CN116860839A - Big data-based aerosol production monitoring management system - Google Patents
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Abstract
The invention relates to the technical field of aerosol supervision, which is used for solving the problems that in the existing aerosol monitoring and treatment mode, an aerosol pollution source cannot be accurately positioned, so that the pollution degree of aerosol cannot be accurately monitored and analyzed, an effective aerosol treatment scheme and purification treatment of aerosol are difficult to formulate, and the environment and human health are seriously damaged. The invention realizes the accurate positioning of the pollution source generated by the aerosol and the accurate judgment of the pollution degree of the aerosol, outputs a reasonable aerosol treatment scheme, realizes the purification treatment of the aerosol and the effective management of the aerosol, and reduces the harm of the aerosol to the environment and the human health.
Description
Technical Field
The invention relates to the technical field of aerosol supervision, in particular to an aerosol production monitoring management system based on big data.
Background
Aerosols refer to solid or liquid particles dispersed in a gas, typically between a few nanometers and tens of microns in size. The aerosol is mainly derived from volcanic eruption, sand storm in nature and industrial waste gas and traffic tail gas in human activities. Among them, industrial waste gas generated in human activities is a major factor causing generation of aerosol. And aerosols have serious harm and impact on air quality and human health. Therefore, it is important to establish an aerosol monitoring and management system to monitor and manage the aerosol.
However, in the existing method for monitoring and treating aerosol, the source of aerosol pollution cannot be rapidly and accurately determined, so that the pollution degree of the aerosol produced by industrial production cannot be accurately monitored and analyzed, and therefore, an effective aerosol treatment plan and scheme are difficult to formulate, so that the aerosol produced by industrial production cannot be rapidly purified and treated, and the environment and human health are seriously harmed.
In order to solve the above-mentioned defect, a technical scheme is provided.
Disclosure of Invention
The invention aims to provide an aerosol production monitoring and management system based on big data.
The aim of the invention can be achieved by the following technical scheme: an aerosol production monitoring management system based on big data, comprising: the system comprises a data acquisition unit, a cloud database, a pollution source dividing unit, a pollution source re-screening unit, an aerosol pollution monitoring unit, a climate influence analysis unit, a comprehensive treatment unit and an execution terminal;
the data acquisition unit is used for acquiring environmental parameter information, data change information, output state information and emission state information of the environment where the pollution source of the aerosol is located, acquiring climate condition information of the place where the aerosol is generated, and transmitting various types of information into the cloud database for storage;
the cloud database is also used for storing an influence change grade judging table, storing a pollution degree generating data table, storing an emission pollution degree data table, storing a total pollution state judging table and storing a treatment strengthening grade judging table;
the pollution source dividing unit is used for monitoring environmental parameter information of the environment where the pollution source of the aerosol is located, judging and analyzing the pollution source generated by the aerosol, and obtaining a set A and a set B;
the pollution source re-screening unit is used for monitoring data change information of each aerosol generation micro source in the set B according to the set B, so that the pollution sources generated by the aerosols marked as the aerosol generation micro sources are re-analyzed;
the aerosol pollution monitoring unit is used for monitoring the output state information of the aerosol generated by the determined source of the aerosol generation and the emission state information of the corresponding emission source according to the set A, so as to analyze the pollution state of the pollution source generated by the aerosol, obtain the aerosol pollution level of each pollution source and send the aerosol pollution level to the comprehensive treatment unit;
the climate influence analysis unit is used for monitoring the climate condition information of the aerosol generating place, analyzing the climate influence state of the aerosol generating place, obtaining the treatment enhancement grade of the aerosol generating place according to the climate influence state, and sending the treatment enhancement grade to the comprehensive treatment unit;
the comprehensive treatment unit is used for comprehensively setting the aerosol treatment state of the pollution sources according to the received aerosol pollution level of the pollution sources and the treatment enhancement level of the aerosol production place, so that an aerosol treatment scheme of the pollution sources is obtained, and the influence of the aerosol on the environment and human health is reduced by executing the corresponding aerosol treatment scheme through the execution terminal.
Preferably, the judging and analyzing are carried out on the pollution source generated by aerosol, and the specific analysis process is as follows:
monitoring chemical component values in environmental parameter information of the environment where each pollution source of aerosol is located in real time, and marking the chemical component values as p;
monitoring the concentration value of the corresponding chemical component in the environmental parameter information of the environment where each pollution source of the aerosol is positioned in real time and recording the concentration value asWhere i represents a set of the number of contamination sources of the aerosol, and i=1, 2,3 … … n;
then real-time monitoring the material accumulation quantity of the environment where each pollution source of the gas is positioned in unit time and recording the material accumulation quantity as；
Analyzing the environment of the corresponding pollution source of the aerosol according to a set data model:thereby obtaining the environmental state coefficients of the various sources of pollution of the aerosol +.>ρ1, ρ2 and ρ3 are weight factor coefficients of the chemical component value, the concentration value of the corresponding chemical component, and the substance accumulation amount, respectively, and ρ1, ρ2 and ρ3 are natural numbers greater than 0;
setting an environment comparison threshold of the environment state coefficient, and comparing and analyzing the obtained environment state coefficient of each pollution source with a preset environment comparison threshold, specifically:
if the environmental state coefficient is greater than or equal to a preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation determination source and is classified into a set A;
otherwise, if the environmental state coefficient is smaller than the preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation micro source and is classified into the set B.
Preferably, the source of pollution generated by aerosol is re-analyzed, and the specific analysis process is as follows:
according to the set B, monitoring the distance difference and the workload in the data change information of each pollution source in the set B in real time, and marking the distance difference and the workload respectivelyIs defined asAnd->And comprehensively analyzing the two items of data according to a set data model:thereby obtaining the influence change coefficient of each pollution source>Wherein j is the number of tiny sources for generating aerosol contained in the set B, j is a positive integer, lambda 1 and lambda 2 are weight factor coefficients of distance difference and workload respectively, and lambda 1 and lambda 2 are natural numbers larger than 0;
comparing and matching the influence change coefficients of all the pollution sources with an influence change level judgment table stored in a cloud database, thereby obtaining change levels of all the pollution sources, wherein each influence change coefficient corresponds to one change level, and the change levels comprise a small-amplitude change level, a medium-amplitude change level and a large-amplitude change level;
if the change level of the pollution source is judged to be a large change level, removing the corresponding aerosol generation micro source from the collection B and reclassifying the aerosol generation micro source in the collection A;
if the change level of the pollution source is judged to be a small-amplitude change level or a medium-amplitude change level, no treatment is performed.
Preferably, the monitoring of the aerosol generation determining source aerosol output state information and the corresponding emission source emission state information specifically includes the following monitoring process:
according to the set A, the output particle quantity, the particle diameter average value and the toxic component ratio in the output state information of the aerosol under each pollution source in the set A are monitored in real time and respectively calibrated as、/>And->And each item of data is calculated and analyzed, and according to a set model: />Thereby obtaining the pollution coefficient of each pollution source>Wherein k represents the number of aerosol generation determining sources contained in the set A, k is a positive integer, delta 1, delta 2 and delta 3 are correction factor coefficients of the output particle quantity, the particle diameter mean value and the ratio of toxic components respectively, and delta 1, delta 2 and delta 3 are natural numbers larger than 0;
monitoring the emission concentration and the emission diffusion value in the emission state information of the emission sources corresponding to the pollution sources in the set A in real time, and calibrating the emission concentration and the emission diffusion value asAnd->And comprehensively analyzing the two items of data according to a set data model: />Whereby the emission pollution coefficient of aerosols at the respective emission source +.>Wherein γ1 and γ2 are normalization factors of the emission concentration and the emission diffusion value, respectively, and γ1 and γ2 are natural numbers greater than 0.
Preferably, the analysis of the pollution state of the pollution source generated by aerosol is performed by the following specific analysis process:
the pollution generation coefficient of the aerosol under the source of the determined aerosol generation is compared and matched with a pollution generation degree data table stored in a cloud database,thus, a first pollution level value is obtained and is recorded asAnd each pollution coefficient obtained has a first pollution degree value corresponding to the first pollution degree value;
performing comparative matching analysis on the emission pollution coefficient of the aerosol at the emission source and an emission pollution degree data table stored in a cloud database to obtain a second pollution degree value, and recording the second pollution degree value asAnd each obtained emission pollution coefficient has a second pollution degree value corresponding to the second pollution degree value;
the first pollution degree value and the second pollution degree value are summed and analyzed, and the formula is used for:thus, the total pollution degree value of each pollution source system is obtained>；
And comparing and matching the total pollution degree values of all the pollution source systems with a total pollution state judgment table stored in a cloud database, so as to obtain aerosol pollution levels of all the pollution source systems, wherein the obtained total pollution degree values correspond to one aerosol pollution level, and the aerosol pollution levels comprise a serious aerosol pollution level, a medium aerosol pollution level and a mild aerosol pollution level.
Preferably, the monitoring of the information of the climate conditions of the aerosol generating place and the analysis of the climate influence state thereof are carried out, and the specific analysis process is as follows:
the method comprises the steps of monitoring temperature change values, humidity change values, wind speeds, pressure change values and illumination intensity in climate condition information of an aerosol generating place in real time, calibrating the temperature change values, the humidity change values, the wind speeds, the pressure change values and the illumination intensity as tem, dam, ws, ap and gqd respectively, comprehensively analyzing various data, and setting a data model: cpv =μ× (tem+dam+ws+ap+ gqd), whereby a climate influence value cpv is obtained, where μ is a conversion factor coefficient and μ is a natural number greater than 0;
and comparing and matching the climate influence values with a treatment enhancement level judgment table stored in the cloud database, so as to obtain treatment enhancement levels of the aerosol generating place, wherein each climate influence value corresponds to one treatment enhancement level, and the treatment enhancement levels comprise a first treatment enhancement level, a second treatment enhancement level and a third treatment enhancement level.
Preferably, the comprehensive setting is performed on the aerosol treatment state of the pollution source, and the specific analysis process is as follows:
the pollution source systems at the same aerosol pollution level are classified into the same collection, and the specific steps are as follows: classifying each pollution source system calibrated to be in a serious aerosol pollution level into a first priority treatment set W1, classifying each pollution source system calibrated to be in a medium aerosol pollution level into a second priority treatment set W2, classifying each pollution source system calibrated to be in a light aerosol pollution level into a third priority treatment set W3, and thus obtaining a first priority treatment set W1, a second priority treatment set W2 and a third priority treatment set W3;
according to the classified various types of priority treatment sets, when the pollution sources are treated, the treatment sequence is as follows: firstly treating each pollution source in a first priority treatment set W1, then treating each pollution source in a second priority treatment set W2, and finally treating each pollution source in a third priority treatment set W3;
according to the received treatment enhancement level of the aerosol generating place, if the treatment enhancement level is a first-stage treatment enhancement level, a first-stage periodic treatment scheme is generated, specifically: performing (t/m 1) times of treatment operations at intervals of m1 duration within t unit time;
if the treatment enhancement level is a second-level treatment enhancement level, a second-order periodic treatment scheme is generated, specifically: performing (t/m 2) times of treatment operations at intervals of m2 duration within t unit time;
if the treatment enhancement level is a three-level treatment enhancement level, a three-level periodic treatment scheme is generated, specifically: and (3) performing (t/m 3) times of treatment operations at intervals of m3 in t unit time, wherein m1 < m2 < m3, and the specific values of t, m1, m2 and m3 are set specifically in specific cases by those skilled in the art.
The invention has the beneficial effects that:
according to the invention, through monitoring and analyzing environmental parameter information of an environment where a pollution source of aerosol is located, a data model is adopted to substitute calculation, data threshold comparison and integrated classification output modes, so that the accurate positioning and classification of the pollution source generated by the aerosol are realized, a foundation is laid for realizing effective treatment of the aerosol, and a formula calculation and data comparison mode is adopted, and secondary screening judgment is carried out on the pollution source generated by the aerosol, so that comprehensive and efficient monitoring and management of aerosol pollution are improved;
the pollution degree of the aerosol is defined by taking the pollution sources generated by the determined aerosol as the basis, calling the output state information and the emission state information under the corresponding pollution source system, adopting a data calculation and big data comprehensive analysis mode, and setting the treatment priority of each pollution source by utilizing a mode of collecting classification and priority setting;
the method has the advantages that the pollution degree of the aerosol to the aerosol is determined by monitoring and analyzing the climate condition information of the aerosol production place, different treatment enhancement levels and aerosol treatment schemes to the aerosol are output from the side face, the aerosol is purified, meanwhile, the efficient monitoring and effective management to the aerosol are realized, and the harm of the aerosol to the environment and human health is reduced.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a system block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described 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.
Referring to fig. 1, the present invention is an aerosol production monitoring and management system based on big data, comprising: the system comprises a data acquisition unit, a cloud database, a pollution source dividing unit, a pollution source re-screening unit, an aerosol pollution monitoring unit, a climate influence analysis unit, a comprehensive treatment unit and an execution terminal.
The data acquisition unit is used for acquiring environmental parameter information, data change information, output state information and emission state information of the environment where the pollution source of the aerosol is located, acquiring climate condition information of the place where the aerosol is generated, and sending various types of information to the cloud database for storage.
The cloud database is also used for storing an influence change grade judging table, storing a pollution degree generating data table, storing an emission pollution degree data table, storing a total pollution state judging table and storing a treatment strengthening grade judging table.
The pollution source dividing unit is used for monitoring environmental parameter information of the environment where the pollution source of the aerosol is located, so that the pollution source generated by the aerosol is judged and analyzed, and the specific analysis process is as follows:
monitoring chemical component values in environmental parameter information of the environment where each pollution source of aerosol is located in real time, and marking the chemical component values as p;
monitoring the concentration value of the corresponding chemical component in the environmental parameter information of the environment where each pollution source of the aerosol is positioned in real time and recording the concentration value asWhere i represents a set of the number of contamination sources of the aerosol, and i=1, 2,3 … … n;
then real-time monitoring the material accumulation quantity of the environment where each pollution source of the gas is positioned in unit time and recording the material accumulation quantity as；
And the environment where the corresponding pollution source of the aerosol is located is dividedAnalysis, according to a set data model:thereby obtaining the environmental state coefficients of the various sources of pollution of the aerosol +.>ρ1, ρ2 and ρ3 are weight factor coefficients of the chemical component value, the concentration value of the corresponding chemical component, the substance accumulation amount, respectively, ρ1, ρ2 and ρ3 are natural numbers greater than 0, and the weight factor coefficients are used for equalizing the duty ratio weights of each item of data in formula calculation, thereby promoting the accuracy of calculation results;
it should be noted that the chemical component value refers to a data value of how many kinds of chemical components are contained in the environment where each pollution source is located, and the substance accumulation amount is a data value indicating the integration of the contents of all substances accumulated and generated in the environment per unit time where each pollution source is located;
setting an environment comparison threshold of the environment state coefficient, and comparing and analyzing the obtained environment state coefficient of each pollution source with a preset environment comparison threshold, specifically:
if the environmental state coefficient is greater than or equal to a preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation determination source and is classified into a set A;
otherwise, if the environmental state coefficient is smaller than the preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation micro source and is classified into a set B;
and sending the generated set B to a pollution source rescanning unit.
The pollution source re-screening unit is used for monitoring data change information of each aerosol generation micro source in the collection B, so that the pollution sources generated by the aerosols marked as the aerosol generation micro sources are re-analyzed, and the pollution sources are specifically:
according to the set B, monitoring the distance difference and the workload in the data change information of the tiny sources generated by each aerosol in the set B in real time, and calibrating the distance difference and the workload asAnd->And comprehensively analyzing the two items of data according to a set data model: />The influence coefficient of the individual aerosol-generating sources is thus obtained +>Wherein j is the number of tiny sources for generating aerosol contained in the set B, j is a positive integer, lambda 1 and lambda 2 are weight factor coefficients of distance difference and workload respectively, and lambda 1 and lambda 2 are natural numbers larger than 0;
it should be noted that the distance difference refers to a distance value between the aerosol-generating micro source and the nearest aerosol-generating determining source, and the work load refers to an increased value of the production work load of the aerosol-generating micro source in a unit time;
comparing and matching the influence change coefficients of all the aerosol generating micro sources with the influence change level judgment tables stored in the cloud database, so as to obtain the change level of each aerosol generating micro source, wherein each influence change coefficient corresponds to one change level, and the change level comprises a small-amplitude change level, a medium-amplitude change level and a large-amplitude change level;
if the change level of the aerosol-generating micro source is judged to be a large-amplitude change level, removing the corresponding aerosol-generating micro source from the set B and reclassifying the aerosol-generating micro source in the set A;
if the level of variation of the aerosol-generating micro source is determined to be a small-amplitude variation level or a medium-amplitude variation level, no processing is performed.
The aerosol pollution monitoring unit is used for monitoring the output state information of the aerosols generated and determined from the source in the set A and the emission state information of the corresponding emission source, and the specific monitoring process is as follows:
according to the set A, each aerosol generation in the set A is monitored in real time to determine the output particle quantity, the particle diameter average value and the toxic component ratio in the output state information of the aerosol at the source, and the output particle quantity, the particle diameter average value and the toxic component ratio are respectively calibrated as、/>And->And each item of data is calculated and analyzed, and according to a set model: />Thus, the pollution coefficient of the generation of the aerosols under the source of each aerosol generation determination is obtained>Wherein k represents the number of aerosol generation determining sources contained in the set A, k is a positive integer, delta 1, delta 2 and delta 3 are correction factor coefficients of the output particle quantity, the particle diameter mean value and the toxic component ratio respectively, delta 1, delta 2 and delta 3 are natural numbers larger than 0, and the correction factor coefficients are used for correcting deviation of various parameters in the formula calculation process, so that more accurate parameter data are calculated;
it should be noted that, the amount of the produced particles refers to a data value corresponding to the total content of various types of aerosol particles accumulated and dispersed in the environment in unit time of the source of the aerosol generation, and the particles include solid particles and liquid particles;
the total particle diameter average value refers to an average value of average particle diameter values of all types of chemical components, and the average particle diameter value refers to an average value of particle diameter values of all particles of a certain type of chemical component at a certain basis weight, for example, if aerosol generation is monitored to determine that the source has 5 types of chemical component particles, v-basis weight particles are randomly collected from the 5 types of chemical component particles, respectively, and the particle diameter of v-basis weight particles of each type of chemical component is subjected to average calculation, thereby obtaining an average particle diameter value of particles of each type of chemical component, and the average particle diameter value of particles of 5 types of chemical component is subjected to average calculation, thereby obtaining a total particle diameter average;
the ratio of toxic components refers to the value of the number of types of toxic chemical components in the environment to the number of types of total chemical components;
monitoring the emission concentration and the emission diffusion value in the emission state information of the emission source corresponding to each aerosol generation determination source in the set A in real time, and calibrating the emission concentration and the emission diffusion value as followsAnd->And comprehensively analyzing the two items of data according to a set data model: />Whereby the emission pollution coefficient of aerosols at the respective emission source +.>Wherein γ1 and γ2 are normalization factors of emission concentration and emission diffusion value, respectively, and γ1 and γ2 are natural numbers greater than 0, and normalization factors are used for representing coefficients for converting various data in the data model into dimensionless form;
it should be noted that, aerosol with different degrees and different forms is generated in each process or each production line of the industrial production, and uniform discharge is performed for the generation of the aerosol in the industrial production, in this case, each aerosol generation determining source is specifically set to set an aerosol discharge source corresponding to the aerosol generation determining source, so as to construct a pollution source system;
it should be noted that the emission spread value is used to represent the extent of aerosol emission spread, and the emission spread value is generally measured in terms of the range of regions in which the aerosol spreads;
the pollution state of the pollution source generated by aerosol is analyzed, and the specific analysis process is as follows:
generating aerosolDetermining the pollution coefficient of the aerosol generated under the source, performing comparison and matching analysis with a pollution degree data table stored in a cloud database, thereby obtaining a first pollution degree value, and recording the first pollution degree value asAnd each pollution coefficient obtained has a first pollution degree value corresponding to the first pollution degree value;
performing comparative matching analysis on the emission pollution coefficient of the aerosol at the emission source and an emission pollution degree data table stored in a cloud database to obtain a second pollution degree value, and recording the second pollution degree value asAnd each obtained emission pollution coefficient has a second pollution degree value corresponding to the second pollution degree value;
the first pollution degree value and the second pollution degree value are summed and analyzed, and the formula is used for:thus, the total pollution degree value of each pollution source system is obtained>；
Comparing and matching the total pollution degree values of all pollution source systems with a total pollution state judgment table stored in a cloud database, so as to obtain aerosol pollution levels of all pollution source systems, wherein the obtained total pollution degree values correspond to one aerosol pollution level, and the aerosol pollution levels comprise a serious aerosol pollution level, a medium aerosol pollution level and a mild aerosol pollution level;
and the obtained aerosol pollution levels of all pollution sources are sent to a comprehensive treatment unit.
The climate influence analysis unit is used for monitoring the climate condition information of the aerosol generating place, so as to analyze the climate influence state of the aerosol generating place, and the specific analysis process is as follows:
the method comprises the steps of monitoring temperature change values, humidity change values, wind speeds, pressure change values and illumination intensity in climate condition information of an aerosol generating place in real time, calibrating the temperature change values, the humidity change values, the wind speeds, the pressure change values and the illumination intensity as tem, dam, ws, ap and gqd respectively, comprehensively analyzing various data, and setting a data model: cpv =μ× (tem+dam+ws+ap+ gqd), whereby a climate influence value cpv is obtained, where μ is a conversion factor coefficient for converting physical quantities of all data items into data coefficients of the same physical quantity, and μ is a natural number greater than 0;
it should be noted that the temperature change value refers to an amplitude value of a temperature change of the aerosol generating place within a certain time, the humidity change value refers to an amplitude value of a humidity change of the aerosol generating place within a certain time, and the pressure change value refers to an amplitude value of an atmospheric pressure change of the aerosol generating place within a certain time;
comparing and matching the climate influence values with a treatment enhancement level judgment table stored in a cloud database, thereby obtaining treatment enhancement levels of aerosol production places, wherein each climate influence value corresponds to one treatment enhancement level, and the treatment enhancement levels comprise a first treatment enhancement level, a second treatment enhancement level and a third treatment enhancement level;
and sending the obtained enhanced treatment grade of the aerosol generating place to the comprehensive treatment unit.
The comprehensive treatment unit comprehensively sets the aerosol treatment state of the pollution sources according to the aerosol pollution level of each pollution source and the treatment enhancement level of the aerosol production place, and the specific analysis process is as follows:
the pollution source systems at the same aerosol pollution level are classified into the same collection, and the specific steps are as follows: classifying each pollution source system calibrated to be in a serious aerosol pollution level into a first priority treatment set W1, classifying each pollution source system calibrated to be in a medium aerosol pollution level into a second priority treatment set W2, classifying each pollution source system calibrated to be in a light aerosol pollution level into a third priority treatment set W3, and thus obtaining a first priority treatment set W1, a second priority treatment set W2 and a third priority treatment set W3;
according to the classified various types of priority treatment sets, when the pollution sources are treated, the treatment sequence is as follows: firstly treating each pollution source in a first priority treatment set W1, then treating each pollution source in a second priority treatment set W2, and finally treating each pollution source in a third priority treatment set W3;
according to the received treatment enhancement level of the aerosol generating place, if the treatment enhancement level is a first-stage treatment enhancement level, a first-stage periodic treatment scheme is generated, specifically: the control operation is carried out for (t/m 1) times by the execution terminal at intervals of m1 time in t unit time;
if the treatment enhancement level is a second-level treatment enhancement level, a second-order periodic treatment scheme is generated, specifically: the control operation is carried out for (t/m 2) times by the execution terminal at intervals of m2 time in t unit time;
if the treatment enhancement level is a three-level treatment enhancement level, a three-level periodic treatment scheme is generated, specifically: performing (t/m 3) treatment operations by the execution terminal at intervals of m3 in t unit time, wherein m1 is less than m2 and less than m3, and setting specific numerical values of t, m1, m2 and m3 is specifically set by a person skilled in the art in specific cases;
the treatment operation comprises purifying the aerosol by adopting purifying equipment such as an adsorbent, a filter, electric dust removal and the like and wet purifying technologies such as spray cooling, wet electric dust removal and the like so as to reduce the harm degree of the aerosol.
When the method is used, the environmental parameter information of the environment where the pollution sources of the aerosol are positioned is monitored and analyzed, the data model is adopted to be substituted into a mode of calculation, data threshold comparison and integrated classification output, so that the accurate positioning and classification of the pollution sources generated by the aerosol are realized, a foundation is laid for realizing the effective treatment of the aerosol, and the pollution sources generated by the aerosol are subjected to secondary screening judgment by adopting a mode of formula calculation and data comparison, so that the comprehensive and efficient monitoring and management of the pollution of the aerosol are improved;
the pollution degree of the aerosol is defined by taking the pollution sources generated by the determined aerosol as the basis, calling the output state information and the emission state information under the corresponding pollution source system, adopting a data calculation and big data comprehensive analysis mode, and setting the treatment priority of each pollution source by utilizing a mode of collecting classification and priority setting;
the method has the advantages that the pollution degree of the aerosol to the aerosol is determined by monitoring and analyzing the climate condition information of the aerosol production place, different treatment enhancement levels and aerosol treatment schemes to the aerosol are output from the side face, the aerosol is purified, meanwhile, the efficient monitoring and effective management to the aerosol are realized, and the harm of the aerosol to the environment and human health is reduced.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (7)
1. Big data-based aerosol production monitoring and management system, characterized by comprising:
the data acquisition unit is used for acquiring environmental parameter information, data change information, output state information and emission state information of the environment where the pollution source of the aerosol is located, acquiring climate condition information of the place where the aerosol is generated, and transmitting various types of information into the cloud database for storage;
the cloud database is also used for storing an influence change grade judging table, storing a pollution degree generating data table, storing an emission pollution degree data table, storing a total pollution state judging table and storing a treatment strengthening grade judging table;
the pollution source dividing unit is used for monitoring environmental parameter information of the environment where the pollution source of the aerosol is located, judging and analyzing the pollution source generated by the aerosol, and obtaining a set A and a set B;
the pollution source re-screening unit is used for monitoring data change information of each aerosol generation micro source in the set B according to the set B, so that the pollution sources generated by the aerosols marked as the aerosol generation micro sources are re-analyzed;
the aerosol pollution monitoring unit is used for monitoring the output state information of the aerosol generated by the determined source of the aerosol generation and the emission state information of the corresponding emission source according to the set A, so as to analyze the pollution state of the pollution source generated by the aerosol, obtain the aerosol pollution level of each pollution source and send the aerosol pollution level to the comprehensive treatment unit;
the climate influence analysis unit is used for monitoring the climate condition information of the aerosol generating place, analyzing the climate influence state of the aerosol generating place, obtaining the treatment enhancement grade of the aerosol generating place according to the climate influence state, and sending the treatment enhancement grade to the comprehensive treatment unit;
and the comprehensive treatment unit is used for comprehensively setting the aerosol treatment state of the pollution sources according to the received aerosol pollution level of each pollution source and the treatment enhancement level of the aerosol production place, so as to obtain an aerosol treatment scheme of each pollution source, and executing a corresponding aerosol treatment scheme through an execution terminal.
2. The big data based aerosol production monitoring and management system according to claim 1, wherein the judging and analyzing the pollution source generated by the aerosol comprises the following specific analysis processes:
monitoring chemical component values in environmental parameter information of the environment where each pollution source of aerosol is located in real time, and marking the chemical component values as p;
monitoring the concentration value of the corresponding chemical component in the environmental parameter information of the environment where each pollution source of the aerosol is positioned in real time and recording the concentration value asWhere i represents a set of the number of contamination sources of the aerosol, and i=1, 2,3 … … n;
then real-time monitoring the material accumulation quantity of the environment where each pollution source of the gas is positioned in unit time and processing the material accumulation quantityIs noted as；
Analyzing the environment of the corresponding pollution source of the aerosol according to a set data model:thereby obtaining the environmental state coefficients of the various sources of pollution of the aerosol +.>ρ1, ρ2 and ρ3 are weight factor coefficients of the chemical component value, the concentration value of the corresponding chemical component, and the substance accumulation amount, respectively;
setting an environment comparison threshold of the environment state coefficient, and comparing and analyzing the obtained environment state coefficient of each pollution source with a preset environment comparison threshold, specifically:
if the environmental state coefficient is greater than or equal to a preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation determination source and is classified into a set A;
otherwise, if the environmental state coefficient is smaller than the preset environmental comparison threshold, the corresponding pollution source is marked as an aerosol generation micro source and is classified into the set B.
3. The big data based aerosol production monitoring and management system of claim 1, wherein the re-analysis of the pollution source generated by the aerosol is performed by the following specific analysis process:
according to the set B, monitoring the distance difference and the workload in the data change information of each pollution source in the set B in real time, and comprehensively analyzing the two items of data to obtain the influence change coefficient of each pollution source;
comparing and matching the influence change coefficients of all the pollution sources with an influence change level judgment table stored in a cloud database, thereby obtaining change levels of all the pollution sources, wherein each influence change coefficient corresponds to one change level, and the change levels comprise a small-amplitude change level, a medium-amplitude change level and a large-amplitude change level;
and if the change level of the pollution source is judged to be a large change level, removing the corresponding aerosol generation micro source from the collection B and re-classifying the aerosol generation micro source into the collection A.
4. The big data based aerosol production monitoring management system according to claim 1, wherein the monitoring of the aerosol production status information under the aerosol production determining source and the emission status information under the corresponding emission source is performed by the following specific monitoring process:
according to the set A, the output particle quantity, the particle diameter average value and the toxic component occupation ratio in the output state information of the aerosol in the set A are monitored in real time, and each item of data is calculated and analyzed, so that the pollution coefficient of each pollution source is obtained;
and (3) monitoring the emission concentration and the emission diffusion value in the emission state information of the emission source corresponding to each emission source in the set A in real time, and comprehensively analyzing the two items of data, so that the emission pollution coefficient of the aerosol under each emission source.
5. The big data based aerosol production monitoring and management system of claim 1, wherein the analysis of the pollution status of the pollution source generated by the aerosol is performed by the following specific analysis process:
comparing and matching the pollution coefficient of the aerosol generated under the source determined by the generation of the aerosol with a pollution degree data table stored in a cloud database, thereby obtaining a first pollution degree value, wherein each obtained pollution degree value corresponds to the first pollution degree value;
performing comparison and matching analysis on the emission pollution coefficient of the aerosol at the emission source and an emission pollution degree data table stored in a cloud database, so as to obtain a second pollution degree value, wherein each obtained emission pollution coefficient has a second pollution degree value corresponding to the second pollution degree value;
carrying out summation analysis on the first pollution degree value and the second pollution degree value, thereby obtaining total pollution degree values under various pollution source systems;
and comparing and matching the total pollution degree values of all the pollution source systems with a total pollution state judgment table stored in a cloud database, so as to obtain aerosol pollution levels of all the pollution source systems, wherein the obtained total pollution degree values correspond to one aerosol pollution level, and the aerosol pollution levels comprise a serious aerosol pollution level, a medium aerosol pollution level and a mild aerosol pollution level.
6. The big data based aerosol production monitoring and management system according to claim 1, wherein the specific analysis process is as follows:
monitoring temperature change value, humidity change value, wind speed, pressure change value and illumination intensity in the climate condition information of the aerosol generating place in real time, and comprehensively analyzing various data to obtain a climate influence value;
and comparing and matching the climate influence values with a treatment enhancement level judgment table stored in the cloud database, so as to obtain treatment enhancement levels of the aerosol generating place, wherein each climate influence value corresponds to one treatment enhancement level, and the treatment enhancement levels comprise a first treatment enhancement level, a second treatment enhancement level and a third treatment enhancement level.
7. The big data-based aerosol production monitoring and management system according to claim 1, wherein the comprehensive setting of the pollution source aerosol treatment state is performed by the following specific analysis process:
classifying all pollution source systems in the same aerosol pollution level into the same set, thereby obtaining a first priority treatment set W1, a second priority treatment set W2 and a third priority treatment set W3;
according to the classified various types of priority treatment sets, when the pollution sources are treated, the treatment sequence is as follows: firstly treating each pollution source in a first priority treatment set W1, then treating each pollution source in a second priority treatment set W2, and finally treating each pollution source in a third priority treatment set W3;
generating a corresponding first-order periodic treatment scheme or a second-order periodic treatment scheme or a third-order periodic treatment scheme according to the treatment enhancement level of the received aerosol generating place.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020125662A1 (en) * | 2020-10-01 | 2022-04-07 | Johannes Herrmann | Method and device for forecasting environmental influences, in particular the progression of diseases |
| CN115688045A (en) * | 2022-09-20 | 2023-02-03 | 西安市智慧环保综合指挥中心 | Pollution source data fusion analysis method |
| CN116067436A (en) * | 2023-04-06 | 2023-05-05 | 安徽配隆天环保科技有限公司 | Environment monitoring system and monitoring method |
| CN116485191A (en) * | 2023-06-26 | 2023-07-25 | 安徽中科蓝壹信息科技有限公司 | Environmental impact early warning method and system based on Lagrange diffusion model |
-
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- 2023-09-04 CN CN202311128063.0A patent/CN116860839B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020125662A1 (en) * | 2020-10-01 | 2022-04-07 | Johannes Herrmann | Method and device for forecasting environmental influences, in particular the progression of diseases |
| CN115688045A (en) * | 2022-09-20 | 2023-02-03 | 西安市智慧环保综合指挥中心 | Pollution source data fusion analysis method |
| CN116067436A (en) * | 2023-04-06 | 2023-05-05 | 安徽配隆天环保科技有限公司 | Environment monitoring system and monitoring method |
| CN116485191A (en) * | 2023-06-26 | 2023-07-25 | 安徽中科蓝壹信息科技有限公司 | Environmental impact early warning method and system based on Lagrange diffusion model |
Non-Patent Citations (1)
| Title |
|---|
| 刘文清;刘建国;谢品华;陆亦怀;高闽光;张玉钧;: "区域大气复合污染立体监测技术系统与应用", 大气与环境光学学报, no. 04, pages 7 - 19 * |
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