensor S4 is an SIN-PSS110 sensor, the pH sensor S5 is an SIN-TDS210 sensor, the dissolved oxygen sensor S6 is an SIN-DM2800 sensor, the water conductivity sensor S7 is an SIN-TDS210 sensor, the ammonia nitrogen sensor S8 is an AMT-W400 sensor, the sound sensor S9 is a JHM-NS02 sensor, and the ultraviolet radiation sensor S10 is a GUVA-S12SD sensor.
The invention has the beneficial effects that: the ecological environment data of different regions of the offshore sea area can be monitored in real time on line, the ecological environment health states of different regions of the offshore sea area are judged, and the monitoring efficiency is improved.
Drawings
FIG. 1 is a schematic structural view of an embodiment;
FIG. 2 is a schematic illustration of a characteristic curve;
FIG. 3 is a diagram of a closed space A1 defined by a multi-axis vector diagram of response characteristic signal values of a sensor;
fig. 4 is a diagram of a closed space a2 enclosed by the response characteristic signal values of the sensor in a multi-axis vector diagram.
In the figure: 1. the monitoring system comprises a monitoring terminal 2, a monitoring buoy 3, a microprocessor 4, a power supply module 5, a GPS module 6, a wireless communication module 7, a data acquisition module 8 and a solar charging module.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b): the offshore sea area ecological environment monitoring system of the embodiment, as shown in fig. 1, includes a monitoring terminal 1 and a plurality of monitoring buoys 2 arranged in different areas of the offshore sea area, each monitoring buoy 2 includes a buoy body, the buoy body is provided with a microprocessor 3, a power module 4, a GPS module 5, a wireless communication module 6, a data acquisition module 7 and a solar charging module 8, the microprocessor 3 is respectively electrically connected with the power module 4, the GPS module 5, the wireless communication module 6 and the data acquisition module 7, the solar charging module 8 is electrically connected with the power module 4, the wireless communication module 6 is wirelessly connected with the monitoring terminal 1 through a wireless network, the data acquisition module 7 includes a negative oxygen ion sensor S1 for detecting the concentration of negative oxygen ions in the sea area, a light particulate matter sensor S2 for detecting the concentration of light particulate matters in the sea area water, and a water temperature sensor S3 for detecting the water temperature in the sea area, The device comprises a heavy particle sensor S4 for detecting the concentration of heavy particles in the water body in the sea area, a PH sensor S5 for detecting the PH value of the water body in the sea area, a dissolved oxygen sensor S6 for detecting the dissolved oxygen amount in the water body in the sea area, a water conductivity sensor S7 for detecting the conductivity of the water body in the sea area, an ammonia nitrogen sensor S8 for detecting the ammonia nitrogen content in the water body in the sea area, a sound sensor S9 for detecting the noise in the sea area and an ultraviolet radiation sensor S10 for detecting the ultraviolet radiation amount in the sea area.
In the scheme, the monitoring buoys are uniformly distributed in different areas of an offshore sea area, each monitoring buoy collects detection data of the area and sends the detection data to the monitoring terminal, and the monitoring terminal analyzes and processes the detection data sent by each monitoring buoy respectively and judges the ecological environment state of the area where the monitoring buoy is located. The solar charging module can charge the power module by utilizing solar energy, so that the monitoring buoy can perform monitoring work for a long time, and the GPS module is used for positioning the position of the monitoring buoy, so that the monitoring terminal can conveniently master the current position of each monitoring buoy.
The method for monitoring the ecological environment of the offshore sea area in the embodiment is used for the system for monitoring the ecological environment of the offshore sea area, and comprises the following steps:
the negative oxygen ion sensor S1 outputs detection data Ds1(t) to the microprocessor, the light particulate matter sensor S2 outputs detection data Ds2(t) to the microprocessor, the water temperature sensor S3 outputs detection data Ds3(t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data Ds4(t) to the microprocessor, the PH sensor S5 outputs detection data Ds5(t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data Ds6(t) to the microprocessor, the water conductivity sensor S7 outputs detection data Ds7(t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data Ds8(t) to the microprocessor, the sound sensor S9 outputs detection data Ds9(t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data Ds10(t) the microprocessor sends the detection data to the monitoring terminal through the wireless communication module, wherein t is time;
the monitoring terminal respectively analyzes and processes the detection data sent by each monitoring buoy and judges the ecological environment state of the area where the monitoring buoy is located, and the method comprises the following steps:
s1: the monitoring terminal will detect data Ds1(t)、Ds2(t)、Ds3(t)、Ds4(t)、Ds5(t)、Ds6(t)、Ds7(t)、Ds8(t)、Ds9(t)、Ds10(t) normalization to [1, 10 ] respectively]Within the interval, corresponding normalized data L is obtaineds1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t)；
S2: the monitoring terminal is based on the normalized data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) calculating the corresponding characteristic value ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10And calculating an ecological environment evaluation parameter SENK;
step S2 includes the following steps:
s21: normalizing the data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) substituting the signals into the ecological discrimination model as input signals X (t) respectively to calculate corresponding characteristic values ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10；
Normalized data Lsi(t) substituting the signal into the ecological discrimination model to calculate the corresponding characteristic value ENsiMethod (2)As follows, i ═ 1 to 10:
mixing L withsi(t) substituting as input signal X (t) into the ecological discriminant model:
Figure BDA0003277178250000091
Figure BDA0003277178250000092
wherein, P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of the lake ecological discrimination model, c, a, b and g are parameters, t is time, cos (2 pi ft) is a frequency component of an input signal, f is frequency, and M is the signal intensity of the excitation signal B (t);
adjusting the value of g from small to large, approaching the formula (1) and the formula (2) to a transition condition, stopping adjusting g when any one of the formula (1) and the formula (2) reaches the transition state, and recording the current value of g as gsiObtaining the characteristic curve FEDP of the lake ecology discrimination modelsi：
Figure BDA0003277178250000101
Characteristic curve FEDPsiAs shown in FIG. 2, a characteristic curve FEDP is takensiMaximum value F1 and minimum value F2, characteristic value ENsi＝F1-F2；
S22: to ENs1As the response characteristic signal value of the negative oxygen ion sensor S1, the signal value is
Figure BDA0003277178250000102
EN is the value of the response characteristic signal of the light particulate matter sensor S2s3As the response characteristic signal value of the water temperature sensor S3, the response characteristic signal value is
Figure BDA0003277178250000103
EN is used as the response characteristic signal value of the heavy particulate matter sensor S4s5As a pH sensor S5 in response to the characteristic signal value, ENs6EN is used as the response characteristic signal value of the dissolved oxygen sensor S6s7As a response characteristic signal value of the water conductivity sensor S7, ENs8As a response characteristic signal value of the ammonia nitrogen sensor S8, EN is useds9EN is the response characteristic signal value of the sound sensor S9s10As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multi-axis vector diagram with 10 sensor response axes on a plane by taking the response characteristic signal of each sensor as the response axis of the sensor, wherein the original points of all the sensor response axes are the same point, the included angle between the sensor Sn response axis and the sensor S (n +1) response axis is 36 degrees, and n is 1, 2 … … 9;
responding characteristic signal value EN corresponding to the sensor S1, the sensor S2, the sensor S4, the sensor S6 and the sensor S7s1、
Figure BDA0003277178250000104
ENs6、ENs7Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space A1, and calculating the sum of the areas of the enclosed spaces SA1 as shown in FIG. 3;
the response characteristic signal value EN corresponding to the sensor S3, the sensor S9 and the sensor S10s3、ENs9、ENs10Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space, and calculating the sum SA2 of the areas of the enclosed closed space A2 as shown in FIG. 4;
calculating an ecological environment evaluation parameter SENK (SA 1-SA 2);
s3: every N seconds of monitoring terminalCalculating the average value SENKA and EN of the first ecological environment evaluation parameter SENKs5Average value of ENAs5、ENs8Average value of ENAs8；
When SENKA is more than or equal to 0.7 and ENAs5Less than 1.2 and less than or equal to 1.0 ENAs8When the ecological environment is less than 3.8, judging the current ecological environment to be excellent;
when the ratio of 0.2 < SENKA < 0.7 and ENAs5Less than 1.2 and less than or equal to 1.0 ENAs8When the ecological environment is less than 3.8, judging that the current ecological environment is moderate;
when SENKA is less than or equal to 0.2 or ENAs5Not less than 1.2 or ENAs8< 1.0 or ENAs8And when the ecological environment is more than or equal to 3.8, judging that the current ecological environment is poor and the like.
In the scheme, ten kinds of data of the regional ecological environment where the monitoring buoy is located are detected by a negative oxygen ion sensor S1, a light particulate matter sensor S2, a water temperature sensor S3, a heavy particulate matter sensor S4, a pH sensor S5, a dissolved oxygen sensor S6, a water conductivity sensor S7, an ammonia nitrogen sensor S8, an acoustic sensor S9 and an ultraviolet radiation sensor S10, the ten kinds of data are conveyed to a monitoring terminal, the monitoring terminal processes and analyzes the data to calculate a parameter SENKA for comprehensively evaluating the ecological environment health state, and the comprehensive judgment on the ecological environment health state of the region where the monitoring buoy is located is carried out by combining the PH value and the ammonia nitrogen content which have large influences on the offshore sea environment.
The negative oxygen ion sensor S1 detects sea area air negative oxygen ion information, the dissolved oxygen sensor S6 detects sea area water body dissolved oxygen information, the water body conductivity sensor S7 detects sea area water body conductivity information, and the larger the detection signals of the sensors are, the better the ecological environment of the sea area is represented; the light particle sensor S2 detects the concentration information of light particles in the sea water, the heavy particle sensor S4 detects the concentration information of heavy particles in the sea water, and the detection index of the heavy particles is related to the ecological information and is in inverse proportion; the water temperature sensor S3 detects water temperature information of water in the sea area, the sound sensor S9 detects noise information of the sea area, and the ultraviolet radiation sensor S10 detects ultraviolet radiation information of the sea area, and the ecological indexes have destructive effects on the ecological environment of the sea area, so that the lower the detection value is, the better the ecological environment of the sea area is. The pH sensor S5 and the ammonia nitrogen sensor S8 with ammonia nitrogen content do not determine whether the ecological environment is good or not in the maximum value or minimum value interval, but influence the evaluation of the ecological environment in a certain interval, so that independent judgment is made.
The negative oxygen ion sensor S1 is an HSTL-FYLZ sensor, the light particulate matter sensor S2 is an SIN-PTU110 sensor, the water temperature sensor S3 is a ZS02 sensor, the heavy particulate matter sensor S4 is an SIN-PSS110 sensor, the pH sensor S5 is an SIN-TDS210 sensor, the dissolved oxygen sensor S6 is an SIN-DM2800 sensor, the water conductivity sensor S7 is an SIN-TDS210 sensor, the ammonia nitrogen sensor S8 is an AMT-W400 sensor, the sound sensor S9 is a JHM-NS02 sensor, and the ultraviolet radiation sensor S10 is a GUVA-S12SD sensor.

Claims (4)

1. The system is characterized by comprising a monitoring terminal (1) and a plurality of monitoring buoys (2) arranged in different areas of an offshore sea area, wherein each monitoring buoy (2) comprises a buoy body, a microprocessor (3), a power module (4), a GPS module (5), a wireless communication module (6), a data acquisition module (7) and a solar charging module (8) are arranged on each buoy body, the microprocessor (3) is respectively and electrically connected with the power module (4), the GPS module (5), the wireless communication module (6) and the data acquisition module (7), the solar charging module (8) is electrically connected with the power module (4), the wireless communication module (6) is wirelessly connected with the monitoring terminal (1) through a wireless network, and the data acquisition module (7) comprises a negative oxygen ion sensor S1 for detecting the concentration of negative oxygen ions in air in the sea area, The device comprises a light particle sensor S2 for detecting the concentration of light particles in the water body in the sea area, a water temperature sensor S3 for detecting the water temperature in the sea area, a heavy particle sensor S4 for detecting the concentration of the heavy particles in the water body in the sea area, a pH sensor S5 for detecting the pH value of the water body in the sea area, a dissolved oxygen sensor S6 for detecting the dissolved oxygen amount in the water body in the sea area, a water conductivity sensor S7 for detecting the conductivity of the water body in the sea area, an ammonia nitrogen sensor S8 for detecting the ammonia nitrogen content in the water body in the sea area, a sound sensor S9 for detecting the noise in the sea area, and an ultraviolet radiation sensor S10 for detecting the ultraviolet radiation amount in the sea area.
2. An offshore marine ecological environment monitoring method for the offshore marine ecological environment monitoring system of claim 1, comprising the steps of:
the negative oxygen ion sensor S1 outputs detection data Ds1(t) to the microprocessor, the light particulate matter sensor S2 outputs detection data Ds2(t) to the microprocessor, the water temperature sensor S3 outputs detection data Ds3(t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data Ds4(t) to the microprocessor, the PH sensor S5 outputs detection data Ds5(t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data Ds6(t) to the microprocessor, the water conductivity sensor S7 outputs detection data Ds7(t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data Ds8(t) to the microprocessor, the sound sensor S9 outputs detection data Ds9(t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data Ds10(t) the microprocessor sends the detection data to the monitoring terminal through the wireless communication module, wherein t is time;
the monitoring terminal respectively analyzes and processes the detection data sent by each monitoring buoy and judges the ecological environment state of the area where the monitoring buoy is located, and the method comprises the following steps:
s1: the monitoring terminal will detect data Ds1(t)、Ds2(t)、Ds3(t)、Ds4(t)、Ds5(t)、Ds6(t)、Ds7(t)、Ds8(t)、Ds9(t)、Ds10(t) normalization to [1, 10 ] respectively]Within the interval, corresponding normalized data L is obtaineds1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t)；
S2: the monitoring terminal is based on the normalized data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) calculating the corresponding characteristic value ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10And calculating an ecological environment evaluation parameter SENK;
s3: the monitoring terminal calculates the average value SENKA and EN of the ecological environment evaluation parameter SENK every N secondss5Average value of ENAs5、ENs8Average value of ENAs8；
When SENKA is more than or equal to W1 and ENAs5、ENAs8When the monitoring buoy is located in the set range, judging that the current ecological environment of the area where the monitoring buoy is located is superior;
when W2 < SENKA < W1 and ENAs5、ENAs8When the monitoring buoy is located in the set range, judging that the current ecological environment of the area where the monitoring buoy is located is medium;
when SENKA is less than or equal to W2 or ENAs5、ENAs8When any one of the monitoring buoys exceeds the set range, the current ecological environment of the area where the monitoring buoys are located is judged to be poor, and the like.
3. The offshore marine ecological environment monitoring method of claim 2, wherein said step S2 comprises the steps of:
s21: normalizing the data Ls1(t)、Ls2(t)、Ls3(t)、Ls4(t)、Ls5(t)、Ls6(t)、Ls7(t)、Ls8(t)、Ls9(t)、Ls10(t) substituting the signals into the ecological discrimination model as input signals X (t) respectively to calculate corresponding characteristic values ENs1、ENs2、ENs3、ENs4、ENs5、ENs6、ENs7、ENs8、ENs8、ENs9、ENs10；
Normalized data Lsi(t) substituting the signal into the ecological discrimination model to calculate the corresponding characteristic value ENsiThe method of (1) is as follows:
mixing L withsi(t) substituting as input signal X (t) into the ecological discriminant model:
Figure FDA0003277178240000031
Figure FDA0003277178240000032
wherein, P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of the lake ecological discrimination model, c, a, b and g are parameters, t is time, cos (2 pi ft) is a frequency component of an input signal, f is frequency, and M is the signal intensity of the excitation signal B (t);
adjusting the value of g from small to large, approaching the formula (1) and the formula (2) to a transition condition, stopping adjusting g when any one of the formula (1) and the formula (2) reaches the transition state, and recording the current value of g as gsiObtaining the characteristic curve FEDP of the lake ecology discrimination modelsi：
Figure FDA0003277178240000041
Taking characteristic curve FEDPsiMaximum value F1 and minimum value F2, characteristic value ENsi＝F1-F2：
S22: to ENs1As the response characteristic signal value of the negative oxygen ion sensor S1, the signal value is
Figure FDA0003277178240000042
EN is the value of the response characteristic signal of the light particulate matter sensor S2s3As the response characteristic signal value of the water temperature sensor S3, the response characteristic signal value is
Figure FDA0003277178240000043
EN is used as the response characteristic signal value of the heavy particulate matter sensor S4s5EN is used as the response characteristic signal value of the PH sensor S5s6EN is used as the response characteristic signal value of the dissolved oxygen sensor S6s7As a response characteristic signal value of the water conductivity sensor S7, ENs8As a response characteristic signal value of the ammonia nitrogen sensor S8, EN is useds9EN is the response characteristic signal value of the sound sensor S9s10As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multi-axis vector diagram with 10 sensor response axes on a plane by taking the response characteristic signal of each sensor as the response axis of the sensor, wherein the original points of all the sensor response axes are the same point, the included angle between the sensor Sn response axis and the sensor S (n +1) response axis is 36 degrees, and n is 1, 2 … … 9;
responding characteristic signal value EN corresponding to the sensor S1, the sensor S2, the sensor S4, the sensor S6 and the sensor S7s1、
Figure FDA0003277178240000044
ENs6、ENs7Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking the corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space A1, and calculating the sum of the areas of the enclosed closed spaces SA 1;
the response characteristic signal value EN corresponding to the sensor S3, the sensor S9 and the sensor S10s3、ENs9、ENs10Marking corresponding response points on corresponding sensor response axes, setting the corresponding response characteristic signal values of the other sensors to be 0.25, marking the corresponding response points on the corresponding sensor response axes, connecting the response points marked on the adjacent sensor response axes through straight lines to form a closed space, and calculating the sum SA2 of the areas of the enclosed closed space A2;
and calculating an ecological environment evaluation parameter SENK-SA 1-SA 2.
4. The offshore sea area ecological environment monitoring method as claimed in claim 2, wherein the negative oxygen ion sensor S1 is an HSTL-FYLZ sensor, the light particulate matter sensor S2 is an SIN-PTU110 sensor, the water temperature sensor S3 is a ZS02 sensor, the heavy particulate matter sensor S4 is an SIN-PSS110 sensor, the PH sensor S5 is an SIN-TDS210 sensor, the dissolved oxygen sensor S6 is an SIN-DM2800 sensor, the water conductivity sensor S7 is an SIN-TDS210 sensor, the ammonia nitrogen sensor S8 is an AMT-W400 sensor, the sound sensor S9 is a JHM-NS02 sensor, and the ultraviolet radiation sensor S10 is a GUVA-S12SD sensor.
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