CN114202450A - High-precision intelligent flow monitoring sensor based on block chain - Google Patents
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Abstract
The invention discloses a high-precision intelligent flow monitoring sensor based on a block chain, belonging to the field of sensors, the intelligent flow monitoring sensor is used for solving the problem that the flow monitoring accuracy is poor due to the fact that the intelligent flow monitoring sensor cannot effectively monitor the environmental data and the pollution number in the area, and comprises an area dividing module, an environmental monitoring module, a pollution monitoring module and a data analysis module, the area division module divides the flowing cavity to obtain a preset monitoring area, the environment monitoring module is used for monitoring the environment data of the flowing cavity, the intelligent flow monitoring sensor is used for monitoring the pollution of a monitoring area corresponding to the flow cavity, and analyzing the flow data of the flow cavity.
Description
Technical Field
The invention belongs to the field of sensors, relates to a flow monitoring technology, and particularly relates to a high-precision intelligent flow monitoring sensor based on a block chain.
Background
The intelligent flow sensor has the functions of sensing and detecting certain information of a measured object; the signal can be learned, reasoned, judged and processed; and has communication and management functions. The intelligent flow sensor has the capabilities of automatic zero calibration, compensation, data acquisition and the like.
In the prior art, the current intelligent flow monitoring sensor is mainly used for flow monitoring, environment data, pollution data and the like in the area where the sensor is located are ignored to be monitored, the environment data and the pollution data can influence the flow monitoring accuracy of the intelligent flow monitoring sensor, and therefore the high-accuracy intelligent flow monitoring sensor based on the block chain is provided.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a high-precision intelligent flow monitoring sensor based on a block chain.
The technical problem to be solved by the invention is as follows:
(1) the intelligent flow monitoring sensor cannot effectively monitor environmental data and pollution number in the area where the intelligent flow monitoring sensor is located, and therefore the flow monitoring accuracy of the intelligent flow monitoring sensor is poor.
The purpose of the invention can be realized by the following technical scheme:
a high-precision intelligent flow monitoring sensor based on a block chain comprises a flow pipeline (1), wherein a control box (5) is installed on the flow pipeline (1), a controller is installed inside the control box (5), the controller is in communication connection with a server, the server is connected with an area dividing module, an environment monitoring module, a pollution monitoring module, a data analysis module and a user terminal, the area dividing module is divided around a flow cavity (2) to obtain a preset monitoring area u, and the area dividing module sends a monitoring area corresponding to the flow cavity (2) to the environment monitoring module and the pollution monitoring module; the controller is connected with a data acquisition module and an alarm terminal, the data acquisition module is used for acquiring environmental data, gas data and water source data of a monitoring area and sending the environmental data, the gas data and the water source data to the controller, the controller sends the environmental data, the gas data and the water source data to a server, and the server sends the environmental data to the environmental monitoring module and sends the gas data and the water source data to the pollution monitoring module;
the environmental monitoring module is used for monitoring the environmental data that flow cavity (2) located, obtains monitoring area's ring shadow value HYu and feeds back to the server, the pollution monitoring module is used for carrying out pollution monitoring to the monitoring area that flow cavity (2) correspond, obtains monitoring area's dirty value SWu and dirty value QWu and feeds back to the server, the server sends monitoring area's ring shadow value, dirty value and dirty value to data analysis module, data analysis module receives monitoring area's ring shadow value, dirty value and dirty value of gas after for flow data condition to flow cavity (2) analyzes, and the flow condition of analysis monitoring area is in normal condition, monitoring state or abnormal state.
Further, the environmental data comprise rainfall value, temperature value, personnel walking number, animal survival number and soil pH value, the water source data comprise pH value, turbidity value, dissolved oxygen value and sulfide value, and the gas data comprise harmful gas molecular weight, harmful gas temperature, harmful gas pressure and harmful gas volume concentration.
Further, the monitoring process of the environment monitoring module is specifically as follows:
the method comprises the following steps: acquiring the geographical position of the flow cavity (2), acquiring weather forecast data of the location of the flow cavity (2) according to the geographical position, and extracting a temperature value and a rainfall value of fifteen days in the future from the weather forecast data;
step two: adding the temperature values of fifteen days in the future in weather forecast and averaging to obtain a temperature average value JWDu of the location of the flow cavity (2); adding rainfall values of fifteen days in the future in weather forecast and averaging to obtain a rainfall average value JJJYU of the place where the flow cavity (2) is located;
step three: calculating to obtain a flow coefficient LXu of the monitoring area by using a formula LXu JWDu/JJYu;
step four: acquiring the soil pH value SJu in the monitored area; acquiring a soil pH value difference value CSJu of the monitored area by comparing the soil pH value with a soil pH value threshold value YSJu corresponding to the monitored area;
step five: counting the number Ru of people walking and the number Du of animals out in the monitored area;
step six: the flow coefficient LXu of the monitoring area is combined with a formula to calculate the ring shadow value HYu of the monitoring area corresponding to the flow cavity (2), wherein the formula is as follows:
Further, the pollution monitoring process of the pollution monitoring module is as follows:
step S1: collecting a water source sample in a monitoring area, and obtaining the pH value PHu, the turbidity value ZDu, the dissolved oxygen value RJu and the sulfide value LHu of the water source sample in the monitoring area;
step S2:
calculating to obtain a water pollution value SWu in the monitored area; in the formula, c1, c2 and c3 are all fixed proportionality coefficient values, and the values of c1, c2 and c3 are all larger than zero;
step S3: collecting a gas sample in a monitoring area, and obtaining the harmful gas molecular weight FZu, the harmful gas temperature WDu, the harmful gas pressure YQu and the harmful gas volume concentration TNu of the gas sample in the monitoring area;
step S4: the air pollution value QWu of the monitored area is calculated by using the formula QWu ═ (FZu/22.4) × [273/(273+ WDu) ] × [ YQu/101325] × TNu.
Further, the analysis process of the data analysis module is specifically as follows:
step SS 1: acquiring an air pollution value QWu, a water pollution value SWu and a ring shadow value HYu of a monitoring area corresponding to the flow cavity (2);
step SS 2: setting corresponding weight coefficients for the ring shadow value, the water pollution value and the air pollution value respectively, and calculating an abnormal value YCu of the monitoring area corresponding to the flow pipeline (1) or the flow cavity (2) through a formula YCu-b 1 × HYu + b2 × SWu + b3 × QWu; wherein b1, b2 and b3 are all weight coefficients, b1, b2 and b3 are all greater than zero, and b1+ b2+ b3 is equal to 1;
step SS 3: if YCu is less than X1, the flow condition of the monitoring area is in a normal state;
step SS 4: if X1 is not less than YCu and is less than X2, the flow condition of the monitoring area is in a monitoring state;
step SS 5: if the X2 is less than or equal to YCu, the flow condition of the monitoring area is in an abnormal state; wherein, X1 and X2 are set thresholds, and X1 < X2.
Furthermore, the server is also connected with a monitoring and control module, the data analysis module feeds back the flow condition of the monitoring area corresponding to the flow cavity (2) to the server, the server sends the flow condition of the monitoring area corresponding to the flow cavity (2) to the monitoring and control module, and the monitoring and control module monitors and controls the monitoring area according to the flow condition of the monitoring area corresponding to the flow cavity (2) to generate a monitoring instruction or an alarm instruction;
the user terminal is used for the staff to receive the monitoring instruction sent by the monitoring control module and then perform entity monitoring on the corresponding flow cavity (2); the server sends the received alarm instruction to the corresponding controller, the controller generates a control signal according to the alarm instruction and loads the control signal to the alarm terminal, the alarm terminal is used for alarming flow data in an abnormal state, and the alarm terminal generates alarm sound when working.
Further, the working process of the supervision and control module is as follows:
if the flow condition of the monitoring area is in a normal state, no operation is performed;
if the flow condition of the monitoring area is a monitoring state, generating a monitoring instruction, and sending the monitoring instruction to the user terminal;
and if the flow condition of the monitoring area is in an abnormal state, generating an alarm instruction and feeding the alarm instruction back to the server.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the intelligent flow monitoring sensor, the area dividing module is used for dividing the area around the flow pipeline or the flow cavity to obtain the monitoring area, the environment data, the gas data and the water source data of the monitoring area are collected and sent to the environment monitoring module and the pollution monitoring module, the environment monitoring module is used for detecting the environment data of the flow pipeline or the flow cavity to obtain the ring shadow value of the monitoring area, the pollution monitoring module is used for monitoring the pollution of the monitoring area corresponding to the flow pipeline or the flow cavity to obtain the gas pollution value of the monitoring area, the environment data and the pollution data in the area where the intelligent flow monitoring sensor is located are conveniently monitored, and the monitoring accuracy of the intelligent flow monitoring sensor is improved;
2. the flow data condition of the flow pipeline or the flow cavity is analyzed through the data analysis module, corresponding weight coefficients are set for the ring shadow value, the water pollution value and the gas pollution value respectively, the abnormal value of the monitoring area corresponding to the flow pipeline or the flow cavity is obtained through calculation in combination with a formula, the abnormal value of the monitoring area is compared with a set threshold value to obtain the flow condition of the monitoring area, and a monitoring instruction or an alarm instruction is generated according to the flow condition of the monitoring area.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic structural view of the present invention;
fig. 2 is a block diagram of the system of the present invention.
In the figure: 1. a flow conduit; 2. a flow chamber; 3. a flange plate; 4. a flow sensor body; 5. control box, 6, display screen.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, a block chain-based high-precision intelligent flow monitoring sensor includes a flow pipe 1, a flow cavity 2, flanges 3, a flow sensor main body 4, a control box 5 and a display screen 6, where the flanges 3 are installed at both ends of the flow pipe 1, the flow pipe 1 is installed with the flow cavity 2, the flow cavity 2 is installed with the flow sensor main body 4, the flow pipe 1 is installed with the control box 5 at one side of the flow sensor main body 4, and the control box 5 is installed with a controller inside;
the controller is in communication connection with a server, the server is connected with an area dividing module, an environment monitoring module, a pollution monitoring module, a data analysis module, a supervision and control module and a user terminal, the area dividing module divides around the flow pipeline 1 or the flow cavity 2 to obtain a preset monitoring area, and the monitoring area is marked as u, wherein u is 1, 2, … …, and z is a positive integer; the region dividing module sends a monitoring region corresponding to the flow pipeline 1 or the flow cavity 2 to the environment monitoring module and the pollution monitoring module;
in specific implementation, when the flow pipe 1 is aimed, monitoring regions with preset fixed lengths can be divided on two sides of the flow pipe 1, that is, the monitoring range of the flow cavity 2 is rectangular, and when the flow cavity 2 is aimed, the monitoring regions with preset lengths can be divided by taking the flow cavity 2 as the center, that is, the monitoring range of the flow cavity 2 is circular;
the controller is connected with a data acquisition module and an alarm terminal, the data acquisition module is used for acquiring environmental data, gas data and water source data of a monitoring area and sending the environmental data, the gas data and the water source data to the controller, and the controller sends the received environmental data, the gas data and the water source data to the server;
the environment data comprises rainfall value, temperature value, personnel walking number, animal survival number, soil pH value and the like, the water source data comprises pH value, turbidity value, dissolved oxygen value, sulfide value and the like, and the gas data comprises harmful gas molecular weight, harmful gas temperature, harmful gas pressure, harmful gas volume concentration and the like;
the server sends the environmental data to the environmental monitoring module, and the server sends the gas data and the water source data to the pollution monitoring module; the environment monitoring module is used for monitoring the environment data of the flow pipeline 1 or the flow cavity 2, and the monitoring process is as follows:
the method comprises the following steps: acquiring the geographical position of the flow pipeline 1 or the flow cavity 2, acquiring weather forecast data of the location of the flow pipeline 1 or the flow cavity 2 according to the geographical position, and extracting a temperature value and a rainfall value of fifteen days in the future from the weather forecast data;
step two: adding the temperature values of fifteen days in the future in weather forecast, and averaging to obtain a temperature average value JWDu of the location of the flow pipeline 1 or the flow cavity 2; adding the rainfall values of fifteen days in the future in the weather forecast, and averaging to obtain a rainfall average value JJJYu of the location of the flow pipeline 1 or the flow cavity 2;
step three: calculating to obtain a flow coefficient LXu of the monitoring area by using a formula LXu JWDu/JJYu;
step four: acquiring the soil pH value SJu in the monitored area; acquiring a soil pH value difference value CSJu of the monitored area by comparing the soil pH value with a soil pH value threshold value YSJu corresponding to the monitored area;
step five: counting the number Ru of people walking and the number Du of animals out in the monitoring area since the self-setting of the flow pipeline 1 or the flow cavity 2;
step six: the flow coefficient LXu of the monitoring area is calculated by combining a formula to obtain a ring shadow value HYu (the ring shadow value is an environmental impact value for short, and the ring shadow value is used to replace the environmental impact value subsequently) of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2, wherein the formula is as follows:
the environmental monitoring module feeds back the ring shadow value HYu of the corresponding monitoring area of the flow pipeline 1 or the flow cavity 2 to the server, the pollution monitoring module is used for carrying out pollution monitoring on the corresponding monitoring area of the flow pipeline 1 or the flow cavity 2, and the pollution monitoring process is as follows:
step S1: randomly collecting water source samples in a monitoring area through sampling equipment, and then respectively obtaining the pH value PHu, the turbidity value ZDu, the dissolved oxygen value RJu and the sulfide value LHu of the water source samples in the monitoring area;
step S2:
calculating to obtain a water pollution value SWu (the water pollution value is short for a water source pollution value, and the water pollution value is adopted to replace the water source pollution value in the following steps); in the formula, c1, c2 and c3 are all fixed proportionality coefficient values, and the values of c1, c2 and c3 are all larger than zero;
step S3: randomly collecting gas samples in a monitoring area through sampling equipment, and then respectively obtaining the harmful gas molecular weight FZu, the harmful gas temperature WDu, the harmful gas pressure YQu and the harmful gas volume concentration TNu of the gas samples in the monitoring area;
step S4: converting the volume concentration of the harmful gas into the mass concentration of the harmful gas according to a calculation formula of the mass concentration of the gas, and calculating by using a formula QWu, wherein the formula is (FZu/22.4) x [273/(273+ WDu) ] × [ YQu/101325] × TNu to obtain a gas pollution value QWu of the monitored area (the gas pollution value is short for the gas pollution value, and the gas pollution value is used for replacing the gas pollution value in the following steps);
in specific implementation, water source samples and gas samples in a plurality of monitoring areas can be collected, then the water pollution values and the gas pollution values of the plurality of water source samples are calculated, the water pollution values of the plurality of water source samples and the gas pollution values of the plurality of gas samples are respectively averaged to obtain a water pollution average value and a gas pollution average value, and the method is mainly used for preventing data inaccuracy and facilitating more accurate numerical values;
the pollution monitoring module feeds back the water and sewage value and the gas and sewage value of the corresponding monitoring area of the flowing pipeline 1 or the flowing cavity 2 to the server, the server sends the received ring shadow value, the water and sewage value and the gas and sewage value of the monitoring area to the data analysis module, the data analysis module receives the ring shadow value, the water and sewage value and the gas and sewage value of the monitoring area sent by the server and then is used for analyzing the flow data condition of the flowing pipeline 1 or the flowing cavity 2, and the analysis process is as follows specifically:
step SS 1: acquiring an air pollution value QWu, a water pollution value SWu and a ring shadow value HYu of a monitoring area corresponding to the flow pipeline 1 or the flow cavity 2;
step SS 2: setting corresponding weight coefficients for the ring shadow value, the water pollution value and the air pollution value respectively, wherein b1 corresponds to the ring shadow value HYu, b2 corresponds to the water pollution value SWu, and b3 corresponds to the air pollution value QWu, and calculating an abnormal value YCu of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 according to a formula YCu which is b1 × HYu + b2 × SWu + b3 × QWu; wherein b1, b2 and b3 are all weight coefficients, b1, b2 and b3 are all greater than zero, and b1+ b2+ b3 is equal to 1;
step SS 3: if YCu is less than X1, the flow condition of the monitoring area is in a normal state;
step SS 4: if X1 is not less than YCu and is less than X2, the flow condition of the monitoring area is in a monitoring state;
step SS 5: if the X2 is less than or equal to YCu, the flow condition of the monitoring area is in an abnormal state; wherein, X1 and X2 are both set thresholds, and X1 is less than X2, and in specific implementation, corresponding values are set according to the actual situation of a monitoring area, so that X1 and X2 are fixed values, and the value of X1 is less than X2;
the data analysis module feeds back the flow condition of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to the server, and the server sends the flow condition of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to the supervision and control module;
the monitoring control module is used for monitoring and controlling the monitoring area according to the flow condition of the corresponding monitoring area of the flow pipeline 1 or the flow cavity 2, and the process is as follows:
if the flow condition of the monitoring area is in a normal state, no operation is performed;
if the flow condition of the monitoring area is a monitoring state, generating a monitoring instruction, and sending the monitoring instruction to the user terminal;
if the flow condition of the monitoring area is an abnormal state, generating an alarm instruction, and feeding the alarm instruction back to the server;
the user terminal is used for receiving the monitoring instruction sent by the monitoring control module by the staff of the flow pipeline 1 or the flow cavity 2, and the user terminal carries out entity monitoring on the corresponding flow pipeline 1 or the flow cavity 2 according to the monitoring instruction; the server sends the received alarm instruction to the corresponding controller, the controller generates a control signal according to the alarm instruction and loads the control signal to the alarm terminal, the alarm terminal is used for alarming flow data in an abnormal state, and the alarm terminal generates alarm sound when working.
A high-precision intelligent flow monitoring sensor based on a block chain is characterized in that during work, a preset monitoring area is obtained by dividing around a flow pipeline 1 or a flow cavity 2 through an area dividing module, then the area dividing module sends the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to an environment monitoring module and a pollution monitoring module, meanwhile, environment data, gas data and water source data of the monitoring area are collected through a data collecting module, the environment data, the gas data and the water source data are sent to a controller, the controller sends the received environment data, the gas data and the water source data to a server, the server sends the environment data to the environment monitoring module, and the gas data and the water source data to the pollution monitoring module;
the method comprises the steps of monitoring environmental data of a flow pipeline 1 or a flow cavity 2 through an environmental monitoring module, obtaining the geographic position of the flow pipeline 1 or the flow cavity 2, obtaining weather forecast data of the location of the flow pipeline 1 or the flow cavity 2 according to the geographic position, extracting temperature values and rainfall values of fifteen days in the weather forecast data in the future to obtain a rainfall mean value JJJYu of the location of the flow pipeline 1 or the flow cavity 2, and utilizing a formulaLXu JWDu/JJYU, calculating to obtain flow coefficient LXu of the monitored area, then obtaining soil pH SJu, soil pH difference CSJu, personnel walking number Ru and animal survival number Du in the monitored area, and combining the flow coefficient LXu of the monitored area with a formula
Calculating to obtain an annular shadow value HYu of the monitoring region corresponding to the flow pipeline 1 or the flow cavity 2, and feeding back an annular shadow value HYu of the monitoring region corresponding to the flow pipeline 1 or the flow cavity 2 to the server by the environment monitoring module;
the pollution monitoring module is used for monitoring the pollution of a monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to obtain the pH value PHu, the turbidity value ZDu, the dissolved oxygen value RJu and the sulfide value LHu of a water source sample in the monitoring area,
calculating to obtain a water pollution value SWu in a monitoring area, then obtaining a harmful gas molecular weight FZu, a harmful gas temperature WDu, a harmful gas pressure YQu and a harmful gas volume concentration TNu of a gas sample in the monitoring area, and obtaining (FZu/22.4) x [273/(273+ WDu) by using a formula QWu]×[YQu/101325]The x TNu is calculated to obtain a gas-sewage value QWu of the monitoring area, the pollution monitoring module feeds back the water-sewage value and the gas-sewage value of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to the server, and the server sends the received ring shadow value, the water-sewage value and the gas-sewage value of the monitoring area to the data analysis module;
after receiving the ring shadow value, the water pollution value and the gas pollution value of the monitoring area sent by the server, the data analysis module analyzes the flow data condition of the flow pipeline 1 or the flow cavity 2, sets corresponding weight coefficients for the ring shadow value, the water pollution value and the gas pollution value respectively, calculates an abnormal value YCu of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 by using a formula YCu-b 1 × HYu + b2 × SWu + b3 × QWu, if YCu < X1, the flow condition of the monitoring area is in a normal state, if X1 is not less than YCu and less than X2, the flow condition of the monitoring area is in a monitoring state, if X2 is not less than YCu, the flow condition of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 is fed back to the server by the data analysis module, and the server sends the flow condition of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2 to the monitoring control module, the monitoring control module monitors and controls the monitoring area according to the flow condition of the monitoring area corresponding to the flow pipeline 1 or the flow cavity 2, if the flow condition of the monitoring area is a normal state, no operation is performed, if the flow condition of the monitoring area is a monitoring state, a monitoring instruction is generated and sent to the user terminal, and if the flow condition of the monitoring area is an abnormal state, an alarm instruction is generated and fed back to the server;
the user terminal receives the monitoring instruction sent by the monitoring and controlling module, entity monitoring is carried out on the corresponding flow pipeline 1 or the flow cavity 2 according to the monitoring instruction, the server sends the received alarm instruction to the corresponding controller, the controller generates a control signal according to the alarm instruction and loads the control signal to the alarm terminal, and the alarm terminal is used for alarming flow data in an abnormal state.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A high-precision intelligent flow monitoring sensor based on a block chain comprises a flow pipeline (1) and is characterized in that a control box (5) is installed on the flow pipeline (1), a controller is installed inside the control box (5), the controller is in communication connection with a server, the server is connected with an area dividing module, an environment monitoring module, a pollution monitoring module, a data analysis module and a user terminal, the area dividing module is divided around a flow cavity (2) to obtain a preset monitoring area u, and the area dividing module sends a monitoring area corresponding to the flow cavity (2) to the environment monitoring module and the pollution monitoring module; the controller is connected with a data acquisition module and an alarm terminal, the data acquisition module is used for acquiring environmental data, gas data and water source data of a monitoring area and sending the environmental data, the gas data and the water source data to the controller, the controller sends the environmental data, the gas data and the water source data to a server, and the server sends the environmental data to the environmental monitoring module and sends the gas data and the water source data to the pollution monitoring module;
the environmental monitoring module is used for monitoring the environmental data that flow cavity (2) located, obtains monitoring area's ring shadow value HYu and feeds back to the server, the pollution monitoring module is used for carrying out pollution monitoring to the monitoring area that flow cavity (2) correspond, obtains monitoring area's dirty value SWu and dirty value QWu and feeds back to the server, the server sends monitoring area's ring shadow value, dirty value and dirty value to data analysis module, data analysis module receives monitoring area's ring shadow value, dirty value and dirty value of gas after for flow data condition to flow cavity (2) analyzes, and the flow condition of analysis monitoring area is in normal condition, monitoring state or abnormal state.
2. The sensor of claim 1, wherein the environmental data comprises rainfall value, temperature value, number of people walking, number of animals coming out and soil pH value, the water source data comprises pH value, turbidity value, dissolved oxygen value and sulfide value, and the gas data comprises harmful gas molecular weight, harmful gas temperature, harmful gas pressure and harmful gas volume concentration.
3. The sensor according to claim 1, wherein the monitoring process of the environment monitoring module is as follows:
the method comprises the following steps: acquiring the geographical position of the flow cavity (2), acquiring weather forecast data of the location of the flow cavity (2) according to the geographical position, and extracting a temperature value and a rainfall value of fifteen days in the future from the weather forecast data;
step two: adding the temperature values of fifteen days in the future in weather forecast and averaging to obtain a temperature average value JWDu of the location of the flow cavity (2); adding rainfall values of fifteen days in the future in weather forecast and averaging to obtain a rainfall average value JJJYU of the place where the flow cavity (2) is located;
step three: calculating to obtain a flow coefficient LXu of the monitoring area by using a formula LXu JWDu/JJYu;
step four: acquiring the soil pH value SJu in the monitored area; acquiring a soil pH value difference value CSJu of the monitored area by comparing the soil pH value with a soil pH value threshold value YSJu corresponding to the monitored area;
step five: counting the number Ru of people walking and the number Du of animals out in the monitored area;
step six: the flow coefficient LXu of the monitoring area is combined with a formula to calculate the ring shadow value HYu of the monitoring area corresponding to the flow cavity (2), wherein the formula is as follows:
4. The sensor according to claim 1, wherein the pollution monitoring process of the pollution monitoring module is as follows:
step S1: collecting a water source sample in a monitoring area, and obtaining the pH value PHu, the turbidity value ZDu, the dissolved oxygen value RJu and the sulfide value LHu of the water source sample in the monitoring area;
step S2:
calculating to obtain a water pollution value SWu in the monitored area; in the formula, c1, c2 and c3 are all fixed proportionality coefficient values, and the values of c1, c2 and c3 are all larger than zero;
step S3: collecting a gas sample in a monitoring area, and obtaining the harmful gas molecular weight FZu, the harmful gas temperature WDu, the harmful gas pressure YQu and the harmful gas volume concentration TNu of the gas sample in the monitoring area;
step S4: the air pollution value QWu of the monitored area is calculated by using the formula QWu ═ (FZu/22.4) × [273/(273+ WDu) ] × [ YQu/101325] × TNu.
5. The sensor of claim 1, wherein the data analysis module specifically performs the following analysis process:
step SS 1: acquiring an air pollution value QWu, a water pollution value SWu and a ring shadow value HYu of a monitoring area corresponding to the flow cavity (2);
step SS 2: setting corresponding weight coefficients for the ring shadow value, the water pollution value and the air pollution value respectively, and calculating an abnormal value YCu of the monitoring area corresponding to the flow pipeline (1) or the flow cavity (2) through a formula YCu-b 1 × HYu + b2 × SWu + b3 × QWu; wherein b1, b2 and b3 are all weight coefficients, b1, b2 and b3 are all greater than zero, and b1+ b2+ b3 is equal to 1;
step SS 3: if YCu is less than X1, the flow condition of the monitoring area is in a normal state;
step SS 4: if X1 is not less than YCu and is less than X2, the flow condition of the monitoring area is in a monitoring state;
step SS 5: if the X2 is less than or equal to YCu, the flow condition of the monitoring area is in an abnormal state; wherein, X1 and X2 are set thresholds, and X1 < X2.
6. The sensor is characterized in that the server is further connected with a supervision and control module, the data analysis module feeds back the flow condition of the flow cavity (2) corresponding to the monitoring area to the server, the server sends the flow condition of the flow cavity (2) corresponding to the monitoring area to the supervision and control module, and the supervision and control module supervises and controls the monitoring area according to the flow condition of the flow cavity (2) corresponding to the monitoring area to generate a monitoring instruction or an alarm instruction;
the user terminal is used for the staff to receive the monitoring instruction sent by the monitoring control module and then perform entity monitoring on the corresponding flow cavity (2); the server sends the received alarm instruction to the corresponding controller, the controller generates a control signal according to the alarm instruction and loads the control signal to the alarm terminal, the alarm terminal is used for alarming flow data in an abnormal state, and the alarm terminal generates alarm sound when working.
7. The sensor according to claim 6, wherein the supervisory control module specifically operates as follows:
if the flow condition of the monitoring area is in a normal state, no operation is performed;
if the flow condition of the monitoring area is a monitoring state, generating a monitoring instruction, and sending the monitoring instruction to the user terminal;
and if the flow condition of the monitoring area is in an abnormal state, generating an alarm instruction and feeding the alarm instruction back to the server.
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