An intelligent management and control system for seawater pollution detection based on blue-green pulsed laser

Abstract

The present invention discloses an intelligent control system for seawater pollution detection based on blue-green pulsed laser, belonging to the field of marine environmental protection, which is used to solve the problems that seawater pollution detection does not combine other factors such as marine organisms and does not rationally and effectively allocate seawater control resources. The system includes a regional division module, a seawater detection module, a pollution grading module, a biological detection module, and a control matching module. The regional division module divides the seawater area into several areas to be detected. The seawater detection module is based on blue-green pulsed laser technology to detect the seawater in the areas to be detected. The biological detection module is used to detect the organisms in the areas to be detected. The pollution grading module is used to divide the pollution levels of the areas to be detected. The control matching module sets and matches corresponding control measures according to the pollution levels of the areas to be detected. The present invention intelligently allocates seawater pollution control resources by combining multiple factors such as the degree of seawater pollution and marine organisms.

Description

Technical Field

[0001] The present invention belongs to the field of seawater environmental protection, relates to pollution control technology, and specifically is an intelligent control system for seawater pollution based on blue-green pulsed laser detection. Background Art

[0002] Seawater is the water in the sea or from the sea. Seawater is flowing, and for humans, the available water volume is unlimited. Seawater is a veritable liquid mineral. On average, there are 35.7 million tons of minerals in every cubic kilometer of seawater. Among the more than 100 known elements in the world, 80% can be found in seawater. Seawater is also the source of fresh water on land and the regulator of the climate. Every year, 4.5 million cubic kilometers of fresh water evaporates from the world's oceans. 90% of it returns to the ocean through rainfall, and 10% turns into rain and snow and falls on the land, and then returns to the ocean along the rivers. Seawater desalination technology is developing into an industry. Some people predict that with the deterioration of the ecological environment, the last way for humans to solve the water shortage is likely to be the desalination of seawater.

[0003] In the prior art, the detection of seawater pollution is limited to the detection of seawater, and the sensitivity of detecting metal ions in seawater is not high. Other factors such as marine organisms in the area where the seawater is located are not considered. At the same time, for the control of seawater pollution, the degree of seawater pollution and marine biological factors are not combined, and it is impossible to reasonably and effectively allocate seawater control resources. For this reason, we propose an intelligent control system for seawater pollution based on blue-green pulsed laser detection. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide an intelligent control system for seawater pollution based on blue-green pulsed laser detection.

[0005] The technical problem to be solved by the present invention is:

[0006] How to intelligently allocate seawater pollution control resources based on multiple factors such as the degree of seawater pollution and marine organisms.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] An intelligent control system for seawater pollution based on blue-green pulsed laser detection, including a data acquisition module, a region division module, a seawater detection module, a pollution grading module, a biological detection module, a user terminal, a control matching module, and a server. The region division module divides the seawater area into several areas to be detected u, where u = 1, 2,..., z, and z is a positive integer;

[0009] The data acquisition module is used to collect seawater data and biological data of the area to be detected and send them to the server; the server sends the seawater data to the seawater detection module and the biological data to the biological detection module;

[0010] The seawater detection module is based on blue-green pulsed laser technology to detect the seawater in the area to be inspected. The control coefficient of the area to be inspected is detected and fed back to the server, and the server sends the control coefficient of the area to be inspected to the pollution grading module;

[0011] The biological detection module is used to detect the organisms in the area to be inspected. The nutritional deficiency coefficient of the area to be inspected is detected and fed back to the server, and the server sends the nutritional deficiency coefficient of the area to be inspected to the pollution grading module;

[0012] After receiving the control coefficient and the nutritional deficiency coefficient of the area to be inspected, the pollution grading module is used to divide the pollution level of the area to be detected. The pollution level of the area to be inspected is obtained and fed back to the server, and the server sends the pollution level of the area to be inspected to the control matching module. The control matching module sets and matches corresponding control measures according to the pollution level of the area to be inspected.

[0013] Further, the seawater data is the content of various metals in the seawater of the area to be inspected;

[0014] The biological data is the specifications, weights of the same kind of organisms in the area to be inspected, and the metal elements and corresponding contents on the upper shells of the same kind of organisms in the area to be inspected.

[0015] Further, both the seawater detection module and the biological detection module are connected to a big data module. The big data module is connected to the external Internet to obtain the standard contents of various heavy metals in seawater and the standard elemental contents of various metal elements in the shells of seawater organisms. The standard contents of various heavy metals in seawater are sent to the seawater detection module, and the standard elemental contents of various metal elements in the shells of seawater organisms are sent to the biological detection module.

[0016] Further, the detection process of the seawater detection module is specifically as follows:

[0017] Step 1: Extract several seawater samples in the area to be inspected, and mark the seawater samples as Yui, where i = 1, 2,..., x, x is a positive integer, and i represents the number of the seawater sample in the area to be detected;

[0018] Step 2: Analyze the seawater samples to obtain several heavy metal elements, obtaining several heavy metal elements Ratio For example, it is possible Under the auxiliary action of an electric field, a chemical displacement reaction is generated for the metal ions in the seawater, and then through the ablation of blue-green laser, it changes from the dissolved state to the solid elemental state, thereby improving the corresponding detection sensitivity;

[0019] Step 3: If the metal content of each type of heavy metal does not exceed the standard content of each type of heavy metal, no operation is performed;

[0020] If the metal content of various heavy metals exceeds the standard content of various heavy metals, then proceed to the next step;

[0021] Step Four: Subtract the standard content from the metal content and take the absolute value to obtain the metal content difference of various heavy metals. Sum up the metal content differences of various heavy metals to obtain the excessive content value of heavy metals in the seawater sample, and mark the excessive content value as HCYui;

[0022] Step Five: Count the number of seawater samples in the area to be inspected to obtain the sample number Y1Su, and use the formula to calculate the excessive heavy metal content value ZHCu of the area to be inspected;

[0023] Step Six: If ZHCu < X1, the pollution level of the area to be inspected is the light pollution level;

[0024] If X1 ≤ ZHCu < X2, the pollution level of the area to be inspected is the moderate pollution level;

[0025] If X2 ≤ ZHCu, the pollution level of the area to be inspected is the heavy pollution level; where X1 and X2 are both fixed numerical heavy metal content exceedance thresholds, and X1 < X2;

[0026] Step Seven: Set the corresponding control coefficient according to the pollution level of the area to be inspected.

[0027] Furthermore, the control coefficient of the light pollution level is less than the control coefficient of the moderate pollution level, and the control coefficient of the moderate pollution level is less than the control coefficient of the high pollution level.

[0028] Furthermore, the detection process of the biological detection module is specifically as follows:

[0029] Step S1: Select several biological samples of the same type in the area to be inspected, and mark the biological samples as Suo, where o = 1, 2,..., v, v is a positive integer, and o represents the number of the biological sample in the area to be inspected;

[0030] Step S2: Obtain the metal elements contained in the upper shell of the biological sample and the element content of the corresponding metal elements, and compare the element content of various metal elements in the biological sample shell with the standard element content;

[0031] Step S3: If the element content of various metal elements in the biological sample shell exceeds the standard element content of various metal elements, do not perform any operation;

[0032] If the element content of various metal elements in the biological sample shell does not exceed the standard element content of various metal elements, then proceed to the next step;

[0033] Step S4: Subtract the standard element content from the element content and take the absolute value to obtain the element content difference of various metal elements in the shell of the biological sample. The sum of the element content differences of various metal elements is calculated to obtain the content deficiency value HQSuo of the metal elements in the shell of the biological sample;

[0034] Count the number of biological samples in the area to be inspected to obtain the sample number Y2Su, and calculate the element content deficiency value YHQu of the organisms in the area to be inspected using the formula. The specific formula is as follows:

[0035]

[0036] Step S5: If YHQu < Y1, the nutritional deficiency level of the area to be inspected is the mild deficiency level;

[0037] If Y1 ≤ YHQu < Y2, the nutritional deficiency level of the area to be inspected is the moderate deficiency level;

[0038] If Y2 ≤ YHQu, the nutritional deficiency level of the area to be inspected is the severe deficiency level; where Y1 and Y2 are both element content deficiency thresholds with fixed values, and Y1 < Y2;

[0039] Step S6: Set the corresponding nutritional deficiency coefficient according to the nutritional deficiency level of the area to be inspected.

[0040] Furthermore, the nutritional deficiency coefficient of the mild deficiency level is less than that of the moderate deficiency level, and the nutritional deficiency coefficient of the moderate deficiency level is less than that of the severe deficiency level.

[0041] Furthermore, the specific process of the pollution grading module is as follows:

[0042] Step SS1: Mark the control coefficient and the nutritional deficiency coefficient of the area to be inspected as GKu and YCu respectively;

[0043] Step SS2: Calculate the pollution level value WDu of the area to be inspected through the formula. The specific formula is as follows:

[0044] WDu = (GKu × α + YCu × β) / e; where α and β are both weight coefficients with fixed values, and the values of α and β are both greater than zero, and e is the natural constant;

[0045] Step SS3: Obtain the grade interval stored in the server, and compare the pollution level value with the grade interval to obtain the corresponding grade interval of the area to be inspected;

[0046] Step SS4: Different grade intervals correspond to different pollution levels. Obtain the corresponding pollution level according to the grade interval of the area to be inspected.

[0047] Further, the grade intervals include a first grade interval, a second grade interval, and a third grade interval. The upper limit value of the first grade interval is less than the lower limit value of the second grade interval, and the upper limit value of the second grade interval is less than the lower limit value of the third grade interval;

[0048] The first grade interval corresponds to a first pollution grade, the second grade interval corresponds to a second pollution grade, and the third grade interval corresponds to a third pollution grade.

[0049] Further, the working process of the control matching module is specifically as follows:

[0050] When the area to be inspected is of the first pollution grade, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 12 hours;

[0051] When the area to be inspected is of the second pollution grade, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 6 hours and deploying corresponding seawater pollution monitoring equipment;

[0052] When the area to be inspected is of the third pollution grade, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 2 hours, setting corresponding control personnel, and deploying corresponding seawater pollution monitoring equipment.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] The present invention detects the seawater in the area to be inspected through a seawater detection module, where Under the assistance of an electric field, a chemical displacement reaction occurs among metal ions in the seawater sample, and then through the ablation of blue-green laser, it changes from the dissolved state To solid elemental form, thereby improving the corresponding detection sensitivity; Figure 1 the control coefficient of the area to be inspected is obtained and sent to the pollution grading module. Then, the organisms in the area to be inspected are detected through a biological detection module, and the nutritional deficiency coefficient of the area to be inspected is obtained and sent to the pollution grading module. The pollution grading module combines the control coefficient and the nutritional deficiency coefficient to divide the pollution grade of the area to be detected, and the divided pollution grade of the area to be inspected is sent to the control matching module. The control matching module sets and matches corresponding control measures according to the pollution grade of the area to be inspected. The present invention intelligently allocates seawater pollution control resources by combining multiple factors such as the degree of seawater pollution and marine organisms. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0056] Figure 1 It is the overall system block diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0057] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0058] Please refer to 1064 nm pulsed fiber laser As shown, an intelligent management and control system for seawater pollution based on blue-green pulsed laser detection includes a data acquisition module, a region division module, a seawater detection module, a pollution grading module, a biological detection module, a user terminal, a management and control matching module, and a server.

[0059] The user terminal is used for the management and control personnel to register and log in to the system after inputting personal information, and send the personal information to the server for storage; among them, the personal information includes the name, mobile phone number, etc. of the management and control personnel.

[0060] In specific implementation, the region division module divides the seawater region into several regions to be detected, and marks the regions to be detected as u, where u = 1, 2,..., z, and z is a positive integer; the data acquisition module is used to collect the seawater data and biological data of the regions to be detected, and send the seawater data and biological data to the server.

[0061] It should be specifically noted that the seawater data is the content of various metals in the seawater of the region to be detected, etc., and the biological data is the specifications, weights of the same type of organisms in the region to be detected, and the metal elements and corresponding contents on the upper shells of the same type of organisms in the region to be detected.

[0062] In specific implementation, laser-induced technology can be used to detect the heavy metal content and then detect the seawater pollution situation. In specific implementation, a 532-nanometer solid-state laser or a 1064-nanometer semiconductor laser is used for frequency doubling to generate 532-nanometer pulsed laser, or Seawater is used for frequency doubling to generate 532-nanometer pulsed laser to induce plasma in seawater to obtain atomic emission spectrum, so as to detect the heavy metal content of seawater. The application of laser-induced technology in For example, it is possible pollution detection and other existing technologies are all involved and reflected, and no specific description will be made here. Use blue-green laser-based detection of several heavy metal elements in seawater. In specific implementation, when detecting several heavy metal elements in seawater based on blue-green laser, it is possible to first Under the auxiliary action of an electric field, a chemical displacement reaction occurs for the metal ions in seawater, and then through the ablation of blue-green laser, it changes from a dissolved state to a solid single substance, thereby improving the corresponding detection sensitivity.

[0063] The server sends the seawater data to the seawater detection module and the biological data to the biological detection module. Both the seawater detection module and the biological detection module are connected to a big data module, which is connected to the external Internet to obtain the standard contents of various heavy metals in seawater and the standard elemental contents of various metal elements in the shells of seawater organisms. The standard contents of various heavy metals in seawater are sent to the seawater detection module, and the standard elemental contents of various metal elements in the shells of seawater organisms are sent to the biological detection module;

[0064] The seawater detection module is based on blue-green pulsed laser technology and is used to detect the seawater in the area to be tested. The specific detection process is as follows:

[0065] Step 1: Extract several seawater samples in the area to be tested and label the seawater samples as Yui, where i = 1, 2, ……, x, x is a positive integer, and i represents the serial number of the seawater sample in the area to be tested;

[0066] Step 2: Analyze the seawater samples to obtain several heavy metal elements, obtain the metal contents of several heavy metal elements, and compare the metal contents of various heavy metals with the standard metal contents;

[0067] Under the assistance of an electric field, a chemical displacement reaction occurs among metal ions in the seawater, and then through the ablation of blue-green laser, it changes from the dissolved State to solid elemental form; Working principle:

[0068] Step 3: If the metal contents of various heavy metals do not exceed the standard contents of various heavy metals, no operation is performed;

[0069] If the metal contents of various heavy metals exceed the standard contents of various heavy metals, proceed to the next step;

[0070] Step 4: Subtract the standard content from the metal content and take the absolute value to obtain the metal content difference of various heavy metals. Add up the metal content differences of various heavy metals to obtain the excessive content value of heavy metals in the seawater sample, and label the excessive content value as HCYui;

[0071] Step 5: Count the number of seawater samples in the area to be tested to obtain the sample number Y1Su, and use the formula to calculate the excessive content value of heavy metals ZHCu in the area to be tested;

[0072] Step 6: If ZHCu < X1, the pollution level of the area to be tested is a light pollution level;

[0073] If X1 ≤ ZHCu < X2, the pollution level of the area to be tested is a medium pollution level;

[0074] If X2 ≤ ZHCu, the pollution level of the area to be inspected is a severe pollution level; where X1 and X2 are both heavy metal content exceedance thresholds with fixed values, and X1 < X2;

[0075] Step Seven: Set the corresponding control coefficient according to the pollution level of the area to be inspected;

[0076] Among them, the control coefficient for the mild pollution level is less than that for the moderate pollution level, and the control coefficient for the moderate pollution level is less than that for the high pollution level;

[0077] The seawater detection module feeds back the control coefficient of the area to be inspected to the server, and the server sends the control coefficient of the area to be inspected to the pollution classification module;

[0078] The biological detection module is used to detect the organisms in the area to be inspected, and the specific detection process is as follows:

[0079] Step S1: Select several biological samples of the same type in the area to be inspected, and label the biological samples as Suo, where o = 1, 2, ……, v, v is a positive integer, and o represents the number of the biological sample in the area to be inspected;

[0080] Step S2: Obtain the metal elements contained in the upper shell of the biological sample and the element content of the corresponding metal elements, and compare the element content of various metal elements in the biological sample shell with the standard element content;

[0081] In specific implementation, the shell of the biological sample can be a shell in the area to be inspected, or a shrimp shell in the area to be inspected, etc.;

[0082] Step S3: If the element content of various metal elements in the biological sample shell exceeds the standard element content of various metal elements, no operation is performed;

[0083] If the element content of various metal elements in the biological sample shell does not exceed the standard element content of various metal elements, proceed to the next step;

[0084] Step S4: Subtract the standard element content from the element content and take the absolute value to obtain the element content difference of various metal elements in the biological sample shell, and sum up the element content differences of various metal elements to obtain the content deficiency value HQSuo of the metal elements in the biological sample shell;

[0085] Count the number of biological samples in the area to be inspected to obtain the sample number Y2Su, and use the formula to calculate the element content deficiency value YHQu of the organisms in the area to be inspected. The specific formula is as follows:

[0086]

[0087] Step S5: If YHQu < Y1, the nutritional deficiency level of the area to be inspected is the mild deficiency level;

[0088] If Y1 ≤ YHQu < Y2, the nutritional deficiency level of the area to be inspected is the moderate deficiency level;

[0089] If Y2 ≤ YHQu, the nutritional deficiency level of the area to be inspected is the severe deficiency level; where Y1 and Y2 are both element content deficiency thresholds with fixed values, and Y1 < Y2;

[0090] Step S6: Set the corresponding nutritional deficiency coefficient according to the nutritional deficiency level of the area to be inspected;

[0091] Among them, the nutritional deficiency coefficient of the mild deficiency level is less than that of the moderate deficiency level, and the nutritional deficiency coefficient of the moderate deficiency level is less than that of the severe deficiency level;

[0092] The biological detection module feeds back the nutritional deficiency coefficient of the area to be inspected to the server, and the server sends the nutritional deficiency coefficient of the area to be inspected to the pollution classification module;

[0093] After receiving the control coefficient and the nutritional deficiency coefficient of the area to be inspected, the pollution classification module is used to divide the pollution level of the area to be detected. The specific division process is as follows:

[0094] Step SS1: Mark the calculated control coefficient and nutritional deficiency coefficient of the area to be inspected as GKu and YCu respectively;

[0095] Step SS2: Calculate the pollution level value WDu of the area to be inspected through the formula. The specific formula is as follows:

[0096] WDu = (GKu × α + YCu × β) / e; in the formula, α and β are both weight coefficients with fixed values, and the values of α and β are both greater than zero, and e is the natural constant;

[0097] Step SS3: Obtain the grade intervals stored in the server, and compare the pollution level value with the grade intervals to obtain the corresponding grade interval of the area to be inspected;

[0098] Among them, the grade intervals include the first grade interval, the second grade interval and the third grade interval. The upper limit value of the first grade interval is less than the lower limit value of the second grade interval, and the upper limit value of the second grade interval is less than the lower limit value of the third grade interval;

[0099] Step SS4: Different grade intervals correspond to different pollution levels. Obtain the corresponding pollution level according to the grade interval of the area to be inspected;

[0100] Among them, the first-level interval corresponds to the first pollution level, the second-level interval corresponds to the second pollution level, and the third-level interval corresponds to the third pollution level;

[0101] The pollution grading module feeds back the pollution level of the area to be inspected to the server, and the server sends the pollution level of the area to be inspected to the control matching module. The control matching module sets and matches corresponding control measures according to the pollution level of the area to be inspected, as follows:

[0102] When the area to be inspected is at the first pollution level, the control measure for the area to be inspected is: set a seawater detection cycle with an interval of 12 hours;

[0103] When the area to be inspected is at the second pollution level, the control measure for the area to be inspected is: set a seawater detection cycle with an interval of 6 hours and deploy corresponding seawater pollution monitoring equipment;

[0104] When the area to be inspected is at the third pollution level, the control measure for the area to be inspected is: set a seawater detection cycle with an interval of 2 hours, set corresponding control personnel, and deploy corresponding seawater pollution monitoring equipment.

[0105] ​ The seawater area is divided into several areas to be inspected u by the area division module. Then, the seawater data and biological data of the areas to be inspected are collected by the data collection module and sent to the server. The server sends the seawater data to the seawater detection module and the biological data to the biological detection module;

[0106] At the same time, both the seawater detection module and the biological detection module are connected to a big data module. The big data module is connected to the external Internet to obtain the standard content of various heavy metals in seawater and the standard elemental content of various metal elements in the shells of seawater organisms. The standard content of various heavy metals in seawater is sent to the seawater detection module, and the standard elemental content of various metal elements in the shells of seawater organisms is sent to the biological detection module;

[0107] The seawater in the area to be inspected is detected by the seawater detection module. Several seawater samples Yui are extracted in the area to be inspected, and several heavy metal elements are obtained by analyzing the seawater samples, and the metal content of several heavy metal elements is obtained. The metal content of various heavy metals is compared with the metal standard content. If the metal content of various heavy metals does not exceed the metal standard content, no operation is performed. If the metal content of various heavy metals exceeds the metal standard content, the absolute value of the difference between the metal content and the standard content is obtained to get the metal content difference value of various heavy metals. The metal content difference values of various heavy metals are added up to obtain the heavy metal content exceedance value HCYui of the seawater sample. The number of seawater samples in the area to be inspected is counted to obtain the sample number Y1Su, and the formula The excessive heavy metal content value ZHCu of the area to be tested is calculated. If ZHCu < X1, the pollution level of the area to be tested is the light pollution level. If X1 ≤ ZHCu < X2, the pollution level of the area to be tested is the medium pollution level. If X2 ≤ ZHCu, the pollution level of the area to be tested is the heavy pollution level. The corresponding control coefficient is set according to the pollution level of the area to be tested. The seawater detection module feeds back the control coefficient of the area to be tested to the server, and the server sends the control coefficient of the area to be tested to the pollution grading module;

[0108] The organisms in the area to be tested are detected by the biological detection module. Several biological samples Suo of the same type are selected in the area to be tested, and the metal elements contained in the upper shell of the biological sample and the element content of the corresponding metal elements are obtained. The element content of various metal elements in the biological sample shell is compared with the standard element content. If the element content of various metal elements in the biological sample shell exceeds the standard element content of various metal elements, no operation is performed. If the element content of various metal elements in the biological sample shell does not exceed the standard element content of various metal elements, the absolute value of the difference between the element content and the standard element content is obtained by subtracting the standard element content from the element content, and the sum of the element content differences of various metal elements is obtained as the content deficiency value HQSuo of the metal elements in the biological sample shell. The number of biological samples in the area to be tested is counted to obtain the sample number Y2Su, and the formula is used to calculate the element content deficiency value YHQu of the organisms in the area to be tested. If YHQu < Y1, the nutritional deficiency level of the area to be tested is the light deficiency level. If Y1 ≤ YHQu < Y2, the nutritional deficiency level of the area to be tested is the medium deficiency level. If Y2 ≤ YHQu, the nutritional deficiency level of the area to be tested is the heavy deficiency level. The corresponding nutritional deficiency coefficient is set according to the nutritional deficiency level of the area to be tested. The biological detection module feeds back the nutritional deficiency coefficient of the area to be tested to the server, and the server sends the nutritional deficiency coefficient of the area to be tested to the pollution grading module;

[0109] After receiving the control coefficient and the nutritional deficiency coefficient of the area to be tested, the pollution grading module divides the pollution level of the area to be tested. The control coefficient and the nutritional deficiency coefficient of the area to be tested calculated above are respectively marked as GKu and YCu. The pollution level value WDu of the area to be tested is calculated by the formula WDu = (GKu × α + YCu × β) / e. The grade interval stored in the server is obtained, and the pollution level value is compared with the grade interval to obtain the corresponding grade interval of the area to be tested. Different grade intervals correspond to different pollution levels. The corresponding pollution level is obtained according to the grade interval of the area to be tested. The pollution grading module feeds back the pollution level of the area to be tested to the server, and the server sends the pollution level of the area to be tested to the control matching module;

[0110] The control matching module sets and matches corresponding control measures according to the pollution level of the area to be inspected. When the area to be inspected is at the first pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 12 hours. When the area to be inspected is at the second pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 6 hours and deploying corresponding seawater pollution monitoring equipment. When the area to be inspected is at the third pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 2 hours, setting corresponding control personnel, and deploying corresponding seawater pollution monitoring equipment.

[0111] The above formulas are all calculated by taking the numerical values after dimensionless. The formula is a formula obtained by collecting a large amount of data for software simulation to get the closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation. The magnitudes of the weight coefficient and the proportionality coefficient are specific numerical values obtained for quantifying each parameter, which is convenient for subsequent comparison. Regarding the magnitudes of the weight coefficient and the proportionality coefficient, as long as they do not affect the proportional relationship between the parameters and the quantified numerical values.

[0112] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent management and control system for seawater pollution detection based on blue-green pulsed laser, characterized in that, It includes a data acquisition module, a regional division module, a seawater detection module, a pollution grading module, a biological detection module, a user terminal, a control matching module, and a server. The regional division module divides the seawater area into several areas to be inspected \(u\), where \(u = 1, 2,\cdots,z\), and \(z\) is a positive integer; The data acquisition module is used to collect seawater data and biological data of the areas to be inspected and send them to the server; the server sends the seawater data to the seawater detection module and the biological data to the biological detection module; The seawater detection module is based on the blue-green pulsed laser technology to detect the seawater in the areas to be inspected, and the control coefficient of the areas to be inspected is detected and fed back to the server. The server sends the control coefficient of the areas to be inspected to the pollution grading module; The biological detection module is used to detect the organisms in the areas to be inspected, and the nutritional deficiency coefficient of the areas to be inspected is detected and fed back to the server. The server sends the nutritional deficiency coefficient of the areas to be inspected to the pollution grading module; After receiving the control coefficient and the nutritional deficiency coefficient of the areas to be inspected, the pollution grading module is used to divide the pollution level of the areas to be inspected, and the pollution level of the areas to be inspected is divided and fed back to the server. The server sends the pollution level of the areas to be inspected to the control matching module, and the control matching module sets corresponding control measures according to the pollution level of the areas to be inspected; The detection process of the biological detection module is specifically as follows: Step S1: Select several biological samples of the same type in the area to be inspected, and label the biological samples as \(S_{uo}\), where \(o = 1, 2,\cdots,v\), \(v\) is a positive integer, and \(o\) represents the number of the biological sample in the area to be inspected; Step S2: Obtain the metal elements contained in the upper shell of the biological sample and the element content of the corresponding metal elements, and compare the element content of various metal elements in the biological sample shell with the standard element content; Step S3: If the element content of various metal elements in the biological sample shell exceeds the standard element content of various metal elements, no operation is performed; If the element content of various metal elements in the biological sample shell does not exceed the standard element content of various metal elements, proceed to the next step; Step S4: Subtract the standard element content from the element content and take the absolute value to obtain the element content difference of various metal elements in the biological sample shell, and sum the element content differences of various metal elements to obtain the content deficiency value \(HQ_{S_{uo}}\) of the metal elements in the biological sample shell; Count the number of biological samples in the area to be inspected to obtain the sample number \(Y2_{Su}\), and use the formula to calculate the element content deficiency value \(YHQ_{u}\) of the organisms in the area to be inspected. The specific formula is as follows: Step S5: If \(YHQ_{u}<Y1\), the nutritional deficiency level of the area to be inspected is the mild deficiency level; If \(Y1\leq YHQ_{u}<Y2\), the nutritional deficiency level of the area to be inspected is the moderate deficiency level; If \(Y2\leq YHQ_{u}\), the nutritional deficiency level of the area to be inspected is the severe deficiency level; where \(Y1\) and \(Y2\) are both fixed numerical element content deficiency thresholds, and \(Y1 < Y2\); Step S6: Set the corresponding nutritional deficiency coefficient according to the nutritional deficiency level of the area to be inspected; The nutritional deficiency coefficient of the mild deficiency level is less than that of the moderate deficiency level, and the nutritional deficiency coefficient of the moderate deficiency level is less than that of the high deficiency level; The division process of the pollution classification module is specifically as follows: Step SS1: Mark the control coefficient and the nutritional deficiency coefficient of the area to be inspected as GKu and YCu respectively; Step SS2: Calculate the pollution level value WDu of the area to be inspected through the formula. The specific formula is as follows: WDu = (GKu × α + YCu × β) / e; where α and β are both weight coefficients with fixed values, and the values of α and β are both greater than zero, and e is the natural constant; Step SS3: Obtain the grade intervals stored in the server, and compare the pollution level value with the grade intervals to obtain the corresponding grade interval of the area to be inspected; Step SS4: Different grade intervals correspond to different pollution levels. Obtain the corresponding pollution level according to the grade interval of the area to be inspected.

2. The intelligent control system for seawater pollution detection based on blue-green pulsed laser according to claim 1, characterized in that, The seawater data is the content of various metals in the seawater of the area to be inspected; The biological data is the specifications, weights of the same kind of organisms in the area to be inspected, and the metal elements and corresponding contents on the upper shells of the same kind of organisms in the area to be inspected.

3. The intelligent management and control system for seawater pollution detection based on blue-green pulsed laser according to claim 2, characterized in that, Both the seawater detection module and the biological detection module are connected to a big data module, and the big data module is connected to the external Internet to obtain the standard contents of various heavy metals in seawater and the standard element contents of various metal elements in the shells of seawater organisms. The standard contents of various heavy metals in seawater are sent to the seawater detection module, and the standard element contents of various metal elements in the shells of seawater organisms are sent to the biological detection module.

4. The intelligent control system for seawater pollution detection based on blue-green pulsed laser according to claim 3, wherein, The detection process of the seawater detection module is specifically as follows: Step 1: Extract several seawater samples in the area to be inspected, and mark the seawater samples as Yui, i = 1, 2,..., x, where x is a positive integer, and i represents the number of the seawater sample in the area to be detected; Step 2: Analyze the seawater samples to obtain several heavy metal elements, obtain the metal contents of several heavy metal elements, and compare the metal contents of various heavy metals with the metal standard contents; Step 3: If the metal contents of various heavy metals do not exceed the standard contents of various heavy metals, no operation is performed; If the metal contents of various heavy metals exceed the standard contents of various heavy metals, proceed to the next step; Step 4: Subtract the standard content from the metal content and take the absolute value to obtain the metal content difference of various heavy metals. Add up the metal content differences of various heavy metals to obtain the content over-standard value of heavy metals in the seawater sample, and mark the content over-standard value as HCYui; Step 5: Count the number of seawater samples in the area to be inspected to obtain the sample number Y1Su, and use the formula to calculate the excessive standard value ZHCu of heavy metal content in the area to be inspected; Step 6: If ZHCu < X1, the pollution level of the area to be inspected is the mild pollution level; If X1 ≤ ZHCu < X2, the pollution level of the area to be inspected is the moderate pollution level; If X2 ≤ ZHCu, the pollution level of the area to be inspected is the severe pollution level; where X1 and X2 are both heavy metal content over-standard thresholds with fixed values, and X1 < X2; Step 7: Set the corresponding control coefficient according to the pollution level of the area to be inspected.

5. The intelligent control system for seawater pollution detection based on blue-green pulsed laser according to claim 4, characterized in that, The control coefficient of the mild pollution level is less than that of the moderate pollution level, and the control coefficient of the moderate pollution level is less than that of the high pollution level.

6. The intelligent control system for seawater pollution detection based on blue-green pulsed laser according to claim 5, characterized in that, The level intervals include a first level interval, a second level interval, and a third level interval. The upper limit value of the first level interval is less than the lower limit value of the second level interval, and the upper limit value of the second level interval is less than the lower limit value of the third level interval; The first level interval corresponds to a first pollution level, the second level interval corresponds to a second pollution level, and the third level interval corresponds to a third pollution level.

7. An intelligent management and control system for seawater pollution detection based on blue-green pulsed laser according to claim 5, characterized in that, The working process of the control matching module is specifically as follows: When the area to be inspected is at the first pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 12 hours; When the area to be inspected is at the second pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 6 hours and deploying corresponding seawater pollution monitoring equipment; When the area to be inspected is at the third pollution level, the control measures for the area to be inspected are: setting a seawater detection cycle with an interval of 2 hours, setting corresponding control personnel, and deploying corresponding seawater pollution monitoring equipment.

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