Water quality analysis apparatus, water quality analysis method, and program

Abstract

To provide a water quality analyzer capable of appropriately analyzing water quality, a water quality analysis method, and a program.SOLUTION: A water quality analysis device according to the present disclosure includes an acquisition unit that acquires a measurement value of a hydrogen ion concentration index of a target water that is water to be monitored, a measurement value of an electrical conductivity of the target water, and a measurement value of an acid electrical conductivity that is the electrical conductivity of the target water after passing through a cation exchange resin that adsorbs cations or after removing cations other than hydrogen ions, and an evaluation model unit that calculates water quality of the target water based on the measurement value of the hydrogen ion concentration index, the measurement value of the electrical conductivity, and the measurement value of the acid electrical conductivity.SELECTED DRAWING: FIG. 2A

Description

[Technical Field]

[0001] The present disclosure relates to a water quality analysis device, a water quality analysis method, and a program. [Background technology]

[0002] One of the most serious problems in gas turbine combined cycle engines is a seawater leak from the condenser. The condenser is equipped with cooling pipes through which seawater or other cooling water flows, cooling the steam. However, if the cooling pipes are damaged, such as by cracks or ruptures, for any reason, seawater can be mixed into the steam cycle feedwater, potentially causing serious corrosion damage due to impurities such as chloride ions, sulfate ions, sodium ions, and magnesium ions contained in the seawater.

[0003] For example, Patent Document 1 listed below discloses a water quality monitoring device for a turbine facility comprising a steam turbine operated by boiler steam, a condenser that condenses exhaust gas from the steam turbine, and a feedwater system that sends the condensed water condensed in the condenser to the heat recovery boiler side, characterized in that the water quality monitoring device for a turbine facility is equipped with an electrical conductivity meter that extracts a portion of feedwater to which ammonia has been added as an agent for preventing iron corrosion and measures the electrical conductivity of the feedwater, a cation exchange resin that is provided downstream of the electrical conductivity meter and adsorbs cations in the feedwater, and an acid electrical conductivity meter that is provided downstream of the cation exchange resin and measures the electrical conductivity of the feedwater after the cations have been removed. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2009-243972 Summary of the Invention [Problem to be solved by the invention]

[0005] The water quality monitoring device described in Patent Document 1 measures both electrical conductivity and acid electrical conductivity. However, if either seawater or carbon dioxide is mixed into the feedwater, for example, both will increase the acid electrical conductivity of the feedwater, and it is not possible to determine which of the two components is causing the increase. For example, there is room for improvement in order to properly analyze the water quality of the monitored object.

[0006] In view of the above-mentioned problems, the present disclosure aims to provide a water quality analysis device, a water quality analysis method, and a program that can appropriately analyze water quality. [Means for solving the problem]

[0007] The water quality analysis device of the present disclosure includes an acquisition unit that acquires a measured value of a hydrogen ion concentration index for target water, which is water to be monitored, a measured value of electrical conductivity for the target water, and a measured value of acid electrical conductivity, which is the electrical conductivity of the target water after passing the target water through a cation exchange resin that adsorbs cations or after removing cations other than hydrogen ions, and an evaluation model unit that calculates the water quality of the target water based on the measured value of the hydrogen ion concentration index, the measured value of electrical conductivity, and the measured value of acid electrical conductivity.

[0008] The water quality analysis method according to the present disclosure includes the steps of obtaining a measured value of a hydrogen ion concentration index for target water, which is water to be monitored, a measured value of electrical conductivity for the target water, and a measured value of acid electrical conductivity, which is the electrical conductivity of the target water after passing it through a cation exchange resin that adsorbs cations, and calculating the water quality of the target water based on the measured value of the hydrogen ion concentration index, the measured value of electrical conductivity, and the measured value of acid electrical conductivity.

[0009] The program of the present disclosure causes a computer to execute the steps of acquiring a measured value of hydrogen ion concentration index for target water, which is water to be monitored, a measured value of electrical conductivity for the target water, and a measured value of acid electrical conductivity, which is the electrical conductivity of the target water after it has been passed through a cation exchange resin that adsorbs cations, and calculating the water quality of the target water based on the measured value of hydrogen ion concentration index, the measured value of electrical conductivity, and the measured value of acid electrical conductivity. [Effects of the Invention]

[0010] According to the present disclosure, it is possible to provide a water quality analysis device, a water quality analysis method, and a program that can appropriately analyze water quality. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a power generation plant according to the present disclosure. [Figure 2A] FIG. 2A is a diagram illustrating a specific example of the configuration of a power plant according to the present disclosure. [Figure 2B] FIG. 2B is a diagram illustrating an example of the configuration of a measuring instrument. [Figure 3] FIG. 3 is a diagram illustrating the action of the cation exchange resin according to the present disclosure. [Figure 4] FIG. 4 is a diagram showing the behavior of changes in each parameter when a foreign substance is mixed into the target water. [Figure 5] FIG. 5 is a diagram illustrating an overview of the evaluation model according to the present disclosure. [Figure 6] FIG. 6 is a diagram showing an example of the configuration of a water quality analysis device according to the present disclosure. [Figure 7] FIG. 7 is a diagram showing an example of information stored in the measurement data storage unit of the water quality analyzer according to the present disclosure. [Figure 8] FIG. 8 is a diagram showing an example of information stored in the determination criteria storage unit of the water quality analyzer according to the present disclosure. [Figure 9] FIG. 9 is a diagram showing an example of a display screen by the output unit of the water quality analyzer according to the present disclosure. [Figure 10] FIG. 10 is a flowchart showing the flow of the water quality analysis method according to the present disclosure. [Figure 11] FIG. 11 is a diagram showing an overview of an evaluation scheme for comparison with calculation software for the evaluation model according to the present disclosure. [Figure 12] FIG. 12 is a diagram showing the results of comparison between the calculated values ​​of the ammonia concentration evaluation model and the calculated values ​​of the calculation software. [Figure 13] FIG. 13 is a diagram showing the results of comparison between the calculated values ​​of the carbon dioxide concentration evaluation model and the calculated values ​​of the calculation software. [Figure 14] FIG. 14 is a diagram showing the results of comparison between the calculated values ​​of the evaluation model for the amount of seawater mixed in and the calculated values ​​of the calculation software. [Figure 15] FIG. 15 is a diagram showing the results of a comparison between the measured values ​​of the power plant when carbon dioxide is mixed in and the calculated values ​​of the evaluation model. [Figure 16] FIG. 16 is a diagram showing the results of a comparison between the measured values ​​of the power plant when seawater is mixed in and the calculated values ​​of the evaluation model. [Figure 17] FIG. 17 is a hardware configuration diagram showing an example of a computer that realizes the functions of the water quality analysis device according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. However, the present disclosure is not limited to the embodiments described below.

[0013] The water quality analysis device 100 according to this embodiment is a device that inspects the water quality of target water W to be monitored. The target water W may be any medium containing water, but in this embodiment, it is preferably water containing ammonia, and more specifically, it is preferably water used in an environment where at least one of seawater and carbon dioxide (in this example, both) may be added. In this embodiment, the water quality analysis device 100 monitors the quality of the water used in the power plant 1, using the target water W as water used in the power plant 1 (including at least one of condensate, feedwater, steam, and boiler water (if sodium phosphate is added to the boiler water, it is excluded from the target water W)).

[0014] (Power plant configuration) A power plant 1 according to this embodiment will be described with reference to Figs. 1 and 2A. Fig. 1 is a diagram showing an example of the configuration of a power plant according to the present disclosure, and Fig. 2A is a diagram showing a specific example of the configuration of a power plant according to the present disclosure. As shown in Fig. 1, the power plant 1 according to the present disclosure includes a water quality analysis device 100, a steam utilization section 200, a steam generation section 300, piping 400, an addition section 500, and a measuring instrument 600. The configuration of these components will be briefly described below.

[0015] The water quality analysis device 100 is a device that analyzes the quality of the target water W of the power plant 1. As shown in Figures 1 and 2A, the water quality analysis device 100 is connected to a measuring instrument 600 provided in a pipe 400 through which the target water W flows between the steam utilization unit 200 and the steam generation unit 300, so as to be able to exchange information by wire or wirelessly. Details of the water quality analysis device 100 will be described later.

[0016] As shown in FIG. 2A, the steam utilization section 200 includes a steam turbine 210 and a condenser 220.

[0017] The steam turbine 210 rotates a turbine using high-temperature, high-pressure steam, converting the thermal energy of the steam into rotational energy, which then rotates a generator to generate electricity. The steam turbine 210 includes a rotor stage with multiple moving blades attached to a rotating shaft, and a stator stage with multiple stationary blades. That is, the steam turbine 210 converts the thermal energy of the steam into rotational energy by changing the direction of the steam using the stator stage and directing the steam against the rotor stage. The steam turbine 210 is connected to a generator (not shown).

[0018] The condenser 220 cools and condenses the exhaust gas from the steam turbine 210 to produce condensed water. The condenser 220 may be implemented as a direct contact condenser that cools and condenses steam by contacting steam flowing into the body with cooling pipes that pass through the body and through which cooling water such as seawater flows. The condensed water generated in the condenser 220 is introduced into the steam generating section 300 via piping 400 by a condensate pump.

[0019] The steam generating unit 300 generates steam to be supplied to the steam turbine 210. Specifically, the steam generating unit 300 may be a heat recovery boiler of a gas turbine combined cycle plant, a boiler of a waste incineration energy plant, or a nuclear reactor of a nuclear power plant. The boiler of a waste incineration energy plant generates steam by heat exchange with combustion exhaust gas generated by waste incineration. The nuclear reactor of a nuclear power plant includes a reactor pressure vessel, a reactor containment vessel, a steam generator, primary piping, secondary piping, a pressurizer, etc. The nuclear reactor of a nuclear power plant generates steam using heat generated by nuclear fission while controlling the fuel rods. In the detailed description of the steam generating unit 300 described below, a case will be described in which the steam generating unit 300 is a heat recovery boiler.

[0020] The piping 400 supplies the target water W condensed in the condenser 220 to the steam generating section 300, and supplies the steam generated in the steam generating section 300 to the steam turbine 210. Note that although the piping 400 is depicted as a single pipe in FIG. 1, as shown in FIG. 2A, the piping 400 includes a pipe 400A that supplies the condensed water of the condenser 220 to the steam generating section 300, and a pipe 400B that supplies the steam generated in the steam generating section 300 to the steam turbine 210.

[0021] 1, the network N connects the water quality analysis device 100 and the measuring instrument 600 so that they can exchange information with each other. If the network N is wired, it may be realized by ETHERNET (registered trademark) as defined in IEEE802.3, a USB (Universal Serial Bus) cable, or various control signal cables. If the network N is wireless, it may be realized by a wireless LAN (Local Area Network) as defined in IEEE802.11.

[0022] (Steam generation section) Next, the configuration of the steam generating unit 300 according to the present disclosure will be described with reference to Fig. 2A. In Fig. 2A, in addition to the configuration of the steam generating unit 300, the water quality analyzing device 100, the steam turbine 210, and the condenser 220 are shown, and their relationships are illustrated; however, these have been briefly explained above, so their explanation will be omitted. When the steam generating unit 300 is a heat recovery boiler, high-temperature exhaust gas is supplied from a gas turbine (not shown), and steam is generated inside the heat recovery boiler via a superheater, and the generated steam is sent to the steam turbine 210, where work is performed.

[0023] The steam generating section 300 includes a flue 320, an economizer 330, a drum 340, an evaporator 350, and a superheater 360. A pipe 400 is connected to the steam generating section 300. In order to improve the heat recovery rate, the steam generating section 300 may be provided with multiple stages (e.g., high-pressure, medium-pressure, and low-pressure) of economizers 330, drums 340, evaporators 350, and superheaters 360 in the flue 320. These components will be described in order below.

[0024] The flue 320 is a structure that serves as a flow path for exhaust gas from the gas turbine. As shown in Fig. 2A, an economizer 330, an evaporator 350, and a superheater 360 are provided inside the flue 320. That is, inside the flue 320, heat exchange occurs between the feedwater or steam flowing inside these components and the exhaust gas from the gas turbine.

[0025] The economizer 330 is a heat exchanger that preheats the feedwater before supplying it to the drum 340. The economizer 330 heats the feedwater by exchanging heat with the exhaust gas from the gas turbine. As shown in Fig. 2A, the economizer 330 is provided downstream of the exhaust gas from the gas turbine in the flue 320.

[0026] The drum 340 receives condensate from the condenser 220 via the economizer 330, stores the feedwater, and separates the feedwater from the steam. That is, the flow path on the outlet side of the economizer 330 is connected to the drum 340. The drum 340 is also connected to the evaporator 350, which will be described later.

[0027] The evaporator 350 heats and evaporates the feedwater stored in the drum 340. That is, the feedwater from the drum 340 is superheated in the evaporator 350 and circulated back to the source, and the steam and the feedwater are separated inside the drum 340. The steam separated in the drum 340 is then supplied to the superheater 360, which will be described later.

[0028] The superheater 360 is a heat exchanger that further superheats the steam from the drum 340. The superheater 360 heats the wet steam to a temperature equal to or higher than the saturation temperature to produce superheated steam for delivery to the steam turbine. A portion of the steam from the superheater 360 may be introduced into the steam turbine 210 for cooling the high-temperature section of the steam turbine 210.

[0029] (Additional part) The doping unit 500 is connected to the piping 400 and is a device that adds a pH adjuster to the feedwater (target water W) flowing through the piping 400. In this embodiment, the doping unit 500 is connected to the piping 400A and supplies the pH adjuster to the feedwater supplied from the condenser 220 to the steam generating unit 300. The pH adjuster may contain any component, but in this embodiment, it contains ammonia. Generally, if the pH of the feedwater falls below 9.0, erosion and corrosion may occur in various components of the gas turbine combined cycle. For this reason, ammonia is added to the feedwater to maintain the pH of the feedwater inside the drum 270 at 9.0 or higher. Ammonia is easily evaporative and, as the pressure decreases, it is more likely to mix with the gas phase (it is less likely to remain in the liquid phase). Therefore, sodium phosphate may be used to prevent a decrease in pH because ammonia is easily volatilized.

[0030] (Measuring Instruments) The measuring instrument 600 is a device for measuring the water quality of the target water W. The measuring instrument 600 is connected to the piping 400 or the steam generating unit 300, and measures the target water W in the piping 400 or the target water W in the steam generating unit 300. In the example of FIG. 2A , measuring instruments 600A, 600B, 600C, 600D, and 600E are provided as the measuring instrument 600. The measuring instrument 600A is connected to the piping 400A between the connection point with the adding unit 500 and the condenser 220. The measuring instrument 600B is connected to the piping 400A between the connection point with the adding unit 500 and the steam generating unit 300 (economiser 330). The measuring instrument 600C is connected to the piping 400B between the drum 340 and the superheater 360. The measuring instrument 600D is connected to the drum 340. The measuring instrument 600E is connected to the piping 400B between the steam generating section 300 (superheater 360) and the steam turbine 210. When the target water W is gaseous steam inside the piping 400, it may be cooled by a cooler to become condensed water, and measurements may be performed on this condensed water. The measuring instrument 600 does not necessarily have to include all of the measuring instruments 600A to 600E, and at least one of them may be provided.

[0031] FIG. 2B is a diagram showing an example of the configuration of the measuring device. The measuring device 600 measures the hydrogen ion concentration exponent (pH) of the target water W, the electrical conductivity of the target water W, and the acid electrical conductivity, which is the electrical conductivity of the target water W after passing through a cation exchange resin. In other words, the acid electrical conductivity is the electrical conductivity of the target water W after passing through a cation exchange resin. + ) or hydrogen ions (H +) can be referred to as the electrical conductivity after ion exchange with cation exchange resin 620. Specifically, as shown in FIG. 2B , measuring instrument 600 has main pipe 610, branch pipes 610A, 610B, and 610C, cation exchange resin 620, acid electrical conductivity meter 630A, electrical conductivity meter 630B, and pH meter 630C. Main pipe 610 is connected to power plant 1 (piping 400 or steam generating section 300 in this example) and is a pipe through which target water W flows. Branch pipes 610A, 610B, and 610C are pipes branching off from main pipe 610, and target water W is supplied from main pipe 610. Cation exchange resin 620 is a cation exchange membrane provided in branch pipe 610A and adsorbs cations. Acid conductivity meter 630A is provided in branch pipe 610A downstream of cation exchange resin 620 and measures the electrical conductivity of target water W after cation removal. Electrical conductivity meter 630B is provided in branch pipe 610B and measures the electrical conductivity of target water W. A pH meter is provided in branch pipe 610C and measures the hydrogen ion concentration exponent pH of target water W.

[0032] However, the configuration of measuring instrument 600 shown in Fig. 2B is one example, and is not limited to the configuration shown in Fig. 2B in which target water W sampled from the same location on piping 400 by main pipe 610 is branched off by branch pipes to perform each measurement. For example, the configuration may be such that each measurement is performed using target water W sampled at different locations on piping 400.

[0033] Acid electrical conductivity is an index for evaluating soluble salts containing anions other than hydroxide ions, and can be obtained by measuring the electrical conductivity of the target water W after cation removal. The electrical conductivity meter and acid electrical conductivity meter may be electrode-type, and electrical conductivity is determined by passing an alternating current between sensor electrodes immersed in the solution and measuring the resulting voltage. The measuring instruments 600 may be installed at multiple locations in the piping 400 or the water supply system connected thereto, and may be connected to the water quality analysis device 100 via wire or wirelessly to transmit and receive measurement value information.

[0034] The function of the cation exchange resin will now be described with reference to FIG. 3. FIG. 3 is a diagram illustrating the function of the cation exchange resin according to the present disclosure. Before passing through the cation exchange resin, the target water W is mostly composed of ammonia ions from the pH adjuster, and the electrical conductivity is strongly affected by the ammonia ions, making it difficult to detect chloride ions due to the inclusion of seawater. In contrast, when the water is passed through the cation exchange resin, the ammonia ions are removed by reacting with the cation exchange resin. The cation exchange resin may be a copolymer of styrene and p-divinylbenzene to which an acidic functional group such as a sulfonic acid group -SO3H has been introduced.

[0035] Specifically, a cation exchange resin with a sulfonic acid group -SO3H as an exchange group can exchange fixed ions -SO3 - and counterion H + This dissociates into hydrogen ions (H-form), which form ammonia (NH4 + ) cations and replace them with the original H + Therefore, after passing through the cation exchange resin, the influence of ammonia ions disappears and the counter ions of the anions become H + Therefore, it is highly sensitive to Cl - can be detected.

[0036] During steady-state operation of the power plant 1 described above, the condenser 220 is maintained at a high vacuum by a vacuum pump to improve thermal efficiency. However, if the operation of the power plant 1 is stopped and the vacuum in the condenser 220 is broken, atmospheric air flows into the condenser 220, and carbon dioxide from the atmosphere dissolves in the condensate. The inventors have found that, upon subsequent startup, carbon dioxide remains dissolved in the condensate, causing an increase in acid conductivity due to carbonate ions and bicarbonate ions. Therefore, it becomes difficult to quickly detect seawater leaks based on acid conductivity until the carbon dioxide is sufficiently discharged outside the water-steam cycle. Therefore, it is necessary to be able to appropriately analyze water quality even when carbon dioxide is present.

[0037] (Overview of water quality analyzer) Next, an overview of the water quality analysis device 100 according to the present disclosure will be described. The water quality analysis device 100 according to the present disclosure can appropriately analyze the water quality of the target water W by analyzing the water quality of the target water W as described below, and can appropriately analyze the water quality even when the target water W is contaminated with carbon dioxide.

[0038] FIG. 4 shows an overview of the changes in water quality when carbon dioxide and seawater are mixed into the target water W. FIG. 4 illustrates the changes in each parameter when a foreign substance is mixed into the target water W. As shown in FIG. 4, when an increase in acid conductivity is detected, it is impossible to determine whether the increase is due to carbon dioxide or seawater. However, the present inventors discovered that when carbon dioxide dissolves in the water-steam cycle, the pH decreases because carbon dioxide acts as an acid in water. However, because seawater is neutral, the pH hardly changes even when a trace amount of seawater is mixed in. Furthermore, the present inventors discovered that because carbon dioxide and seawater have different electrical conductivities per unit volume, the behavior of electrical conductivity also differs depending on the contaminating components. Focusing on this point, the present inventors developed an evaluation model for analyzing water quality based on acid conductivity, pH, and electrical conductivity, and implemented this evaluation model in the water quality analysis device 100.

[0039] Next, an overview of the evaluation model will be described with reference to Fig. 5. Fig. 5 is a diagram illustrating an overview of the evaluation model according to the present disclosure. As shown in Fig. 5, by inputting the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity measured in an actual power plant 1 into an evaluation model constructed by combining various mathematical formulas, the ammonia concentration, carbon dioxide concentration, and amount of mixed seawater can be calculated.

[0040] (Configuration of water quality analyzer) Next, the configuration of the water quality analysis device 100 according to the present disclosure will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the configuration of the water quality analysis device according to the present disclosure. As shown in Fig. 6, the water quality analysis device 100 according to the present disclosure includes a communication unit 110, a storage unit 120, a control unit 130, an input unit 140, and a display unit 150. Below, these components will be described in order.

[0041] The communication unit 110 is responsible for transmitting and receiving information to and from external devices and equipment. For example, the communication unit 110 is responsible for transmitting and receiving information to and from the measuring instrument 600. The communication unit 110 may be realized by, for example, a wireless LAN (Local Area Network) card, a serial communication interface device, an antenna, etc. Alternatively, the communication unit 110 may be realized by, for example, a HART (Highway Addressable Remote Transducer) communication modem, a ProfibusDP (registered trademark) communication connector, etc.

[0042] The storage unit 120 is a storage device that stores various types of information. The storage unit 120 includes a main storage device and an auxiliary storage device. The main storage device may be realized by a semiconductor memory element such as a random access memory (RAM), a read only memory (ROM), or a flash memory. The auxiliary storage device may be realized by a hard disk or a solid state drive (SSD), for example.

[0043] 6, the storage unit 120 includes a measurement data storage unit 121 and a determination criterion storage unit 122. An example of information stored by these components will be described below.

[0044] The measurement data storage unit 121 stores information related to various measurement data of the power plant 1. The measurement data of the power plant 1 includes measurement values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water W measured by the measuring instrument 600. An example of information stored in the measurement data storage unit 121 will now be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of information stored in the measurement data storage unit of the water quality analysis device according to the present disclosure.

[0045] As shown in FIG. 7, the measurement data storage unit 121 stores information relating to the items of "measurement time," "first hydrogen ion concentration index," "first electrical conductivity," and "first acid electrical conductivity."

[0046] "Measurement time" is information indicating the date and time when the measurement data was measured. "First hydrogen ion concentration index" is information indicating the hydrogen ion concentration index of the target water W drained at the first location of the power plant 1. "First electrical conductivity" is information indicating the electrical conductivity of the target water W drained at the first location of the power plant 1. "First acid electrical conductivity" is information indicating the acid electrical conductivity of the target water W drained at the first location of the power plant 1.

[0047] The measurement data storage unit 121 may store measurement values ​​for more locations and types.

[0048] That is, FIG. 7 shows an example in which a first hydrogen ion concentration index "FRPH#1", a first electrical conductivity "FRKP#1", and a first acid electrical conductivity "FRKPA#1-1", all measured at measurement time "TIME#1", are linked and stored.

[0049] The information stored in the measurement data memory unit 121 is not limited to information relating to the items "measurement time," "first pressure measurement value," "first temperature measurement value," and "first flow rate measurement value," but may also store information relating to various other measurement data of any power plant 1.

[0050] The judgment criterion storage unit 122 stores information related to the judgment criterion. As will be described later, the judgment criterion refers to a judgment criterion for the error between the calculated values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity calculated by the evaluation model and the measured values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity measured by the measuring instrument 600. Here, an example of information stored in the judgment criterion storage unit 122 will be described with reference to FIG. 8. FIG. 8 is a diagram showing an example of information stored in the judgment criterion storage unit of the water quality analysis device according to the present disclosure.

[0051] As shown in FIG. 8, the determination criterion storage unit 122 stores information relating to the items "threshold ID," "first threshold," "second threshold," and "third threshold."

[0052] "Threshold ID" is an identifier that identifies the threshold used for judgment, and is represented by a character string, a number, etc. "First threshold" is information that indicates the first threshold. "Second threshold" is information that indicates the second threshold. "Third threshold" is information that indicates the third threshold.

[0053] That is, FIG. 8 shows an example in which the first threshold "FRTRD#1", the second threshold "SCTRD#1", and the third threshold "THTRD#1" measured with the threshold ID "TRDID#1" are linked and stored.

[0054] The information stored in the judgment criteria storage unit 122 is not limited to information relating to the items "threshold ID," "first threshold," "second threshold," and "third threshold," but may also store information relating to any other judgment criteria.

[0055] The control unit 130 is a controller that manages the water quality analysis device 100. The control unit 130 is realized by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like executing various programs stored in the storage unit 120 using RAM as a work area. The control unit 130 may also be realized by an integrated circuit, such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0056] 6, control unit 130 includes acquisition unit 131, setting unit 132, calculated value calculation unit 133, error calculation unit 134, determination unit 135, and output unit 136. The configuration including setting unit 132, calculated value calculation unit 133, error calculation unit 134, and determination unit 135 is referred to as an evaluation model unit. In other words, it can be said that the evaluation model unit includes setting unit 132, calculated value calculation unit 133, error calculation unit 134, and determination unit 135.

[0057] The control unit 130 realizes these functions and executes these processes by reading and executing a program (software) from the storage unit 120. Note that these functions of the control unit 130 may be realized by electronic circuits. The control unit 130 may execute these processes using a single CPU, or may be provided with multiple CPUs that execute these processes in parallel. These configurations will be explained below in order.

[0058] (Water quality analysis equipment processing) (Acquisition of measurement values) The acquisition unit 131 acquires various measurement values ​​related to the power plant 1. For example, the acquisition unit 131 acquires measurement values ​​of the electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity of the target water W that becomes steam to be supplied to the steam turbine 210. That is, the acquisition unit 131 acquires the measurement values ​​of the electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity from a measuring instrument 600 provided in the power plant 1 via the communication unit 110 and the network N. After acquiring the measurement values ​​of the electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity, the acquisition unit 131 stores the acquired electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity in the measurement data storage unit 121.

[0059] (Water quality calculation) The evaluation model unit calculates the water quality of the target water W based on the measured values ​​of the electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity of the target water W. The water quality calculated by the evaluation model unit may be any parameter that can be calculated from the electrical conductivity, hydrogen ion concentration index, and acid electrical conductivity, but in this embodiment, it is at least one of the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in the target water W, and more preferably all of the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in.

[0060] The evaluation model unit may calculate the water quality of the target water W using any method based on the above-mentioned measurement values, but it is preferable to calculate the water quality (particularly the carbon dioxide concentration and the amount of seawater mixed in) based on the difference between the change in hydrogen ion concentration index when carbon dioxide is mixed into the target water W and the change in hydrogen ion concentration index when seawater is mixed into the target water W. Furthermore, it is preferable for the evaluation model unit to calculate the water quality so that the lower the hydrogen ion concentration index of the target water W, the higher the carbon dioxide concentration. It is also preferable for the evaluation model unit to calculate the water quality so that the lower the hydrogen ion concentration index of the target water W, the less seawater is mixed in. It is also preferable for the evaluation model unit to calculate the water quality (particularly the carbon dioxide concentration and the amount of seawater mixed in) based on the difference between the change in electrical conductivity when carbon dioxide is mixed into the target water W and the change in electrical conductivity when seawater is mixed into the target water W.

[0061] A specific example of the method for calculating water quality in this embodiment will be described below.

[0062] (Setting provisional values) The setting unit 132 sets provisional values ​​(initial values ​​in the first calculation) of the ammonia concentration, carbon dioxide concentration, and amount of mixed seawater to be input into the evaluation model. Here, X represents the ammonia concentration, Y represents the carbon dioxide concentration, and Z represents the amount of mixed seawater. Note that X, Y, and Z are symbols used in the formulas that appear in the following explanation and refer to the same thing. Note that these initial values ​​may be set as values ​​within a predetermined range.

[0063] For example, the setting unit 132 may set the initial value of X to an ammonia concentration equivalent to a pH of 9.8 to 10.1, which is expected to be around target water WpH=10, in an actual plant that conforms to AVT (All Volatile Treatment) (LO) specified in JIS B 8223 and applies High-AVT (LO), which indicates that the target water WpH is 9.8 or higher. The setting unit 132 may set the initial value of Y based on a carbon dioxide concentration actually measured at the start of the actual plant. The setting unit 132 may set the initial value of Z to a value in the range of 0.5 μS / cm to 1.0 μS / cm, which is the feedwater management reference value and the reference value for determining a large-scale seawater leakage specified in JIS B 8223.

[0064] The setting unit 132 determines the sum of errors ε T If it is determined that the absolute value of is not equal to or less than the predetermined threshold, and an instruction to return to the processing of the setting unit 132 is given, the sum of errors ε T Based on the absolute value of the above, the provisional values ​​of X, Y, and Z may be reset using the Newton-Raphson method or a genetic algorithm (GA).

[0065] (Calculation of water quality values) The calculated value calculation unit 133 calculates the calculated values ​​of the hydrogen ion concentration exponent, the electrical conductivity, and the acid electrical conductivity based on the provisional values ​​of X, Y, and Z. An example of a method for calculating the calculated values ​​will be described below.

[0066] The calculated value calculation unit 133 calculates a calculated value of the water quality (oxygen ion concentration index of the target water W) based on the set provisional values ​​of X, Y, and Z and the first relational expression. The first relational expression is an expression that uses the ammonia concentration, carbon dioxide concentration, and amount of mixed seawater as variables and indicates that the amounts of cations and anions in the target water W are equal. That is, the calculated value calculation unit 133 calculates a calculated value of the oxygen ion concentration index of the target water W by substituting the provisional values ​​of X, Y, and Z for the variables of the ammonia concentration, carbon dioxide concentration, and amount of mixed seawater in the first relational expression. An example of the first relational expression is shown in Equation (1). That is, in this example, the calculated value calculation unit 133 uses the following Equation (1) to calculate C H : Calculate the hydrogen ion concentration of the target water W.

[0067] where K N is the dissociation constant of ammonia, γ=1+K N C H , C SC is the cation concentration in seawater, K W is the dissociation constant of water, K C1 is the dissociation constant of carbon dioxide, K C2 is the dissociation constant of bicarbonate ion, β=1+K C1 / C H +K C1 K C2 / C H 2 , C dSA is the total carbon dioxide concentration in seawater, C SA is the concentration of cations in seawater excluding carbon dioxide.

[0068]

number

[0069] Next, the calculation value calculation unit 133 calculates C H : Based on the hydrogen ion concentration, the hydrogen ion concentration index (pH) is calculated using equation (2).

[0070]

number

[0071] Furthermore, the calculated value calculation unit 133 calculates a calculated value of the water quality (electrical conductivity of the target water W) based on the set provisional values ​​of X, Y, and Z and the second relational expression. The second relational expression is an expression that shows the relationship between the ammonia concentration, carbon dioxide concentration, amount of mixed seawater, and electrical conductivity. More specifically, the second relational expression is preferably an expression that shows the relationship between the ammonia concentration, carbon dioxide concentration, amount of mixed seawater, and hydrogen ion concentration, and electrical conductivity. That is, the calculated value calculation unit 133 substitutes the provisional values ​​of X, Y, and Z for the variables of the ammonia concentration, carbon dioxide concentration, and amount of mixed seawater in the second relational expression, and substitutes the calculated value of the hydrogen ion concentration for the variable of the hydrogen ion concentration in the second relational expression to calculate the calculated value of the electrical conductivity of the target water W. An example of the second relational expression is shown in Equation (3). That is, in this example, the calculated value calculation unit 133 calculates the calculated value of the electrical conductivity of the target water W using X: ammonia concentration, Y: carbon dioxide concentration, Z: amount of mixed seawater, and C H κ: Electrical conductivity is calculated based on the hydrogen ion concentration using the following formula (3).

[0072]

number

[0073] Here, λ H is the molar electrical conductivity of hydrogen ions, λ NH4 is the molar conductivity of ammonium ions, λ SC is the molar electrical conductivity of cations in seawater, λ OH is the molar conductivity of hydroxide ions, λ HCO3 is the molar conductivity of bicarbonate ions, λ CO3 is the molar electrical conductivity of carbonate ions, λ SA is the molar electrical conductivity of the anions in seawater excluding carbon dioxide.

[0074] Furthermore, the calculated value calculation unit 133 calculates a calculated value of the water quality of the target water W (hydrogen ion concentration of the target water W after passing through the cation exchange resin) based on the set provisional values ​​of Y and Z and the third relational expression. The third relational expression is an expression that uses the carbon dioxide concentration and the amount of mixed seawater as variables and indicates that the amounts of cations and anions in the target water W after passing through the cation exchange resin are equal. That is, the calculated value calculation unit 133 substitutes the provisional values ​​of Y and Z for the variables of the carbon dioxide concentration and the amount of mixed seawater in the third relational expression to calculate a calculated value of the hydrogen ion concentration of the target water W after passing through the cation exchange resin. An example of the third relational expression is shown in Equation (4). That is, in this example, the calculated value calculation unit 133 calculates C using the following Equation (4) based on Y: carbon dioxide concentration and Z: amount of mixed seawater. H * : Calculate the hydrogen ion concentration after passing through the cation exchange resin.

[0075]

number

[0076] The calculated value calculation unit 133 also calculates a calculated value of the water quality (the acid electrical conductivity of the target water W) based on the provisional values ​​of Y and Z and the fourth relational expression. The fourth relational expression is an expression that shows the relationship between the carbon dioxide concentration, the amount of seawater mixed in, and the acid electrical conductivity. More specifically, the fourth relational expression is preferably an expression that shows the relationship between the carbon dioxide concentration, the amount of seawater mixed in, the hydrogen ion concentration of the target water W, and the hydrogen ion concentration of the target water W after passing through a cation exchange resin, and the acid electrical conductivity. That is, the calculated value calculation unit 133 substitutes the provisional values ​​of Y and Z for the variables of the carbon dioxide concentration and the amount of seawater mixed in the fourth relational expression, substitutes the calculated value of the hydrogen ion concentration for the variable of the hydrogen ion concentration in the fourth relational expression, and substitutes the calculated value of the hydrogen ion concentration after passing through a cation exchange resin for the variable of the hydrogen ion concentration after passing through a cation exchange resin in the fourth relational expression, thereby calculating the calculated value of the acid electrical conductivity of the target water W. An example of the fourth relational expression is shown in Equation (5). That is, in this example, the calculated value calculation unit 133 calculates C H * : Hydrogen ion concentration after passing through the cation exchange resin, CH κ is calculated using the following equation (5) based on: hydrogen ion concentration, Y: carbon dioxide concentration, and Z: amount of seawater mixed in. * : Calculate the acid conductivity.

[0077]

number

[0078] Here, β * is expressed by the following equation (6).

[0079]

number

[0080] (Calculation of error) The determination unit 135 calculates the water quality of the target water W (in this example, the determined values ​​of X, Y, and Z) based on the error between the measured values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water W acquired by the acquisition unit 131 and the calculated values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water W calculated by the calculated value calculation unit 133. If this error is within a predetermined range (i.e., if the judgment criterion is met), the determination unit 135 sets the provisional values ​​of the water quality (in this example, the provisional values ​​of X, Y, and Z) used to calculate the calculated values ​​as the water quality of the target water W (the determined value of the water quality).

[0081] In the example of this embodiment, the error calculation unit 134 calculates the sum of the errors between the hydrogen ion concentration exponent, electrical conductivity, and acid electrical conductivity obtained from the measured values ​​and the hydrogen ion concentration exponent, electrical conductivity, and acid electrical conductivity obtained by calculation.

[0082] First, the error calculation unit 134 calculates the measured value pH mea and the calculated hydrogen ion concentration pH cal Error ε pH is calculated using the following equation (7): where A1 is a normalization factor, which may be 100, for example.

[0083]

number

[0084] Next, the error calculation unit 134 calculates the measured value κ of the electrical conductivity mea and the measured electrical conductivity κ cal Error ε κ is calculated using the following equation (8): where A2 is a normalization factor, which may be 1, for example.

[0085]

number

[0086] Next, the error calculation unit 134 calculates the measured value κ of the acid electrical conductivity * mea and the measured value of acid electrical conductivity κ * cal Error ε κ * is calculated using the following equation (9): where A3 is a normalization factor, which may be 50, for example.

[0087]

number

[0088] Next, the error calculation unit 134 calculates the sum ε of these errors using the following equation (10): T Calculate.

[0089]

number

[0090] The determination unit 135 determines whether the absolute value of the sum of the errors is equal to or less than a predetermined threshold. Here, the predetermined threshold may be set arbitrarily, for example, 1×10 -4 Specifically, the determination unit 135 determines the measured value pH of the hydrogen ion concentration exponent. mea and the calculated value of hydrogen ion concentration exponent pH cal Error εpH , the measured value of electrical conductivity κ mea and the measured electrical conductivity κ cal Error ε κ , the measured value of acid conductivity κ * mea and the measured value of acid electrical conductivity κ * cal Error ε κ * The sum of ε T It is determined whether the absolute value of is equal to or less than a predetermined threshold value.

[0091] The decision unit 135 calculates the sum of the errors ε T is not equal to or less than the predetermined threshold, the determination unit 135 instructs the setting unit 132 to return to the processing, and executes the subsequent processing by the calculated value calculation unit 133, the error calculation unit 134, and the determination unit 135. T This is repeated until it is determined that the absolute value of is equal to or less than a predetermined threshold value.

[0092] On the other hand, the decision unit 135 determines the sum of the errors ε T If it is determined that the absolute value of is equal to or less than the predetermined threshold, the determination unit 135 ends the process and passes the values ​​of X, Y, and Z at this point to the output unit 136.

[0093] (Water quality output) The output unit 136 displays the calculation results of the measurement values ​​on the display unit 150. FIG. 9 is a diagram showing an example of a display screen displayed by the output unit of the water quality analysis device according to the present disclosure. As shown in FIG. 9, the output unit 136 may display, for example, a graph showing the time series change in the output of the generator of the power plant 1, a graph showing the time series change in the ammonia concentration, a graph showing the time series change in the amount of seawater mixed in, and evaluation values ​​for these graphs side by side. In addition, guidance showing the results of an overall evaluation of these monitoring items may be displayed as text. In other words, the total value of the evaluation values ​​and the guidance text may be associated and stored in the memory unit 120.

[0094] The input unit 140 receives various types of operation information from an operation manager or the like. The input unit 140 may be realized by an input device such as a keyboard, a mouse, a lever, or a switch. The operation manager inputs, via the input unit 140, operation information for operating various devices of the power plant 1, operation information for displaying a GUI (Graphical User Interface) showing various types of information related to the power plant 1, and the like.

[0095] The display unit 150 is a display device that displays various types of information. For example, the display unit 150 may display flow rate measurements, pressure measurements, temperature measurements, and the like related to the power plant 1 in a time-series graph. The display unit 150 may be realized by, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, a micro LED (Light Emitting Diode) display, or the like.

[0096] (effect) According to the water quality analyzer 100 described above, the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity measured for the target water W can be input into the evaluation model to perform various calculations, thereby appropriately calculating the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in. Therefore, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0097] (Water quality analysis method) Next, the water quality analysis method according to the present disclosure will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the flow of the water quality analysis method according to the present disclosure. Below, the water quality analysis method according to the present disclosure will be described along the flow shown in Fig. 10.

[0098] First, the water quality analyzer 100 sets provisional values ​​(initial values ​​in the first calculation) for X: ammonia concentration, Y: carbon dioxide concentration, and Z: amount of seawater mixed in (step S101). Next, the water quality analyzer 100 calculates C using formula (1) based on the set X, Y, and Z. HNext, the water quality analyzer 100 calculates the hydrogen ion concentration (step S102). H Next, the water quality analyzer 100 calculates the hydrogen ion concentration index (pH) using the formula (2) based on the hydrogen ion concentration (step S103). Next, the water quality analyzer 100 calculates the ammonia concentration, Y the carbon dioxide concentration, Z the amount of seawater mixed in, and C H Next, the water quality analyzer 100 calculates κ: electrical conductivity using equation (4) based on Y: carbon dioxide concentration and Z: amount of seawater mixed in (step S104). H * Calculate the hydrogen ion concentration after passing through the cation exchange resin (step S105).

[0099] Next, the water quality analyzer 100 H * κ is calculated using equation (5) based on: hydrogen ion concentration after passing through the cation exchange resin, Y: carbon dioxide concentration, and Z: amount of seawater mixed in. * Next, the water quality analyzer 100 calculates pH: hydrogen ion concentration exponent, κ: electrical conductivity, κ: acid electrical conductivity (step S106). * The error between the measured value and the calculated value of the acid electrical conductivity is calculated using equations (7) to (9) (step S107). Next, the water quality analyzer 100 calculates the total value of the errors using equation (10) (step S108). Next, the water quality analyzer 100 calculates the total value of the errors using equation (10) (step S109 ...). Next, the water quality analyzer 100 calculates the total value of the errors using equation (10). -4 ) (step S109). In step S109, it is determined whether the absolute value of the sum of the errors is 1×10 -4 If it is determined that the value is equal to or less than the predetermined value (step S109: Yes), the water quality analyzing device 100 ends the calculation (step S110).

[0100] In step S109, the absolute value of the sum of the errors is 1×10 -4 If it is determined that the concentrations are not equal to or greater than the above (step S109: No), the water quality analyzing apparatus 100 resets the provisional values ​​of X: ammonia concentration, Y: carbon dioxide concentration, and Z: amount of mixed seawater (step S111).

[0101] According to the water quality analysis method described above, the amount of seawater mixed in can be accurately detected even in the presence of carbon dioxide, and therefore, a water quality analysis method that can appropriately analyze water quality even in special environments can be provided.

[0102] (Regarding validation of the evaluation model) Next, the results of verifying the evaluation model implemented in the water quality analysis device 100 according to the present disclosure will be described. Specifically, for water quality simulating a water-steam cycle, X: ammonia concentration, Y: carbon dioxide concentration, and Z: amount of mixed seawater were calculated, and the validity of the evaluation model according to the present disclosure was evaluated by comparing with commercially available chemical equilibrium calculation software. The commercially available software OLI Analyzer ver. 11.0 (OLI Inc.) was used as the chemical equilibrium calculation software. An outline of the evaluation scheme for the validity of the evaluation model according to the present disclosure is shown in FIG. 11. FIG. 11 is a diagram showing an outline of the evaluation scheme for comparison with the calculation software of the evaluation model according to the present disclosure. As shown in FIG. 11, in the evaluation scheme, pH, κ, and κ were calculated using the OLI Analyzer for X: ammonia concentration, Y: carbon dioxide concentration, and Z: amount of mixed seawater, which are assumed in an actual device. * Calculate this pH, κ, κ * The ammonia concentration (X), carbon dioxide concentration (Y), and seawater inclusion amount (Z) calculated by the evaluation model using the above as input values ​​were compared with the input values ​​of the OLI Analyzer.

[0103] First, the results of a comparison between the calculated values ​​of the ammonia concentration evaluation model and the calculated values ​​of the calculation software will be described using FIG. 12. FIG. 12 is a diagram showing the results of a comparison between the calculated values ​​of the ammonia concentration evaluation model and the calculated values ​​of the calculation software. In FIG. 12, the horizontal axis shows the calculated values ​​of the ammonia concentration using the commercially available software, and the vertical axis shows the calculated values ​​of the ammonia concentration using the evaluation model according to the present disclosure. As shown in FIG. 12, the calculated values ​​of the ammonia concentration using the evaluation model according to the present disclosure and the calculated values ​​of the ammonia concentration using the commercially available software are in good agreement within a certain concentration range. Specifically, in the range of 5.1 to 17.9 mg / L, the error between the two is in the range of 0.0 to 1.6%.

[0104] Next, the comparison results between the calculated values ​​of the carbon dioxide concentration evaluation model and the calculated values ​​of the calculation software will be described using FIG. 13. FIG. 13 is a diagram showing the comparison results between the calculated values ​​of the carbon dioxide concentration evaluation model and the calculated values ​​of the calculation software. In FIG. 13, the horizontal axis shows the calculated values ​​of the carbon dioxide concentration of the calculation software, and the vertical axis shows the calculated values ​​of the carbon dioxide concentration of the evaluation model according to the present disclosure. As shown in FIG. 13, the calculated values ​​of the carbon dioxide concentration of the evaluation model according to the present disclosure and the calculated values ​​of the carbon dioxide concentration of the calculation software are in good agreement within a certain concentration range. Specifically, in the range of 0.1 to 5 mg / L, the error between the two is in the range of 0.0 to 18%.

[0105] Next, the results of comparison between the calculated values ​​of the evaluation model for the amount of seawater mixed in and the calculated values ​​of the calculation software will be explained using FIG. 14. FIG. 14 is a diagram showing the results of comparison between the calculated values ​​of the evaluation model for the amount of seawater mixed in and the calculated values ​​of the calculation software. In FIG. 14, the horizontal axis shows the calculated values ​​of the amount of seawater mixed in using the calculation software, and the vertical axis shows the calculated values ​​of the amount of seawater mixed in using the evaluation model according to the present disclosure. As shown in FIG. 14, the calculated values ​​of the amount of seawater mixed in using the evaluation model according to the present disclosure and the calculated values ​​of the amount of seawater mixed in using the calculation software are in good agreement within a certain concentration range. Specifically, in the range of 1×10 -6 From 5 x 10 -5 m 3 / m 3 In this range, the error between the two ranges from 0.0 to 20%.

[0106] Next, the comparison result between the measured value of the power plant 1 when carbon dioxide is mixed in and the calculated value of the evaluation model according to the present disclosure will be described with reference to Fig. 15. Fig. 15 is a diagram showing the comparison result between the measured value of the power plant when carbon dioxide is mixed in and the calculated value of the evaluation model. In Fig. 15, pH of the actual power plant 1 when carbon dioxide is mixed in is expressed as pH: hydrogen ion concentration exponent, κ: electrical conductivity, κ *:1 shows a graph showing time series changes in acid electrical conductivity, and a graph showing time series changes in X: ammonia concentration, Y: carbon dioxide concentration, and Z: amount of seawater mixed in the evaluation model. Y: carbon dioxide concentration calculated by the evaluation model according to the present disclosure, and measured κ *: The trend is consistent with the acid electrical conductivity, and is consistent with the results expected from the state of Power Plant 1 described above. In addition, Z: seawater contamination amount was below the lower limit of quantification (1 x 10 -6 m 3 / m 3 ) which is consistent with the results of manual analysis. From the above, it has been demonstrated that the evaluation model according to the present disclosure can accurately estimate the carbon dioxide concentration even in an actual power plant 1 when carbon dioxide is mixed in.

[0107] Next, a comparison result between the measured values ​​of the power plant 1 when seawater is mixed in and the calculated values ​​of the evaluation model according to the present disclosure will be described with reference to Fig. 16. Fig. 16 is a diagram showing the comparison result between the measured values ​​of the power plant when seawater is mixed in and the calculated values ​​of the evaluation model. In Fig. 16, pH of the actual power plant 1 when seawater is mixed in is expressed as pH: hydrogen ion concentration exponent, κ: electrical conductivity, κ *: The graphs show the time series changes in acid electrical conductivity and the time series changes in X (ammonia concentration), Y (carbon dioxide concentration), and Z (amount of seawater mixed in) of the evaluation model according to the present disclosure. The carbon dioxide concentration Y calculated by the evaluation model according to the present disclosure is 0 mg / L for all data, which is consistent with the expected behavior. Furthermore, for Z (amount of seawater mixed in), κ *: The transition is consistent with the acid electrical conductivity, and this is also considered to be appropriate behavior for the above-described state of the power plant 1. From the above, it was confirmed that the evaluation model according to the present disclosure can accurately estimate the amount of seawater mixed in even in an actual power plant 1.

[0108] As explained above, a comparison between the evaluation model according to the present disclosure and the calculation software showed good agreement between the two. Furthermore, when the evaluation model according to the present disclosure was used to calculate the carbon dioxide concentration and the amount of seawater mixed in for the water quality data of the actual power plant 1, the calculation results showed behavior consistent with the transitions expected from the state of the power plant 1, and reasonable results were obtained when compared with the water quality data of the actual power plant 1. As described above, the evaluation model according to the present disclosure makes it possible to detect seawater leakage early even when carbon dioxide is mixed in.

[0109] (Hardware configuration) The water quality analysis apparatus 100 according to the above-described embodiment is realized, for example, by a computer 1000 configured as shown in Fig. 17. Fig. 17 is a hardware configuration diagram showing an example of a computer that realizes the functions of the water quality analysis apparatus according to the present disclosure. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected via a bus 1090.

[0110] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device that stores data used by the arithmetic device 1030 for various calculations and various databases, and is realized by a ROM, HDD, flash memory, or the like.

[0111] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface), etc. The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, scanner, etc., and is realized by a USB, etc.

[0112] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

[0113] The network IF 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0114] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0115] For example, when the computer 1000 functions as the water quality analysis device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 of the water quality analysis device 100 by executing a program loaded onto the primary memory device 1040.

[0116] (Composition and Effects) The water quality analysis device 100 of the first embodiment includes an acquisition unit 131 that acquires a measured value of the hydrogen ion concentration index for the target water W, which is the water to be monitored, a measured value of the electrical conductivity for the target water W, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water W after passing it through a cation exchange resin that adsorbs cations or after removing cations other than hydrogen ions, and an evaluation model unit that calculates the water quality of the target water W based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity.

[0117] This configuration allows the water quality to be calculated appropriately using the measured values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity, thereby providing a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0118] The water quality analysis device 100 of the second embodiment is the water quality analysis device 100 of the first embodiment, and its evaluation model unit calculates at least one of the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in the target water W as the water quality of the target water W.

[0119] According to this configuration, the ammonia concentration, the carbon dioxide concentration, and the amount of mixed seawater can be calculated appropriately.

[0120] The water quality analysis device 100 of the third embodiment is the water quality analysis device 100 of the second embodiment, and its evaluation model unit calculates the water quality of the target water based on the difference between the change in hydrogen ion concentration index when carbon dioxide is mixed into the target water W and the change in hydrogen ion concentration index when seawater is mixed into the target water W.

[0121] With this configuration, the water quality of the target water W can be calculated based on the difference between the change in hydrogen ion concentration index when carbon dioxide is mixed into the target water W and the change in hydrogen ion concentration index when seawater is mixed into the target water W. Therefore, it is possible to provide a water quality analysis device 100 that can appropriately analyze water quality even in special environments.

[0122] The water quality analysis device 100 of the fourth embodiment is a water quality analysis device 100 of any one of the first to third embodiments, and its evaluation model unit calculates the water quality of the target water W based on the difference between the change in electrical conductivity when carbon dioxide is mixed into the target water W and the change in electrical conductivity when seawater is mixed into the target water W.

[0123] According to this configuration, the water quality of the target water W can be calculated based on the difference between the change in electrical conductivity when carbon dioxide is mixed into the target water W and the change in electrical conductivity when seawater is mixed into the target water W. Therefore, it is possible to provide a water quality analysis device 100 that can appropriately analyze water quality even in special environments.

[0124] The water quality analysis device 100 of the fifth embodiment is a water quality analysis device 100 of any one of the first to fourth embodiments, and its evaluation model unit includes a setting unit 132 that sets provisional values ​​for the water quality of the target water W, a calculated value calculation unit 133 that calculates calculated values ​​for the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water based on the provisional values, and a determination unit 135 that calculates the water quality based on the error between the measured values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water W and the calculated values ​​of the hydrogen ion concentration index, electrical conductivity, and acid electrical conductivity of the target water W.

[0125] According to this configuration, the error between the calculated value and the measured value can be used to calculate the water quality with high accuracy, and therefore, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0126] The water quality analysis device 100 of the sixth aspect is the water quality analysis device 100 of the fifth aspect, and when the error is equal to or less than a predetermined value, the judgment unit 135 sets the provisional value of the water quality used in calculating the error as the determined value of the water quality.

[0127] According to this configuration, the error between the calculated value and the measured value can be used to calculate the water quality with high accuracy. Therefore, it is possible to provide a water quality analysis device 100 that can appropriately analyze water quality even in special environments.

[0128] The water quality analysis device 100 of the seventh embodiment is a water quality analysis device 100 of any one of the second to sixth embodiments, and its evaluation model section calculates the water quality of the target water W based on a first relational equation in which the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in are variables and the amount of cations and anions in the target water W is equal.

[0129] According to this configuration, by using the first relational expression, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0130] The water quality analysis device 100 of the eighth aspect is the water quality analysis device 100 of any one of the second to seventh aspects, and its evaluation model unit calculates the water quality of the target water based on a second relational equation showing the relationship between the ammonia concentration, carbon dioxide concentration, and amount of seawater mixed in, and the electrical conductivity.

[0131] According to this configuration, by using the second relational expression, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0132] The water quality analysis device 100 of the ninth embodiment is a water quality analysis device 100 of any one of the second to eighth embodiments, and its evaluation model section calculates the water quality of the target water based on a third relational equation in which the carbon dioxide concentration and the amount of seawater mixed in are variables and the amount of cations and anions in the target water after passing through a cation exchange resin are equal.

[0133] According to this configuration, by using the third relational expression, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0134] The water quality analysis device 100 of the tenth aspect is the water quality analysis device 100 of any one of the second to ninth aspects, and its evaluation model unit calculates the water quality of the target water based on a fourth relational equation showing the relationship between the carbon dioxide concentration, the amount of seawater mixed in, and the acid electrical conductivity.

[0135] According to this configuration, by using the fourth relational expression, it is possible to provide a water quality analyzer 100 that can appropriately analyze water quality even in special environments.

[0136] The water quality analysis method according to the first embodiment includes the steps of obtaining a measured value of the hydrogen ion concentration index for target water W, which is the water to be monitored, a measured value of the electrical conductivity for the target water W, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water W after it has been passed through a cation exchange resin that adsorbs cations, and calculating the water quality of the target water W based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity.

[0137] According to this configuration, it is possible to provide a water quality analysis method that can appropriately analyze water quality even in special environments.

[0138] The program according to the first aspect of the invention is a water quality analysis method that causes a computer to execute the steps of acquiring a measured value of the hydrogen ion concentration index for target water W, which is the water to be monitored, a measured value of the electrical conductivity for the target water W, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water W after it has been passed through a cation exchange resin that adsorbs cations, and calculating the water quality of the target water W based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity.

[0139] This configuration makes it possible to provide a program that can appropriately analyze water quality even in special environments.

[0140] Although the embodiments of the present invention have been described above, the embodiments are not limited to the contents of these embodiments. Furthermore, the above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the scope of what is called equivalents. Furthermore, the above-described components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments. [Explanation of symbols]

[0141] 100 Water quality analyzer 110 Communications Department 120 Storage section 121 Measurement data storage unit 122 Judgment criteria storage unit 130 Control Unit 131 Acquisition Department 132 Settings 133 Calculation value calculation section 134 Error calculation section 135 Judgment section 136 Output section 140 Input section 150 Display section 200 Steam Utilization Section 210 Steam Turbine 220 Condenser 300 Steam generation unit 320 Flue 330 Economizer 340 drums 350 Evaporator 360 superheater 400 Piping 600 Measuring Instruments N Network

Claims

1. an acquisition unit that acquires a measured value of the hydrogen ion concentration index of the target water, which is the water to be monitored, a measured value of the electrical conductivity of the target water, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water after passing it through a cation exchange resin that adsorbs cations or after removing cations other than hydrogen ions; and an evaluation model unit that calculates the water quality of the target water based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity. Water quality analyzer.

2. The evaluation model unit calculates at least one of an ammonia concentration, a carbon dioxide concentration, and an amount of seawater mixed in the target water as the water quality of the target water. The water quality analyzer according to claim 1 .

3. the evaluation model unit calculates the water quality of the target water based on a difference between a change in hydrogen ion concentration index when carbon dioxide is mixed into the target water and a change in hydrogen ion concentration index when seawater is mixed into the target water. The water quality analysis device according to claim 2 .

4. The evaluation model unit calculates the water quality of the target water based on the difference between a change in electrical conductivity when carbon dioxide is mixed into the target water and a change in electrical conductivity when seawater is mixed into the target water. The water quality analysis device according to claim 3.

5. The evaluation model unit includes a setting unit that sets a provisional value of the water quality of the target water; a calculation unit that calculates values ​​of a hydrogen ion concentration index, an electrical conductivity, and an acid electrical conductivity of the target water based on the provisional values; a determination unit that calculates the water quality based on the errors between the measured values ​​of the hydrogen ion concentration index, the electrical conductivity, and the acid electrical conductivity of the target water and the calculated values ​​of the hydrogen ion concentration index, the electrical conductivity, and the acid electrical conductivity of the target water; Equipped with The water quality analyzer according to claim 1 .

6. When the error is equal to or smaller than a predetermined value, the determination unit determines the provisional value of the water quality used in calculating the error as the determined value of the water quality. The water quality analysis device according to claim 5.

7. The evaluation model unit calculates the water quality of the target water based on a first relational expression in which the ammonia concentration, the carbon dioxide concentration, and the amount of seawater mixed in are variables and the amounts of cations and anions in the target water are equal. The water quality analysis device according to claim 2 .

8. The evaluation model unit calculates the water quality of the target water based on a second relational expression showing the relationship between the ammonia concentration, the carbon dioxide concentration, and the amount of seawater mixed in, and the electrical conductivity. The water quality analysis device according to claim 2 .

9. The evaluation model unit calculates the water quality of the target water based on a third relational expression in which the carbon dioxide concentration and the amount of seawater mixed in are variables and the amount of cations and anions in the target water after passing through the cation exchange resin are equal. The water quality analysis device according to claim 2 .

10. The evaluation model unit calculates the water quality of the target water based on a fourth relational expression showing the relationship between the carbon dioxide concentration, the amount of seawater mixed in, and the acid electrical conductivity. The water quality analysis device according to claim 2 .

11. A step of obtaining a measured value of the hydrogen ion concentration index of the target water, which is the water to be monitored, a measured value of the electrical conductivity of the target water, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water after passing it through a cation exchange resin that adsorbs cations; Calculating the water quality of the target water based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity; Including, Water quality analysis method.

12. A step of obtaining a measured value of the hydrogen ion concentration index of the target water, which is the water to be monitored, a measured value of the electrical conductivity of the target water, and a measured value of the acid electrical conductivity, which is the electrical conductivity of the target water after passing it through a cation exchange resin that adsorbs cations; Calculating the water quality of the target water based on the measured value of the hydrogen ion concentration index, the measured value of the electrical conductivity, and the measured value of the acid electrical conductivity; to the computer, program.

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