CN113865645B - Offshore area ecological environment monitoring system and method - Google Patents
Offshore area ecological environment monitoring system and method Download PDFInfo
- Publication number
- CN113865645B CN113865645B CN202111132476.7A CN202111132476A CN113865645B CN 113865645 B CN113865645 B CN 113865645B CN 202111132476 A CN202111132476 A CN 202111132476A CN 113865645 B CN113865645 B CN 113865645B
- Authority
- CN
- China
- Prior art keywords
- sensor
- response
- ecological environment
- monitoring
- microprocessor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING
- B63B22/00—Buoys
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING
- B63B22/00—Buoys
- B63B2022/006—Buoys specially adapted for measuring or watch purposes
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/20—Controlling water pollution; Waste water treatment
Landscapes
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- Ocean & Marine Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
- Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
Abstract
The invention discloses an offshore area ecological environment monitoring system and method. The system comprises a monitoring terminal and a plurality of monitoring buoys arranged in different areas of an offshore area, wherein each monitoring buoy comprises a buoy body, a microprocessor, a power 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 module, the GPS module, the wireless communication module and the data acquisition module, the solar charging module is electrically connected with the power module, and the wireless communication module is in wireless connection with the monitoring terminal through a wireless network. The invention can monitor the ecological environment data of different areas of the offshore area on line in real time and judge the ecological environment health status of the different areas of the offshore area.
Description
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to an offshore area ecological environment monitoring system and method.
Background
The coastline from north to south in China is a long-lasting coastline, and the offshore area is rich in resources, but in recent years, as the influence of human activities on the environment of the offshore area is increasingly serious, the real-time monitoring of the ecological environment of the offshore area and the health evaluation are of great significance. At present, the evaluation of the health of the offshore area ecological system is usually carried out by only studying and judging the ecological condition of the offshore area according to certain measured key indexes, and the detection of the key indexes is generally carried out by manual measurement and analysis, so that the efficiency is low, the cost is high, and the whole condition in the detected area is difficult to effectively monitor in real time according to a theoretical optimal model.
Disclosure of Invention
The invention aims to solve the technical problems, and provides an offshore area ecological environment monitoring system and method, which can monitor ecological environment data of different areas of an offshore area on line in real time and judge ecological environment health states of the different areas of the offshore area.
In order to solve the problems, the invention is realized by adopting the following technical scheme:
the invention discloses an offshore area ecological environment monitoring system which comprises a monitoring terminal and a plurality of monitoring buoys arranged in different areas of an offshore 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 and 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, each data acquisition module comprises a negative oxygen ion sensor S1 for detecting the concentration of air negative oxygen ions in the sea area, 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 water body in the sea area, a PH sensor S5 for detecting the PH water body value in the sea area, an oxygen dissolving sensor S6 for detecting the dissolved oxygen content in the water body in the sea area, a water body conductivity sensor S7 for detecting the water body in the sea area, a water body conductivity sensor S for detecting the water body 8 for detecting the water body temperature and a UV radiation sensor for the ammonia nitrogen radiation sensor in the sea area.
In the scheme, the monitoring buoys are uniformly distributed in different areas of an offshore area, each monitoring buoy collects detection data of the area where the monitoring buoy is located and transmits the detection data to the monitoring terminal, and the monitoring terminal analyzes and processes the detection data transmitted 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 supply module by utilizing solar energy, so that the monitoring buoy can monitor for a long time, and the GPS module is used for positioning the position of the monitoring buoy, so that the monitoring terminal can grasp the current position of each monitoring buoy.
The invention discloses an offshore area ecological environment monitoring method which is used for the offshore area ecological environment monitoring system and comprises the following steps:
negative oxygen ion sensor S1 outputs detection data D s1 (t) to the microprocessor, the light particulate matter sensor S2 outputs detection data D s2 (t) to the microprocessor, the water temperature sensor S3 outputs the detection data D s3 (t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data D s4 (t) to the microprocessor, the PH sensor S5 outputs the detection data D s5 (t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data D s6 (t) to the microprocessor, the water conductivity sensor S7 outputs detection data D s7 (t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data D s8 (t) to the microprocessor, the sound sensor S9 outputs the detection data D s9 (t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data D s10 (t) to the microprocessor, wherein t is time, and the microprocessor transmits detection data to the monitoring terminal through the wireless communication module;
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 D s1 (t)、D s2 (t)、D s3 (t)、D s4 (t)、D s5 (t)、D s6 (t)、D s7 (t)、D s8 (t)、D s9 (t)、D s10 (t) respectively normalizing to [1, 10 ]]Obtaining corresponding normalized data L in the interval s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t)；
S2: the monitoring terminal is based on the normalized data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) calculating a corresponding feature value EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 Calculating a ecological environment evaluation parameter SENK;
s3: the monitoring terminal calculates average values SENKA and EN of the ecological environment evaluation parameters SENK once every N seconds s5 Average value ENA of (2) s5 、EN s8 Average value ENA of (2) s8 ；
When SENCA is greater than or equal to W1 and ENA s5 、ENA s8 When the current ecological environment is within the set range, judging that the current ecological environment of the area where the monitoring buoy is positioned is superior;
when W2 is less than SENKA and less than W1 and ENA s5 、ENA s8 When the current ecological environment is within the set range, judging that the current ecological environment of the area where the monitoring buoy is positioned is medium;
when SENCA is less than or equal to W2 or ENA s5 、ENA s8 When any one of the monitoring buoys exceeds the set range, judging that the current ecological environment of the area where the monitoring buoy is positioned is poor, and the like.
In the scheme, ten data of the ecological environment of the area where the monitoring buoy is located are detected by the negative oxygen ion sensor S1, the light particulate matter sensor S2, the water temperature sensor S3, the heavy particulate matter sensor S4, the PH sensor S5, the dissolved oxygen sensor S6, the water body conductivity sensor S7, the ammonia nitrogen sensor S8, the sound sensor S9 and the ultraviolet radiation sensor S10 and are transmitted to the monitoring terminal, the monitoring terminal processes and analyzes the data to calculate the parameter SENSA for comprehensively evaluating the health state of the ecological environment, and the environmental health state of the area where the monitoring buoy is located is comprehensively judged by combining the PH value and the ammonia nitrogen content which have great influence on the environment of the offshore area.
Preferably, the step S2 includes the steps of:
s21: will normalize data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) substituting the input signals X (t) into the ecological discrimination model to calculate corresponding characteristic values EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 ；
Normalized data L si (t) substituting the input signal X (t) into the ecological discrimination model to calculate the corresponding characteristic value ENs i The method of (1) is as follows, i=1-10:
will L si (t) substituting the input signal X (t) into the ecological discrimination model:
wherein P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of a physiological discrimination model, c, a, B, g is a parameter, t is time, cos (2pi ft) is a frequency component of an input signal, f is frequency, and M is a signal intensity of the excitation signal B (t);
regulating the value of g from small to large, approaching transition conditions of the formula (1) and the formula (2), stopping regulating g when any one of the formula (1) and the formula (2) reaches a transition state, and recording the current value of g as g si Obtaining the characteristic curve FEDP of the ecological discrimination model si ：
Taking characteristic curve FEDP si Maximum value F1 and minimum value F2 of (a), characteristic value EN si ＝F1-F2；
S22: EN is added s1 As a response characteristic signal value of the negative oxygen ion sensor S1, the following will beEN is set as a response characteristic signal value of the light particulate matter sensor S2 s3 As a response characteristic signal value of the water temperature sensor S3, will +.>EN is set as a response characteristic signal value of the heavy particulate matter sensor S4 s5 As a response characteristic signal value of the PH sensor S5, EN is set s6 EN is set as a response characteristic signal value of the dissolved oxygen sensor S6 s7 As the response characteristic signal value of the water body conductivity sensor S7, EN is taken s8 As a response characteristic signal value of the ammonia nitrogen sensor S8, EN is set s9 As a response characteristic signal value of the sound sensor S9, EN is set s10 As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multiaxial vector diagram with 10 sensor response axes on a plane by taking the response characteristic signals of each sensor as the response axes of the sensor, wherein the origins of all the sensor response axes are the same point, the included angle between the sensor Sn response axes and the sensor S (n+1) response axes is 36 degrees, and n=1, 2 … …;
according to response characteristic signal values EN corresponding to the negative oxygen ion sensor S1, the light particulate matter sensor S2, the heavy particulate matter sensor S4, the dissolved oxygen sensor S6 and the water body conductivity sensor S7 s1 、EN s6 、EN s7 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on the response shafts of adjacent sensors are connected through straight lines to form a closed space A1, and the sum SA1 of the areas of the enclosed closed spaces is calculated;
according to the response characteristic signal value EN corresponding to the water temperature sensor S3, the sound sensor S9 and the ultraviolet radiation sensor S10 s3 、EN s9 、EN s10 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on adjacent sensor response shafts are connected through a straight line to form a closed space, and the sum SA2 of the areas of the enclosed closed spaces A2 is calculated;
the ecological environment evaluation parameter senk=sa 1-SA2 is calculated.
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 body 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 beneficial effects of the invention are as follows: the ecological environment data of different areas of the offshore area can be monitored on line in real time, the ecological environment health states of the different areas of the offshore area can be 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 schematic diagram of the response characteristic signal values of the sensor in a multiaxial vector diagram enclosing an enclosed space A1;
fig. 4 is a schematic diagram of the response characteristic signal value of the sensor in the multiaxial vector diagram to form an enclosed space A2.
In the figure: 1. the monitoring system comprises a monitoring terminal, a monitoring buoy, a microprocessor, a power module, a GPS module, a wireless communication module, a data acquisition module, a solar charging module and a data acquisition module.
Detailed Description
The technical scheme of the invention is further specifically described below through examples and with reference to the accompanying drawings.
Examples: the 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 the 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 in wireless connection with the monitoring terminal 1 through a wireless network, the data acquisition module 7 comprises a negative oxygen ion sensor S1 for detecting the concentration of air negative oxygen ions in the sea area, a light particle sensor S2 for detecting the concentration of light particles in the water 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 heavy particles in the water in the sea area, a PH sensor S5 for detecting the PH water value in the sea area, an oxygen sensor S6 for detecting the dissolved oxygen amount in the sea area, an ammonia nitrogen sensor S for detecting the water content of the sea area and an ultraviolet radiation sensor for the sea area 10.
In the scheme, the monitoring buoys are uniformly distributed in different areas of an offshore area, each monitoring buoy collects detection data of the area where the monitoring buoy is located and transmits the detection data to the monitoring terminal, and the monitoring terminal analyzes and processes the detection data transmitted 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 supply module by utilizing solar energy, so that the monitoring buoy can monitor for a long time, and the GPS module is used for positioning the position of the monitoring buoy, so that the monitoring terminal can grasp the current position of each monitoring buoy.
The method for monitoring the ecological environment of the offshore area in the embodiment is used for the system for monitoring the ecological environment of the offshore area, and comprises the following steps:
negative oxygen ion sensor S1 outputs detection data D s1 (t) to the microprocessor, the light particulate matter sensor S2 outputs detection data D s2 (t) to the microprocessor, the water temperature sensor S3 outputs the detection data D s3 (t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data D s4 (t) to the microprocessor, the PH sensor S5 outputs the detection data D s5 (t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data D s6 (t) to the microprocessor, the water conductivity sensor S7 outputs detection data D s7 (t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data D s8 (t) to the microprocessor, the sound sensor S9 outputs the detection data D s9 (t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data D s10 (t) to the microprocessor, wherein t is time, and the microprocessor transmits detection data to the monitoring terminal through the wireless communication module;
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 D s1 (t)、D s2 (t)、D s3 (t)、D s4 (t)、D s5 (t)、D s6 (t)、D s7 (t)、D s8 (t)、D s9 (t)、D s10 (t) respectively normalizing to [1, 10 ]]Obtaining corresponding normalized data L in the interval s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t)；
S2: the monitoring terminal is based on the normalized data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) calculating a corresponding feature value EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 Calculating a ecological environment evaluation parameter SENK;
step S2 comprises the steps of:
s21: will normalize data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) substituting the input signals X (t) into the ecological discrimination model to calculate corresponding characteristic values EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 ；
Normalized data L si (t) substituting the input signal X (t) into the ecological discrimination model to calculate the corresponding characteristic value EN si The method of (1) is as follows, i=1-10:
will L si (t) substituting the input signal X (t) into the ecological discrimination model:
wherein P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of a physiological discrimination model, c, a, B, g is a parameter, t is time, cos (2pi ft) is a frequency component of an input signal, f is frequency, and M is a signal intensity of the excitation signal B (t);
regulating the value of g from small to large, approaching transition conditions of the formula (1) and the formula (2), stopping regulating g when any one of the formula (1) and the formula (2) reaches a transition state, and recording the current value of g as g si Obtaining the characteristic curve FEDP of the ecological discrimination model si ：
Characteristic curve FEDP si As shown in FIG. 2, a characteristic curve FEDP is taken si Maximum value F1 and minimum value F2 of (a), characteristic value EN si ＝F1-F2；
S22: EN is added s1 As a response characteristic signal value of the negative oxygen ion sensor S1, the following will beEN is set as a response characteristic signal value of the light particulate matter sensor S2 s3 As a response characteristic signal value of the water temperature sensor S3, will +.>EN is set as a response characteristic signal value of the heavy particulate matter sensor S4 s5 As a response characteristic signal value of the PH sensor S5, EN is set s6 EN is set as a response characteristic signal value of the dissolved oxygen sensor S6 s7 As the response characteristic signal value of the water body conductivity sensor S7, EN is taken s8 As a response characteristic signal value of the ammonia nitrogen sensor S8, EN is set s9 As a response characteristic signal value of the sound sensor S9, EN is set s10 As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multiaxial vector diagram with 10 sensor response axes on a plane by taking the response characteristic signals of each sensor as the response axes of the sensor, wherein the origins of all the sensor response axes are the same point, the included angle between the sensor Sn response axes and the sensor S (n+1) response axes is 36 degrees, and n=1, 2 … …;
according to the negative oxygen ion sensor S1, the light particulate matter sensor S2 and the heavy particulate matterResponse characteristic signal value EN corresponding to particulate matter sensor S4, dissolved oxygen sensor S6 and water body conductivity sensor S7 s1 、EN s6 、EN s7 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on the response shafts of adjacent sensors are connected through straight lines to form a closed space A1, and as shown in FIG. 3, the sum SA1 of the areas of the enclosed closed spaces is calculated;
according to the response characteristic signal value EN corresponding to the water temperature sensor S3, the sound sensor S9 and the ultraviolet radiation sensor S10 s3 、EN s9 、EN s10 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on the response shafts of adjacent sensors are connected through straight lines to form a closed space, and the sum SA2 of the areas of the enclosed closed spaces A2 is calculated as shown in FIG. 4;
calculating an ecological environment evaluation parameter senk=sa 1-SA2;
s3: the monitoring terminal calculates average values SENKA and EN of the ecological environment evaluation parameters SENK once every N seconds s5 Average value ENA of (2) s5 、EN s8 Average value ENA of (2) s8 ；
When SENCA is more than or equal to 0.7 and ENA s5 Less than 1.2 and less than or equal to 1.0 ENA s8 When the current ecological environment is less than 3.8, judging the current ecological environment to be superior;
when SENCA is more than 0.2 and less than 0.7 and ENA is more than 0.2 s5 Less than 1.2 and less than or equal to 1.0 ENA s8 When the current ecological environment is less than 3.8, judging that the current ecological environment is medium;
when SENCA is less than or equal to 0.2 or ENA s5 Not less than 1.2 or ENA s8 < 1.0 or ENA s8 And when the current ecological environment is not less than 3.8, judging that the current ecological environment is poor, and the like.
In the scheme, ten data of the ecological environment of the area where the monitoring buoy is located are detected by the negative oxygen ion sensor S1, the light particulate matter sensor S2, the water temperature sensor S3, the heavy particulate matter sensor S4, the PH sensor S5, the dissolved oxygen sensor S6, the water body conductivity sensor S7, the ammonia nitrogen sensor S8, the sound sensor S9 and the ultraviolet radiation sensor S10 and are transmitted to the monitoring terminal, the monitoring terminal processes and analyzes the data to calculate the parameter SENSA for comprehensively evaluating the health state of the ecological environment, and the environmental health state of the area where the monitoring buoy is located is comprehensively judged by combining the PH value and the ammonia nitrogen content which have great influence on the environment of the offshore area.
The negative oxygen ion sensor S1 detects sea area air negative oxygen ion information, the dissolved oxygen sensor S6 detects sea area water dissolved oxygen amount information, the water conductivity sensor S7 detects sea area water 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 particulate matter sensor S2 detects the concentration information of light particulate matters in the water body in the sea area, the heavy particulate matter sensor S4 detects the concentration information of heavy particulate matters in the water body in the sea area, and the detection indexes of the light particulate matter sensor S2 are closely related to the ecology but are in inverse relation; the water temperature sensor S3 detects the water temperature information of the water body in the sea area, the sound sensor S9 detects the noise information of the sea area, the ultraviolet radiation sensor S10 detects the ultraviolet radiation amount 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 of the ammonia nitrogen content do not determine whether the ecological environment is good or bad in the maximum value or minimum value interval, but influence the ecological environment evaluation 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 body 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 (2)
1. An offshore area ecological environment monitoring method is used for an offshore area ecological environment monitoring system, the offshore area ecological environment monitoring system comprises a monitoring terminal (1) and a plurality of monitoring buoys (2) arranged in different areas of an offshore area, each monitoring buoy (2) comprises a buoy body, a microprocessor (3), a power supply 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 electrically connected with the power supply 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 supply module (4), the wireless communication module (6) is in wireless connection with the monitoring terminal (1) through a wireless network, and each data acquisition module (7) comprises a water temperature sensor S2 for detecting the concentration of water area air negative oxygen ions, a PH sensor S4 for detecting the concentration of water area water body, and a sensor S4 for detecting the water body concentration of ammonia nitrogen and pH sensor for detecting the water body A sound sensor S9 for detecting sea noise, and an ultraviolet radiation sensor S10 for detecting sea ultraviolet radiation, comprising the steps of:
negative oxygen ion sensor S1 outputs detection data D s1 (t) to the microprocessor, the light particulate matter sensor S2 outputs detection data D s2 (t) to the microprocessor, the water temperature sensor S3 outputs the detection data D s3 (t) to the microprocessor, the heavy particulate matter sensor S4 outputs detection data D s4 (t) to the microprocessor, the PH sensor S5 outputs the detection data D s5 (t) to the microprocessor, the dissolved oxygen sensor S6 outputs detection data D s6 (t) to the microprocessor, the water conductivity sensor S7 outputs detection data D s7 (t) to the microprocessor, the ammonia nitrogen sensor S8 outputs detection data D s8 (t) to the microprocessor, the sound sensor S9 outputs a detectionData D s9 (t) to the microprocessor, the ultraviolet radiation sensor S10 outputs detection data D s10 (t) to the microprocessor, wherein t is time, and the microprocessor transmits detection data to the monitoring terminal through the wireless communication module;
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 D s1 (t)、D s2 (t)、D s3 (t)、D s4 (t)、D s5 (t)、D s6 (t)、D s7 (t)、D s8 (t)、D s9 (t)、D s10 (t) respectively normalizing to [1, 10 ]]Obtaining corresponding normalized data L in the interval s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t)；
S2: the monitoring terminal is based on the normalized data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) calculating a corresponding feature value EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 Calculating a ecological environment evaluation parameter SENK;
s3: the monitoring terminal calculates average values SENKA and EN of the ecological environment evaluation parameters SENK once every N seconds s5 Average value ENA of (2) s5 、EN s8 Average value ENA of (2) s8 ；
When SENCA is greater than or equal to W1 and ENA s5 、ENA s8 When the current ecological environment is within the set range, judging that the current ecological environment of the area where the monitoring buoy is positioned is superior;
when W2 is less than SENKA and less than W1 and ENA s5 、ENA s8 When the current ecological environment is within the set range, the current ecological environment of the area where the monitoring buoy is located is judged to be medium；
When SENCA is less than or equal to W2 or ENA s5 、ENA s8 When any one of the monitoring buoys exceeds the set range, judging that the current ecological environment of the area where the monitoring buoy is positioned is poor, and the like;
the step S2 includes the steps of:
s21: will normalize data L s1 (t)、L s2 (t)、L s3 (t)、L s4 (t)、L s5 (t)、L s6 (t)、L s7 (t)、L s8 (t)、L s9 (t)、L s10 (t) substituting the input signals X (t) into the ecological discrimination model to calculate corresponding characteristic values EN s1 、EN s2 、EN s3 、EN s4 、EN s5 、EN s6 、EN s7 、EN s8 、EN s9 、EN s10 ；
Normalized data L si (t) substituting the input signal X (t) into the ecological discrimination model to calculate the corresponding characteristic value ENs i The method of (1) is as follows, i=1-10:
will L si (t) substituting the input signal X (t) into the ecological discrimination model:
wherein P (y) is a load system, B (t) is an excitation signal, y is a dynamic parameter of a physiological discrimination model, c, a, B, g is a parameter, t is time, cos (2pi ft) is a frequency component of an input signal, f is frequency, and M is a signal intensity of the excitation signal B (t);
regulating the value of g from small to large, approaching transition conditions of the formula (1) and the formula (2), stopping regulating g when any one of the formula (1) and the formula (2) reaches a transition state, and recording the current value of g as g si Obtaining the characteristic curve FEDP of the ecological discrimination model si ：
Taking characteristic curve FEDP si Maximum value F1 and minimum value F2 of (a), characteristic value EN si ＝F1-F2；
S22: EN is added s1 As a response characteristic signal value of the negative oxygen ion sensor S1, the following will beEN is set as a response characteristic signal value of the light particulate matter sensor S2 s3 As a response characteristic signal value of the water temperature sensor S3, will +.>EN is set as a response characteristic signal value of the heavy particulate matter sensor S4 s5 As a response characteristic signal value of the PH sensor S5, EN is set s6 EN is set as a response characteristic signal value of the dissolved oxygen sensor S6 s7 As the response characteristic signal value of the water body conductivity sensor S7, EN is taken s8 As a response characteristic signal value of the ammonia nitrogen sensor S8, EN is set s9 As a response characteristic signal value of the sound sensor S9, EN is set s10 As a response characteristic signal value of the ultraviolet radiation sensor S10;
drawing a multiaxial vector diagram with 10 sensor response axes on a plane by taking the response characteristic signals of each sensor as the response axes of the sensor, wherein the origins of all the sensor response axes are the same point, the included angle between the sensor Sn response axes and the sensor S (n+1) response axes is 36 degrees, and n=1, 2 … …;
according to response characteristic signal values EN corresponding to the negative oxygen ion sensor S1, the light particulate matter sensor S2, the heavy particulate matter sensor S4, the dissolved oxygen sensor S6 and the water body conductivity sensor S7 s1 、EN s6 、EN s7 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on the response shafts of adjacent sensors are connected through straight lines to form a closed space A1, and the sum SA1 of the areas of the enclosed closed spaces is calculated;
according to the response characteristic signal value EN corresponding to the water temperature sensor S3, the sound sensor S9 and the ultraviolet radiation sensor S10 s3 、EN s9 、EN s10 Corresponding response points are marked on corresponding sensor response shafts, response characteristic signal values corresponding to other sensors are set to be 0.25, corresponding response points are marked on corresponding sensor response shafts, the response points marked on adjacent sensor response shafts are connected through a straight line to form a closed space, and the sum SA2 of the areas of the enclosed closed spaces A2 is calculated;
the ecological environment evaluation parameter senk=sa 1-SA2 is calculated.
2. The offshore area ecological environment monitoring method of claim 1, wherein the negative oxygen ion sensor S1 is an HSTL-FYLZ sensor, the light particulate sensor S2 is an SIN-PTU110 sensor, the water temperature sensor S3 is a ZS02 sensor, the heavy particulate 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 body 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 guava-S12 SD sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111132476.7A CN113865645B (en) | 2021-09-24 | 2021-09-24 | Offshore area ecological environment monitoring system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111132476.7A CN113865645B (en) | 2021-09-24 | 2021-09-24 | Offshore area ecological environment monitoring system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113865645A CN113865645A (en) | 2021-12-31 |
| CN113865645B true CN113865645B (en) | 2023-08-18 |
Family
ID=78991034
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111132476.7A Active CN113865645B (en) | 2021-09-24 | 2021-09-24 | Offshore area ecological environment monitoring system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113865645B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116125023A (en) * | 2023-02-03 | 2023-05-16 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Automatic synchronous monitoring technology for vertical section and transverse direction of water body |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20010104898A (en) * | 2000-05-16 | 2001-11-28 | 이재성 | apparatus for watching state in maritime buoy |
| CN104802936A (en) * | 2015-04-28 | 2015-07-29 | 中国农业大学 | Paralic environment monitoring buoy and system |
| CN205664866U (en) * | 2016-05-31 | 2016-10-26 | 广东海洋大学 | Ocean quality of water data acquisition system of on -board |
| CN106778013A (en) * | 2016-12-29 | 2017-05-31 | 钦州学院 | A kind of integrated evaluating method of offshore sea waters ecological environment |
| CN212134670U (en) * | 2020-04-29 | 2020-12-11 | 湖南国天电子科技有限公司 | Online monitoring and data management system applied to ocean buoy |
-
2021
- 2021-09-24 CN CN202111132476.7A patent/CN113865645B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20010104898A (en) * | 2000-05-16 | 2001-11-28 | 이재성 | apparatus for watching state in maritime buoy |
| CN104802936A (en) * | 2015-04-28 | 2015-07-29 | 中国农业大学 | Paralic environment monitoring buoy and system |
| CN205664866U (en) * | 2016-05-31 | 2016-10-26 | 广东海洋大学 | Ocean quality of water data acquisition system of on -board |
| CN106778013A (en) * | 2016-12-29 | 2017-05-31 | 钦州学院 | A kind of integrated evaluating method of offshore sea waters ecological environment |
| CN212134670U (en) * | 2020-04-29 | 2020-12-11 | 湖南国天电子科技有限公司 | Online monitoring and data management system applied to ocean buoy |
Non-Patent Citations (1)
| Title |
|---|
| 城市生态安全的多种评价模型及应用;李佩武;李贵才;张金花;徐凤;陈莉;;地理研究(02);293-302 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113865645A (en) | 2021-12-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113865645B (en) | Offshore area ecological environment monitoring system and method | |
| CN110231111A (en) | A kind of contactless stress method of real-time of buried pipeline | |
| CN205941678U (en) | Power battery current detection device based on shunt | |
| CN101782567B (en) | Intelligent ammonia nitrogen transmitting system and ammonia nitrogen in situ high-frequency detection method | |
| CN202379324U (en) | Intelligent container sensor | |
| CN103942965A (en) | Geomagnetic vehicle detector | |
| CN201291774Y (en) | Electrokinetic cell package flooding detecting device | |
| CN107449884A (en) | A kind of sewage monitoring system based on wireless sensor network | |
| CN206892087U (en) | A kind of optics water quality on-line monitoring system based on technology of Internet of things | |
| CN206892088U (en) | A kind of surface water quality online monitoring system based on technology of Internet of things | |
| CN207067109U (en) | A kind of drinking water quality online monitoring system based on technology of Internet of things | |
| CN107490617B (en) | Weak magnetic nondestructive detection sensor for defects of coal bed gas pipeline and use method | |
| CN206258123U (en) | A kind of multifunctional intellectual display terminal | |
| CN105825682B (en) | Earth magnetism vehicle detection apparatus | |
| CN113654598B (en) | Lake ecological environment monitoring system and method | |
| CN113847954B (en) | Forest ecological environment monitoring method | |
| CN207180747U (en) | A kind of multi-parameter water quality computer monitoring system | |
| CN206648744U (en) | The temperature monitoring equipment of substation equipment | |
| CN105913628B (en) | Magnetic Sensor output circuit and data wireless transmission and control system method | |
| CN202887453U (en) | Vehicle detector with low power consumption wireless communication and solar energy collection mechanism | |
| CN202748234U (en) | Power transmission iron tower intensity and vibration off-line intelligent inspection tour system | |
| CN207198344U (en) | A kind of ZigBee vehicle detecting systems based on GMR | |
| CN113686395B (en) | Mountain forest land ecological environment monitoring device and method | |
| CN206258136U (en) | A kind of Multifunction Sensor | |
| CN102831665A (en) | Power transmission tower intensity and vibration off-line intelligent routing inspection system and early warning method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |