CN116151621A - Atmospheric pollution treatment risk detection system based on data analysis - Google Patents
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Abstract
The invention belongs to the field of atmospheric pollution treatment, relates to a data analysis technology, and aims to solve the problem that a treatment efficiency is low due to the fact that a targeted treatment scheme cannot be formulated for an area in the prior art, and particularly relates to an atmospheric pollution treatment risk detection system based on data analysis, which comprises a risk detection platform, wherein the risk detection platform is in communication connection with an area detection module, a period management module, a risk analysis module and a storage module; dividing an atmospheric pollution treatment area into a plurality of detection areas, setting a detection period, acquiring smoke data, disulfide data and carbon data of the detection areas in the detection period, and performing numerical calculation to obtain pollution coefficients of the detection areas; the invention performs regional analysis on the pollution state of the air pollution treatment area, and simultaneously provides data support for the characteristic analysis process and the risk analysis process in a periodic division and regional division mode.
Description
Technical Field
The invention belongs to the field of atmospheric pollution control, relates to a data analysis technology, and in particular relates to an atmospheric pollution control risk detection system based on data analysis.
Background
Atmospheric pollutants enter the atmosphere from artificial sources or natural sources, participate in the circulation process of the atmosphere, are removed from the atmosphere through chemical reactions, biological activities and physical sedimentation in the atmosphere after a certain residence time, and are relatively accumulated in the atmosphere if the output rate is lower than the input rate, so that the concentration of certain substances in the atmosphere is increased;
the atmospheric pollution treatment risk detection system in the prior art can only detect the concentration of harmful substances with atmospheric pollution, and feed back the atmospheric pollution degree through the concentration detection result, but lacks the function of comprehensively analyzing the historical detection result of the same area, so that the treatment characteristics of the area cannot be analyzed, and a targeted treatment scheme cannot be formulated for the area, so that the atmospheric pollution treatment efficiency is low and the effect is not ideal;
aiming at the technical problems, the application provides a solution.
Disclosure of Invention
The invention aims to provide an atmospheric pollution treatment risk detection system based on data analysis, which is used for solving the problem that the treatment efficiency is low due to the fact that a targeted treatment scheme cannot be formulated for an area in the atmospheric pollution treatment risk detection system in the prior art.
The technical problems to be solved by the invention are as follows: how to provide an atmospheric pollution control risk detection system based on data analysis, which can perform characteristic analysis on historical control data of an area.
The aim of the invention can be achieved by the following technical scheme:
the atmospheric pollution treatment risk detection system based on data analysis comprises a risk detection platform, wherein the risk detection platform is in communication connection with a region detection module, a period management module, a risk analysis module and a storage module;
the area detection module is used for carrying out area division on the air pollution treatment area: dividing an atmospheric pollution control area into a plurality of detection areas, setting a detection period, acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period, and performing numerical calculation to obtain a pollution coefficient WR of the detection areas; marking the pollution characteristic of the detection area as normal or abnormal according to the value of the pollution coefficient WR;
the period management module is used for periodically managing the treatment state of the atmospheric treatment pollution area: obtaining the atmospheric pollution detection results of the detection area in the latest L2 detection periods, and marking the ratio of the number of times that the pollution characteristics of the detection area are marked as normal to L2 as a normal coefficient; acquiring a switching coefficient of a detection area; acquiring a normal threshold value and a switching threshold value through a storage module; the normal coefficient and the switching coefficient of the detection area are respectively compared with a normal threshold value and a switching threshold value, and the detection area is marked as a treatment difficult area, a treatment key area or a qualified area according to the comparison result; the treatment difficult area, the treatment important area and the qualified area are sent to a mobile phone terminal of a manager through a risk detection platform;
the risk analysis module is used for analyzing the pollution risk degree of the air pollution treatment area and judging whether the pollution risk meets the requirement.
As a preferred embodiment of the present invention, the process of acquiring the smoke data YC of the detection area includes: setting L1 detection points in a detection area, detecting the smoke concentration at the detection points in real time, marking the maximum value of the smoke concentration of the detection points in a detection period as a smoke concentration value, and marking the maximum value of the smoke concentration values of all the detection points as smoke data HC of the detection area; the acquisition process of the disulfide data EL of the detection region includes: sulfur dioxide detection is carried out in real time at detection points, the maximum value of the sulfur dioxide concentration of the detection points in the detection period is marked as a sulfur concentration value, and the maximum value of the sulfur concentration values of all the detection points is marked as disulfide data EL; the process for acquiring the one-carbon data YT of the detection area comprises the following steps: and carrying out carbon monoxide detection at the detection points in real time, marking the maximum value of the carbon monoxide concentration of the detection points in the detection period as a carbon concentration value, and marking the maximum value of the carbon concentration values of all the detection points as carbon data YT.
As a preferred embodiment of the present invention, the specific process of marking the contamination feature of the detection area as normal or abnormal includes: the pollution threshold WRmax is obtained through the storage module, and the pollution coefficient WR of the detection area is compared with the pollution threshold WRmax: if the pollution coefficient WR is smaller than the pollution threshold WRmax, judging that the atmospheric pollution detection result in the detection area is qualified, and marking the pollution characteristic of the corresponding detection area as normal; if the pollution coefficient WR is greater than or equal to the pollution threshold WRmax, judging that the air pollution detection result in the detection area is unqualified, marking the pollution characteristic of the corresponding detection area as abnormal, and simultaneously, sending the detection area with the abnormal pollution characteristic to a mobile phone terminal of a manager through a risk detection platform by the area monitoring module.
As a preferred embodiment of the present invention, the process of acquiring the switching coefficient of the detection area includes: acquiring the air pollution detection results of the detection area in two adjacent detection periods, and if the two detection periods are normal or abnormal, marking the stable characteristics of the detection area in the corresponding two detection periods as being maintained; otherwise, the stable characteristic of the detection area in the corresponding two detection periods is marked as switching; the ratio of the number of times the detection area is marked as switched for the stable feature over L2 detection periods to L2 is marked as a switching coefficient.
As a preferred embodiment of the present invention, the specific process of comparing the normal coefficient and the switching coefficient of the detection area with the normal threshold and the switching threshold, respectively, includes: if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is smaller than or equal to the switching threshold value, marking the corresponding detection area as a treatment difficulty area; if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is larger than the switching threshold value, marking the corresponding detection area as a treatment key area; if the normal coefficient is larger than the normal threshold value, the corresponding detection area is marked as a qualified area.
As a preferred embodiment of the present invention, the specific process of analyzing the pollution risk level of the air pollution control area by the risk analysis module includes: acquiring different-surface data YC, double different-surface data SY and different-site data YD of an atmospheric pollution treatment area, and performing numerical calculation to obtain a risk coefficient FX; and acquiring a risk threshold FXmax through the storage module, comparing the risk coefficient FX with the risk threshold FXmax, and judging whether the pollution risk meets the requirement or not according to a comparison result.
As a preferred embodiment of the present invention, the out-of-plane data YC is a sum of area values of all detection areas whose contamination characteristics are abnormal; the acquisition process of the double-hetero data SY comprises the following steps: if the pollution characteristics of two adjacent detection areas are abnormal, marking the corresponding two detection areas as associated areas, intercepting the superposition positions of boundary lines of the associated areas, marking the length values of the intercepted boundary lines as superposition values, and marking the sum of the superposition values of all the associated areas as double-abnormal data SY; the off-site data YD is the number of detection areas in the atmospheric pollution control region, which are characterized by abnormality.
As a preferred embodiment of the present invention, the specific process of comparing the risk factor FX with the risk threshold FXmax comprises: if the risk coefficient FX is smaller than the risk threshold FXmax, judging that the pollution risk of the atmospheric pollution treatment area meets the requirement; if the risk coefficient FX is greater than or equal to the risk threshold FXmax, judging that the pollution risk of the air pollution treatment area does not meet the requirement, and sending a pollution early warning signal to a mobile phone terminal of a manager through a risk detection platform by the risk analysis module.
The working method of the atmospheric pollution treatment risk detection system based on data analysis comprises the following steps:
step one: the method comprises the following steps of carrying out regional division on an atmospheric pollution treatment area: dividing an atmospheric pollution treatment area into a plurality of detection areas, setting a detection period, acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period, performing numerical calculation to obtain a pollution coefficient WR, and marking the pollution characteristics of the detection areas as normal or abnormal according to the numerical value of the pollution coefficient WR;
step two: the method comprises the steps of periodically managing the treatment state of an atmospheric treatment pollution area: acquiring normal coefficients and switching coefficients of the detection area in the latest L2 detection periods, and marking the detection area as a qualified area, a treatment key area or a treatment difficult area according to the values of the normal coefficients and the switching coefficients;
step three: and analyzing the pollution risk degree of the air pollution treatment area: and acquiring different-surface data YC, double different-surface data SY and different-site data YD of the air pollution control area, carrying out numerical calculation to obtain a risk coefficient FX, and judging whether the pollution risk of the air pollution control area meets the requirement or not according to the numerical value of the risk coefficient FX.
The invention has the following beneficial effects:
1. the invention carries out regional analysis on the pollution state of an atmospheric pollution treatment area through an area monitoring module, calculates and analyzes various pollution parameters in a detection area to obtain a pollution coefficient, thereby feeding back the pollution degree of the detection area through the numerical value of the pollution coefficient, and simultaneously providing data support for a characteristic analysis process and a risk analysis process through a periodic division and an area division mode;
2. the invention can also carry out periodic management on the treatment state of the atmospheric treatment pollution area through the period management module, and obtains the normal coefficient and the pollution coefficient by analyzing the pollution monitoring result of the detection area in all the recent detection periods, thereby feeding back the pollution treatment characteristics of the detection area through the values of the normal coefficient and the pollution coefficient, making a targeted treatment scheme for the detection area through the pollution treatment characteristics, and improving the pollution treatment effect of the detection area;
3. and the pollution risk degree of the air pollution treatment area can be analyzed through the risk analysis module, the risk coefficient is obtained through comprehensively analyzing the area, the number and the distribution condition of the detection area with abnormal pollution characteristics, the actual pollution risk state of the air pollution treatment area is fed back through the risk coefficient, and early warning can be timely carried out when the risk is abnormal.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in FIG. 1, the atmospheric pollution control risk detection system based on data analysis comprises a risk detection platform, wherein the risk detection platform is in communication connection with a region detection module, a period management module, a risk analysis module and a storage module.
The area detection module is used for dividing the area of the air pollution treatment area: dividing an air pollution control area into a plurality of detection areas, setting a detection period, and acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period; the process of acquiring the smoke data YC of the detection area includes: setting L1 detection points in a detection area, detecting the smoke concentration at the detection points in real time, marking the maximum value of the smoke concentration of the detection points in a detection period as a smoke concentration value, and marking the maximum value of the smoke concentration values of all the detection points as smoke data HC of the detection area; the acquisition process of the disulfide data EL of the detection region includes: sulfur dioxide detection is carried out in real time at detection points, the maximum value of the sulfur dioxide concentration of the detection points in the detection period is marked as a sulfur concentration value, and the maximum value of the sulfur concentration values of all the detection points is marked as disulfide data EL; the process for acquiring the one-carbon data YT of the detection area comprises the following steps: carrying out carbon monoxide detection at the detection points in real time, marking the maximum value of the carbon monoxide concentration of the detection points in the detection period as a carbon concentration value, and marking the maximum value of the carbon concentration values of all the detection points as carbon data YT; obtaining pollution data WR of the detection area in the detection period through a formula WR=α1HC+α2EL+α3YT, wherein the pollution coefficient is a numerical value reflecting the pollution degree of the detection area in the detection period, and the larger the numerical value of the pollution coefficient is, the higher the pollution degree of the detection area in the detection period is; wherein α1, α2, and α3 are proportionality coefficients, and α3 > α2 > α1 > 1; the pollution threshold WRmax is obtained through the storage module, and the pollution coefficient WR of the detection area is compared with the pollution threshold WRmax: if the pollution coefficient WR is smaller than the pollution threshold WRmax, judging that the atmospheric pollution detection result in the detection area is qualified, and marking the pollution characteristic of the corresponding detection area as normal; if the pollution coefficient WR is greater than or equal to a pollution threshold WRmax, judging that the air pollution detection result in the detection area is unqualified, marking the pollution characteristic of the corresponding detection area as abnormal, and simultaneously, transmitting the detection area with the abnormal pollution characteristic to a mobile phone terminal of a manager through a risk detection platform by the area monitoring module; the pollution state of the air pollution treatment area is subjected to regional analysis, and each pollution parameter in the detection area is calculated and analyzed to obtain a pollution coefficient, so that the pollution degree of the detection area is fed back through the numerical value of the pollution coefficient, and meanwhile, data support is provided for a characteristic analysis process and a risk analysis process in a periodical division and area division mode.
The period management module is used for periodically managing the treatment state of the atmospheric treatment pollution area: obtaining the atmospheric pollution detection results of the detection area in the latest L2 detection periods, marking the normal times of the pollution characteristics of the detection area and the ratio of L2 as normal coefficients, wherein L1 and L2 are constant values, and the values of L1 and L2 are set by a manager; acquiring a switching coefficient of a detection area: acquiring the air pollution detection results of the detection area in two adjacent detection periods, and if the two detection periods are normal or abnormal, marking the stable characteristics of the detection area in the corresponding two detection periods as being maintained; otherwise, the stable characteristic of the detection area in the corresponding two detection periods is marked as switching; marking the ratio of the number of times that the stable characteristic of the detection area is marked as being switched in L2 detection periods to L2 as a switching coefficient; acquiring a normal threshold value and a switching threshold value through a storage module; comparing the normal coefficient and the switching coefficient of the detection area with a normal threshold value and a switching threshold value respectively: if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is smaller than or equal to the switching threshold value, marking the corresponding detection area as a treatment difficulty area; if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is larger than the switching threshold value, marking the corresponding detection area as a treatment key area; if the normal coefficient is larger than the normal threshold value, marking the corresponding detection area as a qualified area; the treatment difficult area, the treatment important area and the qualified area are sent to a mobile phone terminal of a manager through a risk detection platform; the method comprises the steps of periodically managing the treatment state of an atmospheric treatment pollution area, analyzing the pollution monitoring results of the detection area in all the recent detection periods to obtain a normal coefficient and a pollution coefficient, feeding back the pollution treatment characteristics of the detection area through the values of the normal coefficient and the pollution coefficient, and making a targeted treatment scheme for the detection area through the pollution treatment characteristics to improve the pollution treatment effect of the detection area.
The risk analysis module is used for analyzing the pollution risk degree of the air pollution treatment area: acquiring different-surface data YC, double different-surface data SY and different-site data YD of an air pollution treatment area, wherein the different-surface data YC is the sum of area values of all detection areas with abnormal pollution characteristics; the acquisition process of the double-hetero data SY comprises the following steps: if the pollution characteristics of two adjacent detection areas are abnormal, marking the corresponding two detection areas as associated areas, intercepting the superposition positions of boundary lines of the associated areas, marking the length values of the intercepted boundary lines as superposition values, and marking the sum of the superposition values of all the associated areas as double-abnormal data SY; the off-site data YD is the number value of detection areas with abnormal pollution characteristics in the atmospheric pollution treatment area; obtaining a risk coefficient FX of the air pollution control region according to the formula FX=β1×YC+β2×SY+β3×YD, wherein the risk coefficient is a numerical value reflecting the pollution risk severity of the air pollution control region, and the larger the numerical value of the risk coefficient is, the higher the pollution risk severity of the air pollution control region is; wherein β1, β2 and β3 are proportionality coefficients, and β1 > β2 > β3 > 1; acquiring a risk threshold FXmax through a storage module, and comparing the risk coefficient FX with the risk threshold FXmax: if the risk coefficient FX is smaller than the risk threshold FXmax, judging that the pollution risk of the atmospheric pollution treatment area meets the requirement; if the risk coefficient FX is greater than or equal to the risk threshold FXmax, judging that the pollution risk of the atmospheric pollution treatment area does not meet the requirement, and sending a pollution early warning signal to a mobile phone terminal of a manager through a risk detection platform by a risk analysis module; the pollution risk degree of the air pollution treatment area is analyzed, the risk coefficient is obtained by comprehensively analyzing the area, the number and the distribution condition of the detection area with abnormal pollution characteristics, the actual pollution risk state of the air pollution treatment area is fed back through the risk coefficient, and early warning can be timely carried out when the risk is abnormal.
Example two
As shown in fig. 2, the method for detecting the risk of treating the atmospheric pollution based on data analysis comprises the following steps:
step one: the method comprises the following steps of carrying out regional division on an atmospheric pollution treatment area: dividing an atmospheric pollution treatment area into a plurality of detection areas, setting a detection period, acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period, performing numerical calculation to obtain a pollution coefficient WR, and marking the pollution characteristics of the detection areas as normal or abnormal according to the numerical value of the pollution coefficient WR;
step two: the method comprises the steps of periodically managing the treatment state of an atmospheric treatment pollution area: acquiring normal coefficients and switching coefficients of the detection area in the latest L2 detection periods, and marking the detection area as a qualified area, a treatment key area or a treatment difficult area according to the values of the normal coefficients and the switching coefficients;
step three: and analyzing the pollution risk degree of the air pollution treatment area: and acquiring different-surface data YC, double different-surface data SY and different-site data YD of the air pollution control area, carrying out numerical calculation to obtain a risk coefficient FX, and judging whether the pollution risk of the air pollution control area meets the requirement or not according to the numerical value of the risk coefficient FX.
When the invention works, the atmospheric pollution control area is divided into a plurality of detection areas, a detection period is set, the smoke data, the disulfide data and the carbon data of the detection areas are obtained in the detection period, the pollution coefficient is obtained by numerical calculation, and the pollution characteristic of the detection areas is marked as normal or abnormal according to the numerical value of the pollution coefficient; acquiring normal coefficients and switching coefficients of the detection area in the latest L2 detection periods, and marking the detection area as a qualified area, a treatment key area or a treatment difficult area according to the values of the normal coefficients and the switching coefficients; and acquiring different-surface data, double different-surface data and different-place data of the air pollution treatment area, performing numerical calculation to obtain a risk coefficient, judging whether the pollution risk of the air pollution treatment area meets the requirement or not according to the numerical value of the risk coefficient, and performing early warning in time.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: the formula wr=α1hc+α2el+α3 yt; collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding pollution coefficient for each group of sample data; substituting the set pollution coefficient and the collected sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 which are 3.74, 2.97 and 2.65 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the pollution coefficient which is preliminarily set by a person skilled in the art for each group of sample data; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the pollution coefficient is directly proportional to the value of the smoke data.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form 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 understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (9)
1. The atmospheric pollution treatment risk detection system based on data analysis is characterized by comprising a risk detection platform, wherein the risk detection platform is in communication connection with a region detection module, a period management module, a risk analysis module and a storage module;
the area detection module is used for carrying out area division on the air pollution treatment area: dividing an atmospheric pollution control area into a plurality of detection areas, setting a detection period, acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period, and performing numerical calculation to obtain a pollution coefficient WR of the detection areas; marking the pollution characteristic of the detection area as normal or abnormal according to the value of the pollution coefficient WR;
the period management module is used for periodically managing the treatment state of the atmospheric treatment pollution area: obtaining the atmospheric pollution detection results of the detection area in the latest L2 detection periods, and marking the ratio of the number of times that the pollution characteristics of the detection area are marked as normal to L2 as a normal coefficient; acquiring a switching coefficient of a detection area; acquiring a normal threshold value and a switching threshold value through a storage module; the normal coefficient and the switching coefficient of the detection area are respectively compared with a normal threshold value and a switching threshold value, and the detection area is marked as a treatment difficult area, a treatment key area or a qualified area according to the comparison result; the treatment difficult area, the treatment important area and the qualified area are sent to a mobile phone terminal of a manager through a risk detection platform;
the risk analysis module is used for analyzing the pollution risk degree of the air pollution treatment area and judging whether the pollution risk meets the requirement.
2. The atmospheric pollution abatement risk detection system based on data analysis of claim 1, wherein the process of obtaining the soot data YC of the detection area comprises: setting L1 detection points in a detection area, detecting the smoke concentration at the detection points in real time, marking the maximum value of the smoke concentration of the detection points in a detection period as a smoke concentration value, and marking the maximum value of the smoke concentration values of all the detection points as smoke data HC of the detection area; the acquisition process of the disulfide data EL of the detection region includes: sulfur dioxide detection is carried out in real time at detection points, the maximum value of the sulfur dioxide concentration of the detection points in the detection period is marked as a sulfur concentration value, and the maximum value of the sulfur concentration values of all the detection points is marked as disulfide data EL; the process for acquiring the one-carbon data YT of the detection area comprises the following steps: and carrying out carbon monoxide detection at the detection points in real time, marking the maximum value of the carbon monoxide concentration of the detection points in the detection period as a carbon concentration value, and marking the maximum value of the carbon concentration values of all the detection points as carbon data YT.
3. The atmospheric pollution abatement risk detection system based on data analysis of claim 2, wherein the specific process of marking the pollution signature of the detection area as normal or abnormal comprises: the pollution threshold WRmax is obtained through the storage module, and the pollution coefficient WR of the detection area is compared with the pollution threshold WRmax: if the pollution coefficient WR is smaller than the pollution threshold WRmax, judging that the atmospheric pollution detection result in the detection area is qualified, and marking the pollution characteristic of the corresponding detection area as normal; if the pollution coefficient WR is greater than or equal to the pollution threshold WRmax, judging that the air pollution detection result in the detection area is unqualified, marking the pollution characteristic of the corresponding detection area as abnormal, and simultaneously, sending the detection area with the abnormal pollution characteristic to a mobile phone terminal of a manager through a risk detection platform by the area monitoring module.
4. A system for detecting risk of atmospheric pollution abatement based on data analysis as defined in claim 3, wherein the process of obtaining the switching coefficient of the detection area comprises: acquiring the air pollution detection results of the detection area in two adjacent detection periods, and if the two detection periods are normal or abnormal, marking the stable characteristics of the detection area in the corresponding two detection periods as being maintained; otherwise, the stable characteristic of the detection area in the corresponding two detection periods is marked as switching; the ratio of the number of times the detection area is marked as switched for the stable feature over L2 detection periods to L2 is marked as a switching coefficient.
5. The atmospheric pollution abatement risk detection system based on data analysis of claim 4, wherein the specific process of comparing the normal coefficient and the switching coefficient of the detection area with the normal threshold and the switching threshold, respectively, comprises: if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is smaller than or equal to the switching threshold value, marking the corresponding detection area as a treatment difficulty area; if the normal coefficient is smaller than or equal to the normal threshold value and the switching coefficient is larger than the switching threshold value, marking the corresponding detection area as a treatment key area; if the normal coefficient is larger than the normal threshold value, the corresponding detection area is marked as a qualified area.
6. The atmospheric pollution abatement risk detection system based on data analysis of claim 5, wherein the specific process of analyzing the pollution risk level of the atmospheric pollution abatement zone by the risk analysis module comprises: acquiring different-surface data YC, double different-surface data SY and different-site data YD of an atmospheric pollution treatment area, and performing numerical calculation to obtain a risk coefficient FX; and acquiring a risk threshold FXmax through the storage module, comparing the risk coefficient FX with the risk threshold FXmax, and judging whether the pollution risk meets the requirement or not according to a comparison result.
7. The atmospheric pollution abatement risk detection system based on data analysis of claim 6, wherein the outlier data YC is the sum of the area values of all detection areas whose pollution characteristics are abnormal; the acquisition process of the double-hetero data SY comprises the following steps: if the pollution characteristics of two adjacent detection areas are abnormal, marking the corresponding two detection areas as associated areas, intercepting the superposition positions of boundary lines of the associated areas, marking the length values of the intercepted boundary lines as superposition values, and marking the sum of the superposition values of all the associated areas as double-abnormal data SY; the off-site data YD is the number of detection areas in the atmospheric pollution control region, which are characterized by abnormality.
8. The atmospheric pollution abatement risk detection system of claim 7, wherein comparing risk factor FX to risk threshold FXmax comprises: if the risk coefficient FX is smaller than the risk threshold FXmax, judging that the pollution risk of the atmospheric pollution treatment area meets the requirement; if the risk coefficient FX is greater than or equal to the risk threshold FXmax, judging that the pollution risk of the air pollution treatment area does not meet the requirement, and sending a pollution early warning signal to a mobile phone terminal of a manager through a risk detection platform by the risk analysis module.
9. A method of operating an atmospheric pollution abatement risk detection system based on data analysis according to any one of claims 1 to 8, comprising the steps of:
step one: the method comprises the following steps of carrying out regional division on an atmospheric pollution treatment area: dividing an atmospheric pollution treatment area into a plurality of detection areas, setting a detection period, acquiring smoke data YC, disulfide data EL and carbon data YT of the detection areas in the detection period, performing numerical calculation to obtain a pollution coefficient WR, and marking the pollution characteristics of the detection areas as normal or abnormal according to the numerical value of the pollution coefficient WR;
step two: the method comprises the steps of periodically managing the treatment state of an atmospheric treatment pollution area: acquiring normal coefficients and switching coefficients of the detection area in the latest L2 detection periods, and marking the detection area as a qualified area, a treatment key area or a treatment difficult area according to the values of the normal coefficients and the switching coefficients;
step three: and analyzing the pollution risk degree of the air pollution treatment area: and acquiring different-surface data YC, double different-surface data SY and different-site data YD of the air pollution control area, carrying out numerical calculation to obtain a risk coefficient FX, and judging whether the pollution risk of the air pollution control area meets the requirement or not according to the numerical value of the risk coefficient FX.
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