CN111177639A - Indoor air quality evaluation method based on fuzzy analysis - Google Patents
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- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/0037—Specially adapted to detect a particular component for NOx
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/0039—Specially adapted to detect a particular component for O3
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/004—Specially adapted to detect a particular component for CO, CO2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/0042—Specially adapted to detect a particular component for SO2, SO3
Abstract
The invention discloses an indoor air quality evaluation method based on fuzzy analysis, which comprises the steps of determining an evaluation standard set of a research object, determining an evaluation factor set of the research object, determining a factor weight set, establishing a membership function, establishing a fuzzy comprehensive evaluation matrix, carrying out composite operation on the solved membership matrix and the weight matrix, and quantifying a fuzzy evaluation weighted average grade; the invention considers the inherent ambiguity of the indoor air quality grade boundary, and the evaluation result can display the membership degree of different grades, which is closer to the thinking habit of people. The method comprehensively considers each index influencing the overall performance of the object, considers the importance degree, namely the weight, of each index in the influencing object by combining medical literature, determines the judgment matrix of each index by introducing a membership function, and judges the quality sequence of the measured indoor air quality by carrying out fuzzy transformation on the weight of each index and the judgment matrix to obtain the size of each evaluated value.
Description
Technical Field
The invention relates to the technical field of indoor air quality evaluation, in particular to an indoor air quality evaluation method based on fuzzy analysis.
Background
People are increasingly demanding high quality indoor air in production, work and life activities. PM today2.5Has become the first pollutant to interfere with air quality, and is the most important pollutant for peopleContaminants of interest. When people go out, special people do not resist external air pollution enough, and various respiratory diseases and even carcinogenesis are easily induced.
PM2.5The particles with aerodynamic diameter less than or equal to 2.5 mu m have huge specific surface area, can adsorb toxic and harmful substances, can enter the lung of a human body for deposition, even permeate into blood, and diffuse to the whole body. Long term exposure to PM2.5The environment with high concentration causes great harm to the respiratory system, the cardiovascular system, the nervous system, the immune system and the like of a human body, and scientific research shows that PM in the environment2.5An increase in concentration can significantly accelerate premature death in the population.
There may be a relationship between CO exposure and the occurrence of arteriosclerosis, heart disease: the development of atherosclerotic disease is associated with other risk factors (e.g., increased cholesterol levels) and CO exposure can exacerbate the development of underlying atherosclerotic disease, ultimately narrowing the coronary arteries. At a concentration of 50% to 70% CO, coma, respiratory paralysis and death occur. O is3Is harmful to human health, and short-term exposure can cause the increase of the prevalence, hospitalization rate and death rate of cardiovascular and respiratory diseases.
At present, SO2、NO2Has a greater increase in the mortality rate of PM10、PM2.5Second, O3The mortality rate of (c) is minimally increased. PM in air2.5、PM10、CO、O3、SO2And NO2The risk of residents suffering from respiratory diseases is increased, and the risk is one of the reasons for the increase of outpatient services of the respiratory diseases. The occurrence of sick building syndrome makes people pay more and more attention to the problem of indoor air quality, and among a plurality of methods for evaluating the indoor air quality, a fuzzy mathematical theory is a method with high recognition.
The indoor air quality has randomness, uncertainty and inherent ambiguity, and a comprehensive index for evaluating the indoor air quality is lacked at present. In the current national standard, the discontinuous distribution of the graded concentration of the pollutant indexes and the continuous distribution of the change of the indoor air quality index concentration are not consistent with each other, so that the specific grading standard of the traditional mathematics is used for evaluating the indoor environment air pollution degree and has the disadvantage.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an indoor air quality evaluation method based on fuzzy analysis, which carries out multi-level, multi-direction and multi-angle evaluation on the indoor air quality, has very important significance for improving the indoor air environment and the management level, can objectively provide more accurate evaluation, and has the advantages of scientific and reasonable method, strong applicability, high accuracy, easy evaluation and the like.
The purpose of the invention is realized by the following technical scheme:
an indoor air quality evaluation method based on fuzzy analysis comprises the following steps:
step one, determining an evaluation criterion set V ═ V of a research object1，V2，…，VmDividing the pollution degree of each pollution factor to the air environment into five grades, namely I (clean), II (light pollution), III (moderate pollution), IV (heavy pollution) and V (heavy pollution), according to indoor evaluation indexes and by combining the actual situation of the indoor air pollution degree;
step two, determining an evaluation factor set U ═ U of the research object1，U2，…，UnComprehensively analyzing all indexes influencing the air environment quality, wherein the basic pollutants in the environment air comprise the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a Therefore, the set of evaluation factors is established as U ═ { PM ═ PM2.5，PM10，CO，O3，SO2，NO2}；
Step three, determining a factor weight set; according to medical related documents, according to the influence degree of various air chemical pollutants on human health, weight coefficients of pollution parameters contained in indoor air quality are rearranged, and the weight coefficients are respectively as follows: PM (particulate matter)2.5(0.25)，PM10(0.2)，CO(0.2)，O3(0.15)，SO2(0.1) and NO2(0.1), so the set of factor weights a ═ a1a2…a5]＝[0.250.20.2 0.15 0.1 0.1]；
Step four, establishing a membership function; according to the evaluation factor set and the evaluation standard set determined above and the actual situation of the problem to be researched, the function form of the halving trapezoid is adopted to establish the membership function r of each pollution factor to each level standardij(ii) a The specific calculation formula is as follows:
in the stage i, when j is 1, the expression of the membership function is:
when the class II to IV, i.e. j is 2, 3, 4, the expression of the membership function is as follows:
in the stage iv, i.e., when j is 4, the membership function expression is:
in the function segmentation expression, i represents a certain evaluation factor in an evaluation factor set U; j represents a certain evaluation criterion in the evaluation criterion set V; u. ofiA measured contaminant concentration value from a location indicative of an ith evaluation factor; sjA concentration limit value of a j-th grade representing an ith evaluation factor;
step five, establishing a fuzzy comprehensive evaluation matrix; substituting the monitoring values of the pollutants into corresponding membership function expressions respectively, calculating the membership of each evaluation factor to each grade to form a membership set of each pollution factor, namely, taking the V < th > valueiSingle factor evaluation of individual factors Ri＝(ri1，ri2，…，rin)TAs a fuzzy subset, where rinThe evaluation matrix of all the factors is R-R (R) for the membership degree of the ith factor to the jth grade1R2…Rn)；
Step six, get abovePerforming a complex operation on the obtained membership matrix R and the weight matrix a to obtain a comprehensive evaluation vector B, i.e., B ═ a · R ═ B1，…，bm) In the traditional fuzzy mathematical theory, b is assumed according to the principle of maximum membershipkIs b isj(j ═ 1, …, m), it can be concluded that the indoor air quality belongs to class k:
step seven, under certain conditions, the principle of maximum membership causes loss of a lot of information, so that objective and effective evaluation cannot be carried out, and one-sided results may occur; therefore, the improved fuzzy evaluation weighted average grade method carries out weighted average according to a formula, so that the evaluation grade is quantized and more intuitive:
in the formula: j is a grade evaluation value, and J is more than or equal to 0 and less than or equal to 100; j is more than or equal to 0 and less than or equal to 50 and belongs to the V level, J is more than or equal to 50 and less than or equal to 60 and belongs to the IV level, J is more than or equal to 60 and less than or equal to 70 and belongs to the III level, J is more than or equal to 70 and less than or equal to 85 and belongs to the II level, and J is more than or equal to 85 and.
Compared with the prior art, the invention has the following beneficial effects:
the invention considers the inherent ambiguity of the indoor air quality grade boundary, and the evaluation result can display the membership degree of different grades, which is closer to the thinking habit of people. The method comprehensively considers each index influencing the overall performance of the object, considers the importance degree, namely the weight, of each index in the influencing object by combining medical literature, determines the judgment matrix of each index by introducing a membership function, and judges the quality sequence of the measured indoor air quality by carrying out fuzzy transformation on the weight of each index and the judgment matrix to obtain the size of each evaluated value.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
The invention introduces a fuzzy mathematical principle, establishes a corresponding fuzzy mathematical model for the building indoor air monitoring data, and carries out fuzzy comprehensive evaluation on the indoor environmental air quality of six evaluation objects by applying the model, thereby providing scientific basis for indoor air pollution monitoring and treatment and respiratory health evaluation of personnel in public building workplace.
According to comprehensive analysis of various indexes affecting the air environment quality, basic pollutants in the ambient air comprise the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a The invention obtains the grade of the evaluation object by compound calculation with the help of the membership function and the weight coefficient.
Specifically, as shown in fig. 1, a fuzzy analysis based indoor air quality evaluation method includes the following steps:
step one, determining an evaluation criterion set V ═ V of a research object1，V2，…，VmDividing the pollution degree of each pollution factor to the air environment into five grades, namely I (clean), II (light pollution), III (moderate pollution), IV (heavy pollution) and V (heavy pollution), according to indoor evaluation indexes and by combining the actual situation of the indoor air pollution degree;
step two, determining an evaluation factor set U ═ U of the research object1，U2，…，UnComprehensively analyzing all indexes influencing the air environment quality, wherein the basic pollutants in the environment air comprise the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a Therefore, the set of evaluation factors is established as U ═ { PM ═ PM2.5，PM10，CO，O3，SO2，NO2}；
Step three, determining a factor weight set; according to the medical related literature, the pollution parameters contained in the indoor air quality are rearranged according to the influence degree of various air chemical pollutants on the human healthThe coefficients, respectively: PM (particulate matter)2.5(0.25)，PM10(0.2)，CO(0.2)，O3(0.15)，SO2(0.1) and NO2(0.1), so the set of factor weights a ═ a1a2…a5]＝[0.250.20.2 0.15 0.1 0.1]；
Step four, establishing a membership function; according to the evaluation factor set and the evaluation standard set determined above and the actual situation of the problem to be researched, the function form of the halving trapezoid is adopted to establish the membership function r of each pollution factor to each level standardij(ii) a The specific calculation formula is as follows:
in the stage i, when j is 1, the expression of the membership function is:
when the class II to IV, i.e. j is 2, 3, 4, the expression of the membership function is as follows:
in the stage iv, i.e., when j is 4, the membership function expression is:
in the function segmentation expression, i represents a certain evaluation factor in an evaluation factor set U; j represents a certain evaluation criterion in the evaluation criterion set V; u. ofiA measured contaminant concentration value from a location indicative of an ith evaluation factor; sjA concentration limit value of a j-th grade representing an ith evaluation factor;
step five, establishing a fuzzy comprehensive evaluation matrix; substituting the monitoring values of the pollutants into corresponding membership function expressions respectively, calculating the membership of each evaluation factor to each grade to form a membership set of each pollution factor, namely, taking the V < th > valueiSingle factor evaluation of individual factors Ri＝(ri1，ri2，…，rin)TAs a fuzzy subset, itMiddle rinThe evaluation matrix of all the factors is R-R (R) for the membership degree of the ith factor to the jth grade1R2…Rn)；
Step six, performing composite operation on the obtained membership matrix R and the weight matrix A to obtain a comprehensive evaluation vector B, namely B ═ A · R ═ B1，…，bm) In the traditional fuzzy mathematical theory, b is assumed according to the principle of maximum membershipkIs b isj(j ═ 1, …, m), it can be concluded that the indoor air quality belongs to class k:
the air quality detection data of the two rooms A and B at representative time are adopted, and are shown in the following table:
calculating the maximum characteristic vector by means of a Matlab program, and carrying out consistency check to finally obtain two weight sets R1、R2：
The obtained comprehensive evaluation vector values of different places are summarized in the following table:
step seven, under certain conditions, the principle of maximum membership causes loss of a lot of information, so that objective and effective evaluation cannot be carried out, and one-sided results may occur; therefore, the improved fuzzy evaluation weighted average grade method carries out weighted average according to a formula, so that the evaluation grade is quantized and more intuitive:
in the formula: j is a grade evaluation value, and J is more than or equal to 0 and less than or equal to 100; j is more than or equal to 0 and less than or equal to 50 and belongs to the V level, J is more than or equal to 50 and less than or equal to 60 and belongs to the IV level, J is more than or equal to 60 and less than or equal to 70 and belongs to the III level, J is more than or equal to 70 and less than or equal to 85 and belongs to the II level, and J is more than or equal to 85 and. Calculating to obtain a grade evaluation value J of the first place by adopting the weighted average grade186.810 (class I and class II), the evaluation value J of the grade of the Japanese area293.032 (stage I). It can be easily seen that the air quality in room b is better than that in room a.
Fig. 1 is a flow chart of an indoor air quality evaluation method based on fuzzy analysis.
Overall, as shown in fig. 1: (1) determining evaluation criterion set V ═ V of study object1，V2，…，VmDividing the pollution degree of each pollution factor to the air environment into five grades, namely I (clean), II (light pollution), III (moderate pollution), IV (heavy pollution) and V (heavy pollution), according to indoor evaluation indexes and by combining the actual situation of the indoor air pollution degree; (2) determining evaluation factor set U ═ U of research object1，U2，…，UnComprehensively analyzing all indexes influencing the air environment quality, wherein the basic pollutants in the environment air comprise the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a Therefore, the set of evaluation factors is established as U ═ { PM ═ PM2.5，PM10，CO，O3，SO2，NO2}; (3) determining a factor weight set; according to medical related documents, according to the influence degree of various air chemical pollutants on human health, the weight coefficients of pollution parameters contained in indoor air quality are rearranged, and are respectively as follows: PM (particulate matter)2.5(0.25)，PM10(0.2)，CO(0.2)，O3(0.15)，SO2(0.1)，NO2(0.1), so the set of factor weights a ═ a1a2…a5]＝[0.25 0.2 0.2 0.15 0.1 0.1](ii) a (4) Establishing a membership function; establishing each pollution factor pair by adopting a function form of half-reduced trapezoid according to the determined evaluation factor set and evaluation standard set and combining the actual situation of the problem to be researchedMembership function r of each level of standardij(ii) a (5) Establishing a fuzzy comprehensive evaluation matrix; substituting the monitoring values of the pollutants into corresponding membership function expressions respectively, calculating the membership of each evaluation factor to each grade to form a membership set of each pollution factor, namely, taking the V < th > valueiSingle factor evaluation of individual factors Ri＝(ri1，ri2，…，rin)TAs a fuzzy subset, where rinThe evaluation matrix of all the factors is R-R (R) for the membership degree of the ith factor to the jth grade1R2…Rn) (ii) a (6) Performing a complex operation on the obtained membership matrix R and the weight matrix a to obtain a comprehensive evaluation vector B, i.e., B ═ a · R ═ B1，…，bm) In the traditional fuzzy mathematical theory, b is assumed according to the principle of maximum membershipkIs b isj(j ═ 1, …, m), it is concluded that the indoor air quality belongs to class k; (7) in some cases, the maximum membership rule causes a lot of information loss, so that the evaluation cannot be carried out objectively and effectively, and a one-sided result may occur. The invention carries out weighted average according to a formula by an improved fuzzy evaluation weighted average grade method, so that the evaluation grade is quantized and more visual.
The invention aims to apply an indoor air quality judgment program based on fuzzy analysis to make up for an indoor evaluation method. The fuzzy logic-based evaluation method overcomes the limitations of the traditional indoor environment evaluation method. The indoor air quality is not a clear boundary, i.e. the indoor air quality can be said to be a vague concept. Comprehensive consideration of influence factors is one of the characteristics of the fuzzy comprehensive evaluation method, and the evaluation grade is calculated by utilizing the membership function and the weighting factor. Therefore, fuzzy mathematical theory becomes an important method in the field of indoor air quality evaluation. The indoor air quality is a comprehensive problem about human health, environmental safety and building design, and a program scheme convenient for decoration personnel to use is required to be constructed, and the program scheme is verified by using measured data, and is suitable for various occasions or becomes a basis for regulating and improving the air quality based on a new dynamic evaluation model and a corresponding evaluation method.
The method comprises the steps of determining an evaluation standard set of a research object, determining an evaluation factor set of the research object, determining a factor weight set, establishing a membership function, establishing a fuzzy comprehensive evaluation matrix, carrying out composite operation on the obtained membership matrix and the weight matrix, and quantifying the weighted average grade of the fuzzy evaluation. The evaluation criteria set comprises I (clean), II (light pollution), III (moderate pollution), IV (heavy pollution) and V (heavy pollution); the evaluation factor set includes the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a The factor weight sets are respectively PM2.5(0.25)，PM10(0.2)，CO(0.2)，O3(0.15)，SO2(0.1)，NO2(0.1); the membership function adopts a half-reduced trapezoid; the fuzzy evaluation weighted average grade method carries out weighted average according to a formula so as to quantify the evaluation grade.
The invention considers the inherent ambiguity of the indoor air quality grade boundary, and the evaluation result can display the membership degree of different grades, which is closer to the thinking habit of people. The method comprehensively considers each index influencing the overall performance of the object, considers the importance degree, namely the weight, of each index in the influencing object by combining medical literature, determines the judgment matrix of each index by introducing a membership function, and judges the quality sequence of the measured indoor air quality by carrying out fuzzy transformation on the weight of each index and the judgment matrix to obtain the size of each evaluated value.
The present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents and are included in the scope of the present invention.
Claims (1)
1. A fuzzy analysis based indoor air quality evaluation method is characterized by comprising the following steps:
step one, determining an evaluation criterion set V ═ V of a research object1，V2，…，Vm}，According to indoor evaluation indexes and by combining the actual situation of indoor air pollution degree, the pollution degree of each pollution factor to the air environment is divided into five grades, namely I (clean), II (light pollution), III (moderate pollution), IV (heavy pollution) and V (severe pollution);
step two, determining an evaluation factor set U ═ U of the research object1，U2，…，UnComprehensively analyzing all indexes influencing the air environment quality, wherein the basic pollutants in the environment air comprise the following six items: PM (particulate matter)2.5、PM10、CO、O3、SO2And NO2(ii) a Therefore, the set of evaluation factors is established as U ═ { PM ═ PM2.5，PM10，CO，O3，SO2，NO2}；
Step three, determining a factor weight set; according to medical related documents, according to the influence degree of various air chemical pollutants on human health, weight coefficients of pollution parameters contained in indoor air quality are rearranged, and the weight coefficients are respectively as follows: PM (particulate matter)2.5(0.25)，PM10(0.2)，CO(0.2)，O3(0.15)，SO2(0.1) and NO2(0.1), so the set of factor weights a ═ a1a2…a5]＝[0.250.2 0.2 0.15 0.1 0.1]；
Step four, establishing a membership function; according to the evaluation factor set and the evaluation standard set determined above and the actual situation of the problem to be researched, the function form of the halving trapezoid is adopted to establish the membership function r of each pollution factor to each level standardij(ii) a The specific calculation formula is as follows:
in the stage i, when j is 1, the expression of the membership function is:
when the class II to IV, i.e. j is 2, 3, 4, the expression of the membership function is as follows:
in the stage iv, i.e., when j is 4, the membership function expression is:
in the function segmentation expression, i represents a certain evaluation factor in an evaluation factor set U; j represents a certain evaluation criterion in the evaluation criterion set V; u. ofiA measured contaminant concentration value from a location indicative of an ith evaluation factor; sjA concentration limit value of a j-th grade representing an ith evaluation factor;
step five, establishing a fuzzy comprehensive evaluation matrix; substituting the monitoring values of the pollutants into corresponding membership function expressions respectively, calculating the membership of each evaluation factor to each grade to form a membership set of each pollution factor, namely, taking the V < th > valueiSingle factor evaluation of individual factors Ri＝(ri1，ri2，…，rin)TAs a fuzzy subset, where rinThe evaluation matrix of all the factors is R-R (R) for the membership degree of the ith factor to the jth grade1R2…Rn)；
Step six, performing composite operation on the obtained membership matrix R and the weight matrix A to obtain a comprehensive evaluation vector B, namely B ═ A · R ═ B1，…，bm) In the traditional fuzzy mathematical theory, b is assumed according to the principle of maximum membershipkIs b isj(j ═ 1, …, m), it can be concluded that the indoor air quality belongs to class k:
step seven, under certain conditions, the principle of maximum membership causes loss of a lot of information, so that objective and effective evaluation cannot be carried out, and one-sided results may occur; therefore, the improved fuzzy evaluation weighted average grade method carries out weighted average according to a formula, so that the evaluation grade is quantized and more intuitive:
in the formula: j is a grade evaluation value, and J is more than or equal to 0 and less than or equal to 100; j is more than or equal to 0 and less than or equal to 50 and belongs to the V level, J is more than or equal to 50 and less than or equal to 60 and belongs to the IV level, J is more than or equal to 60 and less than or equal to 70 and belongs to the III level, J is more than or equal to 70 and less than or equal to 85 and belongs to the II level, and J is more than or equal to 85 and.
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| CN112183950A (en) * | 2020-09-08 | 2021-01-05 | 西安建筑科技大学 | Air quality evaluation model, model construction method and application thereof |
| CN112700140A (en) * | 2020-12-30 | 2021-04-23 | 哈尔滨工业大学 | River pollution key section quantitative identification method based on fuzzy comprehensive evaluation |
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| CN115860561A (en) * | 2022-12-20 | 2023-03-28 | 成都联客信息技术有限公司 | Method for quantitatively evaluating water quality |
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| 李光耀;刘晓红;: "基于层次分析法的室内空气品质等级模糊综合评价", 苏州大学学报(工科版) * |
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| CN112183950B (en) * | 2020-09-08 | 2023-09-26 | 西安建筑科技大学 | Air quality evaluation model, model construction method and application thereof |
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| CN113962335A (en) * | 2021-12-22 | 2022-01-21 | 北京恒信启华信息技术股份有限公司 | Flexibly configurable data whole-process processing method |
| CN113962335B (en) * | 2021-12-22 | 2022-04-12 | 北京恒信启华信息技术股份有限公司 | Flexibly configurable data whole-process processing method |
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