CN117557099A - Method, device and system for evaluating running condition of biological activated carbon in water plant - Google Patents
Method, device and system for evaluating running condition of biological activated carbon in water plant Download PDFInfo
- Publication number
- CN117557099A CN117557099A CN202311575700.9A CN202311575700A CN117557099A CN 117557099 A CN117557099 A CN 117557099A CN 202311575700 A CN202311575700 A CN 202311575700A CN 117557099 A CN117557099 A CN 117557099A
- Authority
- CN
- China
- Prior art keywords
- activated carbon
- data
- index
- water plant
- water quality
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 963
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 500
- 238000000034 method Methods 0.000 title claims abstract description 65
- 238000011156 evaluation Methods 0.000 claims abstract description 199
- 238000012544 monitoring process Methods 0.000 claims abstract description 184
- 229910052799 carbon Inorganic materials 0.000 claims description 179
- 239000000126 substance Substances 0.000 claims description 75
- 238000004364 calculation method Methods 0.000 claims description 22
- 238000012545 processing Methods 0.000 claims description 19
- 238000007689 inspection Methods 0.000 claims description 18
- 230000000975 bioactive effect Effects 0.000 claims description 11
- 238000013145 classification model Methods 0.000 claims description 9
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 238000004140 cleaning Methods 0.000 claims description 4
- 238000012847 principal component analysis method Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 230000008901 benefit Effects 0.000 abstract description 4
- 230000008569 process Effects 0.000 description 23
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 8
- 238000001514 detection method Methods 0.000 description 8
- RBTBFTRPCNLSDE-UHFFFAOYSA-N 3,7-bis(dimethylamino)phenothiazin-5-ium Chemical compound C1=CC(N(C)C)=CC2=[S+]C3=CC(N(C)C)=CC=C3N=C21 RBTBFTRPCNLSDE-UHFFFAOYSA-N 0.000 description 7
- ZCYVEMRRCGMTRW-UHFFFAOYSA-N 7553-56-2 Chemical compound [I] ZCYVEMRRCGMTRW-UHFFFAOYSA-N 0.000 description 7
- 239000002028 Biomass Substances 0.000 description 7
- 229910052740 iodine Inorganic materials 0.000 description 7
- 239000011630 iodine Substances 0.000 description 7
- 229960000907 methylthioninium chloride Drugs 0.000 description 7
- 230000036541 health Effects 0.000 description 6
- 239000011159 matrix material Substances 0.000 description 6
- 238000012360 testing method Methods 0.000 description 6
- 230000004071 biological effect Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 230000007812 deficiency Effects 0.000 description 4
- 238000012552 review Methods 0.000 description 3
- 239000000090 biomarker Substances 0.000 description 2
- 238000012854 evaluation process Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 239000003610 charcoal Substances 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- VUZPPFZMUPKLLV-UHFFFAOYSA-N methane;hydrate Chemical class C.O VUZPPFZMUPKLLV-UHFFFAOYSA-N 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 238000013441 quality evaluation Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 102220030763 rs1385129 Human genes 0.000 description 1
- 102220304080 rs145404836 Human genes 0.000 description 1
- 102220049405 rs147669920 Human genes 0.000 description 1
- 102220037545 rs187184327 Human genes 0.000 description 1
- 102220168578 rs199904091 Human genes 0.000 description 1
- 102220013903 rs372736227 Human genes 0.000 description 1
- 102220014332 rs397517039 Human genes 0.000 description 1
- 102220047008 rs587776405 Human genes 0.000 description 1
- 102220024548 rs62636518 Human genes 0.000 description 1
- 102220126301 rs782402689 Human genes 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Water Treatment By Sorption (AREA)
Abstract
The invention relates to the technical field of biological activated carbon evaluation, and particularly discloses a method, a device and a system for evaluating the running condition of biological activated carbon in a water plant, which comprise the following steps: dynamically calculating according to historical activated carbon index monitoring data of the water plant and real-time evaluation results of the activated carbon indexes of the water plant to determine the current activated carbon monitoring data result; determining an adjustment result of raw water quality data on activated carbon monitoring data according to the raw water quality data; determining an adjustment result of the water plant comprehensive management data on the activated carbon monitoring data according to the water plant comprehensive management data; according to the current activated carbon monitoring data result, the raw water quality data and the adjustment result of the activated carbon monitoring data, the water plant comprehensive management data comprehensively calculates the adjustment result of the activated carbon monitoring data to determine the water plant activated carbon evaluation score; and determining the water plant activated carbon evaluation grade according to the water plant activated carbon evaluation score. The method for evaluating the running condition of the biological activated carbon in the water plant has the advantages of high evaluation efficiency and high accuracy.
Description
Technical Field
The invention relates to the technical field of biological activated carbon evaluation, in particular to a water plant biological activated carbon running condition evaluation method, a water plant biological activated carbon running condition evaluation device and a water plant biological activated carbon running condition evaluation system.
Background
In actual production operation of a water plant, the problems of unsatisfactory treatment effect and high operation cost of the activated carbon are often caused by the reduction of the treatment efficiency of the activated carbon or improper operation management mode of the water plant. The comprehensive evaluation of the running condition of the biological activated carbon of the water plant can provide guidance for the running mode of the water plant, not only can reduce the running cost, but also can optimize the running parameters, so that the process running is stable, and the quality of the effluent water is improved. However, the current evaluation process for the running condition of the biological activated carbon is complicated, the time consumption is long, the evaluation method is single, and the uncertainty of the evaluation analysis result is high.
Therefore, how to improve the accuracy and efficiency of the evaluation of the biological activated carbon in the water plant is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides a water plant biological activated carbon running condition evaluation method, a water plant biological activated carbon running condition evaluation device and a water plant biological activated carbon running condition evaluation system, which solve the problems of low accuracy and low efficiency of water plant biological activated carbon evaluation in the related technology.
As a first aspect of the present invention, there is provided a water plant biological activated carbon operation condition evaluation method, comprising:
carrying out dynamic calculation according to historical active carbon index monitoring data of a water plant and a real-time evaluation result of the active carbon index of the water plant to determine the result of the current active carbon monitoring data, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises real-time evaluation result of the active carbon physical and chemical index, real-time evaluation result of the active carbon biological index and real-time evaluation result of the active carbon filter outlet water quality index;
acquiring raw water quality data, and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
acquiring water plant comprehensive management data, and determining an adjustment result of the water plant comprehensive management data on activated carbon monitoring data according to the water plant comprehensive management data;
according to the current activated carbon monitoring data result, the raw water quality data and the adjustment result of the activated carbon monitoring data, the water plant comprehensive management data comprehensively calculates the adjustment result of the activated carbon monitoring data to determine the water plant activated carbon evaluation score;
Comparing the water plant activated carbon evaluation score with a preset activated carbon evaluation grade table to determine a water plant activated carbon evaluation grade;
outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
Further, according to the historical activated carbon index monitoring data of the water plant and the real-time evaluation result of the activated carbon index of the water plant, the current activated carbon monitoring data result is dynamically calculated and determined, and the method comprises the following steps:
performing data processing and calculating and determining the weight data of the relevant indexes of the activated carbon according to the historical activated carbon index monitoring data of the water plant;
and calculating and determining the current activated carbon monitoring data result according to the activated carbon related index weight data and the real-time evaluation result of the activated carbon index of the water plant.
Further, according to the historical activated carbon index monitoring data of the water plant, performing data processing and calculating to determine the relevant index weight data of the activated carbon, including:
respectively judging and processing the data integrity of the historical active carbon physical and chemical index monitoring data, the historical active carbon biological index monitoring data and the historical active carbon filter outlet water quality index monitoring data to obtain corresponding active carbon physical and chemical index processing data, active carbon biological index processing data and carbon filter outlet water quality processing data;
And respectively calculating the ratio of the physical and chemical indexes of the activated carbon in the activated carbon physical and chemical index treatment data, the ratio of the biological indexes of the activated carbon in the activated carbon biological index treatment data and the ratio of the water quality index of the effluent of the carbon filter in the water quality treatment data of the effluent of the carbon filter according to a weight calculation algorithm, and determining the weight data of the physical and chemical indexes of the activated carbon, the weight data of the biological indexes of the activated carbon and the weight data of the water quality index of the effluent of the carbon filter, wherein the weight calculation algorithm at least comprises an entropy method and/or a principal component analysis method.
Further, according to the activated carbon related index weight data and the real-time evaluation result of the water plant activated carbon index, calculating and determining the current activated carbon monitoring data result, including:
respectively carrying out data cleaning and judging treatment according to the real-time evaluation result of the physical and chemical indexes of the activated carbon, the real-time evaluation result of the biological indexes of the activated carbon and the real-time evaluation result of the water quality indexes of the effluent of the carbon filter, and obtaining the corresponding scores of the physical and chemical indexes of the activated carbon, the corresponding scores of the biological indexes of the activated carbon and the corresponding scores of the water quality indexes of the effluent of the carbon filter;
and calculating and determining current activated carbon physical and chemical index monitoring data according to the activated carbon physical and chemical index weight data and the activated carbon physical and chemical index corresponding score, calculating and determining current activated carbon biochemical index monitoring data according to the activated carbon biological index weight data and the activated carbon biological index corresponding score, and calculating and determining current carbon filter outlet water quality index monitoring data according to the carbon filter outlet water quality index weight data and the carbon filter outlet water quality index corresponding score.
Further, acquiring raw water quality data, and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data, including:
judging whether historical data in the raw water quality database meets the requirement of being larger than the preset raw water quality data quantity or not;
if the historical data in the raw water quality database is larger than the preset raw water quality data quantity, calculating a risk coefficient according to the historical data in the raw water quality database to obtain a raw water risk coefficient.
Further, calculating a risk coefficient according to the historical data in the raw water quality database to obtain a raw water quality risk coefficient, including:
judging whether the maximum value of each raw water quality index in the raw water quality database is smaller than or equal to a preset maximum threshold value corresponding to the index;
if the maximum value of the current raw water quality index in the raw water quality database is smaller than or equal to the preset maximum threshold value corresponding to the index, determining the risk coefficient of the raw water quality index to be 1, and outputting the risk coefficient of the raw water quality index;
if the maximum value of the current raw water quality index in the raw water quality database is larger than the preset maximum threshold corresponding to the index, judging whether the occurrence frequency of the maximum value of the current raw water quality index is larger than the preset frequency threshold;
If the occurrence frequency of the maximum value of the current raw water quality index is greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a first risk coefficient, wherein the first risk coefficient is smaller than 1;
if the occurrence frequency of the maximum value of the current raw water quality index is not greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a second risk coefficient, wherein the second risk coefficient is smaller than 1, and the second risk coefficient is smaller than the first risk coefficient;
and determining the raw water risk coefficient according to the multiplication result of the risk coefficient of each raw water quality index in the raw water substance database.
Further, acquiring water plant integrated management data, and determining an adjustment result of the water plant integrated management data on activated carbon monitoring data according to the water plant integrated management data, wherein the adjustment result comprises:
judging whether historical data in a water plant comprehensive management database is larger than a preset water plant comprehensive management data volume or not;
if the historical data in the water plant comprehensive management database is larger than the preset water plant comprehensive management data amount, determining the water plant comprehensive management coefficient according to a classification model in the water plant comprehensive management data, wherein the classification model comprises a personnel quality inspection model, a system guarantee inspection model and a hardware facility inspection model.
Further, comparing the water plant activated carbon evaluation score with a preset activated carbon evaluation grade table to determine a water plant activated carbon evaluation grade, comprising:
sequentially comparing the water plant activated carbon evaluation scores according to the sequence from high to low of preset activated carbon evaluation grades to determine the water plant activated carbon evaluation grades, wherein the preset activated carbon evaluation grades sequentially comprise: very healthy, sub-healthy, unhealthy and ill.
As another aspect of the present invention, there is provided a water plant bioactive carbon operation condition evaluation device for implementing the water plant bioactive carbon operation condition evaluation method described above, comprising:
the active carbon monitoring data determining module is used for dynamically calculating and determining the current active carbon monitoring data result according to the historical active carbon index monitoring data of the water plant and the real-time evaluation result of the active carbon index of the water plant, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises an active carbon physical and chemical index real-time evaluation result, an active carbon biological index real-time evaluation result and a carbon filter outlet water quality index real-time evaluation result;
The raw water quality influence module is used for acquiring raw water quality data and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
the water plant comprehensive management data influence module is used for acquiring water plant comprehensive management data and determining an adjustment result of the water plant comprehensive management data on the activated carbon monitoring data according to the water plant comprehensive management data;
the evaluation score determining module is used for comprehensively calculating the adjustment result of the activated carbon monitoring data according to the current activated carbon monitoring data result, the raw water quality data and the water plant comprehensive management data to determine the water plant activated carbon evaluation score;
the evaluation grade determining module is used for determining the evaluation grade of the activated carbon of the water plant by comparing the evaluation score of the activated carbon of the water plant with a preset activated carbon evaluation grade table;
and the output module is used for outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
As another aspect of the present invention, there is provided a water plant bioactive carbon operation condition evaluation system, comprising: the water plant biological activated carbon running condition evaluation device comprises a water plant historical activated carbon index monitoring database, a raw water quality database, a water plant comprehensive management database and the water plant biological activated carbon running condition evaluation device, wherein the water plant historical activated carbon index monitoring database, the raw water quality database and the water plant comprehensive management database are all in communication connection with the water plant biological activated carbon running condition evaluation device.
According to the water plant biological activated carbon running condition assessment method provided by the invention, the current activated carbon monitoring data result is determined based on the historical activated carbon index monitoring data and the activated carbon real-time assessment result, the influence degree of the historical activated carbon index monitoring data and the current activated carbon monitoring data result is determined according to the raw water quality data and the water plant comprehensive management data, and finally the water plant activated carbon assessment score is determined based on the influence degree of the raw water quality data and the water plant comprehensive management data and the current activated carbon monitoring data result, so that the assessment of the water plant biological activated carbon running condition is realized. According to the water plant biological activated carbon running condition assessment method, the accuracy of a final assessment result can be effectively improved due to the fact that raw water quality data and water plant comprehensive management data are added in the assessment process to adjust the current activated carbon monitoring data result, and the assessment method automatically assesses based on historical data, real-time assessment results and the like and has the advantage of high assessment efficiency.
Drawings
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate the invention and together with the description serve to explain, without limitation, the invention.
FIG. 1 is a flow chart of the method for evaluating the running condition of the biological activated carbon in the water plant.
FIG. 2 is a flow chart of determining current activated carbon monitoring data results provided by the present invention.
FIG. 3 is a flow chart of determining the weight data of the physical and chemical indexes of the activated carbon according to the historical physical and chemical index monitoring data of the activated carbon.
FIG. 4 is a flow chart of determining activated carbon biological index weight data from historical activated carbon biological index monitoring data provided by the invention.
FIG. 5 is a flow chart of determining the weight data of the effluent quality index of the carbon filter according to the historical effluent quality index monitoring data of the carbon filter.
FIG. 6 is a flow chart of obtaining the corresponding scores of the physicochemical indexes of the activated carbon.
Fig. 7 is a flowchart for obtaining the corresponding score of the activated carbon biological index provided by the invention.
FIG. 8 is a flow chart for obtaining the corresponding score of the effluent quality index of the carbon filter.
FIG. 9 is a flowchart of a process for calculating scores of a calculation index according to the present invention.
FIG. 10 is a flow chart of obtaining corresponding monitoring data according to the physicochemical index weights of the activated carbon and the index score data corresponding to each activated carbon.
Fig. 11 is a flowchart for determining a raw water risk coefficient according to the present invention.
Fig. 12 is a specific flowchart for determining raw water risk factors for raw water quality data according to the present invention.
Fig. 13 is a flowchart of an embodiment of obtaining a final raw water risk factor score according to the present invention.
FIG. 14 is a flow chart of determining the overall management coefficients of a water plant provided by the invention.
FIG. 15 is a flowchart of determining the score of the integrated management coefficient of the water plant according to the classification model provided by the invention.
FIG. 16 is a flow chart of determining an evaluation level according to an evaluation score provided by the present invention.
FIG. 17 is a block diagram of a system for evaluating the operation condition of biological activated carbon in a water plant.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this embodiment, a method for evaluating the running condition of biological activated carbon in a water plant is provided, fig. 1 is a flowchart of the method for evaluating the running condition of biological activated carbon in a water plant according to an embodiment of the present invention, as shown in fig. 1, including:
s100, dynamically calculating according to historical active carbon index monitoring data of a water plant and a real-time evaluation result of the active carbon index of the water plant to determine the current active carbon monitoring data result, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises an active carbon physical and chemical index real-time evaluation result, an active carbon biological index real-time evaluation result and a carbon filter outlet water quality index real-time evaluation result;
Specifically, the current activated carbon monitoring data result can be obtained based on the historical activated carbon index monitoring data of the water plant and the real-time evaluation result of the activated carbon index of the water plant, and because the historical activated carbon index monitoring database is a dynamic database and is updated in real time, the current activated carbon monitoring data result is also a dynamic result, namely, changes along with the changes of the real-time evaluation result of the activated carbon index of the water plant, because the real-time evaluation result of the activated carbon index of the water plant is specifically the latest primary data in the historical activated carbon index monitoring database.
In addition, in the embodiment of the invention, the activated carbon index specifically can comprise an activated carbon physicochemical index, an activated carbon water biological index and a carbon filter outlet water quality index, so that the historical activated carbon index monitoring data of the water plant comprise historical activated carbon physicochemical index monitoring data, historical activated carbon biological index monitoring data and historical carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the activated carbon index of the water plant comprises a real-time evaluation result of the activated carbon physicochemical index, a real-time evaluation result of the activated carbon biological index and a real-time evaluation result of the carbon filter outlet water quality index.
S200, acquiring raw water quality data, and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
In the embodiment of the invention, the raw water quality data can influence the current active carbon monitoring data result, so that the influence degree of the raw water quality data on the active carbon monitoring data is determined.
S300, acquiring water plant integrated management data, and determining an adjustment result of the water plant integrated management data on activated carbon monitoring data according to the water plant integrated management data;
in the embodiment of the invention, the water plant comprehensive management data also influences the current activated carbon monitoring data result, so that the influence degree of the water plant comprehensive management data on the activated carbon monitoring data is determined, and a more accurate activated carbon monitoring data result can be obtained.
S400, comprehensively calculating the adjustment result of the activated carbon monitoring data according to the current activated carbon monitoring data result, the adjustment result of the raw water quality data on the activated carbon monitoring data and the water plant comprehensive management data to determine the water plant activated carbon evaluation score;
in the embodiment of the invention, the current activated carbon monitoring data result is determined according to the historical activated carbon index monitoring data, and the evaluation score of the activated carbon of the water plant can be determined by combining the raw water quality data and the influence degree of the water plant comprehensive management data on the current activated carbon monitoring data.
S500, comparing the water plant activated carbon evaluation score with a preset activated carbon evaluation grade table to determine a water plant activated carbon evaluation grade;
different evaluation grades can be preset for water plants with different evaluation results of the activated carbon, and the evaluation grade confirmation is carried out on the evaluation scores of the activated carbon according to the preset evaluation grades of the activated carbon.
S600, outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
In summary, the method for evaluating the running condition of the biological activated carbon of the water plant provided by the embodiment of the invention determines the current activated carbon monitoring data result based on the historical activated carbon index monitoring data and the real-time activated carbon evaluation result, further determines the influence degree of the historical activated carbon monitoring data result on the current activated carbon monitoring data result according to the raw water quality data and the water plant comprehensive management data, and finally determines the evaluation score of the activated carbon of the water plant based on the influence degree of the raw water quality data and the water plant comprehensive management data and the current activated carbon monitoring data result, thereby realizing the evaluation of the running condition of the biological activated carbon of the water plant. According to the water plant biological activated carbon running condition assessment method, the accuracy of a final assessment result can be effectively improved due to the fact that raw water quality data and water plant comprehensive management data are added in the assessment process to adjust the current activated carbon monitoring data result, and the assessment method automatically assesses based on historical data, real-time assessment results and the like and has the advantage of high assessment efficiency.
As a specific embodiment, the method for dynamically calculating and determining the current activated carbon monitoring data result according to the historical activated carbon index monitoring data of the water plant and the real-time evaluation result of the activated carbon index of the water plant, as shown in fig. 2, includes:
s110, performing data processing and calculation according to historical activated carbon index monitoring data of a water plant to determine relevant index weight data of the activated carbon;
in the embodiment of the invention, in order to determine the current activated carbon monitoring data result, the weight ratio of the relevant indexes of the activated carbon needs to be determined first.
Specifically, the method comprises the following steps:
1) Respectively judging and processing the data integrity of the historical active carbon physical and chemical index monitoring data, the historical active carbon biological index monitoring data and the historical active carbon filter outlet water quality index monitoring data to obtain corresponding active carbon physical and chemical index processing data, active carbon biological index processing data and carbon filter outlet water quality processing data;
2) And respectively calculating the ratio of the physical and chemical indexes of the activated carbon in the activated carbon physical and chemical index treatment data, the ratio of the biological indexes of the activated carbon in the activated carbon biological index treatment data and the ratio of the water quality index of the effluent of the carbon filter in the water quality treatment data of the effluent of the carbon filter according to a weight calculation algorithm, and determining the weight data of the physical and chemical indexes of the activated carbon, the weight data of the biological indexes of the activated carbon and the weight data of the water quality index of the effluent of the carbon filter, wherein the weight calculation algorithm at least comprises an entropy method and/or a principal component analysis method.
In the embodiment of the invention, as shown in fig. 3 to 5, the flow charts respectively determine the weight data of the physical and chemical indexes of the activated carbon according to the monitoring data of the physical and chemical indexes of the historical activated carbon, the weight data of the biological indexes of the activated carbon according to the monitoring data of the biological indexes of the historical activated carbon and the weight data of the water quality indexes of the effluent of the carbon filter according to the monitoring data of the water quality indexes of the effluent of the historical carbon filter.
As shown in fig. 3, the data inspection process is performed on the historical activated carbon physicochemical index monitoring data to determine that each data table in the historical activated carbon physicochemical index monitoring database has data, if so, whether the number of each data table is greater than a preset number threshold value is further determined, for example, the historical activated carbon physicochemical index may specifically include indexes such as intensity, iodine value, methylene blue value, etc., that is, whether the data table corresponding to each index has data is firstly determined, and if data is missing, deletion process is performed on the index data table corresponding to the missing value. If the data tables all have data, judging whether the number of each index data table is larger than a preset number threshold (for example, the number of the index data tables can be 2), and calculating the weight of each index according to a weight calculation algorithm under the condition that the preset number threshold is met, for example, the entropy method can be adopted for calculating the physicochemical index of the activated carbon.
Fig. 3 shows that taking the example that the physical and chemical indexes of the activated carbon comprise 8 indexes, 8 weight duty ratios are finally output.
Similarly, data processing is performed on the activated carbon biological indexes, and the data table is judged, so that the weight ratio of the activated carbon biological indexes is obtained, as shown in fig. 4. In this fig. 4, the activated carbon biological index is exemplified by 6 indexes, and may include biomass, biological activity, simpson index, and the like, for example.
Fig. 5 shows calculation of the weight of the effluent quality of the carbon filter, wherein 7 specific indexes are taken as examples, and finally the weight ratio of the effluent quality of the carbon filter is obtained. In the embodiment of the invention, the effluent quality index of the carbon filter can specifically comprise a permanganate index removal rate, a TOC removal rate, an ammonia nitrogen removal rate and the like.
And S120, calculating and determining the current activated carbon monitoring data result according to the activated carbon related index weight data and the real-time evaluation result of the water plant activated carbon index.
In the embodiment of the invention, the obtained activated carbon related index weight data and the real-time evaluation result of the water plant activated carbon index are calculated to obtain the activated carbon monitoring data result.
Specifically, the method comprises the following steps:
1) Respectively carrying out data cleaning and judging treatment according to the real-time evaluation result of the physical and chemical indexes of the activated carbon, the real-time evaluation result of the biological indexes of the activated carbon and the real-time evaluation result of the water quality indexes of the effluent of the carbon filter, and obtaining the corresponding scores of the physical and chemical indexes of the activated carbon, the corresponding scores of the biological indexes of the activated carbon and the corresponding scores of the water quality indexes of the effluent of the carbon filter;
In the embodiment of the invention, as shown in fig. 6 to 8, flowcharts of the corresponding score of the physical and chemical indexes of the activated carbon, the corresponding score of the biological index of the activated carbon and the corresponding score of the water quality index of the effluent of the carbon filter are respectively obtained.
As shown in fig. 6, data inspection is performed on the data in the activated carbon physicochemical index evaluation data table to determine whether there is a deficiency in the data table, if there is a deficiency, the deficiency value may be filled in by the lagrangian difference value, and if there is no deficiency, each score of the activated carbon physicochemical index in the data table is directly calculated, and finally, each corresponding score is obtained. In fig. 6, the activated carbon physical and chemical index includes 8 specific indexes as an example.
Similarly, the index score acquisition process shown in fig. 7 and 8 is similar.
In this embodiment, the calculation process of specifically calculating the respective scores of the index may refer to the calculation flow shown in fig. 9.
When score evaluation is performed on a specific index item in any one index, firstly judging whether data of the index is larger than or equal to a preset maximum threshold, outputting the index evaluation score to be A=1 if the condition is met, continuously judging whether the index data is smaller than or equal to the preset minimum threshold if the condition is not met, outputting the index evaluation score to be A=0 if the condition is met, and outputting the index evaluation score to be A= (C-Amin)/(Amax-Amin) if the index data is smaller than the preset maximum threshold and larger than the preset minimum threshold, wherein C represents the index data, amin represents the preset minimum threshold, and Amax represents the preset maximum threshold.
Based on the above, the corresponding score of the physical and chemical indexes of the activated carbon, the corresponding score of the biological indexes of the activated carbon and the corresponding score of the water quality indexes of the effluent of the carbon filter are obtained.
2) And calculating and determining current activated carbon physical and chemical index monitoring data according to the activated carbon physical and chemical index weight data and the activated carbon physical and chemical index corresponding score, calculating and determining current activated carbon biochemical index monitoring data according to the activated carbon biological index weight data and the activated carbon biological index corresponding score, and calculating and determining current carbon filter outlet water quality index monitoring data according to the carbon filter outlet water quality index weight data and the carbon filter outlet water quality index corresponding score.
In the embodiment of the present invention, as shown in fig. 10, corresponding monitoring data may be obtained by performing multiplication calculation according to the activated carbon physicochemical index weight and the index score data corresponding to each, for example, the activated carbon physicochemical index weight data and the activated carbon physicochemical index corresponding score may be multiplied to obtain activated carbon physicochemical index monitoring data, the activated carbon biological index weight data and the activated carbon biological index corresponding score may be multiplied to obtain activated carbon biological index monitoring data, and the activated carbon filter water outlet index weight data and the activated carbon filter water outlet index corresponding score may be multiplied to obtain carbon filter water outlet index monitoring data.
In order to obtain the activated carbon evaluation result more precisely, in the embodiment of the present invention, as shown in fig. 11, raw water quality data is obtained, and an adjustment result of raw water quality data on activated carbon monitoring data is determined according to the raw water quality data, including:
s210, judging whether historical data in a raw water quality database meets the requirement that the historical data is larger than the preset raw water quality data amount or not;
it should be understood that before the raw water risk coefficient is calculated, it is first determined whether the historical data in the raw water quality database is sufficient, that is, a relatively accurate raw water risk coefficient can be obtained if the historical data is sufficient.
S220, if the historical data in the raw water quality database is larger than the preset raw water quality data quantity, calculating a risk coefficient according to the historical data in the raw water quality database to obtain a raw water risk coefficient.
Further specifically, the step of calculating the risk coefficient according to the historical data in the raw water quality database to obtain a raw water quality risk coefficient comprises the following steps:
judging whether the maximum value of each raw water quality index in the raw water quality database is smaller than or equal to a preset maximum threshold value corresponding to the index;
if the maximum value of the current raw water quality index in the raw water quality database is smaller than or equal to the preset maximum threshold value corresponding to the index, determining the risk coefficient of the raw water quality index to be 1, and outputting the risk coefficient of the raw water quality index;
If the maximum value of the current raw water quality index in the raw water quality database is larger than the preset maximum threshold corresponding to the index, judging whether the occurrence frequency of the maximum value of the current raw water quality index is larger than the preset frequency threshold;
if the occurrence frequency of the maximum value of the current raw water quality index is greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a first risk coefficient, wherein the first risk coefficient is smaller than 1;
if the occurrence frequency of the maximum value of the current raw water quality index is not greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a second risk coefficient, wherein the second risk coefficient is smaller than 1, and the second risk coefficient is smaller than the first risk coefficient;
and determining the raw water risk coefficient according to the multiplication result of the risk coefficient of each raw water quality index in the raw water substance database.
As shown in fig. 12, a specific flowchart for determining raw water risk factors for raw water quality data is shown.
It should be noted that, for the raw water quality, there are also a plurality of raw water quality indexes, for the data E corresponding to each raw water quality index, it is first determined whether the maximum value thereof is less than or equal to a preset maximum threshold value, if the condition is satisfied, it is determined that the raw water risk coefficient is e=1, that is, the raw water quality has no influence on the current activated carbon monitoring data, if the maximum value of the data E corresponding to the raw water quality index is greater than the preset maximum threshold value, it is further determined that the maximum value occurs times, that is, it is determined that the risk coefficient of the raw water quality index is a first risk coefficient according to whether the occurrence times of the maximum value is greater than the preset times, if the occurrence times of the maximum value is greater than the preset times, it is determined that the risk coefficient of the raw water quality index is a second risk coefficient if the occurrence times of the maximum value is not greater than the preset times threshold value, the second risk coefficient is less than the first risk coefficient, and both the second risk coefficient and the first risk coefficient are less than 1. For example, the second risk factor may be 0.89, the first risk factor may be 0.92, etc., and the specific values may be set according to different requirements of the water plant, which is not limited herein.
And determining the risk coefficient score of each raw water quality index based on the method, and multiplying the risk coefficients of all the raw water quality indexes to obtain the raw water risk coefficient score. As shown in fig. 13, taking an example in which the raw water quality includes 5 indexes, raw water quality risk coefficient scores E1, E2, E3, E4, and E5 of the 5 indexes are obtained, and a final raw water risk coefficient score is obtained by multiplying the 5 raw water quality risk coefficient scores, i.e., i2=e1×e2×e3×e4×e5.
In order to obtain the influence degree of the water plant integrated management data on the activated carbon monitoring data, specifically, as shown in fig. 14, the embodiment of the invention obtains the water plant integrated management data, determines the adjustment result of the water plant integrated management data on the activated carbon monitoring data according to the water plant integrated management data, and includes:
s310, judging whether historical data in a water plant comprehensive management database is larger than a preset water plant comprehensive management data volume or not;
it should be understood here that, first, it is determined whether the historical data in the water plant integrated management database meets the requirement of the data amount, if so, the water plant integrated management coefficient is determined based on the data, and if not, the data of the water plant integrated management database is constructed until it is satisfied.
S320, if the historical data in the water plant integrated management database is larger than the preset water plant integrated management data amount, determining the water plant integrated management coefficient according to a classification model in the water plant integrated management data, wherein the classification model comprises a personnel quality inspection model, a system guarantee inspection model and a hardware facility inspection model.
In the embodiment of the invention, the personnel quality inspection model specifically can comprise personnel academic information, personnel post training record information, personnel service life information and the like, the system guarantee inspection model specifically can comprise water plant management system information, operation rule information, emergency plan information, carbon pool management file establishment information and the like, and the hardware facility inspection model specifically can comprise facility equipment integrity information, carbon filter operation life information, carbon filter load rate information, carbon filter after-filter on-line instrument arrangement information and the like.
As shown in fig. 15, a water plant integrated management coefficient score I1 is determined according to a classification model, where the integrated management coefficient score I1 may specifically be a product of respective scores of the classification model, that is, if a score obtained by a personnel quality related inspection model through expert review is B1, a score obtained by a system guarantee inspection model through expert review is B2, and a score obtained by a hardware facility inspection model through expert review is B3, the scores of B1, B2 and B3 are normalized, that is, the scores obtained by normalization of B1, B2 and B3 are not greater than 1, so i1=b1×b2×b3.
In an embodiment of the present invention, to determine a water plant activated carbon evaluation level, determining the water plant activated carbon evaluation level by comparing a water plant activated carbon evaluation score with a preset activated carbon evaluation level table includes:
sequentially comparing the water plant activated carbon evaluation scores according to the sequence from high to low of preset activated carbon evaluation grades to determine the water plant activated carbon evaluation grades, wherein the preset activated carbon evaluation grades sequentially comprise: very healthy, sub-healthy, unhealthy and ill.
As shown in fig. 16, the activated carbon evaluation score is set to S here, and the corresponding rank is determined according to the specific score comparison of S. It should be understood that the score level correspondence shown in fig. 16 is an example, and may be specifically set according to actual situations, and is not limited herein.
The following describes the specific implementation process of the water plant biological activated carbon operation condition assessment method provided by the invention by taking the assessment of the health condition of the 4# carbon filter in the XX water plant of 8 months and 1 days of 2023 as an example.
Firstly, carrying out data processing and calculating and determining the weight data of the relevant indexes of the activated carbon according to the historical activated carbon index monitoring data of the water plant.
(1) Generating an activated carbon physical and chemical index weight data table (3 activated carbon physical and chemical indexes are selected as an example)
And (3) accessing a historical active carbon physical and chemical index monitoring database to carry out data examination, firstly judging whether each table in the database has data, and secondly continuously judging whether the number of the data tables is more than or equal to 2. In the example, each table of the database has data, and the number of the data tables is 8, which meets the requirement. Therefore, an activated carbon physical and chemical index weight data table can be generated.
Table 1 historical active carbon physicochemical index monitoring database
The index weight is obtained through calculation by an entropy method, and the specific calculation method of the entropy method is as follows:
1) Normalizing the indexes, and calculating the ratio R of the jth index value of the ith sample ij ：
2) Calculating entropy value H of jth index j ：
3) Calculating the difference coefficient G of the j-th index j ：
G j ＝1-H j ，j＝1,2,…,m
4) Calculating the weight K of each index j :
Wherein R is ij Representing the proportion of the index value of the ith sample to the total index value; p (P) ij Representing a specific value of a j index of an i sample; h j Entropy value representing the j-th index; g j A difference coefficient indicating a j-th index; k (K) j Refers to the weights of j indices.
Table 2 weight results table
Thus, the weight ratios of intensity, iodine value, methylene blue value were calculated as: k1 An activated carbon physicochemical index weight data table was generated, with =1.62%, k2= 86.97%, k3=11.41%.
Table 3 activated carbon physical and chemical index weight data table
| Index name | Weight duty cycle |
| Strength of | K1＝1.62％ |
| Iodine value | K2＝86.97％ |
| Methylene blue value | K3＝11.41％ |
(2) Generating an activated carbon biological index weight data table (3 activated carbon biological indexes are selected as an example)
And (3) accessing a historical active carbon biological index monitoring database to carry out data examination, firstly judging whether each table in the database has data, and secondly continuously judging whether the number of the data tables is more than or equal to 2. In the example, each table of the database has data, and the number of the data tables is 8, which meets the requirement. Thus, an activated carbon biological index weight data table can be generated.
TABLE 4 historical activated carbon biological index monitoring data sheet
The weight ratio of the biomass, the bioactivity and the simpson index is calculated by a principal component analysis method and is respectively as follows: k9 An activated carbon biological index weight data table was generated with = 34.90%, k10=32.39%, k11=32.71%. The main component analysis method comprises the following calculation processes:
1) Test of KMO and Bartlett
Table 5KMO and Bartlett checklist
2) Calculating variance interpretation rate
TABLE 6 variance interpretation rate table
3) Calculating the load coefficient of each index
TABLE 7 load coefficient table
4) Calculating the weight of each index
Table 8 linear combination coefficients and weight results
TABLE 9 activated carbon biological indicator weight data sheet
| Index name | Weight duty cycle |
| Biomass mass | K9＝34.90％ |
| Biological activity | K10＝32.39％ |
| Simpson index | K11＝32.71％ |
(3) Generating a weight data table of the effluent quality indexes of the carbon filter (3 carbon filter effluent quality indexes are selected as an example)
And (3) calling a historical carbon filter effluent water quality index monitoring database, and carrying out data examination, firstly judging whether each table in the database has data, and secondly, continuously judging whether the number of the data tables is more than or equal to 2. In the example, each table of the database has data, and the number of the data tables is 8, which meets the requirement. Therefore, a water quality index weight data table of the effluent of the carbon filter can be generated.
Table 10 historical carbon filter effluent quality index monitoring database
The index weight is obtained through calculation by an entropy method, and the specific calculation method is as follows:
normalizing the indexes, and calculating the ratio R of the jth index value of the ith sample ij ：
Calculating entropy value H of jth index j ：
Calculate item jCoefficient of difference G of index j ：
G j ＝1-H j ，j＝1,2,…,m
Calculating the weight K of each index j :
Wherein R is ij Representing the proportion of the jth index value of the ith sample to the total index value; p (P) ij A specific value representing the j index of the i sample; h j Entropy value representing the j-th index; g j A difference coefficient indicating a j-th index; k (K) j The weight of the j-th index is represented.
Table 11 entropy method calculation weight result table
| Index (I) | Entropy value H | Coefficient of difference G | Weight coefficient K |
| Permanganate index | 0.9970 | 0.0030 | 12.80％ |
| Ammonia nitrogen | 0.9837 | 0.0163 | 68.82％ |
| TOC | 0.9956 | 0.0044 | 18.38％ |
The weight ratios of permanganate index, ammonia nitrogen and TOC calculated from the method are respectively as follows: k15 12.80%, k16= 68.82% and k17=18.38% to generate a carbon filter effluent water quality index weight data table.
Table 12 carbon filter outlet water quality index weight data table
| Index name | Weight duty cycle |
| Permanganate index | K15＝12.80％ |
| Ammonia nitrogen | K16＝68.82％ |
| TOC | K17＝18.38％ |
And secondly, carrying out data cleaning and judging treatment according to the real-time evaluation result of the physical and chemical indexes of the activated carbon, the real-time evaluation result of the biological indexes of the activated carbon and the real-time evaluation result of the water quality indexes of the effluent of the carbon filter, so as to obtain the corresponding scores of the physical and chemical indexes of the activated carbon, the corresponding scores of the biological indexes of the activated carbon and the corresponding scores of the water quality indexes of the effluent of the carbon filter.
(1) Generating score data of physical and chemical indexes of active carbon
And (3) taking the latest data table in the historical active carbon physical and chemical index monitoring database as an active carbon physical and chemical index evaluation data table, performing data examination, and firstly judging whether missing value data exists in the data table. In the example, the data table has no missing data, and meets the requirements. Therefore, an activated carbon physical and chemical index evaluation data table can be generated.
TABLE 13 evaluation data sheet of physical and chemical indicators of activated carbon
Therefore, the calculation process of the score A1 of the intensity index in the physical and chemical indexes of the activated carbon comprises the following steps: here, the maximum threshold A1max of A1 may be set to 98%, the minimum threshold A1min of A1 may be set to 91%, and the system judges that 92% of the intensity detection value is between A1max and A1min, so a1= (92% -A1 min)/(A1 max-A1 min) = (92-91)/(98-91) =0.14;
the calculation process of the score A2 of the iodine value index in the physical and chemical indexes of the activated carbon comprises the following steps: here, the maximum threshold A2max of A2 may be set to 800mg/g, the minimum threshold A2min of A2 may be set to 150mg/g, and the system judges that the iodine value detection value 720mg/g is between A2max and A2min, so a2= (720 mg/g-A2 min)/(A2 max-A2 min) = (720-150)/(800-150) =0.88;
the score A3 of the methylene blue index in the physicochemical indexes of the activated carbon is calculated by the following steps: here, the maximum threshold A3max of A3 may be set to 200mg/g, the minimum threshold A3min of A3 may be set to 100mg/g, and the system judges that the detection value of the methylene blue value is 135mg/g between A3max and A3min, so a3= (135 mg/g-A3 min)/(A3 max-A3 min) = (135-100)/(200-100) =0.35;
in summary, the scores for intensity, iodine value, and methylene blue value were calculated as: a1 An activated carbon physicochemical index score data table was generated with=0.14, a2=0.88, a3=0.35.
TABLE 14 data sheet of physical and chemical index score of active carbon
| Index name | Score of |
| Strength of | A1＝0.14 |
| Iodine value | A2＝0.88 |
| Methylene blue value | A3＝0.35 |
(2) Generating an activated carbon biological index score data table
And taking the latest data table in the historical activated carbon biological index monitoring database as an activated carbon biological index evaluation data table, performing data examination, and firstly judging whether missing value data exists in the data table. In the example, the data table has no missing data, and meets the requirements. Thus, an activated carbon biological index evaluation data table can be generated.
Table 15 activated carbon biological index evaluation data sheet
The calculation process of the score A9 of the biomass in the activated carbon biological index comprises the following steps: here, the maximum threshold A9max of A9 may be set to 200nmol p/gcac, the minimum threshold A9min of A9 may be set to 50nmol p/gcac, and the system judges that the biomass detection value 170nmol p/gcac is between A9max and A9min, so a9= (170 nmol p/gcac-A9 min)/(A9 max-A9 min) = (170-50)/(200-50) =0.8;
the calculation process of the score A10 of the biological activity in the activated carbon biological index comprises the following steps: here, the maximum threshold a10max of a10 may be set to 0.1mg/gbac·h, the minimum threshold a10min of a10 may be set to 0.05mg/gbac·h, and the system judges that the biological activity detection value 0.2mg/gbac·h is higher than A2max, so a10=1;
The score A11 of the simpson index in the activated carbon biological index is calculated by the following steps: here, the maximum threshold a11max of a11 may be set to 1.2, the minimum threshold a11min of a11 may be set to 0.6, and the system judges that the simpson index detection value 1.7 is higher than A3max, so a11=1;
in summary, scores for biomass, bioactivity, and simpson index were calculated as: a9 An activated carbon biomarker score data table was generated with =0.8, a10=1, a11=1.
TABLE 16 activated carbon biological index score data sheet
| Index name | Score of |
| Biomass mass | A9＝0.8 |
| Biological activity | A10＝1 |
| Simpson index | A11＝1 |
(3) Yielding carbon filter effluent quality index score data table
And calling the latest data table in the carbon filter outlet water quality index monitoring database as a carbon filter outlet water quality index evaluation data table, performing data examination, and firstly judging whether missing value data exists in the data table. In the example, the data table has no missing data, and meets the requirements. Therefore, a carbon filter effluent quality index evaluation data table can be generated.
Table 17 carbon filter outlet water quality index evaluation data table
The calculation process of the score A15 of the permanganate index in the effluent quality index of the carbon filter tank comprises the following steps: here, the maximum threshold a15max of a15 may be set to 30%, the minimum threshold a15min of a15 may be set to 15%, and the system judges that 28% of the detection value of the permanganate index removal is between a15max and a15min, so a15= (28% -a15 min)/(a 15max-a15 min) = (28-15)/(30-15) =0.87;
The calculation process of the score A16 of ammonia nitrogen in the effluent quality index of the carbon filter tank comprises the following steps: here, the maximum threshold a16max of a16 may be set to 80%, the minimum threshold a16min of a16 may be set to 40%, and the system judges that the detection value of the ammonia nitrogen removal rate is 100% higher than a16max, so a16=1;
the score A17 of TOC in the effluent quality index of the carbon filter is calculated by the following steps: here, the maximum threshold a17max of a17 may be set to 30%, the minimum threshold a17min of a17 may be set to 18%, and the system determines that the detected value of the TOC removal rate 28% is between a17max and the minimum threshold a17min of a17, so a17= (28% -a17 min)/(a 17max-a17 min) = (28-18)/(30-18) =0.83;
in summary, the scores of permanganate index, ammonia nitrogen and TOC are calculated as follows: a15 The carbon filter outlet water quality index evaluation data table is generated by the following steps of (1) 0.87, a16=1 and a17=0.83.
Table 18 carbon filter outlet water quality index evaluation data table
| Index name | Score of |
| Permanganate index | A15＝0.87 |
| Ammonia nitrogen | A16＝1 |
| TOC | A17＝0.83 |
Thirdly, calculating and determining current activated carbon physical and chemical index monitoring data according to the activated carbon physical and chemical index weight data and the activated carbon physical and chemical index corresponding score, calculating and determining current activated carbon biochemical index monitoring data according to the activated carbon biological index weight data and the activated carbon biological index corresponding score, and calculating and determining current carbon filter outlet water quality index monitoring data according to the carbon filter outlet water quality index weight data and the carbon filter outlet water quality index corresponding score.
Specifically, the physical and chemical indexes of the activated carbon, the biological indexes of the activated carbon and the water quality indexes of the effluent of the carbon filter are first-level indexes, and the weight ratio of the first-level indexes is calculated by using a hierarchical analysis method aiming at the 3 first-level indexes capable of being quantitatively analyzed. The main process is as follows:
and comparing the importance of the three primary indexes of the physical and chemical indexes of the activated carbon, the biological indexes of the activated carbon and the water quality indexes of the effluent of the carbon filter tank with the importance of each index in pairs, scoring, finishing the results to obtain a judgment matrix, carrying out consistency test, continuously readjusting the score until CR is less than 0.1, and then determining the weight of an index system.
And judging the relative importance of every two elements, wherein a 1-9 scale method is selected, namely when 1, 3, 5, 7 and 9 respectively represent 2 elements to be compared, one element is as important, slightly important, obviously important, strongly important and extremely important as the other element, and the known importance meaning is shown in a table 19. According to the same importance of Xi element and Xj element, the Xi is slightly important than Xj element, the Xi is obviously important than Xj element, the Xi is very important than Xj element, the Xi is extremely important than Xj element, the reciprocal of these values is used to represent the unimportance degree of Xi and Xj element, and a judging matrix is established.
TABLE 19 significance level meaning Table
| Scale with a scale bar | Meaning of |
| 1 | Equally important |
| 3 | Slightly important |
| 5 | Is obviously important |
| 7 | Is of great importance |
| 9 | Extremely important |
| 2，4，6，8 | Median of the two adjacent judgments |
| Reciprocal count | A and B are compared if the scale is 3, then B and A are 1/3 |
The calculation formula for judging the consistency of the matrix is as follows:
CR＝CI/RI＝(λ max -n)/[(n-1)×RI]，
wherein n represents the order of the judgment matrix; CR represents a consistency ratio; CI represents a consistency index; RI represents a random consistency index; λmax represents the maximum eigenvalue. And (3) solving a matrix maximum eigenvalue lambda max and a weight value thereof, carrying out consistency test until CR is smaller than 0.1, indicating that all the judgment matrixes pass the consistency test, otherwise, readjusting the judgment matrixes until the judgment matrixes pass the consistency test, and then determining the weight of the index system.
Table 20 determination matrix of intermediate layer index and consistency test result
Therefore, the weight ratio of the physical and chemical indexes of the activated carbon is 40, the weight ratio of the biological indexes of the activated carbon is 20, and the weight ratio of the water quality indexes of the effluent of the carbon filter is 40.
And calling the weight database and the score database to generate the activated carbon monitoring data V.
V＝(A1*K1+A2*K2+A3*K3)*40+(A9*K9+A10*K10+A11*K11)*20+(A15*K15+A16*K16+A17*K17)*40
＝(0.14*1.62％+0.88*86.97％+0.45*11.41％)*40+(0.8*34.90％+1*32.39％+1*32.71％)*20+(0.87*12.80％+1*68.82％+0.83*18.38％)*40＝89.45。
Fourth, a raw water risk factor I1 is calculated (1 raw water quality index is selected as an example).
And calling a raw water quality database, performing data examination, and firstly judging whether historical data in the database are sufficient or not, wherein examples meet requirements. A raw water risk factor can thus be generated.
TABLE 21 raw water quality history data table
| Date of day | Permanganate index (mg/L) |
| 2023, 5, 1 | 3.86 |
| 2023, 5 and 2 days | 2.9 |
| 2023 5 month 3 day | 3.75 |
| 2023, 5 and 4 days | 4.08 |
| 2023, 5 and 5 days | 4.21 |
| 2023, 5 and 6 days | 4.32 |
| 2023, 5 and 7 days | 3.78 |
| 2023, 5, 8 | 3.95 |
| 2023, 5 and 9 days | 3.28 |
Judging whether the maximum value of the permanganate index in the raw water quality database is smaller than or equal to the maximum threshold value of the permanganate index, wherein the maximum threshold value of the permanganate index is set to be 5.5mg/L, and the maximum value in the example is 4.32mg/L and smaller than 5.5mg/L, so E1=1, and indicating that the raw water quality does not have a larger risk at present.
Fifth, calculate the water works comprehensive management coefficient I2 (each module selects one as an example).
And (5) calling a water plant comprehensive management database, determining the quality of personnel, hardware facilities and system guarantee of the main classification module, and generating a water plant comprehensive management coefficient according to the inspection model.
Table 22 water works comprehensive management history data table
Therefore, the water plant integrated management coefficient i2=1×1×1=1.
Finally, an activated carbon health assessment score S is calculated.
And (3) the activated carbon monitoring data V, the raw water risk coefficient I1 and the water plant comprehensive management coefficient I2 are called to generate a 4# carbon filter tank activated carbon health condition evaluation score S of the water plant XX 1 day of 8 months of 2023.
S=vi1×i2=89.45×1×1= 89.45 minutes.
The final output result is: the evaluation score of the health condition of the 4# charcoal filter of the XX water works on 1 day of 8 of 2023 is 89.45, and the health grade is very healthy.
In conclusion, the method for evaluating the running state of the biological activated carbon in the water plant can combine the quantitative index with the qualitative index, and the running state evaluation index of the activated carbon has wider coverage and is more systematic and comprehensive; because the weight analysis algorithm of the evaluation index has logic, representativeness and pertinence, the weight ratio of each index can be updated according to the actual conditions of different water plants according to reasonable basis, so that the evaluation method is objective and fair, the evaluation method is suitable for different water plants, and the obtained evaluation score is more fit with the actual conditions of different water plants; the evaluation process selects two coefficients as positive component and negative component of the deviation correcting activated carbon evaluation score, and as the raw water quality of each place is different, the characteristic pollutants presented by different water sources are different, and the risk condition of the raw water quality can have a certain influence on the biological activated carbon treatment process of the water plant, the raw water risk coefficient is selected as the parallel coefficient or the negative coefficient of the activated carbon evaluation score; the comprehensive management coefficient of the water plant has more evaluation dimension, and the running condition of the activated carbon can have positive influence on the water plant with refined management, so the comprehensive management coefficient of the water plant is selected as the positive coefficient, the parallel coefficient or the negative coefficient of the evaluation score of the activated carbon. And finally, the evaluation result is an evaluation score and a health grade, the operation condition of the activated carbon is more intuitively reflected by the digital display, and the change trend of the treatment efficiency of the activated carbon is revealed at the same time so as to guide the process adjustment of a water plant. In summary, the method for evaluating the running condition of the biological activated carbon in the water plant has the advantages of simple operation of an evaluation program and strong operability, is convenient to effectively implement and apply in the water plant, and is used as a part of daily running maintenance management of the water plant.
As another embodiment of the present invention, there is provided a water plant bioactive carbon operation condition evaluation device, including:
the active carbon monitoring data determining module is used for dynamically calculating and determining the current active carbon monitoring data result according to the historical active carbon index monitoring data of the water plant and the real-time evaluation result of the active carbon index of the water plant, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises an active carbon physical and chemical index real-time evaluation result, an active carbon biological index real-time evaluation result and a carbon filter outlet water quality index real-time evaluation result;
the raw water quality influence module is used for acquiring raw water quality data and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
the water plant comprehensive management data influence module is used for acquiring water plant comprehensive management data and determining an adjustment result of the water plant comprehensive management data on the activated carbon monitoring data according to the water plant comprehensive management data;
the evaluation score determining module is used for comprehensively calculating the adjustment result of the activated carbon monitoring data according to the current activated carbon monitoring data result, the raw water quality data and the water plant comprehensive management data to determine the water plant activated carbon evaluation score;
The evaluation grade determining module is used for determining the evaluation grade of the activated carbon of the water plant by comparing the evaluation score of the activated carbon of the water plant with a preset activated carbon evaluation grade table;
and the output module is used for outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
The working principle and process of the device for evaluating the running condition of the biological activated carbon of the water plant provided by the invention can refer to the description of the method for evaluating the running condition of the biological activated carbon of the water plant, and the description is omitted herein.
As another embodiment of the present invention, there is provided a water plant bioactive carbon operation condition evaluation system, wherein, as shown in fig. 17, comprising: the water plant historical activated carbon index monitoring database 10, the raw water quality database 20, the water plant comprehensive management database 30 and the water plant biological activated carbon running condition assessment device 40 are all in communication connection with the water plant biological activated carbon running condition assessment device 40.
As shown in fig. 17, in the embodiment of the present invention, an activated carbon physicochemical index weight data table, an activated carbon biological weight data table, and a carbon filter outlet water quality index weight data table can be obtained based on the water plant history activated carbon index monitoring database 10, and these weight data tables can be stored in the weight database, whereas an activated carbon physicochemical index evaluation data table, an activated carbon biological index evaluation data table, and a carbon filter outlet water quality evaluation data table (these data tables are the latest data in the history monitoring database) can be obtained based on the water plant history activated carbon index monitoring database 10, and according to these evaluation data tables, an activated carbon physicochemical index score, an activated carbon biological index score, and a carbon filter outlet water quality index score can be stored in the score database.
The current activated carbon monitoring data result can be obtained based on the weight data in the weight database and the score data in the score database.
And determining a raw water risk coefficient according to the raw water quality database, determining a water plant comprehensive management coefficient according to the water plant comprehensive management database, and finally determining a water plant activated carbon evaluation score based on the current activated carbon monitoring data result, the raw water risk coefficient and the water plant comprehensive management coefficient, thereby determining an evaluation grade.
The working process and principle of the system for evaluating the running condition of the biological activated carbon of the water plant provided by the invention can refer to the description of the method for evaluating the running condition of the biological activated carbon of the water plant, and the description is omitted herein.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (10)
1. A method for evaluating the operation condition of biological activated carbon in a water plant, which is characterized by comprising the following steps:
Carrying out dynamic calculation according to historical active carbon index monitoring data of a water plant and a real-time evaluation result of the active carbon index of the water plant to determine the result of the current active carbon monitoring data, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises real-time evaluation result of the active carbon physical and chemical index, real-time evaluation result of the active carbon biological index and real-time evaluation result of the active carbon filter outlet water quality index;
acquiring raw water quality data, and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
acquiring water plant comprehensive management data, and determining an adjustment result of the water plant comprehensive management data on activated carbon monitoring data according to the water plant comprehensive management data;
according to the current activated carbon monitoring data result, the raw water quality data and the adjustment result of the activated carbon monitoring data, the water plant comprehensive management data comprehensively calculates the adjustment result of the activated carbon monitoring data to determine the water plant activated carbon evaluation score;
comparing the water plant activated carbon evaluation score with a preset activated carbon evaluation grade table to determine a water plant activated carbon evaluation grade;
Outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
2. The method for evaluating the running condition of biological activated carbon in a water plant according to claim 1, wherein the step of dynamically calculating and determining the current activated carbon monitoring data result according to the historical activated carbon index monitoring data in the water plant and the real-time evaluation result of the activated carbon index in the water plant comprises the following steps:
performing data processing and calculating and determining the weight data of the relevant indexes of the activated carbon according to the historical activated carbon index monitoring data of the water plant;
and calculating and determining the current activated carbon monitoring data result according to the activated carbon related index weight data and the real-time evaluation result of the activated carbon index of the water plant.
3. The method for evaluating the operation condition of biological activated carbon in water plants according to claim 2, wherein the data processing and the calculation of the weight data of the relevant index of activated carbon are performed according to the historical monitoring data of the index of activated carbon in water plants, comprising:
respectively judging and processing the data integrity of the historical active carbon physical and chemical index monitoring data, the historical active carbon biological index monitoring data and the historical active carbon filter outlet water quality index monitoring data to obtain corresponding active carbon physical and chemical index processing data, active carbon biological index processing data and carbon filter outlet water quality processing data;
And respectively calculating the ratio of the physical and chemical indexes of the activated carbon in the activated carbon physical and chemical index treatment data, the ratio of the biological indexes of the activated carbon in the activated carbon biological index treatment data and the ratio of the water quality index of the effluent of the carbon filter in the water quality treatment data of the effluent of the carbon filter according to a weight calculation algorithm, and determining the weight data of the physical and chemical indexes of the activated carbon, the weight data of the biological indexes of the activated carbon and the weight data of the water quality index of the effluent of the carbon filter, wherein the weight calculation algorithm at least comprises an entropy method and/or a principal component analysis method.
4. The method for evaluating the running condition of the biological activated carbon of the water plant according to claim 3, wherein the step of calculating and determining the current activated carbon monitoring data result according to the activated carbon related index weight data and the real-time evaluation result of the activated carbon index of the water plant comprises the following steps:
respectively carrying out data cleaning and judging treatment according to the real-time evaluation result of the physical and chemical indexes of the activated carbon, the real-time evaluation result of the biological indexes of the activated carbon and the real-time evaluation result of the water quality indexes of the effluent of the carbon filter, and obtaining the corresponding scores of the physical and chemical indexes of the activated carbon, the corresponding scores of the biological indexes of the activated carbon and the corresponding scores of the water quality indexes of the effluent of the carbon filter;
and calculating and determining current activated carbon physical and chemical index monitoring data according to the activated carbon physical and chemical index weight data and the activated carbon physical and chemical index corresponding score, calculating and determining current activated carbon biochemical index monitoring data according to the activated carbon biological index weight data and the activated carbon biological index corresponding score, and calculating and determining current carbon filter outlet water quality index monitoring data according to the carbon filter outlet water quality index weight data and the carbon filter outlet water quality index corresponding score.
5. The method for evaluating the operation condition of biological activated carbon in a water plant according to any one of claims 1 to 4, wherein acquiring raw water quality data and determining the result of adjusting the activated carbon monitoring data from the raw water quality data comprises:
judging whether historical data in the raw water quality database meets the requirement of being larger than the preset raw water quality data quantity or not;
if the historical data in the raw water quality database is larger than the preset raw water quality data quantity, calculating a risk coefficient according to the historical data in the raw water quality database to obtain a raw water risk coefficient.
6. The method for evaluating the operation condition of biological activated carbon in water plant according to claim 5, wherein the step of calculating the risk coefficient according to the historical data in the raw water quality database to obtain the raw water quality risk coefficient comprises the steps of:
judging whether the maximum value of each raw water quality index in the raw water quality database is smaller than or equal to a preset maximum threshold value corresponding to the index;
if the maximum value of the current raw water quality index in the raw water quality database is smaller than or equal to the preset maximum threshold value corresponding to the index, determining the risk coefficient of the raw water quality index to be 1, and outputting the risk coefficient of the raw water quality index;
If the maximum value of the current raw water quality index in the raw water quality database is larger than the preset maximum threshold corresponding to the index, judging whether the occurrence frequency of the maximum value of the current raw water quality index is larger than the preset frequency threshold;
if the occurrence frequency of the maximum value of the current raw water quality index is greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a first risk coefficient, wherein the first risk coefficient is smaller than 1;
if the occurrence frequency of the maximum value of the current raw water quality index is not greater than a preset frequency threshold, determining the risk coefficient of the raw water quality index as a second risk coefficient, wherein the second risk coefficient is smaller than 1, and the second risk coefficient is smaller than the first risk coefficient;
and determining the raw water risk coefficient according to the multiplication result of the risk coefficient of each raw water quality index in the raw water substance database.
7. The method for evaluating the operation condition of biological activated carbon in a water plant according to any one of claims 1 to 4, wherein acquiring water plant integrated management data and determining the result of adjusting activated carbon monitoring data by the water plant integrated management data based on the water plant integrated management data comprises:
judging whether historical data in a water plant comprehensive management database is larger than a preset water plant comprehensive management data volume or not;
If the historical data in the water plant comprehensive management database is larger than the preset water plant comprehensive management data amount, determining the water plant comprehensive management coefficient according to a classification model in the water plant comprehensive management data, wherein the classification model comprises a personnel quality inspection model, a system guarantee inspection model and a hardware facility inspection model.
8. The water mill bioactive carbon operating condition evaluation method as claimed in any one of claims 1 to 4, wherein the determining the water mill bioactive carbon evaluation level based on the water mill bioactive carbon evaluation score and the preset activated carbon evaluation level table comprises:
sequentially comparing the water plant activated carbon evaluation scores according to the sequence from high to low of preset activated carbon evaluation grades to determine the water plant activated carbon evaluation grades, wherein the preset activated carbon evaluation grades sequentially comprise: very healthy, sub-healthy, unhealthy and ill.
9. A water mill bioactive carbon operating condition evaluation device for implementing the water mill bioactive carbon operating condition evaluation method of any one of claims 1 to 8, characterized by comprising:
the active carbon monitoring data determining module is used for dynamically calculating and determining the current active carbon monitoring data result according to the historical active carbon index monitoring data of the water plant and the real-time evaluation result of the active carbon index of the water plant, wherein the historical active carbon index monitoring data of the water plant comprises historical active carbon physical and chemical index monitoring data, historical active carbon biological index monitoring data and historical active carbon filter outlet water quality index monitoring data, and the real-time evaluation result of the active carbon index of the water plant comprises an active carbon physical and chemical index real-time evaluation result, an active carbon biological index real-time evaluation result and a carbon filter outlet water quality index real-time evaluation result;
The raw water quality influence module is used for acquiring raw water quality data and determining an adjustment result of the raw water quality data on the activated carbon monitoring data according to the raw water quality data;
the water plant comprehensive management data influence module is used for acquiring water plant comprehensive management data and determining an adjustment result of the water plant comprehensive management data on the activated carbon monitoring data according to the water plant comprehensive management data;
the evaluation score determining module is used for comprehensively calculating the adjustment result of the activated carbon monitoring data according to the current activated carbon monitoring data result, the raw water quality data and the water plant comprehensive management data to determine the water plant activated carbon evaluation score;
the evaluation grade determining module is used for determining the evaluation grade of the activated carbon of the water plant by comparing the evaluation score of the activated carbon of the water plant with a preset activated carbon evaluation grade table;
and the output module is used for outputting the water plant activated carbon evaluation score and the water plant activated carbon evaluation grade.
10. A water mill bioactive carbon operating condition assessment system, comprising: the water plant historical activated carbon index monitoring database, the raw water quality database, the water plant comprehensive management database and the water plant biological activated carbon operation condition assessment device according to claim 9 are all in communication connection with the water plant biological activated carbon operation condition assessment device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311575700.9A CN117557099B (en) | 2023-11-23 | 2023-11-23 | Method, device and system for evaluating running condition of biological activated carbon in water plant |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311575700.9A CN117557099B (en) | 2023-11-23 | 2023-11-23 | Method, device and system for evaluating running condition of biological activated carbon in water plant |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117557099A true CN117557099A (en) | 2024-02-13 |
| CN117557099B CN117557099B (en) | 2024-08-06 |
Family
ID=89812366
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311575700.9A Active CN117557099B (en) | 2023-11-23 | 2023-11-23 | Method, device and system for evaluating running condition of biological activated carbon in water plant |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117557099B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101088923A (en) * | 2006-06-12 | 2007-12-19 | 株式会社日立制作所 | Managing system of water processing establishment |
| KR20110023055A (en) * | 2009-08-28 | 2011-03-08 | (주)이엠엔씨코리아 | Activated carbon adsorption column for water treatment having sampler of active carbon particles |
| CN104361418A (en) * | 2014-12-05 | 2015-02-18 | 北京师范大学 | Watershed water ecological security monitoring pre-warning platform and watershed water ecological security monitoring pre-warning method |
| CN104761018A (en) * | 2014-01-03 | 2015-07-08 | 清华大学 | Method for carrying out water treatment by using active carbon |
| CN108226400A (en) * | 2018-01-24 | 2018-06-29 | 上海华严检测技术有限公司 | A kind of biological activated carbon filter runs appraisal procedure |
| CN108918354A (en) * | 2018-06-13 | 2018-11-30 | 同济大学 | A kind of method of preferred active carbon |
| JP2019152602A (en) * | 2018-03-06 | 2019-09-12 | オルガノ株式会社 | Method for evaluating contamination risk of water treatment system |
| WO2022099852A1 (en) * | 2020-11-10 | 2022-05-19 | 广东粤海水务股份有限公司 | Health evaluation and diagnosis method for urban landscape lake water ecosystem |
| CN115577018A (en) * | 2022-12-01 | 2023-01-06 | 北京华科仪科技股份有限公司 | Intelligent processing method and system for water quality monitoring data |
| CN115718181A (en) * | 2022-10-21 | 2023-02-28 | 上海城市水资源开发利用国家工程中心有限公司 | Method for evaluating effect of drinking water raw water powder activated carbon adsorption CODMn |
| CN116777201A (en) * | 2023-05-22 | 2023-09-19 | 河海大学 | River type water source site risk comprehensive assessment prediction method, system and electronic equipment |
-
2023
- 2023-11-23 CN CN202311575700.9A patent/CN117557099B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101088923A (en) * | 2006-06-12 | 2007-12-19 | 株式会社日立制作所 | Managing system of water processing establishment |
| KR20110023055A (en) * | 2009-08-28 | 2011-03-08 | (주)이엠엔씨코리아 | Activated carbon adsorption column for water treatment having sampler of active carbon particles |
| CN104761018A (en) * | 2014-01-03 | 2015-07-08 | 清华大学 | Method for carrying out water treatment by using active carbon |
| CN104361418A (en) * | 2014-12-05 | 2015-02-18 | 北京师范大学 | Watershed water ecological security monitoring pre-warning platform and watershed water ecological security monitoring pre-warning method |
| CN108226400A (en) * | 2018-01-24 | 2018-06-29 | 上海华严检测技术有限公司 | A kind of biological activated carbon filter runs appraisal procedure |
| JP2019152602A (en) * | 2018-03-06 | 2019-09-12 | オルガノ株式会社 | Method for evaluating contamination risk of water treatment system |
| CN108918354A (en) * | 2018-06-13 | 2018-11-30 | 同济大学 | A kind of method of preferred active carbon |
| WO2022099852A1 (en) * | 2020-11-10 | 2022-05-19 | 广东粤海水务股份有限公司 | Health evaluation and diagnosis method for urban landscape lake water ecosystem |
| CN115718181A (en) * | 2022-10-21 | 2023-02-28 | 上海城市水资源开发利用国家工程中心有限公司 | Method for evaluating effect of drinking water raw water powder activated carbon adsorption CODMn |
| CN115577018A (en) * | 2022-12-01 | 2023-01-06 | 北京华科仪科技股份有限公司 | Intelligent processing method and system for water quality monitoring data |
| CN116777201A (en) * | 2023-05-22 | 2023-09-19 | 河海大学 | River type water source site risk comprehensive assessment prediction method, system and electronic equipment |
Non-Patent Citations (3)
| Title |
|---|
| 张慧;吴超;何欢;周红中;段友丽;: "生物活性炭运行监测技术与应用实践", 净水技术, vol. 36, no. 03, 26 May 2017 (2017-05-26), pages 8 - 16 * |
| 笪跃武: "水厂O3-BAC深度处理工艺系统的运行管理", 中国给水排水, vol. 29, no. 18, 30 September 2013 (2013-09-30), pages 48 - 55 * |
| 黄美心: "城镇供水厂臭氧活性炭工艺运行管理技术评估研究", 中国优秀硕士学位论文全文数据库 工程科技II辑, 30 April 2022 (2022-04-30), pages 4 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117557099B (en) | 2024-08-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Klarner | The measurement of the partisan balance of state government | |
| McDonald | Measuring the fiscal health of municipalities | |
| CN110648026A (en) | Prediction model construction method, prediction method, device, equipment and medium | |
| CN106940833A (en) | A kind of power grid enterprises' sale of electricity side methods of risk assessment based on fuzzy number and improved AHP method | |
| CN112381476A (en) | Method and device for determining electric energy meter with abnormal state | |
| CN107146009A (en) | A kind of water supply network running status appraisal procedure | |
| CN111882198A (en) | Project performance evaluation method and system | |
| CN109657962A (en) | A kind of appraisal procedure and system of the volume assets of brand | |
| CN114354783A (en) | Health degree evaluation method of extra-high voltage oil chromatography monitoring device based on-operation data | |
| CN111598387A (en) | Method and system for determining quality of electric energy meter in multiple dimensions | |
| CN110516890B (en) | Crop yield monitoring system based on gray combined model | |
| CN117557099B (en) | Method, device and system for evaluating running condition of biological activated carbon in water plant | |
| CN114037202A (en) | Multi-index-associated river water quality evaluation method, system, equipment and storage medium | |
| CN105894138A (en) | Optimum weighted composite prediction method for shipment amount of manufacturing industry | |
| Dritsakis et al. | Cointegration analysis of tourism revenues by the member countries of European Union to Greece | |
| CN115545489A (en) | Public resource transaction platform service quality evaluation method based on AHP-fuzzy comprehensive evaluation | |
| CN113722195B (en) | Local area network operation evaluation system and method based on AHP hierarchical analysis method | |
| Mitroshin et al. | Rating analysis of socioeconomic status of the districts of Moscow Region | |
| CN109214598A (en) | Batch ranking method based on K-MEANS and ARIMA model prediction residential quarters collateral risk | |
| CN114418410A (en) | Army main battle sub-unit equipment combat effectiveness evaluation analysis method | |
| Feruś | The DEA method in managing the credit risk of companies | |
| CN113537759A (en) | User experience measurement model based on weight self-adaptation | |
| Ningrum et al. | The Influence Of Financial Factors And Local Government Characteristics On Financial Distress | |
| Erol | The determinants of food inflation in Turkey | |
| Wojtasiak-Terech et al. | Assessing financial condition of municipalities using taxonomic methods |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |