WO2014157750A1 - Appareil et procédé permettant de fournir des facteurs de causalité concernant la qualité des effluents dans une station d'épuration des eaux usées - Google Patents

Appareil et procédé permettant de fournir des facteurs de causalité concernant la qualité des effluents dans une station d'épuration des eaux usées Download PDF

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WO2014157750A1
WO2014157750A1 PCT/KR2013/002573 KR2013002573W WO2014157750A1 WO 2014157750 A1 WO2014157750 A1 WO 2014157750A1 KR 2013002573 W KR2013002573 W KR 2013002573W WO 2014157750 A1 WO2014157750 A1 WO 2014157750A1
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data
sewage treatment
quality
treatment plant
water quality
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PCT/KR2013/002573
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English (en)
Korean (ko)
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김창원
김예진
김효수
김민수
이승훈
박문화
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부산대학교 산학협력단
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Publication of WO2014157750A1 publication Critical patent/WO2014157750A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F11/00—Treatment of sludge; Devices therefor
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/001—Upstream control, i.e. monitoring for predictive control
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/003—Downstream control, i.e. outlet monitoring, e.g. to check the treating agents, such as halogens or ozone, leaving the process
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/005—Processes using a programmable logic controller [PLC]
    • C02F2209/006—Processes using a programmable logic controller [PLC] comprising a software program or a logic diagram
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/40—Liquid flow rate

Definitions

  • the present invention relates to an apparatus and method for providing causal factors for the condition of effluent quality.
  • the effluent quality of the sewage treatment plant is an external cause including fluctuations in the flow rate and properties of the influent and changes in environmental factors such as temperature and rainfall, and in response to the driver's ability to maintain the effluent quality in a stable manner.
  • the present invention relates to an apparatus and method for providing a causal factor for the condition of the sewage treatment plant effluent quality which can extract the type and pattern from the data to find out the cause of the effluent quality present and provide it to the driver.
  • Biological sewage treatment facility is a process to remove organic matter, nitrogen and phosphorus, which are included in influent, by activated sludge.
  • the performance of the process is changed every hour. Corresponds to the concentration, it is determined by the operation for changing and maintaining the driving conditions efficiently taken by the driver.
  • the process operator decides and executes these actions based on the know-how existing in the driver's empirical knowledge. In this case, the knowledge of which run variables are modified to keep the process stable in the case of any water quality situation is very subjective. Subsequently, even if it is intended to be extracted through interviews or literature studies, it is not easily objectified, and thus it is difficult to extract into visualized documents or intangible rules.
  • the process of determining what effluent quality is in the process and the process of searching for the cause of the effluent are called sewage treatment process diagnosis.
  • the runoff quality of the process is the result of a combination of external factors such as fluctuations in the sewage treatment plant, external factors such as temperature and rainfall, and operational variables of the process. Uneasy. If it is possible to find out what specific non-process and internal causes are the causes of the runoff quality, the driver can modify the operating parameters and keep the process more stable. will be.
  • Diagnosis or operation of such sewage treatment plant processes has often required complex mathematical modeling.
  • the purpose was to provide the process operator with model simulation how much of the operating variables to change.
  • the data collection and coefficient optimization steps are necessary to optimize the coefficient values of the model until these models are able to better simulate the behavior of the target process.
  • the accuracy has changed, making it difficult to achieve reliability for field applications.
  • the present invention has been made to solve such a problem
  • the present invention is the outflow water quality of the sewage treatment plant is to respond to external causes including variations in the flow rate and characteristics of the influent and changes in environmental factors such as temperature, rainfall
  • This is a complex result of the internal cause factors including the driver's operation plan to maintain the effluent quality stably.
  • the external and internal causes of the previously measured process Apparatus for providing a causal factor for the condition of the sewage treatment plant to extract the type and pattern from the cumulative data, which is a record of the causal relationship between the factor and the effluent quality, to identify the cause of the present effluent and provide it to the driver.
  • the purpose is to provide a method.
  • the present invention allows the search process of the cause factor for the state of the runoff quality is automatically derived by a series of predefined algorithms to enable the objective cause driver to be derived and provided without depending on human resources.
  • the purpose of the present invention is to provide an apparatus and method for providing a causal factor on the condition of effluent quality which can provide decision support.
  • a data collection unit for collecting the inflow / outflow water quality data and process operation data required for the provision of the cause factor for the state of the outflow water quality of the sewage treatment plant;
  • a data processing unit for processing the set data collected by the data collection unit at predetermined time intervals;
  • a process state discriminating unit which determines a process state of the outflow water quality data among the processed data by using a discrimination function prepared in advance;
  • a decision tree applying unit searching for a corresponding rule among rules constituting the decision tree by applying a decision tree algorithm prepared in advance to the determined process state; And determining the cause factor for the condition of the outflow water quality of the sewage treatment plant based on the process operation data and the inflow / outflow water quality data constituting the rule searched by the decision tree applying unit.
  • the process operation data is a sewage treatment plant outflow, characterized in that it comprises at least one of the aeration amount, sludge waste amount, sludge transport amount, chemical injection amount, sedimentation capacity and concentration of suspended solids in the reactor
  • a causal factor providing device for the condition of water quality.
  • the process state discriminating unit is a data preparation unit for collecting the BOD, COD, SS, TN, TP data of the effluent quality of a certain section from the data collection unit or a separate database and set and process at a predetermined time interval;
  • An effluent quality grouping unit for grouping the types of effluent quality by clustering all data hierarchically by clustering from the nearest data set using hierarchical clustering method for the data processed by the data preparation unit;
  • a discriminant function deriving unit for deriving a discriminant function to be used as a means for determining which type of new effluent quality data belongs to the type of the grouped effluent quality using Fisher's linear discriminant analysis.
  • the process state discriminating unit may determine a process state of the outflow water quality data among the processed data using the discrimination function derived by the discriminating function extracting unit.
  • the decision tree is generated by the decision tree algorithm separately for the grouped effluent quality
  • the decision tree algorithm is characterized by the following equation.
  • Pi is the fraction of S belonging to class i
  • A is a variable
  • Sv is a subset of S when variable A has the value v.
  • the process state causal factor providing unit classifies the process operation data among the process operation data and the inflow / outflow water quality data constituting the rule searched by the decision tree applying unit as an internal process cause factor of the sewage treatment plant.
  • the inflow / outflow water quality data is categorized as an external process cause factor of the sewage treatment plant to determine whether the cause factor for the condition of the outflow water quality of the sewage treatment plant is an internal process factor or an external process cause factor and is provided to the driver. It is characterized by giving.
  • the process operation data is characterized in that it comprises at least one or more of aeration amount, sludge waste amount, sludge conveyance amount, chemical injection amount, sedimentation capacity and the concentration of suspended solids in the reactor.
  • the process state determination step is to collect the data of the BOD, COD, SS, TN, TP of the effluent quality of a certain section from the data collection unit or a separate database, and set the processing at a predetermined time interval to process the processed data Using hierarchical clustering, we clustered from the nearest dataset to cluster all the data hierarchically to group the type of runoff quality. After deriving a discrimination function to be used as a means for determining whether to belong, using Fisher's linear discriminant analysis, and using the derived discriminant function to determine the process state of the effluent quality data of the processed data.
  • the decision tree is generated by the decision tree algorithm separately for the grouped effluent quality
  • the decision tree algorithm is characterized by the following equation.
  • Pi is the fraction of S belonging to class i
  • A is a variable
  • Sv is a subset of S when variable A has the value v.
  • the process factor providing step is to classify the process operation data among the process operation data and the inflow / outflow water quality data constituting the rules found in the decision tree application step as an internal process factor of the sewage treatment plant
  • the inflow / outflow water quality data is categorized as an external process cause factor of the sewage treatment plant to determine whether the cause factor for the condition of the outflow water quality of the sewage treatment plant is an internal process factor or an external process cause factor and is provided to the driver. It is characterized by giving.
  • the present invention can perform the operation support of the process by searching for the cause of the current effluent quality in the operation of the sewage treatment plant, and can provide a simple and key process cause factor in the process operation of the sewage treatment plant.
  • the search process of causal factors is automatically derived by a series of predefined algorithms, which makes it possible to derive and provide objective causal factors without depending on human resources.
  • the present invention can distinguish whether it is greatly influenced by external factors of the process (changes in inflow quality and flow rate or changes in weather conditions) or internal factors of the process. Integrating sewage collection, sewage treatment plant operation, and discharge water quality management through sewage pipes can clarify whether to improve the operation of sewage treatment plants.
  • FIG. 1 is a block diagram showing a causal factor providing apparatus for the state of the sewage treatment plant effluent quality according to an embodiment of the present invention.
  • Figure 2 is a flow chart showing a method for providing a causal factor for the state of the sewage treatment plant effluent quality in accordance with an embodiment of the present invention.
  • FIG. 3 is a diagram illustrating an example of a decision tree composed of rules regarding cause factors derived in accordance with an embodiment of the present invention.
  • a data collection unit for collecting the inflow / outflow water quality data and process operation data required for the provision of the cause factor for the state of the outflow water quality of the sewage treatment plant;
  • a data processing unit for processing the set data collected by the data collection unit at predetermined time intervals;
  • a process state discriminating unit which determines a process state of the outflow water quality data among the processed data by using a discrimination function prepared in advance;
  • a decision tree applying unit searching for a corresponding rule among rules constituting the decision tree by applying a decision tree algorithm prepared in advance to the determined process state; And determining the cause factor for the condition of the outflow water quality of the sewage treatment plant based on the process operation data and the inflow / outflow water quality data constituting the rule searched by the decision tree applying unit.
  • the process operation data is a sewage treatment plant outflow, characterized in that it comprises at least one of the aeration amount, sludge waste amount, sludge transport amount, chemical injection amount, sedimentation capacity and concentration of suspended solids in the reactor
  • a causal factor providing device for the condition of water quality.
  • FIG. 1 is a block diagram showing a causal factor providing apparatus for the state of the sewage treatment plant effluent quality according to an embodiment of the present invention
  • Figure 2 is a causal factor providing method for the state of effluent water quality according to an embodiment of the present invention
  • 3 is a diagram illustrating an example of a decision tree composed of rules regarding cause factors derived according to an embodiment of the present invention.
  • the causative factor providing apparatus 10 for the state of the sewage treatment plant effluent quality is the data collection unit 100, the data processing unit 200, the process state determination unit 300, decision making It includes a tree applying unit 400 and the process factor providing unit 500.
  • the data collection unit 100 collects inflow / outflow water quality data and process operation data required to provide a cause factor for the condition of the outflow water quality of the sewage treatment plant.
  • the inflow / outflow water quality data includes inflow / outflow flow rates and inflow / outflow component concentrations (BOD 5 , COD Mn , SS, TN, TP, etc.).
  • BOD 5 , COD Mn , SS, TN, TP, etc. the inflow / outflow water quality data is usually measured once a day and recorded, or measured several times a day, and as an average value of the result, all of the inflow and outflow water of the sewage treatment plant existed as one value per day. Recorded data of water quality items and inflows.
  • the inflow / outflow water quality data may include weather factors such as temperature, water temperature, rainfall, sunshine, and humidity that may affect the treatment performance of the sewage treatment plant.
  • the process operation data includes at least one or more of aeration amount, sludge waste amount, sludge conveyance amount, chemical injection amount, sedimentation capacity, and suspended solids concentration in the reactor.
  • process operation data are typically modified once a day by the operator and applied to the process, and the results are typically the operating factors of the sewage treatment plant where the results are present as records, aeration volume, DO concentration and sludge in the reactor. Recorded results of operator factors including one or more of conveyed volume, sludge waste volume and sedimentation capacity (SVI, SV30).
  • the data processing unit 200 serves to process and set the data collected by the data collection unit 100 at predetermined time intervals.
  • the data processing unit 200 averages the data collected at different time intervals to exist as one representative value per day or week, or processes the data by various statistical methods for selecting other representative values and collected at predetermined time intervals. This means that data is present in a set.
  • the process state discriminating unit 300 serves to determine the process state of the outflow water quality data among the processed data by using a determination function prepared in advance. That is, the process state discriminating unit 300 determines which state the effluent quality currently in use belongs to by utilizing the state type of the effluent quality derived by hierarchical cluster analysis and the discrimination function derived for each type. will be.
  • the process state discrimination unit 300 includes a data preparation unit 310, a effluent quality grouping unit 320, and a determination function extracting unit 330.
  • the data preparation unit 310 collects BOD, COD, SS, TN, and TP data of effluent quality from a data collection unit 100 or a separate database, and sets and processes the data at predetermined time intervals. do.
  • the effluent quality grouping unit 320 clusters all the data hierarchically by clustering the data processed by the data preparing unit 310 from the closest data set using a hierarchical clustering method. It serves to group.
  • the discrimination function derivation unit 330 serves to derive a discrimination function to be used as a means for determining what type of new effluent quality data belongs to the type of the grouped effluent quality using Fisher's linear discrimination analysis. do. Therefore, the process state discriminating unit 300 determines the process state of the outflow water quality data among the processed data by using the discrimination function derived by the discriminating function extracting unit 330.
  • the hierarchical clustering method mentioned above clusters the datasets having the closest distance or excludes the farthest datasets by performing the distance calculation between each dataset using the distance calculation method proposed by Ward. How to do it.
  • the person who wants to cluster the data determines the number of clusters by identifying the dendrograms.
  • Derived clusters are assigned to each type of water quality by cluster by identifying the characteristics of the datasets included in the cluster (concentration range, mean and standard deviation of each water quality item, etc.).
  • the decision tree application unit 400 serves to search for a corresponding rule among rules constituting the decision tree by applying a decision tree algorithm prepared in advance to the determined process state. That is, the decision tree application unit 400 is prepared in advance for each of the current outflow water quality currently found from the process state discriminating unit 300, the current inflow water quality and environmental factors, processes Apply operational data to determine which of the various rules make up a decision tree.
  • the decision tree is generated by the decision tree algorithm separately for the grouped effluent quality, and the decision tree algorithm is derived by the following equation.
  • Pi is the fraction of S belonging to class i
  • A is a variable
  • Sv is a subset of S when variable A has the value v.
  • the decision tree rearranges the data again according to the type of the grouped water quality, and sets the input variables as influent water quality factors, influent flow rates, and operation history variables to act as classification criteria for rules to be generated in the future. It exists as a collection of rules that make the target variable one or more types of water quality.
  • the rule generated from the decision tree is composed of some causes for one effluent quality, unlike the existing decision trees to find out whether the target is classified as good / bad / normal. There is a distinction as a rule to derive the number of cases, and it is desirable to have one decision tree for one or two combinations of the target runoff quality.
  • the process state causal factor providing unit 500 may determine the state of the outflow water quality of the sewage treatment plant based on the process operation data and the inflow / outflow water quality data constituting the rule searched by the decision tree application unit 400.
  • the cause factor is judged and provided to the driver. Therefore, the process state cause factor providing unit 500 of the process operation data and the inflow / outflow water quality data constituting the rule searched by the decision tree applying unit 400 is the process operation data in the process of the sewage treatment plant.
  • the inflow / outflow water quality data is classified as an out-of-process cause factor of the sewage treatment plant, and whether the cause factor for the outflow water quality of the sewage treatment plant is an in-process or out-of-process cause factor. Determine and provide to the driver.
  • FIG. 2 describes the method for providing a causal factor for the condition of the effluent quality of the sewage treatment plant according to the present invention.
  • the first step is a data input step of receiving inflow / outflow water quality data and process operation data required for providing a causative factor for the condition of outflow water quality from the sewage treatment plant (S110).
  • the second step is a data processing step of processing by setting the input data at predetermined time intervals (S120).
  • the third step is a process state determination step of determining a process state of the outflow water quality data among the processed data by using a determination function prepared in advance (S130).
  • the process state determination step (S130) is to collect the data of the BOD, COD, SS, TN, TP of the effluent quality of a certain section from the data collection unit 100 or a separate database to set and process at a predetermined time interval Using hierarchical clustering, the processed data is clustered from the nearest dataset to cluster all the data hierarchically to group the type of runoff quality, and the new runoff quality data for the type of grouped runoff quality. After deriving a discriminant function to be used as a means for determining which type belongs to using Fisher's linear discriminant analysis, the derived discriminant function is used to determine the process state of the effluent quality data among the processed data.
  • the fourth step is a decision tree application step of searching for a corresponding rule among rules constituting the decision tree by applying a decision tree algorithm prepared in advance to the determined process state (S140).
  • the decision tree is generated by a decision tree algorithm separately for the grouped effluent quality, and the decision tree algorithm is derived by the following equation.
  • Pi is the fraction of S belonging to class i
  • A is a variable
  • Sv is a subset of S when variable A has the value v.
  • the fifth step is a process state causal factor providing step for determining the causal factors for the condition of the outflow water quality of the sewage treatment plant on the basis of the process operation data and the inflow / outflow water quality data constituting the searched rules ( S150).
  • the process state providing factor (S150) the process operation data among the process operation data and the inflow / outflow water quality data constituting the rule searched in the decision tree application step (S140) are internal causes of the sewage treatment plant.
  • the inflow / outflow water quality data is classified as an external process cause factor of the sewage treatment plant to determine whether the cause factor for the effluent quality of the sewage treatment plant is an internal process factor or an external process cause factor. Give it to the driver.
  • the inflow water quality of the measured value per day of the sewage treatment plant and the value of the effluent quality measured once per hour in order to derive the type of effluent quality of the sewage treatment plant and to search for and provide the causative factor The data was processed by collecting the values of the operating variables that were measured and recorded once a day. This means that the collected effluent quality values exist as a daily average so that the collected data exist as one data set per day. 1 data set.
  • a discrimination function that can easily determine which type the new dataset belongs to. That is, in the present invention, a group classified by hierarchical cluster analysis is taken as an external standard, and a functional formula for each classified group, that is, a discriminating functional formula, is derived through Fisher's linear discriminant analysis.
  • the derived discriminant function gives a conclusion that it is the group representing the largest value by comparing the magnitudes of the values computed by the discriminant function of each group, so that any of the existing classified groups Enable evaluation of belonging to groups.
  • a cross-validation technique was used to evaluate the accuracy of group classification by the discriminant function.
  • the accuracy of group classification by the derived classification rule is then evaluated by comparing the group classified by these rules with the actual group given by the external criteria.
  • the process state of effluent quality data is determined from the processed data, and the decision tree algorithm is applied to the determined process state by applying the prepared decision tree algorithm.
  • the results of constructing the decision tree by searching for the corresponding rule among the rules are shown well in FIG. 3.
  • the decision tree of FIG. 3 constitutes a decision tree with respect to two or more types of water quality in order to enhance the classification performance, that is, as a result of generating the decision tree by tying together three types and five types having the most different group characteristics.
  • each rule consists of variables that refer to the combined cause of the internal and external cause factors of the process.
  • the factor of operation status of the process is "The SS removal rate and the TP removal rate of the treatment process are not good because of the SRT (the cause of the effluent water quality) which was kept short due to the shortening of the residence time in the reactor due to the rainfall. Process status and cause can be provided to the operator.
  • the apparatus and method for providing the causative agent for the condition of the effluent quality of the sewage treatment plant according to the present invention are compared to the process operation support system based on the existing complicated mathematical model, and to the operator, "The current effluent quality is good and / or normal. / Bad, good removal of nitrogen and phosphorus / normal / bad, the main cause is improperly maintained aeration tank DO concentration despite routine external disturbance factors / MLSS concentration in the reaction tank is too low / waste sludge amount is small Because it's too short / etc. " One sentence, which contains complex or clear information, is provided as a causal factor for the condition of the effluent quality so that the driver can support objective decision-making.
  • the present invention extracts the type and pattern from the cumulative data, which is a record of the causal relationship between the external and internal causative factors of the existing process and the effluent quality, if any series of undesirable effluent conditions occur. It can be widely used in sewage treatment plants because it grasps the condition of outflow water in sewage treatment plants by providing the driver where the cause is.

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Abstract

La qualité des effluents provenant d'une station d'épuration étant le produit complexe des facteurs de causalité externes, y compris les fluctuations du débit et la propriété des affluents, l'évolution des facteurs environnementaux tels que la température et la pluie, ainsi que les facteurs de causalité internes, notamment les mesures opérationnelles prises par l'opérateur pour maintenir solidement la qualité des effluents en réponse aux facteurs de causalité externes, la présente invention concerne un appareil et un procédé permettant de fournir des facteurs de causalité pour l'état de la qualité des effluents provenant d'une station d'épuration des eaux usées, l'appareil et le procédé permettant : d'extraire des types et des modèles pour une série d'états indésirables de la qualité des effluents, en cas de tels événements, à partir de données cumulatives constituant un enregistrement de la relation de causalité entre les précédents facteurs de causalité externes et internes mesurés dans les processus et la qualité des effluents ; d'identifier les causes de la qualité actuelle des effluents ; et de les fournir à l'opérateur. L'appareil fourni selon la présente invention permet de fournir des facteurs de causalité pour la qualité des effluents d'une station d'épuration des eaux usées, ledit appareil comprenant : une unité de collecte de données permettant de collecter des données concernant la qualité des affluents/effluents et des données d'exploitation de traitement nécessaires à la fourniture des facteurs de causalité pour la qualité des effluents d'une station d'épuration des eaux usées ; une unité de traitement de données permettant de regrouper les données recueillies par l'unité de collecte de données par ensembles, à des intervalles de temps prédéfinis et de les traiter ; une unité de définition d'état de traitement permettant de définir l'état de traitement des données concernant la qualité des effluents parmi les ensembles de données traités à l'aide d'une fonction discriminante préparée à l'avance ; une unité d'application d'arborescence décisionnelle permettant d'appliquer un algorithme d'arborescence décisionnelle préparé à l'avance à l'état de traitement défini et de rechercher une règle pertinente parmi les règles constituant une arborescence décisionnelle ; ainsi qu'une unité de fourniture de facteurs de causalité pour l'état de traitement permettant de déterminer les facteurs de causalité de la qualité des effluents provenant de la station d'épuration des eaux usées sur la base des données d'exploitation de traitement et des données concernant la qualité des affluents/effluents comprenant la règle recherchée par l'unité d'application d'arborescence décisionnelle et les fournir à un opérateur, les données d'exploitation de traitement comprennent au moins un des éléments suivants : quantité d'aération, quantité d'élimination de boues, quantité de boues de retour, quantité d'alimentation en produits chimiques, précipitabilité et concentration de matières en suspension dans un réacteur de la station d'épuration des eaux usées.
PCT/KR2013/002573 2013-03-27 2013-03-28 Appareil et procédé permettant de fournir des facteurs de causalité concernant la qualité des effluents dans une station d'épuration des eaux usées WO2014157750A1 (fr)

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US20180282180A1 (en) * 2015-09-18 2018-10-04 Mitsubishi Hitachi Power Systems, Ltd. Water quality management device, water treatment system, water quality management method, and program for optimizing water treatment system
CN111999754A (zh) * 2020-07-10 2020-11-27 中国辐射防护研究院 一种基于核设施气载流出物监测数据的评价系统

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