Estimation device, prediction device, control device, estimation system, prediction system, control system, estimation program, prediction program, control program, estimation method, prediction method, and control method

Abstract

[Subject] The present invention provides an estimation device, a prediction device, a control device, an estimation system, a prediction system, a control system, an estimation program, a prediction program, a control program, an estimation method, a prediction method, and a control method, which can estimate the index value of scale generated as scale based on water quality information that can be easily measured during operation. [Solution] According to one embodiment of the present invention, an estimation device for the scaling index value of a water system is provided. The estimation device includes a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit. The water quality information acquisition unit acquires water quality information including water quality parameters, which are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, which represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameters. The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information.

Description

Technical Field

[0001] The present invention relates to an estimation device, a prediction device, a control device, an estimation system, a prediction system, a control system, an estimation program, a prediction program, a control program, an estimation method, a prediction method, and a control method. Background Art

[0002] In water systems, various ions contained in water may precipitate as scale and accumulate in pipes, causing operational problems. In such cases, the formation of scale is detected and various anti-scaling agents are added.

[0003] However, scale forms when the concentration product of the ions that make up the scale exceeds the solubility product of those ions. Taking advantage of this, for example, Non-Patent Documents 1 and 2 use the logarithm of the ratio of the product of the valence powers of the concentrations of each ion to the solubility product of each ion as a scaling index, an indicator for determining whether scale is forming. Using this index allows accurate detection of scale formation.

[0004] Prior art literature

[0005] [Non-patent literature]

[0006] [Non-Patent Document 1] Kenji Kibata, Journal of the Paper and Packaging Technology Association, Vol. 57, No. 7, p. 70, 2003.

[0007] [Non-patent document 2] Kenji Kibata, Journal of the Paper and Packaging Technology Association, Vol. 44, No. 7, p. 29, 2001. Summary of the Invention

[0008] Problems to be solved by the invention

[0009] To more effectively inhibit scale formation, it is necessary to quickly calculate an index value that serves as a measure of scale formation and to appropriately add various anti-scaling agents accordingly. However, the scaling index calculation methods described in Non-Patent Documents 1 and 2 often require time to measure the concentrations of the cations and anions that constitute scale, making it difficult to quickly calculate the scaling index.

[0010] In view of the above situation, the present invention provides an estimation device, a prediction device, a control device, an estimation system, a prediction system, a control system, an estimation program, a prediction program, a control program, an estimation method, a prediction method and a control method, which can estimate the index value that serves as a measure of scale generation based on water quality information that can be easily measured during operation.

[0011] Solutions for solving problems

[0012] According to one embodiment of the present invention, there is provided a device for estimating a scaling index value of a water system. The estimating device comprises a water quality information acquisition unit, a relational model information acquisition unit, and an estimating unit. The water quality information acquisition unit acquires water quality information including water quality parameters, which are two or more water quality parameters selected from a group consisting of at least pH (power of hydrogen; acidity and alkalinity), cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, the relational model representing the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimating unit calculates the scaling index estimation value based on the water quality information and the relational model information.

[0013] The present invention can also be provided in the following various aspects.

[0014] In the device for estimating a scaling index value for a water system, the relational model is a model obtained by regression analysis of the scaling index value and a scaling index estimation function that is a function of the water quality parameter.

[0015] In the device for estimating a scaling index value of a water system, the water quality parameter includes at least electrical conductivity.

[0016] A device for predicting scale formation in a water system, characterized in that it includes a water quality information acquisition unit, a relational model information acquisition unit, an estimating unit and a predicting unit; the water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents a relationship between a scaling index value calculated as a function of the concentration of ions that can form scale in the water system and the water quality parameter; the estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; and the predicting unit predicts the presence or possibility of scale formation based on the scaling index estimated value.

[0017] A control device for adding a scale inhibitor to a water system, characterized in that it includes a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit and an addition amount determination unit; the water quality information acquisition unit acquires water quality information including water quality parameters, the water quality parameters being two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a relational model prepared in advance, the relational model representing the relationship between the water quality parameters and the chromaticity of the water system; The scaling index value calculated as a function of the concentration of ions capable of forming scale in the water system and the water quality parameter are used as the estimation unit; the scaling index estimation value is calculated based on the water quality information and the relational model information; the scaling agent addition model information acquisition unit acquires scaling agent addition model information including a pre-made scaling agent addition model, wherein the scaling agent addition model represents the relationship between the scaling index estimation value and the amount of scaling agent added; the amount of addition determination unit determines the amount of scaling agent added based on the scaling index estimation value and the scaling agent addition model information.

[0018] A system for estimating scaling index values ​​of a water system, characterized in that it includes a water quality information acquisition unit, a relational model information acquisition unit and an estimating unit; the water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between a scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameters; the estimating unit calculates the scaling index estimation value based on the water quality information and the relational model information.

[0019] A system for predicting scale formation in a water system, characterized in that it includes a water quality information acquisition unit, a relational model information acquisition unit, an estimating unit and a predicting unit; the water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a relational model prepared in advance, wherein the relational model represents a relationship between a scaling index value calculated as a function of the concentration of ions that can form scale in the water system and the water quality parameter; the estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; and the predicting unit predicts the presence or possibility of scale formation based on the scaling index estimated value.

[0020] A control system for adding a scale inhibitor to a water system, characterized in that it includes a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit and an addition amount determination unit; the water quality information acquisition unit acquires water quality information including water quality parameters, the water quality parameters being two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a relational model prepared in advance, the relational model representing the relationship between the water quality parameters and the chromaticity of the water system; The scaling index value calculated as a function of the concentration of ions capable of forming scale in the water system and the water quality parameter are used as the estimation unit; the scaling index estimation value is calculated based on the water quality information and the relational model information; the scaling agent addition model information acquisition unit acquires scaling agent addition model information including a pre-made scaling agent addition model, wherein the scaling agent addition model represents the relationship between the scaling index estimation value and the amount of scaling agent added; the amount of addition determination unit determines the amount of scaling agent added based on the scaling index estimation value and the scaling agent addition model information.

[0021] A scaling index value estimation program for a water system causes a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit; the water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, electrical conductivity, suspended matter mass, turbidity, and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a pre-made relational model, wherein the relational model represents a relationship between a scaling index value calculated as a function of the concentration of ions that can form scale in the water system and the water quality parameters; the estimation unit calculates a scaling index estimation value based on the water quality information and the relational model information.

[0022] A program for predicting scale formation in a water system, which enables a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimating unit, and a predicting unit; the water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a pre-made relational model, wherein the relational model represents a relationship between a scaling index value calculated as a function of the concentration of ions that can form scale in the water system and the water quality parameter; the estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; and the predicting unit predicts the presence or possibility of scale formation based on the scaling index estimated value.

[0023] A control program for adding a scale inhibitor to a water system, causing a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit; the water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system; the relational model information acquisition unit acquires relational model information including a pre-created relational model, wherein the relational model represents the relationship between the water quality parameters and the chromaticity of the water system; the relationship between the scaling index value calculated by the function of the concentration of ions capable of forming scale in the water system and the water quality parameter; the estimating unit calculates the scaling index estimated value based on the water quality information and the relational model information; the scaling inhibitor addition model information acquiring unit acquires scaling inhibitor addition model information including a pre-made scaling inhibitor addition model, the scaling inhibitor addition model representing the relationship between the scaling index estimated value and the amount of scaling inhibitor added; the amount of addition determining unit determines the amount of scaling inhibitor added based on the scaling index estimated value and the scaling inhibitor addition model information.

[0024] A method for estimating a scaling index value of a water system, characterized in that it includes a water quality information acquisition process, a relational model information acquisition process and an estimation process; in the water quality information acquisition process, water quality information including water quality parameters is acquired, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity of the water system; in the relational model information acquisition process, relational model information including a pre-made relational model is acquired, and the relational model represents the relationship between a scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameters; in the estimation process, an estimated scaling index value is calculated based on the water quality information and the relational model information.

[0025] A method for predicting scale formation in a water system, characterized in that it includes a water quality information acquisition process, a relational model information acquisition process, an estimation process and a prediction process; in the water quality information acquisition process, water quality information including water quality parameters is acquired, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity of the water system; in the relational model information acquisition process, relational model information including a pre-made relational model is acquired, and the relational model represents the relationship between a scaling index value calculated as a function of the concentration of ions that can form scale in the water system and the water quality parameter; in the estimation process, a scaling index estimation value is calculated based on the water quality information and the relational model information; in the prediction process, the presence or possibility of scale formation is predicted based on the scaling index estimation value.

[0026] A method for controlling the addition of a scale inhibitor to a water system, characterized in that it includes a water quality information acquisition step, a relational model information acquisition step, an estimation step, a scale inhibitor addition model information acquisition step, and an addition amount determination step; in the water quality information acquisition step, water quality information including water quality parameters is acquired, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system; in the relational model information acquisition step, relational model information including a relational model prepared in advance is acquired, wherein the relational model represents the relationship between the water system and the water quality. the relationship between the scaling index value calculated by the function of the concentration of ions capable of forming scale in the water system and the water quality parameter; in the estimating step, the scaling index estimated value is calculated based on the water quality information and the relational model information; in the scaling agent addition model information obtaining step, scaling agent addition model information including a pre-made scaling agent addition model is obtained, the scaling agent addition model indicating the relationship between the scaling index estimated value and the amount of scaling agent added; in the amount of addition determining step, the amount of scaling agent added is determined based on the scaling index estimated value and the scaling agent addition model information.

[0027] Of course, it’s not limited to this.

[0028] According to the present invention, an index value serving as a measure of scale generation can be estimated based on water quality information that can be easily measured during operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a schematic diagram of the prediction system according to this embodiment.

[0030] Figure 2 It is a schematic diagram showing the general functional structure of the prediction device according to this embodiment.

[0031] Figure 3 This is a schematic diagram showing the hardware configuration of the prediction device according to this embodiment.

[0032] Figure 4 This is a flowchart of the prediction method of this embodiment.

[0033] Figure 5 This is a graph showing scaling index values ​​for a total of 19 data sets in Example 1 versus estimated scaling index values.

[0034] Figure 6 This is a graph showing scaling index values ​​versus estimated scaling index values ​​for a total of 18 data sets in Example 2. DETAILED DESCRIPTION

[0035] The embodiments of the present invention will be described below with reference to the accompanying drawings. The various components shown in the following embodiments can be combined with each other.

[0036] The program for implementing the software appearing in this embodiment can be provided as a non-transitory computer-readable storage medium (Non-Transitory Computer-Readable Medium), can be downloaded and provided by an external server, and can also be started by an external computer to implement functions on a client terminal (so-called cloud computing).

[0037] In addition, the term "unit" in this embodiment can be a concept that includes, for example, a combination of hardware resources implemented by a circuit in a broad sense and software information processing specifically implemented by these hardware resources. Furthermore, this embodiment involves various types of information, which can be represented by physical values ​​such as signal values ​​representing voltage or current, or by the high or low values ​​of signal values ​​as a binary bit set consisting of 0 or 1, or by quantum superposition (i.e., so-called quantum bits), and can perform communication and calculations on a broad circuit.

[0038] In a broad sense, a circuit is a circuit implemented by appropriately combining at least circuits, circuit classes, processors, and memories. This includes application-specific integrated circuits (ASICs), programmable logic devices (such as simple programmable logic devices (SPLDs) and complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs).

[0039] <Prediction System>

[0040] The prediction system of the present embodiment is a prediction system for scale formation in a water system. Specifically, the prediction system includes a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, and a prediction unit. The water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scaling index estimation value based on the water quality information and the relational model information. The prediction unit predicts the presence or possibility of scale formation based on the scaling index estimation value.

[0041] In addition, although not an essential component, the prediction system of this embodiment may also include one or more of the following: a relational model creation unit, a prediction model creation unit, a prediction model information acquisition unit, a scale inhibitor addition model creation unit, a scale inhibitor addition model information acquisition unit, an addition amount determination unit, an output unit, and a scale inhibitor addition unit. Figure 1 In this paper, the prediction system that has all these elements is mainly described.

[0042] Here, "scale" is a general term for metal salts that precipitate and accumulate in water systems. Specifically, scale is not particularly limited, and examples thereof include calcium oxalate, calcium carbonate, calcium sulfate, calcium phosphate, and barium sulfate.

[0043] The scaling index value is a numerical value that can be used as an index value of scale generation, and is not particularly limited as long as it is a numerical value calculated by a function of the concentration of ions that constitute scale that can be formed in the water system. As the function, for example, the scaling index value SI can be used. Specifically, the scaling index value SI is the logarithm of the ratio of the product of the valence power of the concentration of each ion to the solubility product of each ion. In non-patent document 1, the scaling index value SI of calcium oxalate is shown, and in non-patent document 2, the scaling index value SI of calcium carbonate is shown. Specifically, when the cation is A, the anion is B, the valence of the cation A is +n, the valence of the anion B is -m (n and m are each independently positive integers), and the solubility product of the cation A and the anion B is K sp When , the scaling index value SI is expressed by the following formula (1).

[0044] [Formula 1]

[0045]

[0046] In the formula (1), one type of cation A and one type of anion B are shown. However, the number of cations and anions depends on the type of scale generated and is not limited to one type.

[0047] As described above, the function for determining the scaling index value is not particularly limited to formula (1). As scaling index values ​​other than formula (1), other possible values ​​include not taking the logarithm (the inner part of the logarithm) of formula (1) (formula (2)), taking its reciprocal (formula (3)), setting the inner part of the logarithm of formula (1) to the reciprocal (formula (4)), raising formulas (1) to (4) to powers, adding, subtracting, multiplying, or dividing a constant, and the like.

[0048] [Formula 2]

[0049]

[0050] [Formula 3]

[0051]

[0052] [Formula 4]

[0053]

[0054] As a function for obtaining the scaling index value, the solubility product K may or may not be included. sp , but preferably includes the solubility product K sp. In addition, as a function for calculating the scaling index value, it is preferred that at least one of cations and anions be included, and more preferably all types of cations and anions be included. In one embodiment, as a function for calculating the scaling index value, it is preferred that all types of cations and anions be included, and the function is the ratio of the product of these concentrations to the solubility product of these ions (Formulas (2), (3)).

[0055] [Functional structure of the prediction system]

[0056] Figure 1 1 is a schematic diagram of a prediction system according to this embodiment. The prediction system 1 includes a prediction device 2, an output device 3, a water quality information measuring device 4, and a scale inhibitor adding device 5.

[0057] The prediction device 2 controls information processing for prediction in the prediction system 1 . Figure 2 Schematic diagram showing the functional structure of the prediction device of this embodiment. Figure 2 As shown, the prediction device 2 of this embodiment includes a water quality information acquisition unit 20, a relational model information acquisition unit 21, an estimation unit 22, and a prediction unit 23. In addition, the prediction device 2 of this embodiment also includes a relational model creation unit 24, a prediction model creation unit 25, a prediction model information acquisition unit 26, a scale inhibitor addition model creation unit 27, a scale inhibitor addition model information acquisition unit 28, and an addition amount determination unit 29. These parts are described here as being included in a single device, but each part may also be included in a different device. In addition, the output device 3 is an example of an output unit, the water quality information measuring device 4 is an example of a water quality information measuring unit, and the scale inhibitor addition device 5 is an example of a scale inhibitor addition unit, but they are not specifically distinguished in the following description.

[0058] [Functions of the prediction system]

[0059] Hereinafter, the functions of each unit of the prediction system 1 will be described in detail.

[0060] [Water Quality Information Acquisition Department]

[0061] The water quality information acquisition unit 20 acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter content, turbidity and chromaticity of the water system.

[0062] The pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and color of the water system all have a certain correlation with the scaling index value or ion concentration. Therefore, the water quality information acquisition unit obtains water quality parameters including two or more of these and calculates the estimated scaling index value.

[0063] As water quality parameters, any combination of two or more of pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity is acceptable, but it is preferred that at least conductivity be included. Before scaling, the components that make up scale exist in water as ions. Conductivity is an indicator of the amount of ionic components in water, so conductivity is particularly useful as an indicator related to scaling. In addition, water quality parameters preferably do not include the concentration of cations and anions that make up scale. Residual chlorine concentration refers to the concentration of anions, but since continuous measuring devices are commercially available, they are easy to measure.

[0064] [Relational model information acquisition unit]

[0065] The relational model information acquisition unit 21 acquires relational model information including a relational model prepared in advance, the relational model indicating the relationship between a scaling index value calculated from a function of the concentration of ions constituting scale-forming ions in a water system and a water quality parameter.

[0066] The relational model is a pre-created model that represents the relationship between the scaling index value, calculated as a function of the concentration of ions that can form scale in the water system, and the water quality parameters. "Pre-created" refers to the calculation of the estimated scaling index value before the estimated scaling index value is calculated. This can be done during the calculation of the estimated scaling index value or before the actual operation.

[0067] The relational model is not particularly limited, and examples thereof include a function representing the relationship between the scaling index value and the water quality parameter, a lookup table, or a learned model of the relationship between the scaling index value and the water quality parameter.

[0068] The water quality parameters included in the water quality information obtained by the water quality information acquisition unit 20 and the water quality parameters included in the water quality information used in the relational model are set to two or more common parameters shown below: pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity and chromaticity.

[0069] [Estimation Department]

[0070] The estimating unit 22 calculates a scaling index estimated value based on the water quality information and the relational model information.

[0071] Specifically, the estimating unit 22 inputs the real-time water quality information during operation into a relational model prepared in advance, performs calculations or comparisons, and thereby calculates an estimated scaling index value.

[0072] [Forecast Department]

[0073] The prediction unit 23 predicts the presence or possibility of scale generation based on the scaling index estimated value.

[0074] The estimated scaling index value is used as an index of scale generation in the water system. Here, the estimated scaling index value is input into a previously prepared prediction model to predict the presence or possibility of scale generation.

[0075] When predicting the presence of scale formation, for example, a threshold is set in the estimated scaling index value or the amount of change per unit time in the estimated scaling index value. If the estimated scaling index value is greater than (or less than) the threshold, scale formation can be predicted.

[0076] When predicting the likelihood of scale formation, for example, multiple thresholds may be set for the estimated scaling index value or the amount of change in the estimated scaling index value per unit time, for example, divided into three stages. When the estimated scaling index value or the amount of change in the estimated scaling index value per unit time is in the first stage, it is predicted that scale has definitely formed. When the estimated scaling index value or the amount of change in the estimated scaling index value per unit time is in the second stage, it is predicted that scale may form. When the estimated scaling index value or the amount of change in the estimated scaling index value per unit time is in the third stage, it is predicted that scale will definitely not form. Furthermore, the probability of scale formation can be calculated by functionalizing or modeling the estimated scaling index value or the amount of change in the estimated scaling index value per unit time and the probability of scale formation based on statistical data from actual operations.

[0077] [Relationship model creation department]

[0078] The relational model creation unit 24 creates a relational model that is acquired by the relational model information acquisition unit 21 and used for calculating the scaling index estimated value by the estimation unit 22 .

[0079] For example, a relational model can be created in the following manner. Before calculating the estimated value of the scaling index, the concentration of the ions that constitute scale is measured, and the scaling index value is calculated based on these concentrations. In addition, in the same water system, two or more water quality parameters selected from the group consisting of pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity and chromaticity are measured. Prepare multiple sets of such scaling index values ​​and water quality parameter data sets, for example, change the date or time of measurement, etc., so that the scaling index value and the water quality parameter value change. Then, the scaling index value is assumed to be a function of the water quality parameter (two or more parameters), compared with the actual scaling index value, the function mode or coefficient is determined, and a relational model is constructed. At this time, when determining the coefficient of the function by comparing the function with the actual scaling index value, regression analysis method (linear model, generalized linear model, generalized linear mixed model), decision tree (decision tree, regression tree, random forest, XG Boost, etc.), neural network (simple parser, DNN (Deep Neural Network; Deep Neural Network), CNN (Convolution Neural Network: Convolutional Neural Network), RNN (Recurrent Neural Network; Recurrent Neural Network) etc.), Bayes (natural Bayes, etc.), clustering (k-means, k-means++, etc.), group learning (Boosting, Adaboost, etc.), etc. can be used.

[0080] In one embodiment, the relational model is preferably a model obtained by regression analysis of the scaling index value and the scaling index estimation function as a function of the water quality parameter. The specific method of regression analysis will be described later.

[0081] The ions that make up scale are calcium ions and oxalate ions when the scale is calcium oxalate, calcium ions and carbonate ions when the scale is calcium carbonate, calcium ions and sulfate ions when the scale is calcium sulfate, calcium ions and phosphate ions when the scale is calcium phosphate, and barium ions and sulfate ions when the scale is barium sulfate. The concentration of calcium ions can be replaced by calcium hardness, and carbonate ions can be replaced by M alkalinity.

[0082] The relational model is preferably created in the same water system as the one in which the estimated scaling index value is calculated. Furthermore, even within the same facility, if the water quality of the water system significantly changes (e.g., in a papermaking system of a paper mill, when the pulp used as the papermaking raw material is changed), it is preferable to create and use a relational model for the water system after the change in water quality.

[0083] From this perspective, during the operation of the water system, the concentration of ions constituting scale may be measured regularly or irregularly, and a relational model may be created or updated by adding data depending on the situation.

[0084] The relational model creation unit 24 is not an essential component, and therefore the relational model may be created manually by an operator or the like.

[0085] [Prediction model creation department]

[0086] The prediction model creation unit 25 creates a prediction model that is acquired by the prediction model information acquisition unit 26 described later and used by the prediction unit 23 to predict the presence or possibility of scale generation.

[0087] Here, the prediction model refers to a model that represents the relationship between the scaling index value and the presence or absence of scale generation or the amount of scale generation.

[0088] The prediction model is not particularly limited, and examples thereof include a function representing the relationship between the scaling index value and the presence or amount of scale generation, a lookup table, or a learned model of the relationship between the scaling index value and the presence or amount of scale generation.

[0089] For example, a prediction model can be created in the following manner. Before calculating the estimated value of the scaling index, the concentration of the ions that constitute scale is measured, and the scaling index value is calculated based on these concentrations. In addition, in the same water system, the presence or absence of scale is confirmed, or the amount of scale generated is measured. The data sets of these scaling index values ​​and the presence or absence of scale generation or the amount of scale generation are prepared into multiple groups, for example, by changing the date or time of measurement, etc., so that the numerical values ​​of the scaling index values ​​and the presence or absence of scale generation or the amount of scale generation vary. Then, the probability of scale generation or the amount of scale generation is used as a function of the scaling index value to construct a prediction model. In addition, for example, after preparing multiple groups of scaling index values ​​and the presence or absence of scale generation or the amount of scale generation data sets, a threshold value can be set at a node where scale generation becomes significant or at a node where the amount of scale generation reaches or exceeds the allowable amount, to construct a prediction model.

[0090] The prediction model is preferably created in the same water system as the one in which the estimated scaling index value is calculated. Furthermore, even within the same device, if the water quality of the water system significantly changes (e.g., in a papermaking system of a paper mill, when the pulp used as the papermaking raw material is changed), it is preferable to create and use a prediction model for the water system after the water quality change.

[0091] The prediction model creation unit 25 is not an essential component, and thus the prediction model may be created manually by an operator or the like.

[0092] [Prediction model information acquisition unit]

[0093] The prediction model information acquisition unit 26 acquires a prediction model. The prediction model creation unit 25 may create the prediction model.

[0094] [Scale inhibitor addition model creation section]

[0095] The scale inhibitor addition model creation unit 27 creates a scale inhibitor addition model for the scale inhibitor addition unit 5 to add an appropriate amount of scale inhibitor according to the estimated scaling index value, which is acquired by the prediction model information acquisition unit 26 described later.

[0096] Here, the scale inhibitor addition model refers to a model that represents the relationship between the estimated value of the scaling index and the amount of scale inhibitor added (for example, the minimum amount of addition).

[0097] The scale inhibitor addition model is not particularly limited, and examples thereof include a function representing the relationship between the scale index value and the amount of scale inhibitor added, a lookup table, or a learned model of the relationship between the scale index value and the amount of scale inhibitor added.

[0098] For example, a scale inhibitor addition model can be created in the following manner. Before adding the scale inhibitor, prepare aqueous solutions of cations and anions (with constant pH and temperature), in which the concentration of ions constituting scale is known (i.e., the solubility product and the scaling index value are known). In the aqueous solution of cations, a predetermined amount of scale inhibitor is added and mixed, and then an aqueous solution of anions is added and mixed. Then, the obtained mixed solution is filtered, and the concentration of either the cation or the anion ion in the obtained filtrate is measured. Next, the amount of scale inhibitor added is changed and the same operation is performed to calculate the minimum amount of scale inhibitor added (minimum addition amount) at which the theoretical ion concentration of the mixed solution is consistent with the ion concentration of the filtrate. Then, the concentration of the ions is changed (i.e., the scaling index value is changed) and the above operation is repeated multiple times to model the relationship between the estimated scaling index value and the amount of scale inhibitor added. "Aqueous solutions of cations" and "aqueous solutions of anions" refer to aqueous solutions containing cations and anions that constitute scale. For example, in the case of calcium oxalate scale, the aqueous solution of cations is an aqueous solution of calcium chloride, and the aqueous solution of anions is an aqueous solution of oxalic acid. Just as aqueous solutions of cations contain chloride ions, aqueous solutions of cations and aqueous solutions of anions may also contain counterions to the cations and anions that constitute scale, and their types are not particularly limited.

[0099] As a scale inhibitor, there is no particular limitation as long as it can prevent the formation of target scale. For example, polymers formed by polymerizing carboxylic acid monomers such as acrylic acid, methacrylic acid, maleic acid, and itaconic acid, copolymers formed by polymerizing the carboxylic acid monomers with at least one monomer of styrenesulfonic acid, vinyl alcohol, acrylamide, and 2-hydroxy-3-aryloxy-1-propanesulfonic acid, nitrotrimethylenephosphonic acid, hydroxyethyldiphosphonic acid, phosphinobutanetricarboxylic acid, sodium tripolyphosphate, sodium hexametaphosphate, etc. can be used.

[0100] Since the scale inhibitor addition pattern creation unit 27 is not an essential component, the scale inhibitor addition pattern can be created manually by an operator or the like.

[0101] [Scale inhibitor addition model information acquisition unit]

[0102] The scale inhibitor addition model information acquisition unit 28 acquires the scale inhibitor addition model. The scale inhibitor addition model can be created by the scale inhibitor addition model creation unit 27, for example.

[0103] [Additional Amount Determination Department]

[0104] The addition amount determination unit 29 determines the amount of scale inhibitor to be added based on the estimated scaling index value and the scale inhibitor addition model. The estimated scaling index value may be a value calculated by the estimation unit 22, and the scale inhibitor addition model may be a model created by the scale inhibitor addition model creation unit 27.

[0105] The minimum amount of scale inhibitor added can be determined based on the estimated scaling index and the scale inhibitor addition model. The addition amount determination unit 29 can use the minimum amount directly or use an amount obtained by adding a safety factor to the minimum amount.

[0106] The determined amount of addition is sent to the scale inhibitor adding unit 5 described later, and the scale inhibitor adding unit 5 adds the determined amount of scale inhibitor to the water system.

[0107] In addition, the scale generation amount predicted by the prediction unit 23 may be used instead of the scaling index estimated value calculated by the estimation unit 22 .

[0108] [Output section]

[0109] The output unit 3 is configured to output at least one of the estimated scaling index value and the presence or possibility of scale formation predicted by the prediction unit 23. The estimated scaling index value may be calculated by the estimation unit 22, and the presence or possibility of scale formation may be predicted by the prediction unit 23.

[0110] When the output unit 3 outputs the estimated scaling index value, for example, the estimated scaling index value may be displayed over time (a graph of the estimated scaling index value versus time, etc.).

[0111] When the output unit 3 outputs the presence or possibility of scale formation, for example, when the possibility of scale formation exceeds a certain threshold, a warning may be output.

[0112] The output unit 3 may display water quality parameters, etc., in addition to the above-mentioned estimated scaling index value or the presence or possibility of scale formation. In particular, the water quality parameters may be displayed over time.

[0113] [Water Quality Information Measurement Department]

[0114] The water quality information measuring unit 4 measures water quality parameters of a water system that is a target for scale generation prediction.

[0115] As a measuring device, various sensors can be selected according to the content of the water quality parameters to be measured. As a measuring device, for example, when measuring pH, a pH meter can be used as a measuring device. When measuring the required amount of cations, a colloidal particle charge meter can be used as a measuring device. When measuring the residual chlorine concentration, a residual chlorine meter can be used as a measuring device. When measuring temperature, a thermometer can be used as a measuring device. When measuring conductivity, a conductivity meter can be used as a measuring device. When measuring the amount of suspended matter, a suspended matter concentration meter can be used as a measuring device. When measuring turbidity, a turbidity meter can be used as a measuring device. When measuring color, a colorimeter can be used as a measuring device.

[0116] [Inhibitor Adding Section]

[0117] The scale inhibitor adding unit 5 adds the scale inhibitor to the water system in an amount based on the instruction of the addition amount determining unit 29 described above.

[0118] [Application example of the prediction system: Kraft pulp bleaching process in a paper mill]

[0119] For example, in paper mills, not only do oxalate ions and calcium ions from kraft pulp raw material chips leach into the water system, but the water also contains calcium ions. Furthermore, organic matter is oxidized to produce oxalate ions, particularly during the bleaching process. Consequently, oxalate and calcium ion concentrations in the kraft pulp bleaching water system tend to reach high levels. Furthermore, when these oxalate and calcium ion concentrations exceed a certain level, they become calcium oxalate, causing scale.

[0120] In such a system, as shown in Non-Patent Document 1, the scaling index SI of calcium oxalate is expressed by the following formula (5), where the solubility product of calcium ions and oxalate ions is K sp.

[0121] [Formula (5)]

[0122]

[0123] On the other hand, it is assumed that the scaling index estimated value SI of the water system in the kraft pulp bleaching process is est is a function of temperature, pH, and conductivity, with b0 to b8 as coefficients, expressed by the following equation (6). b0 to b8 can be either positive or negative, and can be integers or decimals. Any six or fewer of these can be 0 (considering the two smallest water quality parameters). In this case, the water quality parameters associated with these coefficients do not need to be measured.

[0124] [Formula (6)]

[0125] Y{SI est = {b0 + (b1 × pH) + (b2 × cation requirement) + (b3 × residual chlorine concentration) + (b4 × temperature) + (b5 × conductivity) + (b6 × suspended solids mass) + (b7 × turbidity) + (b8 × chromaticity)}…(6)

[0126] However, Y{SI est} is SI est , logSI est , log any party.

[0127] Next, in the water system, data sets of calcium ion concentration, oxalate ion concentration, pH, cation demand, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and color are measured over time to obtain multiple data sets.

[0128] Then, the obtained data sets were substituted into SI and SI respectively using analysis software. est Regression analysis was performed to determine the coefficients b0 to b8 and substitute them into the above formula (6) to obtain a relational model showing the relationship between the scaling index value and the water quality parameter.

[0129] Once such a relationship model is obtained, in actual operation, the SI can be calculated as an approximate value of SI by measuring pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids mass, turbidity and color. est That is, according to the prediction system (estimation system) of this embodiment, in order to understand the susceptibility of scale formation, it is no longer necessary to measure the calcium ion concentration or the oxalate ion concentration, and the scaling index value can be obtained instantly and continuously.

[0130] In such a system, the predicted SI estThe larger the value, the more likely scale will form, and a warning will be displayed on the output unit 3. Upon seeing this warning, the operator can add anti-scaling agent to the water system according to the level of the warning. This allows for anti-scaling while also reducing the amount of anti-scaling agent that would otherwise be added when scale is not expected.

[0131] The above description is based on a specific example of a case where the kraft pulp bleaching process in a paper mill is an aqueous system. However, when considering other aqueous systems, the types of ions constituting scale in equation (5) can be changed as needed and used as is.

[0132] In the above description, the bleaching process in a paper mill is used as the water system. However, the water systems targeted by the prediction system and other systems of this embodiment are not particularly limited. Examples of water systems targeted in a paper mill include the digestion process, washing process, black liquor concentration process, and causticization process. Furthermore, in addition to water systems in a paper mill, examples of targeted water systems include blast furnace dust collection water systems and converter dust collection water systems in an ironworks, direct and indirect cooling water systems in continuous casting, hot rolling, and cold rolling processes, and seepage water systems and drainage systems generated on-site. Furthermore, examples of targeted water systems include desulfurization equipment, drainage, and dust collection water systems in power plants and coal chemical plants. Furthermore, examples of targeted water systems include various pipelines, heat exchangers, storage tanks, kilns, cleaning equipment, and the like, in addition to the water systems exemplified above.

[0133] [Hardware structure of the prediction system]

[0134] Figure 3 This is a schematic diagram showing the hardware structure of the prediction device of this embodiment. Figure 3 As shown, the prediction device 2 includes a communication unit 61, a storage unit 62, and a control unit 63. These components are electrically connected within the prediction device 2 via a communication bus 64. These components will be further described below.

[0135] While communication unit 61 preferably utilizes wired communication methods such as USB (Universal Serial Bus), IEEE (Institute of Electrical and Electronics Engineers) 1394, Thunderbolt, and wired LAN (Local Area Network) network communication, it may also include wireless LAN network communication, mobile communication such as 3G (Third Generation Mobile Communication) / LTE (Long Term Evolution) / 5G (Fifth Generation Mobile Communication), and Bluetooth (registered trademark) communication, as needed. Specifically, it is more preferable to implement a combination of these multiple communication methods. This allows the prediction device 2 to exchange information or commands with other communicative devices.

[0136] The storage unit 62 stores the various information defined above. It can be implemented, for example, as a storage device such as a solid-state drive (SSD), or as a memory device such as random access memory (RAM) for storing temporary information necessary for program operations (parameters, arrays, etc.). Furthermore, the storage unit 62 may be a combination of these. Furthermore, the storage unit 62 stores various programs that can be read by the control unit 63, described later.

[0137] The control unit 63 performs processing and control of the overall operation of the prediction device 2. The control unit 63 is, for example, a central processing unit (CPU, not shown). The control unit 63 reads a predetermined program stored in the storage unit 62 to implement various functions related to the prediction device 2. In other words, the information processing based on the software (stored in the storage unit 62) is specifically implemented by the hardware (control unit 63), so that Figure 3 The functions shown in FIG. 6 can be executed as each functional unit in the control unit 63. Figure 3 In the embodiment, the control unit 63 is described as a single unit, but in fact, it is not limited to this, and it can be implemented as having multiple control units 63 according to each function. In addition, a single control unit and multiple control units can also be combined.

[0138] <Estimation System>

[0139] The estimation system of the present embodiment is an estimation system for the scaling index value of a water system. Specifically, the estimation system includes a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit. The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, wherein the relational model represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scaling index estimation value based on the water quality information and the relational model information.

[0140] The water quality information acquisition unit, the relational model information acquisition unit, and the estimation unit can use the same methods as those of the above-mentioned prediction system, and therefore their description is omitted here.

[0141] <Control System>

[0142] The control system of the present embodiment is a control system for adding a scale inhibitor to a water system. Specifically, the control system includes a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit. The water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between the scale index value calculated by the function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the estimated value of the scale index based on the water quality information and the relational model information. The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a pre-created scale inhibitor addition model indicating a relationship between an estimated scale index value and an addition amount of the scale inhibitor. The addition amount determination unit determines the addition amount of the scale inhibitor based on the estimated scale index value and the scale inhibitor addition model information.

[0143] In the control system, particularly when the scale inhibitor adding unit is provided, the control system can also be used as an adding system for adding the scale inhibitor to the water system.

[0144] <Estimation Device>

[0145] The estimation device of the present embodiment is an estimation device for the scaling index value of a water system. Specifically, the estimation device includes a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit. The water quality information acquisition unit acquires water quality information including water quality parameters, which are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scaling index estimation value based on the water quality information and the relational model information.

[0146] The water quality information acquisition unit, the relational model information acquisition unit, and the estimation unit can use the same methods as those of the above-mentioned prediction system, and therefore their description is omitted here.

[0147] <Control device>

[0148] The control device of the present embodiment is a control device for adding a scale inhibitor to a water system. Specifically, the control device includes a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit. The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, wherein the relational model represents the relationship between the scale index value calculated by the function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scale index estimation value based on the water quality information and the relational model information. The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a pre-created scale inhibitor addition model indicating a relationship between an estimated scale index value and an addition amount of the scale inhibitor. The addition amount determination unit determines the addition amount of the scale inhibitor based on the estimated scale index value and the scale inhibitor addition model information.

[0149] The water quality information acquisition unit, the relational model information acquisition unit, the estimation unit, the scale inhibitor addition model information acquisition unit, and the addition amount determination unit can be similar to those of the above-mentioned prediction system, and thus their description is omitted here.

[0150] <Prediction Program>

[0151] The prediction program of this embodiment is a prediction program for scale formation in a water system. Specifically, the prediction program enables a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, and a prediction unit. Among them, the water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between the scaling index value calculated by the function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scaling index estimation value based on the water quality information and the relational model information. The prediction unit predicts the presence or possibility of scale formation based on the scaling index estimation value.

[0152] The water quality information acquisition unit, the relational model information acquisition unit, the estimation unit, and the prediction unit can use the same methods as those of the above-mentioned prediction system, and therefore their description is omitted here.

[0153] <Presumption Procedure>

[0154] The estimation program of the present embodiment is an estimation program for the scaling index value of a water system. Specifically, the estimation program enables a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit. The water quality information acquisition unit acquires water quality information including water quality parameters, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, and the relational model represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the scaling index estimation value based on the water quality information and the relational model information.

[0155] The water quality information acquisition unit, the relational model information acquisition unit, and the estimation unit can use the same methods as those of the above-mentioned prediction system, and therefore their description is omitted here.

[0156] <Control Program>

[0157] The control program of the present embodiment is a control program for adding a scale inhibitor to a water system. Specifically, the control program causes the computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit. The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter amount, turbidity, and chromaticity of the water system. The relational model information acquisition unit acquires relational model information including a relational model prepared in advance, wherein the relational model represents the relationship between the scale index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. The estimation unit calculates the estimated value of the scale index based on the water quality information and the relational model information. The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a pre-created scale inhibitor addition model indicating a relationship between an estimated scale index value and an addition amount of the scale inhibitor. The addition amount determination unit determines the addition amount of the scale inhibitor based on the estimated scale index value and the scale inhibitor addition model information.

[0158] The water quality information acquisition unit, the relational model information acquisition unit, the estimation unit, the scale inhibitor addition model information acquisition unit, and the addition amount determination unit can be similar to those of the above-mentioned prediction system, and thus their description is omitted here.

[0159] Even if not described above as essential components, the estimation system, control system, prediction system, estimation device, control device, prediction program, estimation program, and control program may include a prediction unit, a relational model generator, a prediction model generator, a prediction model information acquisition unit, a scale inhibitor addition model generator, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit. These utilize the same configuration as the prediction system, and thus their description is omitted here. Furthermore, even if not described above as essential components, the estimation system, control system, and prediction system may include an output unit, a water quality information measurement unit, and a scale inhibitor addition unit. These utilize the same configuration as the prediction system, and thus their description is omitted here.

[0160] <Prediction method>

[0161] The prediction method of the present embodiment is a method for predicting scale formation in a water system. Specifically, the prediction method comprises a water quality information acquisition process, a relational model information acquisition process, an estimation process, and a prediction process. In the water quality information acquisition process, water quality information including water quality parameters is acquired, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. In the relational model information acquisition process, relational model information including a relational model prepared in advance is acquired, and the relational model represents the relationship between a scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. In the estimation process, a scaling index estimation value is calculated based on the water quality information and the relational model information. In the prediction process, the presence or absence of scale formation or its possibility is predicted based on the scaling index estimation value.

[0162] Figure 4 Flowchart of the prediction method of this embodiment. Figure 4 As shown, in the prediction method of this embodiment, water quality information is acquired (water quality information acquisition step S1) and relational model information is acquired (relational model information acquisition step S2). These are used as input information to calculate an estimated scaling index value (estimation step S3). Next, the presence or likelihood of scale formation is predicted using the estimated scaling index value as input information (prediction step S4).

[0163] <Estimation method>

[0164] The estimation method of the present embodiment is a method for estimating a scaling index value of a water system. Specifically, the estimation method includes a water quality information acquisition process, a relational model information acquisition process, and an estimation process. In the water quality information acquisition process, water quality information including water quality parameters is acquired, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. In the relational model information acquisition process, relational model information including a relational model prepared in advance is acquired, and the relational model represents the relationship between the scaling index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameters. In the estimation process, the scaling index estimation value is calculated based on the water quality information and the relational model information.

[0165] The flowchart of the inference method is Figure 4 Since the steps up to the estimation step S3 are the same, the description thereof is omitted here.

[0166] <Control Method>

[0167] The control method of the present embodiment is a control method for adding a scale inhibitor to a water system. Specifically, the control method comprises a water quality information acquisition process, a relational model information acquisition process, an estimation process, a scale inhibitor addition model information acquisition process, and an addition amount determination process. In the water quality information acquisition process, water quality information including water quality parameters is acquired, and the water quality parameters are two or more water quality parameters selected from a group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended matter mass, turbidity, and chromaticity of the water system. In the relational model information acquisition process, relational model information including a relational model prepared in advance is acquired, and the relational model represents the relationship between the scale index value calculated by a function of the concentration of ions that can form scale in the water system and the water quality parameter. In the estimation process, the scale index estimation value is calculated based on the water quality information and the relational model information. In the scale inhibitor addition model information acquisition step, scale inhibitor addition model information including a previously created scale inhibitor addition model representing the relationship between the estimated scale index value and the amount of scale inhibitor added is acquired. In the addition amount determination step, the amount of scale inhibitor added is determined based on the estimated scale index value and the scale inhibitor addition model information.

[0168] In the prediction method, estimation method and control method, the water quality information acquisition process, the relational model information acquisition process and the estimation process are the same as the operations of the water quality information acquisition unit, the relational model information acquisition unit and the estimation unit, respectively, and therefore their description is omitted here.

[0169] In the prediction method, the inference method and the control method, even if they are not described above as necessary structures, a prediction process, a relational model creation process, a prediction model creation process, a prediction model information acquisition process, a scale inhibitor addition model creation process, a scale inhibitor addition model information acquisition process and an addition amount determination process can be set. These processes are the same as the actions of the prediction unit, the relational model creation unit, the prediction model creation unit, the prediction model information acquisition unit, the scale inhibitor addition model creation unit, the scale inhibitor addition model information acquisition unit and the addition amount determination unit, so their description is omitted here.

[0170] [Example]

[0171] Hereinafter, the present invention will be described in more detail by showing examples thereof, but the present invention is not limited to the following examples.

[0172] [Example 1]

[0173] In a chlorine dioxide bleaching tower at paper mill A, where calcium oxalate scale is generated, 19 different measurements were performed on the cleaning liquid, including pH, conductivity, temperature, oxalate ion concentration, and calcium ion concentration. For each data set, a scaling index (SI) was calculated based on the oxalate ion concentration, calcium ion concentration, and equation (1).

[0174] Next, using Microsoft Office Excel's analysis tool, we conducted a regression analysis of the relationship between scaling index values ​​and pH, conductivity, and temperature on 10 randomly selected data sets from the total 19 data sets. Using pH, conductivity, and temperature as explanatory variables, we generated a correlation model with a correlation coefficient of 0.919 (p < 0.05).

[0175] Then, for the remaining 9 data sets out of the total 19 data sets, the estimated values ​​of scaling index were calculated using the relational model and pH, conductivity, and temperature. The correlation coefficient of the 9 data sets was 0.831 (p<0.05).

[0176] Figure 5 This is a graph showing the scaling index values ​​versus the estimated scaling index values ​​for a total of 19 data sets in Example 1. Figure 5 In FIG, the horizontal axis represents the estimated scaling index value obtained by regression analysis, and the vertical axis represents the scaling index value obtained from the temperature, oxalate ion concentration, and calcium ion concentration.

[0177] As described above, by using pH, conductivity, temperature, and the relationship model, it is possible to calculate the estimated scaling index value related to the scaling index value without using the oxalate ion concentration and the calcium ion concentration.

[0178] [Example 2]

[0179] The pH, conductivity, temperature, turbidity, M-alkalinity, and calcium hardness of the circulating water from the flue gas desulfurization unit of Plant B, where calcium carbonate scale is generated, were measured 18 times. For each data set, the Scaling Index (SI) was calculated using the measurement results for M-alkalinity (equivalent to carbonate ion concentration) and calcium hardness (equivalent to calcium ion concentration).

[0180] Next, using Microsoft Office Excel's analysis tool, we conducted a regression analysis of the relationship between scaling index values ​​and pH, conductivity, temperature, and turbidity on 11 randomly selected data sets from the total 18 data sets. Using pH, conductivity, temperature, and turbidity as explanatory variables, we generated a correlation model with a correlation coefficient of 0.926 (p < 0.001).

[0181] Then, for the remaining 7 data sets out of the total 18 data sets, the estimated values ​​of scaling index were calculated using the relational model and pH, conductivity, temperature, and turbidity. The correlation coefficient of the 7 data sets was 0.976 (p<0.001).

[0182] Figure 6 This is a graph showing the scaling index values ​​versus the estimated scaling index values ​​for a total of 18 data sets in Example 2. Figure 6 In the figure, the horizontal axis represents the estimated scaling index value obtained by regression analysis, and the vertical axis represents the scaling index value obtained based on temperature, pH, M alkalinity, and calcium hardness.

[0183] As described above, by using pH, conductivity, temperature, turbidity, and the relationship model, it is possible to calculate the estimated scaling index value related to the scaling index value without using the carbonate ion concentration and the calcium ion concentration.

[0184] Explanation of symbols

[0185] 1: Prediction system

[0186] 2: Prediction device

[0187] 3: Output unit or output device

[0188] 4: Water quality information measuring unit or water quality information measuring device

[0189] 5: Anti-scaling agent adding part or anti-scaling agent adding device

[0190] 20: Water Quality Information Acquisition Department

[0191] 21: Relational model information acquisition unit

[0192] 22: Presumption Department

[0193] 23: Forecasting Department

[0194] 24: Relational model creation department

[0195] 25: Prediction model creation department

[0196] 26: Prediction model information acquisition unit

[0197] 27: Scale inhibitor addition model making section

[0198] 28: Anti-scaling agent addition model information acquisition unit

[0199] 29: Addition amount determination section

[0200] 61: Ministry of Communications

[0201] 62: Storage

[0202] 63: Control Department

[0203] 64: Communication bus

Claims

1. A device for estimating a scaling index value of a water system, characterized in that: include: Water quality information acquisition unit, relational model information acquisition unit, and estimation unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relationship model information.

2. The estimation device according to claim 1, wherein: The relational model is a model obtained by regression analysis of the scaling index value and a scaling index estimation function which is a function of the water quality parameter.

3. The estimation device according to claim 1 or 2, wherein: The water quality parameters at least include conductivity.

4. A device for predicting scale formation in a water system, characterized in that: include: Water quality information acquisition unit, relational model information acquisition unit, estimation unit, and prediction unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The prediction unit predicts the presence or possibility of scale generation based on the scaling index estimated value.

5. A control device for adding a scale inhibitor to a water system, characterized in that: include: a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a previously created scale inhibitor addition model, the scale inhibitor addition model indicating a relationship between the estimated scaling index value and the amount of scale inhibitor added; The addition amount determination unit determines the addition amount of the scale inhibitor based on the scaling index estimated value and the scale inhibitor addition model information.

6. A system for estimating a scaling index value of a water system, characterized in that: include: Water quality information acquisition unit, relational model information acquisition unit, and estimation unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relationship model information.

7. A system for predicting scale formation in a water system, characterized in that: include: Water quality information acquisition unit, relational model information acquisition unit, estimation unit, and prediction unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The prediction unit predicts the presence or possibility of scale generation based on the scaling index estimated value.

8. A control system for adding a scale inhibitor to a water system, characterized in that: include: a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a previously created scale inhibitor addition model, the scale inhibitor addition model indicating a relationship between the estimated scaling index value and the amount of scale inhibitor added; The addition amount determination unit determines the addition amount of the scale inhibitor based on the scaling index estimated value and the scale inhibitor addition model information.

9. A computer program product comprising a program for estimating a scaling index value of a water system, the program causing a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, and an estimation unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relationship model information.

10. A computer program product comprising a prediction program for scale formation in a water system, the prediction program causing a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, and a prediction unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The prediction unit predicts the presence or possibility of scale generation based on the scaling index estimated value.

11. A computer program product comprising a control program for adding a scale inhibitor to a water system, the control program causing a computer to function as a water quality information acquisition unit, a relational model information acquisition unit, an estimation unit, a scale inhibitor addition model information acquisition unit, and an addition amount determination unit; The water quality information acquisition unit acquires water quality information including water quality parameters, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; The relationship model information acquisition unit acquires relationship model information including a previously created relationship model, the relationship model representing a relationship between a scaling index value calculated from a function of the concentration of ions that can form scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; The estimating unit calculates a scaling index estimated value based on the water quality information and the relational model information; The scale inhibitor addition model information acquisition unit acquires scale inhibitor addition model information including a previously created scale inhibitor addition model, the scale inhibitor addition model indicating a relationship between the estimated scaling index value and the amount of scale inhibitor added; The addition amount determination unit determines the addition amount of the scale inhibitor based on the scaling index estimated value and the scale inhibitor addition model information.

12. A method for estimating a scaling index value of a water system, characterized in that: include: Water quality information acquisition process, relational model information acquisition process, and estimation process; In the water quality information acquisition step, water quality information including water quality parameters is acquired, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; In the relational model information acquisition step, relational model information including a relational model created in advance is acquired, the relational model representing a relationship between a scaling index value calculated as a function of the concentration of ions capable of forming scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; In the estimating step, a scaling index estimated value is calculated based on the water quality information and the relational model information.

13. A method for predicting scale formation in a water system, characterized in that: include: Water quality information acquisition process, relational model information acquisition process, estimation process, and prediction process; In the water quality information acquisition step, water quality information including water quality parameters is acquired, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; In the relational model information acquisition step, relational model information including a relational model created in advance is acquired, the relational model representing a relationship between a scaling index value calculated as a function of the concentration of ions capable of forming scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; In the estimating step, an estimated scaling index value is calculated based on the water quality information and the relational model information; In the prediction step, the presence or possibility of scale generation is predicted based on the scaling index estimated value.

14. A method for controlling the addition of a scale inhibitor to a water system, characterized in that: include: Water quality information acquisition process, relational model information acquisition process, estimation process, scale inhibitor addition model information acquisition process, and addition amount determination process; In the water quality information acquisition step, water quality information including water quality parameters is acquired, wherein the water quality parameters are two or more water quality parameters selected from the group consisting of at least pH, cation requirement, residual chlorine concentration, temperature, conductivity, suspended solids content, turbidity, and chromaticity of the water system, and the water quality parameters do not include the concentration of cations and anions that constitute scale; In the relational model information acquisition step, relational model information including a relational model created in advance is acquired, the relational model representing a relationship between a scaling index value calculated as a function of the concentration of ions capable of forming scale in the water system and the water quality parameter, wherein the scaling index value is a logarithmic value of a ratio of a product of valence powers of the concentrations of the respective ions to a solubility product of the respective ions; In the estimating step, an estimated scaling index value is calculated based on the water quality information and the relational model information; In the scaling inhibitor addition model information acquisition step, scaling inhibitor addition model information including a previously created scaling inhibitor addition model is acquired, wherein the scaling inhibitor addition model represents a relationship between the scaling index estimated value and the scaling inhibitor addition amount. In the addition amount determination step, the addition amount of the scale inhibitor is determined based on the scaling index estimated value and the scale inhibitor addition model information.

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